id	sid	tid	token	lemma	pos
flr-365	1	1	morena	morena	PROPN
flr-365	1	2	-esteva	-esteva	PROPN
flr-365	1	3	et	et	PROPN
flr-365	1	4	al	al	PROPN
flr-365	1	5	publication	publication	NOUN
flr-365	1	6	frontline	frontline	NOUN
flr-365	1	7	learning	learn	VERB
flr-365	1	8	research	research	NOUN
flr-365	1	9	vol.6	vol.6	PROPN
flr-365	2	1	no	no	INTJ
flr-365	2	2	.	.	NOUN
flr-365	2	3	3	3	NUM
flr-365	2	4	(	(	PUNCT
flr-365	2	5	2018	2018	NUM
flr-365	2	6	)	)	PUNCT
flr-365	2	7	72	72	NUM
flr-365	2	8	84	84	NUM
flr-365	2	9	issn	issn	VERB
flr-365	2	10	2295	2295	NUM
flr-365	2	11	-	-	SYM
flr-365	2	12	3159	3159	NUM
flr-365	2	13	application	application	NOUN
flr-365	2	14	of	of	ADP
flr-365	2	15	mathematical	mathematical	ADJ
flr-365	2	16	and	and	CCONJ
flr-365	2	17	machine	machine	NOUN
flr-365	2	18	learning	learn	VERB
flr-365	2	19	techniques	technique	NOUN
flr-365	2	20	to	to	PART
flr-365	2	21	analyse	analyse	VERB
flr-365	2	22	eye	eye	NOUN
flr-365	2	23	tracking	tracking	NOUN
flr-365	2	24	data	datum	NOUN
flr-365	2	25	enabling	enable	VERB
flr-365	2	26	better	well	ADJ
flr-365	2	27	understanding	understanding	NOUN
flr-365	2	28	of	of	ADP
flr-365	2	29	children	child	NOUN
flr-365	2	30	’s	’s	PART
flr-365	2	31	visual	visual	ADJ
flr-365	2	32	cognitive	cognitive	ADJ
flr-365	2	33	behaviours	behaviour	NOUN
flr-365	2	34	enrique	enrique	PROPN
flr-365	2	35	garcia	garcia	PROPN
flr-365	2	36	moreno	moreno	PROPN
flr-365	2	37	-	-	PUNCT
flr-365	2	38	estevaa	estevaa	PROPN
flr-365	2	39	,	,	PUNCT
flr-365	2	40	sonia	sonia	PROPN
flr-365	2	41	l.	l.	PROPN
flr-365	2	42	j.	j.	PROPN
flr-365	2	43	whiteb	whiteb	PROPN
flr-365	2	44	,	,	PUNCT
flr-365	2	45	joanne	joanne	PROPN
flr-365	2	46	m.	m.	PROPN
flr-365	2	47	woodc	woodc	PROPN
flr-365	2	48	,	,	PUNCT
flr-365	2	49	alex	alex	PROPN
flr-365	2	50	a.	a.	PROPN
flr-365	2	51	black	black	PROPN
flr-365	2	52	c	c	PROPN
flr-365	2	53	adepartment	adepartment	NOUN
flr-365	2	54	of	of	ADP
flr-365	2	55	education	education	NOUN
flr-365	2	56	,	,	PUNCT
flr-365	2	57	university	university	PROPN
flr-365	2	58	of	of	ADP
flr-365	2	59	helsinki	helsinki	PROPN
flr-365	2	60	,	,	PUNCT
flr-365	2	61	finland	finland	PROPN
flr-365	2	62	b	b	PROPN
flr-365	2	63	faculty	faculty	NOUN
flr-365	2	64	of	of	ADP
flr-365	2	65	education	education	NOUN
flr-365	2	66	,	,	PUNCT
flr-365	2	67	queensland	queensland	PROPN
flr-365	2	68	university	university	PROPN
flr-365	2	69	of	of	ADP
flr-365	2	70	technology	technology	PROPN
flr-365	2	71	,	,	PUNCT
flr-365	2	72	australia	australia	PROPN
flr-365	2	73	c	c	PROPN
flr-365	2	74	faculty	faculty	NOUN
flr-365	2	75	of	of	ADP
flr-365	2	76	health	health	NOUN
flr-365	2	77	,	,	PUNCT
flr-365	2	78	queensland	queensland	PROPN
flr-365	2	79	university	university	PROPN
flr-365	2	80	of	of	ADP
flr-365	2	81	technology	technology	PROPN
flr-365	2	82	,	,	PUNCT
flr-365	2	83	australia	australia	PROPN
flr-365	2	84	article	article	NOUN
flr-365	2	85	received	receive	VERB
flr-365	2	86	9	9	NUM
flr-365	2	87	may	may	AUX
flr-365	2	88	2018/	2018/	NUM
flr-365	2	89	revised	revise	VERB
flr-365	2	90	16	16	NUM
flr-365	2	91	september/	september/	NUM
flr-365	2	92	accepted	accept	VERB
flr-365	2	93	17	17	NUM
flr-365	2	94	october/	october/	NUM
flr-365	2	95	available	available	ADJ
flr-365	2	96	online	online	ADJ
flr-365	2	97	7	7	NUM
flr-365	2	98	december	december	NOUN
flr-365	2	99	abstract	abstract	NOUN
flr-365	2	100	in	in	ADP
flr-365	2	101	this	this	DET
flr-365	2	102	research	research	NOUN
flr-365	2	103	,	,	PUNCT
flr-365	2	104	we	we	PRON
flr-365	2	105	aimed	aim	VERB
flr-365	2	106	to	to	PART
flr-365	2	107	investigate	investigate	VERB
flr-365	2	108	the	the	DET
flr-365	2	109	visual	visual	ADJ
flr-365	2	110	-	-	PUNCT
flr-365	2	111	cognitive	cognitive	ADJ
flr-365	2	112	behaviours	behaviour	NOUN
flr-365	2	113	of	of	ADP
flr-365	2	114	a	a	DET
flr-365	2	115	sample	sample	NOUN
flr-365	2	116	of	of	ADP
flr-365	2	117	106	106	NUM
flr-365	2	118	children	child	NOUN
flr-365	2	119	in	in	ADP
flr-365	2	120	year	year	NOUN
flr-365	2	121	3	3	NUM
flr-365	2	122	(	(	PUNCT
flr-365	2	123	8.8	8.8	NUM
flr-365	2	124	±	±	NUM
flr-365	2	125	0.3	0.3	NUM
flr-365	2	126	years	year	NOUN
flr-365	2	127	)	)	PUNCT
flr-365	2	128	while	while	SCONJ
flr-365	2	129	completing	complete	VERB
flr-365	2	130	a	a	DET
flr-365	2	131	mathematics	mathematic	NOUN
flr-365	2	132	bar	bar	NOUN
flr-365	2	133	-	-	PUNCT
flr-365	2	134	graph	graph	NOUN
flr-365	2	135	task	task	NOUN
flr-365	2	136	.	.	PUNCT
flr-365	3	1	eye	eye	NOUN
flr-365	3	2	movements	movement	NOUN
flr-365	3	3	were	be	AUX
flr-365	3	4	recorded	record	VERB
flr-365	3	5	while	while	SCONJ
flr-365	3	6	children	child	NOUN
flr-365	3	7	completed	complete	VERB
flr-365	3	8	the	the	DET
flr-365	3	9	task	task	NOUN
flr-365	3	10	and	and	CCONJ
flr-365	3	11	the	the	DET
flr-365	3	12	patterns	pattern	NOUN
flr-365	3	13	of	of	ADP
flr-365	3	14	eye	eye	NOUN
flr-365	3	15	movements	movement	NOUN
flr-365	3	16	were	be	AUX
flr-365	3	17	explored	explore	VERB
flr-365	3	18	using	use	VERB
flr-365	3	19	machine	machine	NOUN
flr-365	3	20	learning	learning	NOUN
flr-365	3	21	approaches	approach	NOUN
flr-365	3	22	.	.	PUNCT
flr-365	4	1	two	two	NUM
flr-365	4	2	different	different	ADJ
flr-365	4	3	techniques	technique	NOUN
flr-365	4	4	of	of	ADP
flr-365	4	5	machine	machine	NOUN
flr-365	4	6	-	-	PUNCT
flr-365	4	7	learning	learning	NOUN
flr-365	4	8	were	be	AUX
flr-365	4	9	used	use	VERB
flr-365	4	10	(	(	PUNCT
flr-365	4	11	bayesian	bayesian	NOUN
flr-365	4	12	and	and	CCONJ
flr-365	4	13	k	k	NOUN
flr-365	4	14	-	-	PUNCT
flr-365	4	15	means	mean	NOUN
flr-365	4	16	)	)	PUNCT
flr-365	4	17	to	to	PART
flr-365	4	18	obtain	obtain	VERB
flr-365	4	19	separate	separate	ADJ
flr-365	4	20	model	model	NOUN
flr-365	4	21	sequences	sequence	NOUN
flr-365	4	22	or	or	CCONJ
flr-365	4	23	average	average	ADJ
flr-365	4	24	scanpaths	scanpath	NOUN
flr-365	4	25	for	for	ADP
flr-365	4	26	those	those	DET
flr-365	4	27	children	child	NOUN
flr-365	4	28	who	who	PRON
flr-365	4	29	responded	respond	VERB
flr-365	4	30	either	either	CCONJ
flr-365	4	31	correctly	correctly	ADV
flr-365	4	32	or	or	CCONJ
flr-365	4	33	incorrectly	incorrectly	ADV
flr-365	4	34	to	to	ADP
flr-365	4	35	the	the	DET
flr-365	4	36	graph	graph	NOUN
flr-365	4	37	task	task	NOUN
flr-365	4	38	.	.	PUNCT
flr-365	5	1	application	application	NOUN
flr-365	5	2	of	of	ADP
flr-365	5	3	these	these	DET
flr-365	5	4	machine	machine	NOUN
flr-365	5	5	-	-	PUNCT
flr-365	5	6	learning	learn	VERB
flr-365	5	7	approaches	approach	NOUN
flr-365	5	8	indicated	indicate	VERB
flr-365	5	9	distinct	distinct	ADJ
flr-365	5	10	differences	difference	NOUN
flr-365	5	11	in	in	ADP
flr-365	5	12	the	the	DET
flr-365	5	13	resulting	result	VERB
flr-365	5	14	scanpaths	scanpath	NOUN
flr-365	5	15	for	for	ADP
flr-365	5	16	children	child	NOUN
flr-365	5	17	who	who	PRON
flr-365	5	18	completed	complete	VERB
flr-365	5	19	the	the	DET
flr-365	5	20	graph	graph	NOUN
flr-365	5	21	task	task	NOUN
flr-365	5	22	correctly	correctly	ADV
flr-365	5	23	or	or	CCONJ
flr-365	5	24	incorrectly	incorrectly	ADV
flr-365	5	25	:	:	PUNCT
flr-365	5	26	children	child	NOUN
flr-365	5	27	who	who	PRON
flr-365	5	28	responded	respond	VERB
flr-365	5	29	correctly	correctly	ADV
flr-365	5	30	accessed	access	VERB
flr-365	5	31	information	information	NOUN
flr-365	5	32	that	that	PRON
flr-365	5	33	was	be	AUX
flr-365	5	34	mostly	mostly	ADV
flr-365	5	35	categorised	categorise	VERB
flr-365	5	36	as	as	ADP
flr-365	5	37	critical	critical	ADJ
flr-365	5	38	,	,	PUNCT
flr-365	5	39	whereas	whereas	SCONJ
flr-365	5	40	children	child	NOUN
flr-365	5	41	responding	respond	VERB
flr-365	5	42	incorrectly	incorrectly	ADV
flr-365	5	43	did	do	VERB
flr-365	5	44	not	not	PART
flr-365	5	45	.	.	PUNCT
flr-365	6	1	there	there	PRON
flr-365	6	2	was	be	VERB
flr-365	6	3	also	also	ADV
flr-365	6	4	evidence	evidence	NOUN
flr-365	6	5	that	that	SCONJ
flr-365	6	6	the	the	DET
flr-365	6	7	children	child	NOUN
flr-365	6	8	who	who	PRON
flr-365	6	9	were	be	AUX
flr-365	6	10	correct	correct	ADJ
flr-365	6	11	accessed	access	VERB
flr-365	6	12	the	the	DET
flr-365	6	13	graph	graph	NOUN
flr-365	6	14	information	information	NOUN
flr-365	6	15	in	in	ADP
flr-365	6	16	a	a	DET
flr-365	6	17	different	different	ADJ
flr-365	6	18	,	,	PUNCT
flr-365	6	19	more	more	ADV
flr-365	6	20	logical	logical	ADJ
flr-365	6	21	order	order	NOUN
flr-365	6	22	,	,	PUNCT
flr-365	6	23	compared	compare	VERB
flr-365	6	24	to	to	ADP
flr-365	6	25	the	the	DET
flr-365	6	26	children	child	NOUN
flr-365	6	27	who	who	PRON
flr-365	6	28	were	be	AUX
flr-365	6	29	incorrect	incorrect	ADJ
flr-365	6	30	.	.	PUNCT
flr-365	7	1	the	the	DET
flr-365	7	2	visual	visual	ADJ
flr-365	7	3	behaviours	behaviour	NOUN
flr-365	7	4	aligned	align	VERB
flr-365	7	5	with	with	ADP
flr-365	7	6	different	different	ADJ
flr-365	7	7	aspects	aspect	NOUN
flr-365	7	8	of	of	ADP
flr-365	7	9	graph	graph	NOUN
flr-365	7	10	comprehension	comprehension	NOUN
flr-365	7	11	,	,	PUNCT
flr-365	7	12	such	such	ADJ
flr-365	7	13	as	as	ADP
flr-365	7	14	initial	initial	ADJ
flr-365	7	15	understanding	understanding	NOUN
flr-365	7	16	and	and	CCONJ
flr-365	7	17	orienting	orient	VERB
flr-365	7	18	to	to	ADP
flr-365	7	19	the	the	DET
flr-365	7	20	graph	graph	NOUN
flr-365	7	21	,	,	PUNCT
flr-365	7	22	and	and	CCONJ
flr-365	7	23	later	later	ADV
flr-365	7	24	interpretation	interpretation	NOUN
flr-365	7	25	and	and	CCONJ
flr-365	7	26	use	use	NOUN
flr-365	7	27	of	of	ADP
flr-365	7	28	relevant	relevant	ADJ
flr-365	7	29	information	information	NOUN
flr-365	7	30	on	on	ADP
flr-365	7	31	the	the	DET
flr-365	7	32	graph	graph	NOUN
flr-365	7	33	.	.	PUNCT
flr-365	8	1	the	the	DET
flr-365	8	2	findings	finding	NOUN
flr-365	8	3	are	be	AUX
flr-365	8	4	discussed	discuss	VERB
flr-365	8	5	in	in	ADP
flr-365	8	6	terms	term	NOUN
flr-365	8	7	of	of	ADP
flr-365	8	8	the	the	DET
flr-365	8	9	implications	implication	NOUN
flr-365	8	10	for	for	ADP
flr-365	8	11	early	early	ADJ
flr-365	8	12	mathematics	mathematic	NOUN
flr-365	8	13	teaching	teaching	NOUN
flr-365	8	14	and	and	CCONJ
flr-365	8	15	learning	learning	NOUN
flr-365	8	16	,	,	PUNCT
flr-365	8	17	particularly	particularly	ADV
flr-365	8	18	in	in	ADP
flr-365	8	19	the	the	DET
flr-365	8	20	development	development	NOUN
flr-365	8	21	of	of	ADP
flr-365	8	22	graph	graph	NOUN
flr-365	8	23	comprehension	comprehension	NOUN
flr-365	8	24	,	,	PUNCT
flr-365	8	25	as	as	ADV
flr-365	8	26	well	well	ADV
flr-365	8	27	as	as	ADP
flr-365	8	28	the	the	DET
flr-365	8	29	application	application	NOUN
flr-365	8	30	of	of	ADP
flr-365	8	31	machine	machine	NOUN
flr-365	8	32	learning	learn	VERB
flr-365	8	33	techniques	technique	NOUN
flr-365	8	34	to	to	ADP
flr-365	8	35	investigations	investigation	NOUN
flr-365	8	36	of	of	ADP
flr-365	8	37	other	other	ADJ
flr-365	8	38	visual	visual	ADJ
flr-365	8	39	-	-	PUNCT
flr-365	8	40	cognitive	cognitive	ADJ
flr-365	8	41	behaviours	behaviour	NOUN
flr-365	8	42	.	.	PUNCT
flr-365	9	1	graph	graph	NOUN
flr-365	9	2	interpretation	interpretation	NOUN
flr-365	9	3	;	;	PUNCT
flr-365	9	4	eye	eye	NOUN
flr-365	9	5	tracking	tracking	NOUN
flr-365	9	6	;	;	PUNCT
flr-365	9	7	machine	machine	NOUN
flr-365	9	8	learning	learning	NOUN
flr-365	9	9	;	;	PUNCT
flr-365	9	10	mathematics	mathematic	NOUN
flr-365	9	11	education	education	NOUN
flr-365	9	12	;	;	PUNCT
flr-365	9	13	gaze	gaze	NOUN
flr-365	9	14	metrics	metric	NOUN
flr-365	9	15	info	info	NOUN
flr-365	9	16	corresponding	corresponding	ADJ
flr-365	9	17	author	author	NOUN
flr-365	9	18	:	:	PUNCT
flr-365	9	19	enrique.garciamoreno-esteva@helsinki.fi	enrique.garciamoreno-esteva@helsinki.fi	ADJ
flr-365	9	20	doi	doi	NOUN
flr-365	9	21	:	:	PUNCT
flr-365	9	22	https://doi.org/10.14786/flr.v6i3.365	https://doi.org/10.14786/flr.v6i3.365	NOUN
flr-365	9	23	1	1	NUM
flr-365	9	24	.	.	X
flr-365	10	1	introduction	introduction	NOUN
flr-365	10	2	eye	eye	NOUN
flr-365	10	3	tracking	tracking	NOUN
flr-365	10	4	is	be	AUX
flr-365	10	5	rapidly	rapidly	ADV
flr-365	10	6	becoming	become	VERB
flr-365	10	7	an	an	DET
flr-365	10	8	established	establish	VERB
flr-365	10	9	technique	technique	NOUN
flr-365	10	10	for	for	ADP
flr-365	10	11	investigating	investigate	VERB
flr-365	10	12	the	the	DET
flr-365	10	13	cognitive	cognitive	ADJ
flr-365	10	14	processes	process	NOUN
flr-365	10	15	involved	involve	VERB
flr-365	10	16	in	in	ADP
flr-365	10	17	learning	learn	VERB
flr-365	10	18	mathematics	mathematic	NOUN
flr-365	10	19	and	and	CCONJ
flr-365	10	20	other	other	ADJ
flr-365	10	21	subjects	subject	NOUN
flr-365	10	22	.	.	PUNCT
flr-365	11	1	the	the	DET
flr-365	11	2	use	use	NOUN
flr-365	11	3	of	of	ADP
flr-365	11	4	eye	eye	NOUN
flr-365	11	5	tracking	tracking	NOUN
flr-365	11	6	makes	make	VERB
flr-365	11	7	it	it	PRON
flr-365	11	8	possible	possible	ADJ
flr-365	11	9	to	to	PART
flr-365	11	10	make	make	VERB
flr-365	11	11	implicit	implicit	ADJ
flr-365	11	12	visual	visual	ADJ
flr-365	11	13	-	-	PUNCT
flr-365	11	14	cognitive	cognitive	ADJ
flr-365	11	15	behaviours	behaviour	NOUN
flr-365	11	16	explicit	explicit	ADJ
flr-365	11	17	,	,	PUNCT
flr-365	11	18	in	in	ADP
flr-365	11	19	order	order	NOUN
flr-365	11	20	to	to	PART
flr-365	11	21	better	well	ADV
flr-365	11	22	understand	understand	VERB
flr-365	11	23	learning	learning	NOUN
flr-365	11	24	processes	process	NOUN
flr-365	11	25	and	and	CCONJ
flr-365	11	26	subsequently	subsequently	ADV
flr-365	11	27	inform	inform	VERB
flr-365	11	28	educational	educational	ADJ
flr-365	11	29	practice	practice	NOUN
flr-365	11	30	(	(	PUNCT
flr-365	11	31	lai	lai	PROPN
flr-365	11	32	,	,	PUNCT
flr-365	11	33	et	et	PROPN
flr-365	11	34	al	al	PROPN
flr-365	11	35	.	.	PROPN
flr-365	11	36	,	,	PUNCT
flr-365	11	37	2013	2013	NUM
flr-365	11	38	)	)	PUNCT
flr-365	11	39	.	.	PUNCT
flr-365	12	1	previous	previous	ADJ
flr-365	12	2	methods	method	NOUN
flr-365	12	3	,	,	PUNCT
flr-365	12	4	such	such	ADJ
flr-365	12	5	as	as	ADP
flr-365	12	6	interviewing	interview	VERB
flr-365	12	7	and	and	CCONJ
flr-365	12	8	think	think	VERB
flr-365	12	9	aloud	aloud	ADJ
flr-365	12	10	protocols	protocol	NOUN
flr-365	12	11	,	,	PUNCT
flr-365	12	12	have	have	AUX
flr-365	12	13	been	be	AUX
flr-365	12	14	adopted	adopt	VERB
flr-365	12	15	to	to	PART
flr-365	12	16	understand	understand	VERB
flr-365	12	17	the	the	DET
flr-365	12	18	different	different	ADJ
flr-365	12	19	approaches	approach	NOUN
flr-365	12	20	and	and	CCONJ
flr-365	12	21	strategies	strategy	NOUN
flr-365	12	22	used	use	VERB
flr-365	12	23	in	in	ADP
flr-365	12	24	a	a	DET
flr-365	12	25	range	range	NOUN
flr-365	12	26	of	of	ADP
flr-365	12	27	problem	problem	NOUN
flr-365	12	28	-	-	PUNCT
flr-365	12	29	solving	solve	VERB
flr-365	12	30	tasks	task	NOUN
flr-365	12	31	,	,	PUNCT
flr-365	12	32	however	however	ADV
flr-365	12	33	,	,	PUNCT
flr-365	12	34	there	there	PRON
flr-365	12	35	are	be	VERB
flr-365	12	36	limitations	limitation	NOUN
flr-365	12	37	to	to	ADP
flr-365	12	38	these	these	DET
flr-365	12	39	approaches	approach	NOUN
flr-365	12	40	.	.	PUNCT
flr-365	13	1	first	first	ADV
flr-365	13	2	,	,	PUNCT
flr-365	13	3	interviews	interview	NOUN
flr-365	13	4	undertaken	undertake	VERB
flr-365	13	5	following	follow	VERB
flr-365	13	6	task	task	NOUN
flr-365	13	7	completion	completion	NOUN
flr-365	13	8	are	be	AUX
flr-365	13	9	reliant	reliant	ADJ
flr-365	13	10	on	on	ADP
flr-365	13	11	a	a	DET
flr-365	13	12	participant	participant	NOUN
flr-365	13	13	accurately	accurately	ADV
flr-365	13	14	remembering	remember	VERB
flr-365	13	15	and	and	CCONJ
flr-365	13	16	recalling	recall	VERB
flr-365	13	17	specific	specific	ADJ
flr-365	13	18	steps	step	NOUN
flr-365	13	19	.	.	PUNCT
flr-365	14	1	second	second	ADV
flr-365	14	2	,	,	PUNCT
flr-365	14	3	think	think	VERB
flr-365	14	4	aloud	aloud	ADJ
flr-365	14	5	protocols	protocol	NOUN
flr-365	14	6	assume	assume	VERB
flr-365	14	7	the	the	DET
flr-365	14	8	participant	participant	NOUN
flr-365	14	9	has	have	VERB
flr-365	14	10	the	the	DET
flr-365	14	11	cognitive	cognitive	ADJ
flr-365	14	12	flexibility	flexibility	NOUN
flr-365	14	13	to	to	PART
flr-365	14	14	think	think	VERB
flr-365	14	15	out	out	ADP
flr-365	14	16	loud	loud	ADV
flr-365	14	17	while	while	SCONJ
flr-365	14	18	also	also	ADV
flr-365	14	19	engaging	engage	VERB
flr-365	14	20	in	in	ADP
flr-365	14	21	the	the	DET
flr-365	14	22	problem	problem	NOUN
flr-365	14	23	-	-	PUNCT
flr-365	14	24	solving	solve	VERB
flr-365	14	25	task	task	NOUN
flr-365	14	26	(	(	PUNCT
flr-365	14	27	rosenzweig	rosenzweig	PROPN
flr-365	14	28	,	,	PUNCT
flr-365	14	29	krawec	krawec	PROPN
flr-365	14	30	,	,	PUNCT
flr-365	14	31	&	&	CCONJ
flr-365	14	32	montague	montague	PROPN
flr-365	14	33	,	,	PUNCT
flr-365	14	34	2011	2011	NUM
flr-365	14	35	)	)	PUNCT
flr-365	14	36	.	.	PUNCT
flr-365	15	1	for	for	ADP
flr-365	15	2	example	example	NOUN
flr-365	15	3	,	,	PUNCT
flr-365	15	4	to	to	PART
flr-365	15	5	understand	understand	VERB
flr-365	15	6	how	how	SCONJ
flr-365	15	7	young	young	ADJ
flr-365	15	8	children	child	NOUN
flr-365	15	9	engage	engage	VERB
flr-365	15	10	in	in	ADP
flr-365	15	11	mathematics	mathematic	NOUN
flr-365	15	12	problem	problem	NOUN
flr-365	15	13	-	-	PUNCT
flr-365	15	14	solving	solve	VERB
flr-365	15	15	tasks	task	NOUN
flr-365	15	16	,	,	PUNCT
flr-365	15	17	the	the	DET
flr-365	15	18	additional	additional	ADJ
flr-365	15	19	cognitive	cognitive	ADJ
flr-365	15	20	demand	demand	NOUN
flr-365	15	21	of	of	ADP
flr-365	15	22	think	think	VERB
flr-365	15	23	aloud	aloud	ADJ
flr-365	15	24	protocols	protocol	NOUN
flr-365	15	25	could	could	AUX
flr-365	15	26	potentially	potentially	ADV
flr-365	15	27	have	have	VERB
flr-365	15	28	an	an	DET
flr-365	15	29	adverse	adverse	ADJ
flr-365	15	30	impact	impact	NOUN
flr-365	15	31	on	on	ADP
flr-365	15	32	task	task	NOUN
flr-365	15	33	performance	performance	NOUN
flr-365	15	34	.	.	PUNCT
flr-365	16	1	indeed	indeed	ADV
flr-365	16	2	,	,	PUNCT
flr-365	16	3	kotsopoulos	kotsopoulos	PROPN
flr-365	16	4	and	and	CCONJ
flr-365	16	5	lee	lee	PROPN
flr-365	16	6	(	(	PUNCT
flr-365	16	7	2012	2012	NUM
flr-365	16	8	)	)	PUNCT
flr-365	16	9	used	use	VERB
flr-365	16	10	modified	modify	VERB
flr-365	16	11	think	think	VERB
flr-365	16	12	aloud	aloud	ADJ
flr-365	16	13	protocols	protocol	NOUN
flr-365	16	14	and	and	CCONJ
flr-365	16	15	real	real	ADJ
flr-365	16	16	time	time	NOUN
flr-365	16	17	naturalistic	naturalistic	ADJ
flr-365	16	18	analysis	analysis	NOUN
flr-365	16	19	of	of	ADP
flr-365	16	20	students	student	NOUN
flr-365	16	21	completing	complete	VERB
flr-365	16	22	mathematical	mathematical	ADJ
flr-365	16	23	problem	problem	NOUN
flr-365	16	24	-	-	PUNCT
flr-365	16	25	solving	solve	VERB
flr-365	16	26	tasks	task	NOUN
flr-365	16	27	,	,	PUNCT
flr-365	16	28	and	and	CCONJ
flr-365	16	29	reported	report	VERB
flr-365	16	30	that	that	SCONJ
flr-365	16	31	problem	problem	NOUN
flr-365	16	32	-	-	PUNCT
flr-365	16	33	solving	solving	NOUN
flr-365	16	34	often	often	ADV
flr-365	16	35	broke	break	VERB
flr-365	16	36	down	down	ADP
flr-365	16	37	in	in	ADP
flr-365	16	38	the	the	DET
flr-365	16	39	early	early	ADJ
flr-365	16	40	stages	stage	NOUN
flr-365	16	41	of	of	ADP
flr-365	16	42	understanding	understand	VERB
flr-365	16	43	the	the	DET
flr-365	16	44	task	task	NOUN
flr-365	16	45	.	.	PUNCT
flr-365	17	1	the	the	DET
flr-365	17	2	limitations	limitation	NOUN
flr-365	17	3	with	with	ADP
flr-365	17	4	many	many	ADJ
flr-365	17	5	of	of	ADP
flr-365	17	6	these	these	DET
flr-365	17	7	approaches	approach	NOUN
flr-365	17	8	led	lead	VERB
flr-365	17	9	van	van	PROPN
flr-365	17	10	gog	gog	PROPN
flr-365	17	11	,	,	PUNCT
flr-365	17	12	paas	paas	NOUN
flr-365	17	13	,	,	PUNCT
flr-365	17	14	van	van	PROPN
flr-365	17	15	merriënboer	merriënboer	PROPN
flr-365	17	16	and	and	CCONJ
flr-365	17	17	witte	witte	PROPN
flr-365	17	18	(	(	PUNCT
flr-365	17	19	2005	2005	NUM
flr-365	17	20	)	)	PUNCT
flr-365	17	21	to	to	PART
flr-365	17	22	highlight	highlight	VERB
flr-365	17	23	the	the	DET
flr-365	17	24	need	need	NOUN
flr-365	17	25	for	for	SCONJ
flr-365	17	26	research	research	NOUN
flr-365	17	27	methods	method	NOUN
flr-365	17	28	to	to	PART
flr-365	17	29	understand	understand	VERB
flr-365	17	30	different	different	ADJ
flr-365	17	31	problem	problem	NOUN
flr-365	17	32	-	-	PUNCT
flr-365	17	33	solving	solve	VERB
flr-365	17	34	processes	process	NOUN
flr-365	17	35	and	and	CCONJ
flr-365	17	36	supported	support	VERB
flr-365	17	37	the	the	DET
flr-365	17	38	use	use	NOUN
flr-365	17	39	of	of	ADP
flr-365	17	40	eye	eye	NOUN
flr-365	17	41	tracking	tracking	NOUN
flr-365	17	42	methods	method	NOUN
flr-365	17	43	for	for	ADP
flr-365	17	44	more	more	ADJ
flr-365	17	45	complex	complex	ADJ
flr-365	17	46	tasks	task	NOUN
flr-365	17	47	that	that	PRON
flr-365	17	48	involve	involve	VERB
flr-365	17	49	a	a	DET
flr-365	17	50	sequence	sequence	NOUN
flr-365	17	51	of	of	ADP
flr-365	17	52	cognitive	cognitive	ADJ
flr-365	17	53	steps	step	NOUN
flr-365	17	54	.	.	PUNCT
flr-365	18	1	an	an	DET
flr-365	18	2	extensive	extensive	ADJ
flr-365	18	3	body	body	NOUN
flr-365	18	4	of	of	ADP
flr-365	18	5	eye	eye	NOUN
flr-365	18	6	tracking	tracking	NOUN
flr-365	18	7	research	research	NOUN
flr-365	18	8	has	have	AUX
flr-365	18	9	focused	focus	VERB
flr-365	18	10	on	on	ADP
flr-365	18	11	the	the	DET
flr-365	18	12	link	link	NOUN
flr-365	18	13	between	between	ADP
flr-365	18	14	visual	visual	ADJ
flr-365	18	15	gaze	gaze	NOUN
flr-365	18	16	and	and	CCONJ
flr-365	18	17	information	information	NOUN
flr-365	18	18	processing	processing	NOUN
flr-365	18	19	.	.	PUNCT
flr-365	19	1	for	for	ADP
flr-365	19	2	example	example	NOUN
flr-365	19	3	,	,	PUNCT
flr-365	19	4	how	how	SCONJ
flr-365	19	5	a	a	DET
flr-365	19	6	student	student	NOUN
flr-365	19	7	looks	look	VERB
flr-365	19	8	at	at	ADP
flr-365	19	9	a	a	DET
flr-365	19	10	diagram	diagram	NOUN
flr-365	19	11	is	be	AUX
flr-365	19	12	influenced	influence	VERB
flr-365	19	13	by	by	ADP
flr-365	19	14	their	their	PRON
flr-365	19	15	preliminary	preliminary	ADJ
flr-365	19	16	intuitions	intuition	NOUN
flr-365	19	17	and	and	CCONJ
flr-365	19	18	the	the	DET
flr-365	19	19	conceptions	conception	NOUN
flr-365	19	20	activated	activate	VERB
flr-365	19	21	by	by	ADP
flr-365	19	22	the	the	DET
flr-365	19	23	task	task	NOUN
flr-365	19	24	context	context	NOUN
flr-365	19	25	(	(	PUNCT
flr-365	19	26	knoblich	knoblich	PROPN
flr-365	19	27	,	,	PUNCT
flr-365	19	28	ohlsson	ohlsson	PROPN
flr-365	19	29	&	&	CCONJ
flr-365	19	30	raney	raney	PROPN
flr-365	19	31	,	,	PUNCT
flr-365	19	32	2001	2001	NUM
flr-365	19	33	)	)	PUNCT
flr-365	19	34	.	.	PUNCT
flr-365	20	1	eye	eye	NOUN
flr-365	20	2	tracking	tracking	NOUN
flr-365	20	3	research	research	NOUN
flr-365	20	4	has	have	AUX
flr-365	20	5	revealed	reveal	VERB
flr-365	20	6	that	that	SCONJ
flr-365	20	7	more	more	ADV
flr-365	20	8	experienced	experienced	ADJ
flr-365	20	9	problem	problem	NOUN
flr-365	20	10	-	-	PUNCT
flr-365	20	11	solvers	solver	NOUN
flr-365	20	12	(	(	PUNCT
flr-365	20	13	experts	expert	NOUN
flr-365	20	14	)	)	PUNCT
flr-365	20	15	can	can	AUX
flr-365	20	16	identify	identify	VERB
flr-365	20	17	task	task	NOUN
flr-365	20	18	relevant	relevant	ADJ
flr-365	20	19	visual	visual	ADJ
flr-365	20	20	information	information	NOUN
flr-365	20	21	more	more	ADV
flr-365	20	22	rapidly	rapidly	ADV
flr-365	20	23	than	than	ADP
flr-365	20	24	less	less	ADV
flr-365	20	25	experienced	experienced	ADJ
flr-365	20	26	individuals	individual	NOUN
flr-365	20	27	(	(	PUNCT
flr-365	20	28	novices	novice	NOUN
flr-365	20	29	)	)	PUNCT
flr-365	20	30	,	,	PUNCT
flr-365	20	31	and	and	CCONJ
flr-365	20	32	their	their	PRON
flr-365	20	33	visual	visual	ADJ
flr-365	20	34	attention	attention	NOUN
flr-365	20	35	(	(	PUNCT
flr-365	20	36	eye	eye	NOUN
flr-365	20	37	fixation	fixation	NOUN
flr-365	20	38	scanpaths	scanpath	NOUN
flr-365	20	39	)	)	PUNCT
flr-365	20	40	tend	tend	VERB
flr-365	20	41	to	to	PART
flr-365	20	42	be	be	AUX
flr-365	20	43	more	more	ADV
flr-365	20	44	focused	focused	ADJ
flr-365	20	45	on	on	ADP
flr-365	20	46	relevant	relevant	ADJ
flr-365	20	47	than	than	ADP
flr-365	20	48	irrelevant	irrelevant	ADJ
flr-365	20	49	regions	region	NOUN
flr-365	20	50	of	of	ADP
flr-365	20	51	the	the	DET
flr-365	20	52	visual	visual	ADJ
flr-365	20	53	stimulus	stimulus	NOUN
flr-365	20	54	(	(	PUNCT
flr-365	20	55	gegenfurtner	gegenfurtner	NOUN
flr-365	20	56	,	,	PUNCT
flr-365	20	57	lehtinen	lehtinen	PROPN
flr-365	20	58	&	&	CCONJ
flr-365	20	59	säljö	säljö	PROPN
flr-365	20	60	,	,	PUNCT
flr-365	20	61	2011	2011	NUM
flr-365	20	62	;	;	PUNCT
flr-365	20	63	tsai	tsai	PROPN
flr-365	20	64	,	,	PUNCT
flr-365	20	65	hou	hou	PROPN
flr-365	20	66	,	,	PUNCT
flr-365	20	67	lai	lai	PROPN
flr-365	20	68	,	,	PUNCT
flr-365	20	69	liu	liu	PROPN
flr-365	20	70	,	,	PUNCT
flr-365	20	71	&	&	CCONJ
flr-365	20	72	yang	yang	PROPN
flr-365	20	73	,	,	PUNCT
flr-365	20	74	2012	2012	NUM
flr-365	20	75	)	)	PUNCT
flr-365	20	76	;	;	PUNCT
flr-365	20	77	these	these	DET
flr-365	20	78	objective	objective	ADJ
flr-365	20	79	findings	finding	NOUN
flr-365	20	80	were	be	AUX
flr-365	20	81	corroborated	corroborate	VERB
flr-365	20	82	by	by	ADP
flr-365	20	83	self	self	NOUN
flr-365	20	84	-	-	PUNCT
flr-365	20	85	reported	report	VERB
flr-365	20	86	accounts	account	NOUN
flr-365	20	87	of	of	ADP
flr-365	20	88	participants	participant	NOUN
flr-365	20	89	completing	complete	VERB
flr-365	20	90	the	the	DET
flr-365	20	91	task	task	NOUN
flr-365	20	92	(	(	PUNCT
flr-365	20	93	tsai	tsai	PROPN
flr-365	20	94	,	,	PUNCT
flr-365	20	95	et	et	PROPN
flr-365	20	96	al	al	PROPN
flr-365	20	97	.	.	PROPN
flr-365	20	98	,	,	PUNCT
flr-365	20	99	2012	2012	NUM
flr-365	20	100	)	)	PUNCT
flr-365	20	101	.	.	PUNCT
flr-365	21	1	another	another	DET
flr-365	21	2	study	study	NOUN
flr-365	21	3	reported	report	VERB
flr-365	21	4	that	that	SCONJ
flr-365	21	5	novices	novice	NOUN
flr-365	21	6	display	display	VERB
flr-365	21	7	significantly	significantly	ADV
flr-365	21	8	more	more	ADJ
flr-365	21	9	shifts	shift	NOUN
flr-365	21	10	in	in	ADP
flr-365	21	11	visual	visual	ADJ
flr-365	21	12	attention	attention	NOUN
flr-365	21	13	than	than	ADP
flr-365	21	14	experts	expert	NOUN
flr-365	21	15	and	and	CCONJ
flr-365	21	16	have	have	AUX
flr-365	21	17	longer	long	ADJ
flr-365	21	18	gaze	gaze	VERB
flr-365	21	19	sequences	sequence	NOUN
flr-365	21	20	(	(	PUNCT
flr-365	21	21	or	or	CCONJ
flr-365	21	22	scanpaths	scanpath	NOUN
flr-365	21	23	)	)	PUNCT
flr-365	21	24	for	for	ADP
flr-365	21	25	a	a	DET
flr-365	21	26	given	give	VERB
flr-365	21	27	problem	problem	NOUN
flr-365	21	28	-	-	PUNCT
flr-365	21	29	solving	solve	VERB
flr-365	21	30	task	task	NOUN
flr-365	21	31	(	(	PUNCT
flr-365	21	32	kim	kim	PROPN
flr-365	21	33	,	,	PUNCT
flr-365	21	34	aleven	aleven	NOUN
flr-365	21	35	&	&	CCONJ
flr-365	21	36	dey	dey	PROPN
flr-365	21	37	,	,	PUNCT
flr-365	21	38	2014	2014	NUM
flr-365	21	39	)	)	PUNCT
flr-365	21	40	.	.	PUNCT
flr-365	22	1	furthermore	furthermore	ADV
flr-365	22	2	,	,	PUNCT
flr-365	22	3	psychology	psychology	NOUN
flr-365	22	4	research	research	NOUN
flr-365	22	5	indicates	indicate	VERB
flr-365	22	6	that	that	SCONJ
flr-365	22	7	the	the	DET
flr-365	22	8	order	order	NOUN
flr-365	22	9	of	of	ADP
flr-365	22	10	fixations	fixation	NOUN
flr-365	22	11	affects	affect	VERB
flr-365	22	12	cognitive	cognitive	ADJ
flr-365	22	13	functions	function	NOUN
flr-365	22	14	,	,	PUNCT
flr-365	22	15	such	such	ADJ
flr-365	22	16	as	as	ADP
flr-365	22	17	memory	memory	NOUN
flr-365	22	18	(	(	PUNCT
flr-365	22	19	e.g.	e.g.	ADV
flr-365	22	20	bochynska	bochynska	PROPN
flr-365	22	21	&	&	CCONJ
flr-365	22	22	laeng	laeng	PROPN
flr-365	22	23	,	,	PUNCT
flr-365	22	24	2015	2015	NUM
flr-365	22	25	;	;	PUNCT
flr-365	22	26	rinaldi	rinaldi	PROPN
flr-365	22	27	,	,	PUNCT
flr-365	22	28	brugger	brugger	PROPN
flr-365	22	29	,	,	PUNCT
flr-365	22	30	bockisch	bockisch	NOUN
flr-365	22	31	,	,	PUNCT
flr-365	22	32	bertolini	bertolini	NOUN
flr-365	22	33	,	,	PUNCT
flr-365	22	34	girelli	girelli	NOUN
flr-365	22	35	,	,	PUNCT
flr-365	22	36	2015	2015	NUM
flr-365	22	37	)	)	PUNCT
flr-365	22	38	.	.	PUNCT
flr-365	23	1	bochynska	bochynska	PROPN
flr-365	23	2	and	and	CCONJ
flr-365	23	3	laeng	laeng	PROPN
flr-365	23	4	(	(	PUNCT
flr-365	23	5	2015	2015	NUM
flr-365	23	6	)	)	PUNCT
flr-365	23	7	used	use	VERB
flr-365	23	8	eye	eye	NOUN
flr-365	23	9	tracking	tracking	NOUN
flr-365	23	10	in	in	ADP
flr-365	23	11	a	a	DET
flr-365	23	12	visuospatial	visuospatial	ADJ
flr-365	23	13	memory	memory	NOUN
flr-365	23	14	recognition	recognition	NOUN
flr-365	23	15	task	task	NOUN
flr-365	23	16	and	and	CCONJ
flr-365	23	17	found	find	VERB
flr-365	23	18	that	that	SCONJ
flr-365	23	19	both	both	CCONJ
flr-365	23	20	the	the	DET
flr-365	23	21	spatial	spatial	ADJ
flr-365	23	22	information	information	NOUN
flr-365	23	23	and	and	CCONJ
flr-365	23	24	the	the	DET
flr-365	23	25	order	order	NOUN
flr-365	23	26	of	of	ADP
flr-365	23	27	fixations	fixation	NOUN
flr-365	23	28	were	be	AUX
flr-365	23	29	important	important	ADJ
flr-365	23	30	for	for	ADP
flr-365	23	31	visuospatial	visuospatial	ADJ
flr-365	23	32	memory	memory	NOUN
flr-365	23	33	formation	formation	NOUN
flr-365	23	34	,	,	PUNCT
flr-365	23	35	with	with	ADP
flr-365	23	36	increased	increase	VERB
flr-365	23	37	accuracy	accuracy	NOUN
flr-365	23	38	in	in	ADP
flr-365	23	39	trials	trial	NOUN
flr-365	23	40	where	where	SCONJ
flr-365	23	41	the	the	DET
flr-365	23	42	elements	element	NOUN
flr-365	23	43	were	be	AUX
flr-365	23	44	presented	present	VERB
flr-365	23	45	serially	serially	ADV
flr-365	23	46	,	,	PUNCT
flr-365	23	47	in	in	ADP
flr-365	23	48	the	the	DET
flr-365	23	49	same	same	ADJ
flr-365	23	50	order	order	NOUN
flr-365	23	51	as	as	ADP
flr-365	23	52	in	in	ADP
flr-365	23	53	the	the	DET
flr-365	23	54	participant	participant	NOUN
flr-365	23	55	’s	’s	PART
flr-365	23	56	original	original	ADJ
flr-365	23	57	fixation	fixation	NOUN
flr-365	23	58	scanpath	scanpath	NOUN
flr-365	23	59	.	.	PUNCT
flr-365	24	1	the	the	DET
flr-365	24	2	current	current	ADJ
flr-365	24	3	research	research	NOUN
flr-365	24	4	,	,	PUNCT
flr-365	24	5	utilised	utilise	VERB
flr-365	24	6	machine	machine	NOUN
flr-365	24	7	learning	learn	VERB
flr-365	24	8	techniques	technique	NOUN
flr-365	24	9	to	to	PART
flr-365	24	10	make	make	VERB
flr-365	24	11	sense	sense	NOUN
flr-365	24	12	of	of	ADP
flr-365	24	13	the	the	DET
flr-365	24	14	order	order	NOUN
flr-365	24	15	structure	structure	NOUN
flr-365	24	16	of	of	ADP
flr-365	24	17	the	the	DET
flr-365	24	18	multiple	multiple	ADJ
flr-365	24	19	scanpaths	scanpath	NOUN
flr-365	24	20	of	of	ADP
flr-365	24	21	primary	primary	ADJ
flr-365	24	22	school	school	NOUN
flr-365	24	23	children	child	NOUN
flr-365	24	24	while	while	SCONJ
flr-365	24	25	they	they	PRON
flr-365	24	26	completed	complete	VERB
flr-365	24	27	a	a	DET
flr-365	24	28	graph	graph	NOUN
flr-365	24	29	problem	problem	NOUN
flr-365	24	30	-	-	PUNCT
flr-365	24	31	solving	solve	VERB
flr-365	24	32	task	task	NOUN
flr-365	24	33	,	,	PUNCT
flr-365	24	34	in	in	ADP
flr-365	24	35	order	order	NOUN
flr-365	24	36	to	to	PART
flr-365	24	37	better	well	ADV
flr-365	24	38	understand	understand	VERB
flr-365	24	39	the	the	DET
flr-365	24	40	visual	visual	ADJ
flr-365	24	41	cognitive	cognitive	ADJ
flr-365	24	42	behaviours	behaviour	NOUN
flr-365	24	43	involved	involve	VERB
flr-365	24	44	.	.	PUNCT
flr-365	25	1	the	the	DET
flr-365	25	2	rationale	rationale	NOUN
flr-365	25	3	for	for	ADP
flr-365	25	4	using	use	VERB
flr-365	25	5	machine	machine	NOUN
flr-365	25	6	learning	learn	VERB
flr-365	25	7	analysis	analysis	NOUN
flr-365	25	8	is	be	AUX
flr-365	25	9	that	that	SCONJ
flr-365	25	10	it	it	PRON
flr-365	25	11	allows	allow	VERB
flr-365	25	12	us	we	PRON
flr-365	25	13	to	to	PART
flr-365	25	14	examine	examine	VERB
flr-365	25	15	the	the	DET
flr-365	25	16	sequential	sequential	ADJ
flr-365	25	17	(	(	PUNCT
flr-365	25	18	temporal	temporal	ADJ
flr-365	25	19	)	)	PUNCT
flr-365	25	20	structure	structure	NOUN
flr-365	25	21	of	of	ADP
flr-365	25	22	the	the	DET
flr-365	25	23	data	datum	NOUN
flr-365	25	24	.	.	PUNCT
flr-365	26	1	this	this	PRON
flr-365	26	2	is	be	AUX
flr-365	26	3	unlike	unlike	ADP
flr-365	26	4	the	the	DET
flr-365	26	5	approach	approach	NOUN
flr-365	26	6	adopted	adopt	VERB
flr-365	26	7	in	in	ADP
flr-365	26	8	most	most	ADJ
flr-365	26	9	eye	eye	NOUN
flr-365	26	10	tracking	tracking	NOUN
flr-365	26	11	studies	study	NOUN
flr-365	26	12	and	and	CCONJ
flr-365	26	13	allows	allow	VERB
flr-365	26	14	novel	novel	ADJ
flr-365	26	15	insight	insight	NOUN
flr-365	26	16	into	into	ADP
flr-365	26	17	the	the	DET
flr-365	26	18	underlying	underlie	VERB
flr-365	26	19	behaviours	behaviour	NOUN
flr-365	26	20	of	of	ADP
flr-365	26	21	children	child	NOUN
flr-365	26	22	while	while	SCONJ
flr-365	26	23	completing	complete	VERB
flr-365	26	24	these	these	DET
flr-365	26	25	graph	graph	NOUN
flr-365	26	26	tasks	task	NOUN
flr-365	26	27	.	.	PUNCT
flr-365	27	1	while	while	SCONJ
flr-365	27	2	there	there	PRON
flr-365	27	3	are	be	VERB
flr-365	27	4	other	other	ADJ
flr-365	27	5	methods	method	NOUN
flr-365	27	6	to	to	PART
flr-365	27	7	examine	examine	VERB
flr-365	27	8	the	the	DET
flr-365	27	9	temporal	temporal	ADJ
flr-365	27	10	structure	structure	NOUN
flr-365	27	11	of	of	ADP
flr-365	27	12	data	datum	NOUN
flr-365	27	13	,	,	PUNCT
flr-365	27	14	we	we	PRON
flr-365	27	15	felt	feel	VERB
flr-365	27	16	our	our	PRON
flr-365	27	17	approach	approach	NOUN
flr-365	27	18	was	be	AUX
flr-365	27	19	the	the	DET
flr-365	27	20	most	most	ADV
flr-365	27	21	suitable	suitable	ADJ
flr-365	27	22	for	for	ADP
flr-365	27	23	our	our	PRON
flr-365	27	24	research	research	NOUN
flr-365	27	25	purpose	purpose	NOUN
flr-365	27	26	.	.	PUNCT
flr-365	28	1	our	our	PRON
flr-365	28	2	method	method	NOUN
flr-365	28	3	is	be	AUX
flr-365	28	4	also	also	ADV
flr-365	28	5	faster	fast	ADJ
flr-365	28	6	and	and	CCONJ
flr-365	28	7	more	more	ADV
flr-365	28	8	automated	automated	ADJ
flr-365	28	9	than	than	ADP
flr-365	28	10	many	many	ADJ
flr-365	28	11	other	other	ADJ
flr-365	28	12	traditional	traditional	ADJ
flr-365	28	13	methods	method	NOUN
flr-365	28	14	.	.	PUNCT
flr-365	29	1	in	in	ADP
flr-365	29	2	order	order	NOUN
flr-365	29	3	to	to	PART
flr-365	29	4	interpret	interpret	VERB
flr-365	29	5	the	the	DET
flr-365	29	6	scanpaths	scanpath	NOUN
flr-365	29	7	,	,	PUNCT
flr-365	29	8	our	our	PRON
flr-365	29	9	approach	approach	NOUN
flr-365	29	10	used	use	VERB
flr-365	29	11	the	the	DET
flr-365	29	12	sequential	sequential	ADJ
flr-365	29	13	framework	framework	NOUN
flr-365	29	14	of	of	ADP
flr-365	29	15	children	child	NOUN
flr-365	29	16	's	's	PART
flr-365	29	17	data	datum	NOUN
flr-365	29	18	comprehension	comprehension	NOUN
flr-365	29	19	,	,	PUNCT
flr-365	29	20	described	describe	VERB
flr-365	29	21	by	by	ADP
flr-365	29	22	curcio	curcio	PROPN
flr-365	29	23	(	(	PUNCT
flr-365	29	24	2010	2010	NUM
flr-365	29	25	)	)	PUNCT
flr-365	29	26	which	which	PRON
flr-365	29	27	comprises	comprise	VERB
flr-365	29	28	;	;	PUNCT
flr-365	29	29	understanding	understanding	NOUN
flr-365	29	30	,	,	PUNCT
flr-365	29	31	interpretation	interpretation	NOUN
flr-365	29	32	,	,	PUNCT
flr-365	29	33	and	and	CCONJ
flr-365	29	34	prediction	prediction	NOUN
flr-365	29	35	with	with	ADP
flr-365	29	36	data	datum	NOUN
flr-365	29	37	.	.	PUNCT
flr-365	30	1	the	the	DET
flr-365	30	2	first	first	ADJ
flr-365	30	3	level	level	NOUN
flr-365	30	4	of	of	ADP
flr-365	30	5	comprehension	comprehension	NOUN
flr-365	30	6	,	,	PUNCT
flr-365	30	7	‘	'	PUNCT
flr-365	30	8	understanding	understanding	NOUN
flr-365	30	9	’	'	PUNCT
flr-365	30	10	,	,	PUNCT
flr-365	30	11	requires	require	VERB
flr-365	30	12	reading	read	VERB
flr-365	30	13	of	of	ADP
flr-365	30	14	the	the	DET
flr-365	30	15	information	information	NOUN
flr-365	30	16	explicitly	explicitly	ADV
flr-365	30	17	stated	state	VERB
flr-365	30	18	in	in	ADP
flr-365	30	19	the	the	DET
flr-365	30	20	presented	present	VERB
flr-365	30	21	data	datum	NOUN
flr-365	30	22	(	(	PUNCT
flr-365	30	23	e.g.	e.g.	ADV
flr-365	30	24	graph	graph	NOUN
flr-365	30	25	)	)	PUNCT
flr-365	30	26	.	.	PUNCT
flr-365	31	1	the	the	DET
flr-365	31	2	second	second	ADJ
flr-365	31	3	level	level	NOUN
flr-365	31	4	of	of	ADP
flr-365	31	5	comprehension	comprehension	NOUN
flr-365	31	6	,	,	PUNCT
flr-365	31	7	‘	'	PUNCT
flr-365	31	8	interpretation	interpretation	NOUN
flr-365	31	9	’	'	PUNCT
flr-365	31	10	,	,	PUNCT
flr-365	31	11	requires	require	VERB
flr-365	31	12	reading	read	VERB
flr-365	31	13	between	between	ADP
flr-365	31	14	the	the	DET
flr-365	31	15	data	datum	NOUN
flr-365	31	16	and	and	CCONJ
flr-365	31	17	integration	integration	NOUN
flr-365	31	18	of	of	ADP
flr-365	31	19	the	the	DET
flr-365	31	20	presented	present	VERB
flr-365	31	21	information	information	NOUN
flr-365	31	22	,	,	PUNCT
flr-365	31	23	this	this	DET
flr-365	31	24	level	level	NOUN
flr-365	31	25	of	of	ADP
flr-365	31	26	comprehension	comprehension	NOUN
flr-365	31	27	requires	require	VERB
flr-365	31	28	specific	specific	ADJ
flr-365	31	29	skills	skill	NOUN
flr-365	31	30	,	,	PUNCT
flr-365	31	31	such	such	ADJ
flr-365	31	32	as	as	ADP
flr-365	31	33	comparison	comparison	NOUN
flr-365	31	34	or	or	CCONJ
flr-365	31	35	computation	computation	NOUN
flr-365	31	36	(	(	PUNCT
flr-365	31	37	e.g.	e.g.	ADV
flr-365	31	38	addition	addition	NOUN
flr-365	31	39	,	,	PUNCT
flr-365	31	40	subtraction	subtraction	NOUN
flr-365	31	41	,	,	PUNCT
flr-365	31	42	multiplication	multiplication	NOUN
flr-365	31	43	,	,	PUNCT
flr-365	31	44	division	division	NOUN
flr-365	31	45	)	)	PUNCT
flr-365	31	46	.	.	PUNCT
flr-365	32	1	the	the	DET
flr-365	32	2	third	third	ADJ
flr-365	32	3	level	level	NOUN
flr-365	32	4	of	of	ADP
flr-365	32	5	comprehension	comprehension	NOUN
flr-365	32	6	,	,	PUNCT
flr-365	32	7	‘	'	PUNCT
flr-365	32	8	prediction	prediction	NOUN
flr-365	32	9	’	'	PUNCT
flr-365	32	10	,	,	PUNCT
flr-365	32	11	requires	require	VERB
flr-365	32	12	reading	read	VERB
flr-365	32	13	beyond	beyond	ADP
flr-365	32	14	the	the	DET
flr-365	32	15	data	datum	NOUN
flr-365	32	16	and	and	CCONJ
flr-365	32	17	the	the	DET
flr-365	32	18	use	use	NOUN
flr-365	32	19	of	of	ADP
flr-365	32	20	existing	exist	VERB
flr-365	32	21	knowledge	knowledge	NOUN
flr-365	32	22	to	to	PART
flr-365	32	23	make	make	VERB
flr-365	32	24	inferences	inference	NOUN
flr-365	32	25	/	/	SYM
flr-365	32	26	predictions	prediction	NOUN
flr-365	32	27	from	from	ADP
flr-365	32	28	the	the	DET
flr-365	32	29	data	datum	NOUN
flr-365	32	30	.	.	PUNCT
flr-365	33	1	when	when	SCONJ
flr-365	33	2	making	make	VERB
flr-365	33	3	predictions	prediction	NOUN
flr-365	33	4	,	,	PUNCT
flr-365	33	5	the	the	DET
flr-365	33	6	information	information	NOUN
flr-365	33	7	is	be	AUX
flr-365	33	8	neither	neither	CCONJ
flr-365	33	9	explicitly	explicitly	ADV
flr-365	33	10	nor	nor	CCONJ
flr-365	33	11	implicitly	implicitly	ADV
flr-365	33	12	presented	present	VERB
flr-365	33	13	in	in	ADP
flr-365	33	14	the	the	DET
flr-365	33	15	graph	graph	NOUN
flr-365	33	16	.	.	PUNCT
flr-365	34	1	the	the	DET
flr-365	34	2	bar	bar	NOUN
flr-365	34	3	graph	graph	NOUN
flr-365	34	4	task	task	NOUN
flr-365	34	5	used	use	VERB
flr-365	34	6	in	in	ADP
flr-365	34	7	the	the	DET
flr-365	34	8	present	present	ADJ
flr-365	34	9	study	study	NOUN
flr-365	34	10	required	require	VERB
flr-365	34	11	each	each	DET
flr-365	34	12	child	child	NOUN
flr-365	34	13	to	to	PART
flr-365	34	14	engage	engage	VERB
flr-365	34	15	in	in	ADP
flr-365	34	16	the	the	DET
flr-365	34	17	first	first	ADJ
flr-365	34	18	two	two	NUM
flr-365	34	19	levels	level	NOUN
flr-365	34	20	of	of	ADP
flr-365	34	21	data	datum	NOUN
flr-365	34	22	comprehension	comprehension	NOUN
flr-365	34	23	:	:	PUNCT
flr-365	34	24	reading	read	VERB
flr-365	34	25	the	the	DET
flr-365	34	26	question	question	NOUN
flr-365	34	27	and	and	CCONJ
flr-365	34	28	basic	basic	ADJ
flr-365	34	29	details	detail	NOUN
flr-365	34	30	of	of	ADP
flr-365	34	31	the	the	DET
flr-365	34	32	graph	graph	NOUN
flr-365	34	33	(	(	PUNCT
flr-365	34	34	understanding	understanding	NOUN
flr-365	34	35	)	)	PUNCT
flr-365	34	36	,	,	PUNCT
flr-365	34	37	and	and	CCONJ
flr-365	34	38	then	then	ADV
flr-365	34	39	reading	read	VERB
flr-365	34	40	between	between	ADP
flr-365	34	41	the	the	DET
flr-365	34	42	different	different	ADJ
flr-365	34	43	elements	element	NOUN
flr-365	34	44	of	of	ADP
flr-365	34	45	information	information	NOUN
flr-365	34	46	(	(	PUNCT
flr-365	34	47	interpretation	interpretation	NOUN
flr-365	34	48	)	)	PUNCT
flr-365	34	49	in	in	ADP
flr-365	34	50	order	order	NOUN
flr-365	34	51	to	to	PART
flr-365	34	52	complete	complete	VERB
flr-365	34	53	the	the	DET
flr-365	34	54	computation	computation	NOUN
flr-365	34	55	and	and	CCONJ
flr-365	34	56	arrive	arrive	VERB
flr-365	34	57	at	at	ADP
flr-365	34	58	the	the	DET
flr-365	34	59	correct	correct	ADJ
flr-365	34	60	solution	solution	NOUN
flr-365	34	61	.	.	PUNCT
flr-365	35	1	most	most	ADV
flr-365	35	2	importantly	importantly	ADV
flr-365	35	3	,	,	PUNCT
flr-365	35	4	with	with	ADP
flr-365	35	5	graph	graph	NOUN
flr-365	35	6	interpretation	interpretation	NOUN
flr-365	35	7	,	,	PUNCT
flr-365	35	8	both	both	CCONJ
flr-365	35	9	visual	visual	ADJ
flr-365	35	10	and	and	CCONJ
flr-365	35	11	cognitive	cognitive	ADJ
flr-365	35	12	integration	integration	NOUN
flr-365	35	13	is	be	AUX
flr-365	35	14	required	require	VERB
flr-365	35	15	(	(	PUNCT
flr-365	35	16	ratwani	ratwani	PROPN
flr-365	35	17	,	,	PUNCT
flr-365	35	18	trafton	trafton	PROPN
flr-365	35	19	&	&	CCONJ
flr-365	35	20	boehm	boehm	PROPN
flr-365	35	21	-	-	PUNCT
flr-365	35	22	davis	davis	PROPN
flr-365	35	23	,	,	PUNCT
flr-365	35	24	2008	2008	NUM
flr-365	35	25	)	)	PUNCT
flr-365	35	26	,	,	PUNCT
flr-365	35	27	where	where	SCONJ
flr-365	35	28	integration	integration	NOUN
flr-365	35	29	of	of	ADP
flr-365	35	30	relevant	relevant	ADJ
flr-365	35	31	visual	visual	ADJ
flr-365	35	32	attributes	attribute	NOUN
flr-365	35	33	on	on	ADP
flr-365	35	34	the	the	DET
flr-365	35	35	graph	graph	NOUN
flr-365	35	36	,	,	PUNCT
flr-365	35	37	such	such	ADJ
flr-365	35	38	as	as	ADP
flr-365	35	39	labels	label	NOUN
flr-365	35	40	,	,	PUNCT
flr-365	35	41	pattern	pattern	NOUN
flr-365	35	42	recognition	recognition	NOUN
flr-365	35	43	,	,	PUNCT
flr-365	35	44	or	or	CCONJ
flr-365	35	45	other	other	ADJ
flr-365	35	46	spatial	spatial	ADJ
flr-365	35	47	features	feature	NOUN
flr-365	35	48	contribute	contribute	VERB
flr-365	35	49	to	to	ADP
flr-365	35	50	higher	high	ADJ
flr-365	35	51	order	order	NOUN
flr-365	35	52	visual	visual	ADJ
flr-365	35	53	clusters	cluster	NOUN
flr-365	35	54	of	of	ADP
flr-365	35	55	information	information	NOUN
flr-365	35	56	,	,	PUNCT
flr-365	35	57	that	that	PRON
flr-365	35	58	are	be	AUX
flr-365	35	59	compared	compare	VERB
flr-365	35	60	to	to	PART
flr-365	35	61	create	create	VERB
flr-365	35	62	a	a	DET
flr-365	35	63	coherent	coherent	ADJ
flr-365	35	64	representation	representation	NOUN
flr-365	35	65	and	and	CCONJ
flr-365	35	66	response	response	NOUN
flr-365	35	67	.	.	PUNCT
flr-365	36	1	the	the	DET
flr-365	36	2	aim	aim	NOUN
flr-365	36	3	of	of	ADP
flr-365	36	4	this	this	DET
flr-365	36	5	research	research	NOUN
flr-365	36	6	was	be	AUX
flr-365	36	7	thus	thus	ADV
flr-365	36	8	to	to	PART
flr-365	36	9	use	use	VERB
flr-365	36	10	mathematical	mathematical	ADJ
flr-365	36	11	and	and	CCONJ
flr-365	36	12	machine	machine	NOUN
flr-365	36	13	learning	learning	NOUN
flr-365	36	14	based	base	VERB
flr-365	36	15	analysis	analysis	NOUN
flr-365	36	16	of	of	ADP
flr-365	36	17	eye	eye	NOUN
flr-365	36	18	tracking	track	VERB
flr-365	36	19	data	datum	NOUN
flr-365	36	20	to	to	PART
flr-365	36	21	better	well	ADV
flr-365	36	22	understand	understand	VERB
flr-365	36	23	the	the	DET
flr-365	36	24	visual	visual	ADJ
flr-365	36	25	and	and	CCONJ
flr-365	36	26	cognitive	cognitive	ADJ
flr-365	36	27	behaviours	behaviour	NOUN
flr-365	36	28	associated	associate	VERB
flr-365	36	29	with	with	ADP
flr-365	36	30	the	the	DET
flr-365	36	31	completion	completion	NOUN
flr-365	36	32	of	of	ADP
flr-365	36	33	a	a	DET
flr-365	36	34	graph	graph	NOUN
flr-365	36	35	task	task	NOUN
flr-365	36	36	in	in	ADP
flr-365	36	37	a	a	DET
flr-365	36	38	sample	sample	NOUN
flr-365	36	39	of	of	ADP
flr-365	36	40	children	child	NOUN
flr-365	36	41	in	in	ADP
flr-365	36	42	year	year	NOUN
flr-365	36	43	3	3	NUM
flr-365	36	44	.	.	PUNCT
flr-365	36	45	using	use	VERB
flr-365	36	46	a	a	DET
flr-365	36	47	desktop	desktop	NOUN
flr-365	36	48	eye	eye	NOUN
flr-365	36	49	tracking	tracking	NOUN
flr-365	36	50	system	system	NOUN
flr-365	36	51	,	,	PUNCT
flr-365	36	52	children	child	NOUN
flr-365	36	53	completed	complete	VERB
flr-365	36	54	a	a	DET
flr-365	36	55	mathematics	mathematic	NOUN
flr-365	36	56	task	task	NOUN
flr-365	36	57	that	that	PRON
flr-365	36	58	involved	involve	VERB
flr-365	36	59	comprehension	comprehension	NOUN
flr-365	36	60	of	of	ADP
flr-365	36	61	a	a	DET
flr-365	36	62	bar	bar	NOUN
flr-365	36	63	graph	graph	NOUN
flr-365	36	64	.	.	PUNCT
flr-365	37	1	the	the	DET
flr-365	37	2	scanpaths	scanpath	NOUN
flr-365	37	3	and	and	CCONJ
flr-365	37	4	the	the	DET
flr-365	37	5	accuracy	accuracy	NOUN
flr-365	37	6	of	of	ADP
flr-365	37	7	individual	individual	ADJ
flr-365	37	8	responses	response	NOUN
flr-365	37	9	to	to	ADP
flr-365	37	10	the	the	DET
flr-365	37	11	task	task	NOUN
flr-365	37	12	were	be	AUX
flr-365	37	13	analysed	analyse	VERB
flr-365	37	14	to	to	PART
flr-365	37	15	identify	identify	VERB
flr-365	37	16	the	the	DET
flr-365	37	17	visual	visual	ADJ
flr-365	37	18	cognitive	cognitive	ADJ
flr-365	37	19	behaviours	behaviour	NOUN
flr-365	37	20	when	when	SCONJ
flr-365	37	21	completing	complete	VERB
flr-365	37	22	the	the	DET
flr-365	37	23	graph	graph	NOUN
flr-365	37	24	task	task	NOUN
flr-365	37	25	,	,	PUNCT
flr-365	37	26	for	for	ADP
flr-365	37	27	example	example	NOUN
flr-365	37	28	,	,	PUNCT
flr-365	37	29	what	what	PRON
flr-365	37	30	happens	happen	VERB
flr-365	37	31	when	when	SCONJ
flr-365	37	32	children	child	NOUN
flr-365	37	33	are	be	AUX
flr-365	37	34	confronted	confront	VERB
flr-365	37	35	with	with	ADP
flr-365	37	36	such	such	DET
flr-365	37	37	a	a	DET
flr-365	37	38	task	task	NOUN
flr-365	37	39	,	,	PUNCT
flr-365	37	40	which	which	PRON
flr-365	37	41	features	feature	VERB
flr-365	37	42	children	child	NOUN
flr-365	37	43	look	look	VERB
flr-365	37	44	at	at	ADP
flr-365	37	45	,	,	PUNCT
flr-365	37	46	and	and	CCONJ
flr-365	37	47	the	the	DET
flr-365	37	48	order	order	NOUN
flr-365	37	49	in	in	ADP
flr-365	37	50	which	which	PRON
flr-365	37	51	relevant	relevant	ADJ
flr-365	37	52	information	information	NOUN
flr-365	37	53	is	be	AUX
flr-365	37	54	accessed	access	VERB
flr-365	37	55	.	.	PUNCT
flr-365	38	1	the	the	DET
flr-365	38	2	research	research	NOUN
flr-365	38	3	also	also	ADV
flr-365	38	4	aimed	aim	VERB
flr-365	38	5	to	to	PART
flr-365	38	6	determine	determine	VERB
flr-365	38	7	whether	whether	SCONJ
flr-365	38	8	the	the	DET
flr-365	38	9	gaze	gaze	NOUN
flr-365	38	10	patterns	pattern	NOUN
flr-365	38	11	for	for	ADP
flr-365	38	12	children	child	NOUN
flr-365	38	13	who	who	PRON
flr-365	38	14	correctly	correctly	ADV
flr-365	38	15	or	or	CCONJ
flr-365	38	16	incorrectly	incorrectly	ADV
flr-365	38	17	completed	complete	VERB
flr-365	38	18	the	the	DET
flr-365	38	19	task	task	NOUN
flr-365	38	20	were	be	AUX
flr-365	38	21	different	different	ADJ
flr-365	38	22	,	,	PUNCT
flr-365	38	23	and	and	CCONJ
flr-365	38	24	if	if	SCONJ
flr-365	38	25	so	so	ADV
flr-365	38	26	,	,	PUNCT
flr-365	38	27	to	to	PART
flr-365	38	28	identify	identify	VERB
flr-365	38	29	the	the	DET
flr-365	38	30	characteristics	characteristic	NOUN
flr-365	38	31	of	of	ADP
flr-365	38	32	the	the	DET
flr-365	38	33	different	different	ADJ
flr-365	38	34	visual	visual	ADJ
flr-365	38	35	cognitive	cognitive	ADJ
flr-365	38	36	behaviours	behaviour	NOUN
flr-365	38	37	.	.	PUNCT
flr-365	39	1	such	such	ADJ
flr-365	39	2	information	information	NOUN
flr-365	39	3	will	will	AUX
flr-365	39	4	enable	enable	VERB
flr-365	39	5	more	more	ADJ
flr-365	39	6	reliable	reliable	ADJ
flr-365	39	7	inferences	inference	NOUN
flr-365	39	8	about	about	ADP
flr-365	39	9	the	the	DET
flr-365	39	10	implicit	implicit	ADJ
flr-365	39	11	visual	visual	ADJ
flr-365	39	12	cognitive	cognitive	ADJ
flr-365	39	13	behaviours	behaviour	NOUN
flr-365	39	14	of	of	ADP
flr-365	39	15	children	child	NOUN
flr-365	39	16	when	when	SCONJ
flr-365	39	17	engaging	engage	VERB
flr-365	39	18	in	in	ADP
flr-365	39	19	a	a	DET
flr-365	39	20	graph	graph	NOUN
flr-365	39	21	problem	problem	NOUN
flr-365	39	22	-	-	PUNCT
flr-365	39	23	solving	solve	VERB
flr-365	39	24	task	task	NOUN
flr-365	39	25	and	and	CCONJ
flr-365	39	26	other	other	ADJ
flr-365	39	27	cognitive	cognitive	ADJ
flr-365	39	28	tasks	task	NOUN
flr-365	39	29	.	.	PUNCT
flr-365	40	1	2	2	X
flr-365	40	2	.	.	X
flr-365	40	3	method	method	VERB
flr-365	40	4	2.1	2.1	NUM
flr-365	40	5	participants	participant	NOUN
flr-365	40	6	participants	participant	NOUN
flr-365	40	7	included	include	VERB
flr-365	40	8	106	106	NUM
flr-365	40	9	year	year	NOUN
flr-365	40	10	3	3	NUM
flr-365	40	11	children	child	NOUN
flr-365	40	12	(	(	PUNCT
flr-365	40	13	58	58	NUM
flr-365	40	14	females	female	NOUN
flr-365	40	15	,	,	PUNCT
flr-365	40	16	48	48	NUM
flr-365	40	17	males	male	NOUN
flr-365	40	18	;	;	PUNCT
flr-365	40	19	mean	mean	VERB
flr-365	40	20	age	age	NOUN
flr-365	40	21	8.8	8.8	NUM
flr-365	40	22	±	±	NUM
flr-365	40	23	0.3	0.3	NUM
flr-365	40	24	years	year	NOUN
flr-365	40	25	)	)	PUNCT
flr-365	40	26	who	who	PRON
flr-365	40	27	completed	complete	VERB
flr-365	40	28	a	a	DET
flr-365	40	29	graphical	graphical	ADJ
flr-365	40	30	mathematics	mathematic	NOUN
flr-365	40	31	task	task	NOUN
flr-365	40	32	.	.	PUNCT
flr-365	41	1	children	child	NOUN
flr-365	41	2	were	be	AUX
flr-365	41	3	from	from	ADP
flr-365	41	4	three	three	NUM
flr-365	41	5	primary	primary	ADJ
flr-365	41	6	schools	school	NOUN
flr-365	41	7	in	in	ADP
flr-365	41	8	south	south	PROPN
flr-365	41	9	east	east	PROPN
flr-365	41	10	queensland	queensland	PROPN
flr-365	41	11	,	,	PUNCT
flr-365	41	12	australia	australia	PROPN
flr-365	41	13	.	.	PUNCT
flr-365	42	1	data	datum	NOUN
flr-365	42	2	collection	collection	NOUN
flr-365	42	3	occurred	occur	VERB
flr-365	42	4	in	in	ADP
flr-365	42	5	the	the	DET
flr-365	42	6	last	last	ADJ
flr-365	42	7	half	half	NOUN
flr-365	42	8	of	of	ADP
flr-365	42	9	the	the	DET
flr-365	42	10	school	school	NOUN
flr-365	42	11	year	year	NOUN
flr-365	42	12	,	,	PUNCT
flr-365	42	13	and	and	CCONJ
flr-365	42	14	the	the	DET
flr-365	42	15	graph	graph	NOUN
flr-365	42	16	task	task	NOUN
flr-365	42	17	formed	form	VERB
flr-365	42	18	part	part	NOUN
flr-365	42	19	of	of	ADP
flr-365	42	20	a	a	DET
flr-365	42	21	larger	large	ADJ
flr-365	42	22	study	study	NOUN
flr-365	42	23	that	that	PRON
flr-365	42	24	involved	involve	VERB
flr-365	42	25	eye	eye	NOUN
flr-365	42	26	tracking	tracking	NOUN
flr-365	42	27	while	while	SCONJ
flr-365	42	28	children	child	NOUN
flr-365	42	29	completed	complete	VERB
flr-365	42	30	a	a	DET
flr-365	42	31	series	series	NOUN
flr-365	42	32	of	of	ADP
flr-365	42	33	mathematics	mathematic	NOUN
flr-365	42	34	and	and	CCONJ
flr-365	42	35	reading	reading	NOUN
flr-365	42	36	tasks	task	NOUN
flr-365	42	37	.	.	PUNCT
flr-365	43	1	all	all	DET
flr-365	43	2	data	datum	NOUN
flr-365	43	3	collection	collection	NOUN
flr-365	43	4	occurred	occur	VERB
flr-365	43	5	in	in	ADP
flr-365	43	6	a	a	DET
flr-365	43	7	quiet	quiet	ADJ
flr-365	43	8	room	room	NOUN
flr-365	43	9	near	near	ADP
flr-365	43	10	the	the	DET
flr-365	43	11	respective	respective	ADJ
flr-365	43	12	classrooms	classroom	NOUN
flr-365	43	13	.	.	PUNCT
flr-365	44	1	the	the	DET
flr-365	44	2	study	study	NOUN
flr-365	44	3	was	be	AUX
flr-365	44	4	approved	approve	VERB
flr-365	44	5	by	by	ADP
flr-365	44	6	university	university	NOUN
flr-365	44	7	human	human	PROPN
flr-365	44	8	research	research	PROPN
flr-365	44	9	ethics	ethic	NOUN
flr-365	44	10	committee	committee	NOUN
flr-365	44	11	that	that	PRON
flr-365	44	12	operates	operate	VERB
flr-365	44	13	within	within	ADP
flr-365	44	14	the	the	DET
flr-365	44	15	australian	australian	ADJ
flr-365	44	16	national	national	ADJ
flr-365	44	17	statement	statement	NOUN
flr-365	44	18	on	on	ADP
flr-365	44	19	ethical	ethical	ADJ
flr-365	44	20	conduct	conduct	NOUN
flr-365	44	21	in	in	ADP
flr-365	44	22	human	human	ADJ
flr-365	44	23	research	research	NOUN
flr-365	44	24	.	.	PUNCT
flr-365	45	1	approval	approval	NOUN
flr-365	45	2	to	to	PART
flr-365	45	3	conduct	conduct	VERB
flr-365	45	4	research	research	NOUN
flr-365	45	5	in	in	ADP
flr-365	45	6	queensland	queensland	PROPN
flr-365	45	7	state	state	PROPN
flr-365	45	8	schools	school	NOUN
flr-365	45	9	was	be	AUX
flr-365	45	10	also	also	ADV
flr-365	45	11	granted	grant	VERB
flr-365	45	12	by	by	ADP
flr-365	45	13	the	the	DET
flr-365	45	14	queensland	queensland	NOUN
flr-365	45	15	government	government	NOUN
flr-365	45	16	,	,	PUNCT
flr-365	45	17	department	department	NOUN
flr-365	45	18	of	of	ADP
flr-365	45	19	education	education	NOUN
flr-365	45	20	and	and	CCONJ
flr-365	45	21	training	training	NOUN
flr-365	45	22	.	.	PUNCT
flr-365	46	1	2.2	2.2	NUM
flr-365	46	2	task	task	NOUN
flr-365	46	3	the	the	DET
flr-365	46	4	design	design	NOUN
flr-365	46	5	of	of	ADP
flr-365	46	6	the	the	DET
flr-365	46	7	graph	graph	NOUN
flr-365	46	8	task	task	NOUN
flr-365	46	9	was	be	AUX
flr-365	46	10	based	base	VERB
flr-365	46	11	on	on	ADP
flr-365	46	12	the	the	DET
flr-365	46	13	year	year	NOUN
flr-365	46	14	3	3	NUM
flr-365	46	15	australian	australian	ADJ
flr-365	46	16	mathematics	mathematic	NOUN
flr-365	46	17	curriculum	curriculum	NOUN
flr-365	46	18	where	where	SCONJ
flr-365	46	19	children	child	NOUN
flr-365	46	20	are	be	AUX
flr-365	46	21	interpreting	interpret	VERB
flr-365	46	22	and	and	CCONJ
flr-365	46	23	comparing	compare	VERB
flr-365	46	24	data	datum	NOUN
flr-365	46	25	displays	display	NOUN
flr-365	46	26	(	(	PUNCT
flr-365	46	27	acara	acara	NOUN
flr-365	46	28	,	,	PUNCT
flr-365	46	29	2016	2016	NUM
flr-365	46	30	)	)	PUNCT
flr-365	46	31	.	.	PUNCT
flr-365	47	1	as	as	SCONJ
flr-365	47	2	presented	present	VERB
flr-365	47	3	in	in	ADP
flr-365	47	4	figure	figure	NOUN
flr-365	47	5	1	1	NUM
flr-365	47	6	,	,	PUNCT
flr-365	47	7	the	the	DET
flr-365	47	8	graph	graph	NOUN
flr-365	47	9	task	task	NOUN
flr-365	47	10	included	include	VERB
flr-365	47	11	:	:	PUNCT
flr-365	47	12	a	a	X
flr-365	47	13	)	)	PUNCT
flr-365	47	14	a	a	DET
flr-365	47	15	bar	bar	NOUN
flr-365	47	16	graph	graph	NOUN
flr-365	47	17	,	,	PUNCT
flr-365	47	18	where	where	SCONJ
flr-365	47	19	the	the	DET
flr-365	47	20	height	height	NOUN
flr-365	47	21	of	of	ADP
flr-365	47	22	each	each	DET
flr-365	47	23	bar	bar	NOUN
flr-365	47	24	indicated	indicate	VERB
flr-365	47	25	the	the	DET
flr-365	47	26	number	number	NOUN
flr-365	47	27	of	of	ADP
flr-365	47	28	hours	hour	NOUN
flr-365	47	29	worked	work	VERB
flr-365	47	30	by	by	ADP
flr-365	47	31	sarah	sarah	PROPN
flr-365	47	32	during	during	ADP
flr-365	47	33	a	a	DET
flr-365	47	34	given	give	VERB
flr-365	47	35	week	week	NOUN
flr-365	47	36	;	;	PUNCT
flr-365	47	37	b	b	X
flr-365	47	38	)	)	PUNCT
flr-365	47	39	a	a	DET
flr-365	47	40	labelled	label	VERB
flr-365	47	41	coordinate	coordinate	NOUN
flr-365	47	42	system	system	NOUN
flr-365	47	43	,	,	PUNCT
flr-365	47	44	where	where	SCONJ
flr-365	47	45	the	the	DET
flr-365	47	46	x	x	NOUN
flr-365	47	47	-	-	NOUN
flr-365	47	48	axis	axis	NOUN
flr-365	47	49	had	have	VERB
flr-365	47	50	the	the	DET
flr-365	47	51	week	week	NOUN
flr-365	47	52	number	number	NOUN
flr-365	47	53	labels	label	NOUN
flr-365	47	54	,	,	PUNCT
flr-365	47	55	and	and	CCONJ
flr-365	47	56	the	the	DET
flr-365	47	57	y	y	NOUN
flr-365	47	58	-	-	PUNCT
flr-365	47	59	axis	axis	NOUN
flr-365	47	60	had	have	VERB
flr-365	47	61	numbers	number	NOUN
flr-365	47	62	corresponding	correspond	VERB
flr-365	47	63	to	to	ADP
flr-365	47	64	hours	hour	NOUN
flr-365	47	65	;	;	PUNCT
flr-365	47	66	c	c	X
flr-365	47	67	)	)	PUNCT
flr-365	47	68	a	a	DET
flr-365	47	69	sentence	sentence	NOUN
flr-365	47	70	indicating	indicate	VERB
flr-365	47	71	sarah	sarah	PROPN
flr-365	47	72	’s	’s	PART
flr-365	47	73	hourly	hourly	ADJ
flr-365	47	74	wage	wage	NOUN
flr-365	47	75	;	;	PUNCT
flr-365	47	76	d	d	X
flr-365	47	77	)	)	PUNCT
flr-365	47	78	another	another	DET
flr-365	47	79	sentence	sentence	NOUN
flr-365	47	80	indicating	indicate	VERB
flr-365	47	81	the	the	DET
flr-365	47	82	question	question	NOUN
flr-365	47	83	related	relate	VERB
flr-365	47	84	to	to	ADP
flr-365	47	85	sarah	sarah	PROPN
flr-365	47	86	’s	’s	PART
flr-365	47	87	wages	wage	NOUN
flr-365	47	88	in	in	ADP
flr-365	47	89	week	week	NOUN
flr-365	47	90	3	3	NUM
flr-365	47	91	.	.	NOUN
flr-365	47	92	2.3	2.3	NUM
flr-365	47	93	apparatus	apparatus	NOUN
flr-365	47	94	a	a	DET
flr-365	47	95	screen	screen	NOUN
flr-365	47	96	-	-	PUNCT
flr-365	47	97	based	base	VERB
flr-365	47	98	tobii	tobii	PROPN
flr-365	47	99	eye	eye	PROPN
flr-365	47	100	tracker	tracker	PROPN
flr-365	47	101	(	(	PUNCT
flr-365	47	102	tx300	tx300	ADJ
flr-365	47	103	)	)	PUNCT
flr-365	47	104	operating	operate	VERB
flr-365	47	105	at	at	ADP
flr-365	47	106	300	300	NUM
flr-365	47	107	hz	hz	NOUN
flr-365	47	108	recorded	record	VERB
flr-365	47	109	the	the	DET
flr-365	47	110	eye	eye	NOUN
flr-365	47	111	movements	movement	NOUN
flr-365	47	112	of	of	ADP
flr-365	47	113	the	the	DET
flr-365	47	114	children	child	NOUN
flr-365	47	115	as	as	SCONJ
flr-365	47	116	they	they	PRON
flr-365	47	117	completed	complete	VERB
flr-365	47	118	the	the	DET
flr-365	47	119	graph	graph	NOUN
flr-365	47	120	task	task	NOUN
flr-365	47	121	.	.	PUNCT
flr-365	48	1	the	the	DET
flr-365	48	2	task	task	NOUN
flr-365	48	3	was	be	AUX
flr-365	48	4	presented	present	VERB
flr-365	48	5	on	on	ADP
flr-365	48	6	a	a	DET
flr-365	48	7	23	23	NUM
flr-365	48	8	inch	inch	NOUN
flr-365	48	9	screen	screen	NOUN
flr-365	48	10	and	and	CCONJ
flr-365	48	11	participants	participant	NOUN
flr-365	48	12	sat	sit	VERB
flr-365	48	13	comfortably	comfortably	ADV
flr-365	48	14	(	(	PUNCT
flr-365	48	15	without	without	ADP
flr-365	48	16	restraint	restraint	NOUN
flr-365	48	17	)	)	PUNCT
flr-365	48	18	at	at	ADP
flr-365	48	19	a	a	DET
flr-365	48	20	working	work	VERB
flr-365	48	21	distance	distance	NOUN
flr-365	48	22	of	of	ADP
flr-365	48	23	approximately	approximately	ADV
flr-365	48	24	60	60	NUM
flr-365	48	25	cm	cm	NOUN
flr-365	48	26	.	.	PUNCT
flr-365	49	1	the	the	DET
flr-365	49	2	calibration	calibration	NOUN
flr-365	49	3	used	use	VERB
flr-365	49	4	the	the	DET
flr-365	49	5	tx300	tx300	NUM
flr-365	49	6	nine	nine	NUM
flr-365	49	7	point	point	NOUN
flr-365	49	8	calibration	calibration	NOUN
flr-365	49	9	procedure	procedure	NOUN
flr-365	49	10	,	,	PUNCT
flr-365	49	11	with	with	ADP
flr-365	49	12	re	re	NOUN
flr-365	49	13	-	-	NOUN
flr-365	49	14	calibration	calibration	NOUN
flr-365	49	15	conducted	conduct	VERB
flr-365	49	16	for	for	ADP
flr-365	49	17	any	any	DET
flr-365	49	18	points	point	NOUN
flr-365	49	19	where	where	SCONJ
flr-365	49	20	calibration	calibration	NOUN
flr-365	49	21	was	be	AUX
flr-365	49	22	recorded	record	VERB
flr-365	49	23	as	as	ADP
flr-365	49	24	poor	poor	ADJ
flr-365	49	25	(	(	PUNCT
flr-365	49	26	denoted	denote	VERB
flr-365	49	27	in	in	ADP
flr-365	49	28	red	red	NOUN
flr-365	49	29	)	)	PUNCT
flr-365	49	30	.	.	PUNCT
flr-365	50	1	only	only	ADV
flr-365	50	2	when	when	SCONJ
flr-365	50	3	the	the	DET
flr-365	50	4	calibration	calibration	NOUN
flr-365	50	5	procedure	procedure	NOUN
flr-365	50	6	was	be	AUX
flr-365	50	7	completed	complete	VERB
flr-365	50	8	for	for	ADP
flr-365	50	9	all	all	DET
flr-365	50	10	nine	nine	NUM
flr-365	50	11	points	point	NOUN
flr-365	50	12	(	(	PUNCT
flr-365	50	13	denoted	denote	VERB
flr-365	50	14	in	in	ADP
flr-365	50	15	green	green	NOUN
flr-365	50	16	)	)	PUNCT
flr-365	50	17	was	be	AUX
flr-365	50	18	the	the	DET
flr-365	50	19	eye	eye	NOUN
flr-365	50	20	tracking	tracking	NOUN
flr-365	50	21	task	task	NOUN
flr-365	50	22	started	start	VERB
flr-365	50	23	.	.	PUNCT
flr-365	51	1	events	event	NOUN
flr-365	51	2	were	be	AUX
flr-365	51	3	detected	detect	VERB
flr-365	51	4	using	use	VERB
flr-365	51	5	a	a	DET
flr-365	51	6	dispersion	dispersion	NOUN
flr-365	51	7	based	base	VERB
flr-365	51	8	algorithm	algorithm	NOUN
flr-365	51	9	for	for	ADP
flr-365	51	10	detecting	detect	VERB
flr-365	51	11	fixations	fixation	NOUN
flr-365	51	12	.	.	PUNCT
flr-365	52	1	a	a	DET
flr-365	52	2	fixation	fixation	NOUN
flr-365	52	3	was	be	AUX
flr-365	52	4	defined	define	VERB
flr-365	52	5	as	as	ADP
flr-365	52	6	static	static	ADJ
flr-365	52	7	eye	eye	NOUN
flr-365	52	8	movements	movement	NOUN
flr-365	52	9	with	with	ADP
flr-365	52	10	gaze	gaze	NOUN
flr-365	52	11	positions	position	NOUN
flr-365	52	12	remaining	remain	VERB
flr-365	52	13	within	within	ADP
flr-365	52	14	a	a	DET
flr-365	52	15	visual	visual	ADJ
flr-365	52	16	angle	angle	NOUN
flr-365	52	17	of	of	ADP
flr-365	52	18	1.6	1.6	NUM
flr-365	52	19	°	°	NOUN
flr-365	52	20	for	for	ADP
flr-365	52	21	at	at	ADV
flr-365	52	22	least	least	ADV
flr-365	52	23	100	100	NUM
flr-365	52	24	milliseconds	millisecond	NOUN
flr-365	52	25	(	(	PUNCT
flr-365	52	26	tobii	tobii	NOUN
flr-365	52	27	technology	technology	NOUN
flr-365	52	28	,	,	PUNCT
flr-365	52	29	2014	2014	NUM
flr-365	52	30	)	)	PUNCT
flr-365	52	31	.	.	PUNCT
flr-365	53	1	for	for	ADP
flr-365	53	2	the	the	DET
flr-365	53	3	graph	graph	NOUN
flr-365	53	4	task	task	NOUN
flr-365	53	5	,	,	PUNCT
flr-365	53	6	the	the	DET
flr-365	53	7	106	106	NUM
flr-365	53	8	participants	participant	NOUN
flr-365	53	9	had	have	VERB
flr-365	53	10	a	a	DET
flr-365	53	11	mean	mean	ADJ
flr-365	53	12	tracking	tracking	NOUN
flr-365	53	13	percentage	percentage	NOUN
flr-365	53	14	of	of	ADP
flr-365	53	15	87.8	87.8	NUM
flr-365	53	16	±	±	NUM
flr-365	53	17	9.8	9.8	NUM
flr-365	53	18	%	%	NOUN
flr-365	53	19	.	.	PUNCT
flr-365	54	1	the	the	DET
flr-365	54	2	output	output	NOUN
flr-365	54	3	of	of	ADP
flr-365	54	4	the	the	DET
flr-365	54	5	eye	eye	NOUN
flr-365	54	6	tracking	tracking	NOUN
flr-365	54	7	device	device	NOUN
flr-365	54	8	is	be	AUX
flr-365	54	9	typically	typically	ADV
flr-365	54	10	a	a	DET
flr-365	54	11	sequence	sequence	NOUN
flr-365	54	12	of	of	ADP
flr-365	54	13	coordinate	coordinate	NOUN
flr-365	54	14	pairs	pair	NOUN
flr-365	54	15	relative	relative	ADJ
flr-365	54	16	to	to	ADP
flr-365	54	17	the	the	DET
flr-365	54	18	scene	scene	NOUN
flr-365	54	19	that	that	SCONJ
flr-365	54	20	the	the	DET
flr-365	54	21	participant	participant	NOUN
flr-365	54	22	is	be	AUX
flr-365	54	23	viewing	view	VERB
flr-365	54	24	,	,	PUNCT
flr-365	54	25	together	together	ADV
flr-365	54	26	with	with	ADP
flr-365	54	27	a	a	DET
flr-365	54	28	time	time	NOUN
flr-365	54	29	stamp	stamp	NOUN
flr-365	54	30	when	when	SCONJ
flr-365	54	31	the	the	DET
flr-365	54	32	locus	locus	NOUN
flr-365	54	33	of	of	ADP
flr-365	54	34	gaze	gaze	NOUN
flr-365	54	35	is	be	AUX
flr-365	54	36	positioned	position	VERB
flr-365	54	37	at	at	ADP
flr-365	54	38	a	a	DET
flr-365	54	39	given	give	VERB
flr-365	54	40	coordinate	coordinate	NOUN
flr-365	54	41	pair	pair	NOUN
flr-365	54	42	.	.	PUNCT
flr-365	55	1	2.4	2.4	NUM
flr-365	55	2	data	datum	NOUN
flr-365	55	3	extraction	extraction	NOUN
flr-365	55	4	the	the	DET
flr-365	55	5	visual	visual	ADJ
flr-365	55	6	stimulus	stimulus	NOUN
flr-365	55	7	(	(	PUNCT
flr-365	55	8	the	the	DET
flr-365	55	9	graph	graph	NOUN
flr-365	55	10	on	on	ADP
flr-365	55	11	the	the	DET
flr-365	55	12	screen	screen	NOUN
flr-365	55	13	;	;	PUNCT
flr-365	55	14	figure	figure	NOUN
flr-365	55	15	1	1	NUM
flr-365	55	16	)	)	PUNCT
flr-365	55	17	was	be	AUX
flr-365	55	18	subdivided	subdivide	VERB
flr-365	55	19	into	into	ADP
flr-365	55	20	regions	region	NOUN
flr-365	55	21	known	know	VERB
flr-365	55	22	as	as	ADP
flr-365	55	23	areas	area	NOUN
flr-365	55	24	of	of	ADP
flr-365	55	25	interest	interest	NOUN
flr-365	55	26	(	(	PUNCT
flr-365	55	27	aoi	aoi	PROPN
flr-365	55	28	)	)	PUNCT
flr-365	55	29	.	.	PUNCT
flr-365	56	1	initially	initially	ADV
flr-365	56	2	,	,	PUNCT
flr-365	56	3	aoi	aoi	PROPN
flr-365	56	4	sequences	sequence	NOUN
flr-365	56	5	were	be	AUX
flr-365	56	6	generated	generate	VERB
flr-365	56	7	from	from	ADP
flr-365	56	8	the	the	DET
flr-365	56	9	sequence	sequence	NOUN
flr-365	56	10	of	of	ADP
flr-365	56	11	fixations	fixation	NOUN
flr-365	56	12	,	,	PUNCT
flr-365	56	13	as	as	SCONJ
flr-365	56	14	determined	determine	VERB
flr-365	56	15	by	by	ADP
flr-365	56	16	the	the	DET
flr-365	56	17	dispersion	dispersion	NOUN
flr-365	56	18	-	-	PUNCT
flr-365	56	19	based	base	VERB
flr-365	56	20	algorithm	algorithm	NOUN
flr-365	56	21	.	.	PUNCT
flr-365	57	1	the	the	DET
flr-365	57	2	first	first	ADJ
flr-365	57	3	step	step	NOUN
flr-365	57	4	involved	involve	VERB
flr-365	57	5	determining	determine	VERB
flr-365	57	6	which	which	PRON
flr-365	57	7	were	be	AUX
flr-365	57	8	the	the	DET
flr-365	57	9	most	most	ADV
flr-365	57	10	critical	critical	ADJ
flr-365	57	11	aois	aois	NOUN
flr-365	57	12	and	and	CCONJ
flr-365	57	13	labelling	label	VERB
flr-365	57	14	them	they	PRON
flr-365	57	15	as	as	ADP
flr-365	57	16	a1	a1	NOUN
flr-365	57	17	(	(	PUNCT
flr-365	57	18	wage	wage	NOUN
flr-365	57	19	information	information	NOUN
flr-365	57	20	(	(	PUNCT
flr-365	57	21	part	part	NOUN
flr-365	57	22	of	of	ADP
flr-365	57	23	sentence	sentence	NOUN
flr-365	57	24	below	below	ADP
flr-365	57	25	the	the	DET
flr-365	57	26	graph	graph	NOUN
flr-365	57	27	)	)	PUNCT
flr-365	57	28	)	)	PUNCT
flr-365	57	29	,	,	PUNCT
flr-365	57	30	a2	a2	PROPN
flr-365	57	31	(	(	PUNCT
flr-365	57	32	week	week	NOUN
flr-365	57	33	number	number	NOUN
flr-365	57	34	(	(	PUNCT
flr-365	57	35	part	part	NOUN
flr-365	57	36	of	of	ADP
flr-365	57	37	sentence	sentence	NOUN
flr-365	57	38	below	below	ADP
flr-365	57	39	the	the	DET
flr-365	57	40	graph	graph	NOUN
flr-365	57	41	)	)	PUNCT
flr-365	57	42	)	)	PUNCT
flr-365	57	43	,	,	PUNCT
flr-365	57	44	a3	a3	NOUN
flr-365	57	45	(	(	PUNCT
flr-365	57	46	week	week	NOUN
flr-365	57	47	3	3	NUM
flr-365	57	48	bar	bar	NOUN
flr-365	57	49	)	)	PUNCT
flr-365	57	50	,	,	PUNCT
flr-365	57	51	and	and	CCONJ
flr-365	57	52	a4	a4	NOUN
flr-365	57	53	(	(	PUNCT
flr-365	57	54	number	number	NOUN
flr-365	57	55	region	region	NOUN
flr-365	57	56	containing	contain	VERB
flr-365	57	57	the	the	DET
flr-365	57	58	number	number	NOUN
flr-365	57	59	of	of	ADP
flr-365	57	60	hours	hour	NOUN
flr-365	57	61	corresponding	correspond	VERB
flr-365	57	62	to	to	ADP
flr-365	57	63	week	week	NOUN
flr-365	57	64	3	3	NUM
flr-365	57	65	)	)	PUNCT
flr-365	57	66	.	.	PUNCT
flr-365	58	1	these	these	DET
flr-365	58	2	aois	aois	NOUN
flr-365	58	3	were	be	AUX
flr-365	58	4	considered	consider	VERB
flr-365	58	5	as	as	ADP
flr-365	58	6	the	the	DET
flr-365	58	7	minimum	minimum	ADJ
flr-365	58	8	number	number	NOUN
flr-365	58	9	of	of	ADP
flr-365	58	10	areas	area	NOUN
flr-365	58	11	that	that	PRON
flr-365	58	12	needed	need	VERB
flr-365	58	13	to	to	PART
flr-365	58	14	be	be	AUX
flr-365	58	15	fixated	fixated	ADJ
flr-365	58	16	to	to	PART
flr-365	58	17	complete	complete	VERB
flr-365	58	18	the	the	DET
flr-365	58	19	graph	graph	NOUN
flr-365	58	20	task	task	NOUN
flr-365	58	21	successfully	successfully	ADV
flr-365	58	22	.	.	PUNCT
flr-365	59	1	the	the	DET
flr-365	59	2	other	other	ADJ
flr-365	59	3	aois	aois	NOUN
flr-365	59	4	were	be	AUX
flr-365	59	5	labelled	label	VERB
flr-365	59	6	as	as	ADP
flr-365	59	7	somewhat	somewhat	ADV
flr-365	59	8	critical	critical	ADJ
flr-365	59	9	(	(	PUNCT
flr-365	59	10	b	b	NOUN
flr-365	59	11	)	)	PUNCT
flr-365	59	12	and	and	CCONJ
flr-365	59	13	less	less	ADV
flr-365	59	14	critical	critical	ADJ
flr-365	59	15	(	(	PUNCT
flr-365	59	16	c	c	NOUN
flr-365	59	17	)	)	PUNCT
flr-365	59	18	.	.	PUNCT
flr-365	60	1	the	the	DET
flr-365	60	2	categorisation	categorisation	NOUN
flr-365	60	3	of	of	ADP
flr-365	60	4	b	b	PROPN
flr-365	60	5	areas	area	NOUN
flr-365	60	6	as	as	ADP
flr-365	60	7	somewhat	somewhat	ADV
flr-365	60	8	critical	critical	ADJ
flr-365	60	9	was	be	AUX
flr-365	60	10	derived	derive	VERB
flr-365	60	11	as	as	ADP
flr-365	60	12	part	part	NOUN
flr-365	60	13	of	of	ADP
flr-365	60	14	an	an	DET
flr-365	60	15	iterative	iterative	NOUN
flr-365	60	16	process	process	NOUN
flr-365	60	17	,	,	PUNCT
flr-365	60	18	incorporating	incorporate	VERB
flr-365	60	19	typical	typical	ADJ
flr-365	60	20	classroom	classroom	NOUN
flr-365	60	21	practice	practice	NOUN
flr-365	60	22	and	and	CCONJ
flr-365	60	23	qualitative	qualitative	ADJ
flr-365	60	24	inspection	inspection	NOUN
flr-365	60	25	of	of	ADP
flr-365	60	26	the	the	DET
flr-365	60	27	scanpaths	scanpath	NOUN
flr-365	60	28	.	.	PUNCT
flr-365	61	1	typical	typical	ADJ
flr-365	61	2	classroom	classroom	NOUN
flr-365	61	3	practice	practice	NOUN
flr-365	61	4	,	,	PUNCT
flr-365	61	5	or	or	CCONJ
flr-365	61	6	the	the	DET
flr-365	61	7	procedural	procedural	ADJ
flr-365	61	8	frameworks	framework	NOUN
flr-365	61	9	used	use	VERB
flr-365	61	10	to	to	PART
flr-365	61	11	support	support	VERB
flr-365	61	12	children	child	NOUN
flr-365	61	13	engaging	engage	VERB
flr-365	61	14	with	with	ADP
flr-365	61	15	graphs	graph	NOUN
flr-365	61	16	,	,	PUNCT
flr-365	61	17	usually	usually	ADV
flr-365	61	18	includes	include	VERB
flr-365	61	19	reading	read	VERB
flr-365	61	20	the	the	DET
flr-365	61	21	title	title	NOUN
flr-365	61	22	and	and	CCONJ
flr-365	61	23	axis	axis	ADJ
flr-365	61	24	labels	label	NOUN
flr-365	61	25	as	as	ADP
flr-365	61	26	an	an	DET
flr-365	61	27	initial	initial	ADJ
flr-365	61	28	orientation	orientation	NOUN
flr-365	61	29	to	to	ADP
flr-365	61	30	the	the	DET
flr-365	61	31	graph	graph	NOUN
flr-365	61	32	;	;	PUNCT
flr-365	61	33	these	these	DET
flr-365	61	34	areas	area	NOUN
flr-365	61	35	were	be	AUX
flr-365	61	36	therefore	therefore	ADV
flr-365	61	37	labelled	label	VERB
flr-365	61	38	as	as	ADP
flr-365	61	39	somewhat	somewhat	ADV
flr-365	61	40	critical	critical	ADJ
flr-365	61	41	b	b	NOUN
flr-365	61	42	areas	area	NOUN
flr-365	61	43	.	.	PUNCT
flr-365	62	1	furthermore	furthermore	ADV
flr-365	62	2	,	,	PUNCT
flr-365	62	3	qualitative	qualitative	ADJ
flr-365	62	4	inspection	inspection	NOUN
flr-365	62	5	of	of	ADP
flr-365	62	6	scanpaths	scanpath	NOUN
flr-365	62	7	revealed	reveal	VERB
flr-365	62	8	that	that	SCONJ
flr-365	62	9	when	when	SCONJ
flr-365	62	10	reading	read	VERB
flr-365	62	11	the	the	DET
flr-365	62	12	sentences	sentence	NOUN
flr-365	62	13	below	below	ADP
flr-365	62	14	the	the	DET
flr-365	62	15	graph	graph	NOUN
flr-365	62	16	,	,	PUNCT
flr-365	62	17	some	some	DET
flr-365	62	18	children	child	NOUN
flr-365	62	19	failed	fail	VERB
flr-365	62	20	to	to	PART
flr-365	62	21	read	read	VERB
flr-365	62	22	the	the	DET
flr-365	62	23	full	full	ADJ
flr-365	62	24	sentence	sentence	NOUN
flr-365	62	25	and	and	CCONJ
flr-365	62	26	did	do	AUX
flr-365	62	27	not	not	PART
flr-365	62	28	access	access	VERB
flr-365	62	29	the	the	DET
flr-365	62	30	most	most	ADV
flr-365	62	31	critical	critical	ADJ
flr-365	62	32	information	information	NOUN
flr-365	62	33	(	(	PUNCT
flr-365	62	34	a1	a1	NOUN
flr-365	62	35	and	and	CCONJ
flr-365	62	36	a2	a2	NOUN
flr-365	62	37	)	)	PUNCT
flr-365	62	38	,	,	PUNCT
flr-365	62	39	but	but	CCONJ
flr-365	62	40	did	do	AUX
flr-365	62	41	read	read	VERB
flr-365	62	42	the	the	DET
flr-365	62	43	first	first	ADJ
flr-365	62	44	part	part	NOUN
flr-365	62	45	of	of	ADP
flr-365	62	46	each	each	PRON
flr-365	62	47	of	of	ADP
flr-365	62	48	the	the	DET
flr-365	62	49	two	two	NUM
flr-365	62	50	sentences	sentence	NOUN
flr-365	62	51	.	.	PUNCT
flr-365	63	1	to	to	PART
flr-365	63	2	enable	enable	VERB
flr-365	63	3	identification	identification	NOUN
flr-365	63	4	of	of	ADP
flr-365	63	5	this	this	DET
flr-365	63	6	type	type	NOUN
flr-365	63	7	of	of	ADP
flr-365	63	8	incomplete	incomplete	ADJ
flr-365	63	9	reading	reading	NOUN
flr-365	63	10	behaviour	behaviour	NOUN
flr-365	63	11	,	,	PUNCT
flr-365	63	12	the	the	DET
flr-365	63	13	sentences	sentence	NOUN
flr-365	63	14	were	be	AUX
flr-365	63	15	separated	separate	VERB
flr-365	63	16	into	into	ADP
flr-365	63	17	two	two	NUM
flr-365	63	18	different	different	ADJ
flr-365	63	19	areas	area	NOUN
flr-365	63	20	,	,	PUNCT
flr-365	63	21	indicating	indicate	VERB
flr-365	63	22	somewhat	somewhat	ADV
flr-365	63	23	critical	critical	ADJ
flr-365	63	24	(	(	PUNCT
flr-365	63	25	b	b	NOUN
flr-365	63	26	)	)	PUNCT
flr-365	63	27	and	and	CCONJ
flr-365	63	28	most	most	ADV
flr-365	63	29	critical	critical	ADJ
flr-365	63	30	(	(	PUNCT
flr-365	63	31	a	a	PRON
flr-365	63	32	)	)	PUNCT
flr-365	63	33	information	information	NOUN
flr-365	63	34	.	.	PUNCT
flr-365	64	1	finally	finally	ADV
flr-365	64	2	,	,	PUNCT
flr-365	64	3	the	the	PRON
flr-365	64	4	less	less	ADV
flr-365	64	5	critical	critical	ADJ
flr-365	64	6	c	c	NOUN
flr-365	64	7	areas	area	NOUN
flr-365	64	8	were	be	AUX
flr-365	64	9	classified	classify	VERB
flr-365	64	10	because	because	SCONJ
flr-365	64	11	they	they	PRON
flr-365	64	12	represented	represent	VERB
flr-365	64	13	procedural	procedural	ADJ
flr-365	64	14	checking	checking	NOUN
flr-365	64	15	that	that	PRON
flr-365	64	16	may	may	AUX
flr-365	64	17	be	be	AUX
flr-365	64	18	promoted	promote	VERB
flr-365	64	19	as	as	ADP
flr-365	64	20	part	part	NOUN
flr-365	64	21	of	of	ADP
flr-365	64	22	classroom	classroom	NOUN
flr-365	64	23	practice	practice	NOUN
flr-365	64	24	,	,	PUNCT
flr-365	64	25	for	for	ADP
flr-365	64	26	example	example	NOUN
flr-365	64	27	,	,	PUNCT
flr-365	64	28	systematically	systematically	ADV
flr-365	64	29	checking	check	VERB
flr-365	64	30	all	all	DET
flr-365	64	31	bars	bar	NOUN
flr-365	64	32	on	on	ADP
flr-365	64	33	the	the	DET
flr-365	64	34	bar	bar	NOUN
flr-365	64	35	graph	graph	NOUN
flr-365	64	36	before	before	ADP
flr-365	64	37	providing	provide	VERB
flr-365	64	38	a	a	DET
flr-365	64	39	response	response	NOUN
flr-365	64	40	.	.	PUNCT
flr-365	65	1	figure	figure	NOUN
flr-365	65	2	1	1	NUM
flr-365	65	3	.	.	PUNCT
flr-365	66	1	the	the	DET
flr-365	66	2	graph	graph	NOUN
flr-365	66	3	task	task	PROPN
flr-365	66	4	visual	visual	ADJ
flr-365	66	5	stimulus	stimulus	NOUN
flr-365	66	6	partitioned	partition	VERB
flr-365	66	7	into	into	ADP
flr-365	66	8	areas	area	NOUN
flr-365	66	9	of	of	ADP
flr-365	66	10	interest	interest	NOUN
flr-365	66	11	(	(	PUNCT
flr-365	66	12	aois	aois	PROPN
flr-365	66	13	)	)	PUNCT
flr-365	66	14	.	.	PUNCT
flr-365	67	1	in	in	ADP
flr-365	67	2	this	this	DET
flr-365	67	3	diagram	diagram	NOUN
flr-365	67	4	,	,	PUNCT
flr-365	67	5	dashed	dash	VERB
flr-365	67	6	lines	line	NOUN
flr-365	67	7	indicate	indicate	VERB
flr-365	67	8	the	the	DET
flr-365	67	9	original	original	ADJ
flr-365	67	10	stimulus	stimulus	ADJ
flr-365	67	11	size	size	NOUN
flr-365	67	12	and	and	CCONJ
flr-365	67	13	solid	solid	ADJ
flr-365	67	14	lines	line	NOUN
flr-365	67	15	indicate	indicate	VERB
flr-365	67	16	the	the	DET
flr-365	67	17	alignment	alignment	NOUN
flr-365	67	18	of	of	ADP
flr-365	67	19	displacement	displacement	ADJ
flr-365	67	20	zones	zone	NOUN
flr-365	67	21	for	for	ADP
flr-365	67	22	each	each	DET
flr-365	67	23	aoi	aoi	NOUN
flr-365	67	24	.	.	PUNCT
flr-365	68	1	the	the	DET
flr-365	68	2	size	size	NOUN
flr-365	68	3	of	of	ADP
flr-365	68	4	each	each	DET
flr-365	68	5	aoi	aoi	NOUN
flr-365	68	6	regardless	regardless	ADV
flr-365	68	7	of	of	ADP
flr-365	68	8	whether	whether	SCONJ
flr-365	68	9	they	they	PRON
flr-365	68	10	were	be	AUX
flr-365	68	11	categorised	categorise	VERB
flr-365	68	12	as	as	ADP
flr-365	68	13	a	a	DET
flr-365	68	14	,	,	PUNCT
flr-365	68	15	b	b	NOUN
flr-365	68	16	or	or	CCONJ
flr-365	68	17	c	c	NOUN
flr-365	68	18	,	,	PUNCT
flr-365	68	19	was	be	AUX
flr-365	68	20	calculated	calculate	VERB
flr-365	68	21	using	use	VERB
flr-365	68	22	two	two	NUM
flr-365	68	23	criteria	criterion	NOUN
flr-365	68	24	;	;	PUNCT
flr-365	68	25	first	first	ADV
flr-365	68	26	,	,	PUNCT
flr-365	68	27	the	the	DET
flr-365	68	28	aoi	aoi	NOUN
flr-365	68	29	had	have	VERB
flr-365	68	30	to	to	PART
flr-365	68	31	allow	allow	VERB
flr-365	68	32	for	for	ADP
flr-365	68	33	vertical	vertical	ADJ
flr-365	68	34	and	and	CCONJ
flr-365	68	35	horizontal	horizontal	ADJ
flr-365	68	36	displacement	displacement	ADJ
flr-365	68	37	errors	error	NOUN
flr-365	68	38	in	in	ADP
flr-365	68	39	the	the	DET
flr-365	68	40	visual	visual	ADJ
flr-365	68	41	scanpath	scanpath	NOUN
flr-365	68	42	,	,	PUNCT
flr-365	68	43	and	and	CCONJ
flr-365	68	44	second	second	ADJ
flr-365	68	45	,	,	PUNCT
flr-365	68	46	the	the	DET
flr-365	68	47	aois	aois	NOUN
flr-365	68	48	could	could	AUX
flr-365	68	49	not	not	PART
flr-365	68	50	overlap	overlap	VERB
flr-365	68	51	(	(	PUNCT
flr-365	68	52	holmqvist	holmqvist	NOUN
flr-365	68	53	,	,	PUNCT
flr-365	68	54	et	et	PROPN
flr-365	68	55	al	al	PROPN
flr-365	68	56	.	.	PROPN
flr-365	68	57	,	,	PUNCT
flr-365	68	58	2011	2011	NUM
flr-365	68	59	)	)	PUNCT
flr-365	68	60	.	.	PUNCT
flr-365	69	1	while	while	SCONJ
flr-365	69	2	some	some	DET
flr-365	69	3	studies	study	NOUN
flr-365	69	4	involving	involve	VERB
flr-365	69	5	children	child	NOUN
flr-365	69	6	(	(	PUNCT
flr-365	69	7	e.g.	e.g.	ADV
flr-365	69	8	sasson	sasson	NOUN
flr-365	69	9	&	&	CCONJ
flr-365	69	10	elison	elison	PROPN
flr-365	69	11	,	,	PUNCT
flr-365	69	12	2012	2012	NUM
flr-365	69	13	)	)	PUNCT
flr-365	69	14	have	have	AUX
flr-365	69	15	implemented	implement	VERB
flr-365	69	16	a	a	DET
flr-365	69	17	two	two	NUM
flr-365	69	18	degree	degree	NOUN
flr-365	69	19	vertical	vertical	ADJ
flr-365	69	20	and	and	CCONJ
flr-365	69	21	horizontal	horizontal	ADJ
flr-365	69	22	displacement	displacement	NOUN
flr-365	69	23	zone	zone	NOUN
flr-365	69	24	centred	centre	VERB
flr-365	69	25	over	over	ADP
flr-365	69	26	relevant	relevant	ADJ
flr-365	69	27	visual	visual	ADJ
flr-365	69	28	stimuli	stimulus	NOUN
flr-365	69	29	(	(	PUNCT
flr-365	69	30	one	one	NUM
flr-365	69	31	degree	degree	NOUN
flr-365	69	32	above	above	ADV
flr-365	69	33	and	and	CCONJ
flr-365	69	34	one	one	NUM
flr-365	69	35	degree	degree	NOUN
flr-365	69	36	below	below	ADP
flr-365	69	37	the	the	DET
flr-365	69	38	stimulus	stimulus	NOUN
flr-365	69	39	)	)	PUNCT
flr-365	69	40	,	,	PUNCT
flr-365	69	41	this	this	PRON
flr-365	69	42	was	be	AUX
flr-365	69	43	not	not	PART
flr-365	69	44	possible	possible	ADJ
flr-365	69	45	with	with	ADP
flr-365	69	46	the	the	DET
flr-365	69	47	current	current	ADJ
flr-365	69	48	graph	graph	NOUN
flr-365	69	49	task	task	NOUN
flr-365	69	50	as	as	SCONJ
flr-365	69	51	it	it	PRON
flr-365	69	52	would	would	AUX
flr-365	69	53	have	have	AUX
flr-365	69	54	resulted	result	VERB
flr-365	69	55	in	in	ADP
flr-365	69	56	substantial	substantial	ADJ
flr-365	69	57	overlap	overlap	NOUN
flr-365	69	58	of	of	ADP
flr-365	69	59	aois	aois	NOUN
flr-365	69	60	.	.	PUNCT
flr-365	70	1	thus	thus	ADV
flr-365	70	2	wherever	wherever	SCONJ
flr-365	70	3	possible	possible	ADJ
flr-365	70	4	,	,	PUNCT
flr-365	70	5	a	a	DET
flr-365	70	6	1.9	1.9	NUM
flr-365	70	7	degree	degree	NOUN
flr-365	70	8	vertical	vertical	ADJ
flr-365	70	9	and	and	CCONJ
flr-365	70	10	0.5	0.5	NUM
flr-365	70	11	degree	degree	NOUN
flr-365	70	12	horizontal	horizontal	ADJ
flr-365	70	13	displacement	displacement	NOUN
flr-365	70	14	zone	zone	NOUN
flr-365	70	15	was	be	AUX
flr-365	70	16	centred	centre	VERB
flr-365	70	17	over	over	ADP
flr-365	70	18	the	the	DET
flr-365	70	19	stimulus	stimulus	NOUN
flr-365	70	20	and	and	CCONJ
flr-365	70	21	in	in	ADP
flr-365	70	22	the	the	DET
flr-365	70	23	event	event	NOUN
flr-365	70	24	of	of	ADP
flr-365	70	25	overlap	overlap	NOUN
flr-365	70	26	,	,	PUNCT
flr-365	70	27	the	the	DET
flr-365	70	28	horizontal	horizontal	ADJ
flr-365	70	29	displacement	displacement	NOUN
flr-365	70	30	zone	zone	NOUN
flr-365	70	31	was	be	AUX
flr-365	70	32	reduced	reduce	VERB
flr-365	70	33	to	to	ADP
flr-365	70	34	0.15	0.15	NUM
flr-365	70	35	degrees	degree	NOUN
flr-365	70	36	,	,	PUNCT
flr-365	70	37	which	which	PRON
flr-365	70	38	occurred	occur	VERB
flr-365	70	39	for	for	ADP
flr-365	70	40	the	the	DET
flr-365	70	41	following	follow	VERB
flr-365	70	42	aois	aois	NOUN
flr-365	70	43	:	:	PUNCT
flr-365	70	44	a1	a1	NOUN
flr-365	70	45	and	and	CCONJ
flr-365	70	46	b1	b1	NOUN
flr-365	70	47	,	,	PUNCT
flr-365	70	48	a2	a2	PROPN
flr-365	70	49	and	and	CCONJ
flr-365	70	50	b2	b2	NOUN
flr-365	70	51	.	.	PUNCT
flr-365	71	1	to	to	PART
flr-365	71	2	avoid	avoid	VERB
flr-365	71	3	overlap	overlap	NOUN
flr-365	71	4	between	between	ADP
flr-365	71	5	c2	c2	PROPN
flr-365	71	6	and	and	CCONJ
flr-365	71	7	b5	b5	PROPN
flr-365	71	8	aois	aois	PROPN
flr-365	71	9	,	,	PUNCT
flr-365	71	10	b5	b5	PROPN
flr-365	71	11	had	have	VERB
flr-365	71	12	a	a	DET
flr-365	71	13	1.5	1.5	NUM
flr-365	71	14	degree	degree	NOUN
flr-365	71	15	centred	centre	VERB
flr-365	71	16	vertical	vertical	ADJ
flr-365	71	17	displacement	displacement	NOUN
flr-365	71	18	,	,	PUNCT
flr-365	71	19	whereas	whereas	SCONJ
flr-365	71	20	the	the	DET
flr-365	71	21	c2	c2	PROPN
flr-365	71	22	vertical	vertical	ADJ
flr-365	71	23	displacement	displacement	NOUN
flr-365	71	24	zone	zone	NOUN
flr-365	71	25	could	could	AUX
flr-365	71	26	not	not	PART
flr-365	71	27	be	be	AUX
flr-365	71	28	centred	centre	VERB
flr-365	71	29	over	over	ADP
flr-365	71	30	the	the	DET
flr-365	71	31	stimulus	stimulus	NOUN
flr-365	71	32	,	,	PUNCT
flr-365	71	33	so	so	SCONJ
flr-365	71	34	the	the	DET
flr-365	71	35	c2	c2	PROPN
flr-365	71	36	aoi	aoi	PROPN
flr-365	71	37	was	be	AUX
flr-365	71	38	defined	define	VERB
flr-365	71	39	as	as	ADP
flr-365	71	40	0.5	0.5	NUM
flr-365	71	41	degree	degree	NOUN
flr-365	71	42	above	above	ADV
flr-365	71	43	and	and	CCONJ
flr-365	71	44	0.95	0.95	NUM
flr-365	71	45	degree	degree	NOUN
flr-365	71	46	below	below	ADP
flr-365	71	47	the	the	DET
flr-365	71	48	stimulus	stimulus	NOUN
flr-365	71	49	.	.	PUNCT
flr-365	72	1	to	to	PART
flr-365	72	2	distinguish	distinguish	VERB
flr-365	72	3	fixations	fixation	NOUN
flr-365	72	4	on	on	ADP
flr-365	72	5	the	the	DET
flr-365	72	6	y	y	NOUN
flr-365	72	7	-	-	PUNCT
flr-365	72	8	axis	axis	ADJ
flr-365	72	9	,	,	PUNCT
flr-365	72	10	a4	a4	NOUN
flr-365	72	11	and	and	CCONJ
flr-365	72	12	b4	b4	NOUN
flr-365	72	13	had	have	VERB
flr-365	72	14	a	a	DET
flr-365	72	15	1.9	1.9	NUM
flr-365	72	16	degree	degree	NOUN
flr-365	72	17	vertical	vertical	ADJ
flr-365	72	18	displacement	displacement	NOUN
flr-365	72	19	,	,	PUNCT
flr-365	72	20	and	and	CCONJ
flr-365	72	21	a	a	DET
flr-365	72	22	larger	large	ADJ
flr-365	72	23	1	1	NUM
flr-365	72	24	degree	degree	NOUN
flr-365	72	25	horizontal	horizontal	ADJ
flr-365	72	26	displacement	displacement	NOUN
flr-365	72	27	.	.	PUNCT
flr-365	73	1	the	the	DET
flr-365	73	2	data	data	NOUN
flr-365	73	3	sequences	sequence	NOUN
flr-365	73	4	that	that	PRON
flr-365	73	5	were	be	AUX
flr-365	73	6	obtained	obtain	VERB
flr-365	73	7	initially	initially	ADV
flr-365	73	8	were	be	AUX
flr-365	73	9	based	base	VERB
flr-365	73	10	on	on	ADP
flr-365	73	11	fixations	fixation	NOUN
flr-365	73	12	and	and	CCONJ
flr-365	73	13	then	then	ADV
flr-365	73	14	transformed	transform	VERB
flr-365	73	15	into	into	ADP
flr-365	73	16	dwell	dwell	NOUN
flr-365	73	17	sequences	sequence	NOUN
flr-365	73	18	by	by	ADP
flr-365	73	19	coalescing	coalesce	VERB
flr-365	73	20	contiguous	contiguous	ADJ
flr-365	73	21	identical	identical	ADJ
flr-365	73	22	elements	element	NOUN
flr-365	73	23	in	in	ADP
flr-365	73	24	the	the	DET
flr-365	73	25	sequence	sequence	NOUN
flr-365	73	26	.	.	PUNCT
flr-365	74	1	thus	thus	ADV
flr-365	74	2	,	,	PUNCT
flr-365	74	3	for	for	ADP
flr-365	74	4	example	example	NOUN
flr-365	74	5	,	,	PUNCT
flr-365	74	6	if	if	SCONJ
flr-365	74	7	in	in	ADP
flr-365	74	8	a	a	DET
flr-365	74	9	fixation	fixation	NOUN
flr-365	74	10	sequence	sequence	NOUN
flr-365	74	11	we	we	PRON
flr-365	74	12	have	have	VERB
flr-365	74	13	b2	b2	NOUN
flr-365	74	14	,	,	PUNCT
flr-365	74	15	a1	a1	NOUN
flr-365	74	16	,	,	PUNCT
flr-365	74	17	a1	a1	NOUN
flr-365	74	18	,	,	PUNCT
flr-365	74	19	c3	c3	NOUN
flr-365	74	20	,	,	PUNCT
flr-365	74	21	this	this	PRON
flr-365	74	22	would	would	AUX
flr-365	74	23	give	give	VERB
flr-365	74	24	rise	rise	NOUN
flr-365	74	25	to	to	ADP
flr-365	74	26	the	the	DET
flr-365	74	27	dwell	dwell	NOUN
flr-365	74	28	sequence	sequence	NOUN
flr-365	74	29	b2	b2	NOUN
flr-365	74	30	,	,	PUNCT
flr-365	74	31	a1	a1	NOUN
flr-365	74	32	,	,	PUNCT
flr-365	74	33	c3	c3	NOUN
flr-365	74	34	.	.	PUNCT
flr-365	75	1	in	in	ADP
flr-365	75	2	our	our	PRON
flr-365	75	3	analysis	analysis	NOUN
flr-365	75	4	,	,	PUNCT
flr-365	75	5	sequences	sequence	NOUN
flr-365	75	6	of	of	ADP
flr-365	75	7	dwells	dwell	NOUN
flr-365	75	8	were	be	AUX
flr-365	75	9	used	use	VERB
flr-365	75	10	.	.	PUNCT
flr-365	76	1	the	the	DET
flr-365	76	2	data	datum	NOUN
flr-365	76	3	included	include	VERB
flr-365	76	4	106	106	NUM
flr-365	76	5	data	datum	NOUN
flr-365	76	6	sequences	sequence	NOUN
flr-365	76	7	or	or	CCONJ
flr-365	76	8	scanpaths	scanpath	NOUN
flr-365	76	9	(	(	PUNCT
flr-365	76	10	known	know	VERB
flr-365	76	11	as	as	ADP
flr-365	76	12	the	the	DET
flr-365	76	13	inputs	input	NOUN
flr-365	76	14	both	both	DET
flr-365	76	15	terminologies	terminology	NOUN
flr-365	76	16	are	be	AUX
flr-365	76	17	used	use	VERB
flr-365	76	18	to	to	PART
flr-365	76	19	reflect	reflect	VERB
flr-365	76	20	what	what	PRON
flr-365	76	21	is	be	AUX
flr-365	76	22	typically	typically	ADV
flr-365	76	23	used	use	VERB
flr-365	76	24	in	in	ADP
flr-365	76	25	the	the	DET
flr-365	76	26	literature	literature	NOUN
flr-365	76	27	)	)	PUNCT
flr-365	76	28	,	,	PUNCT
flr-365	76	29	one	one	NUM
flr-365	76	30	for	for	ADP
flr-365	76	31	each	each	DET
flr-365	76	32	child	child	NOUN
flr-365	76	33	,	,	PUNCT
flr-365	76	34	and	and	CCONJ
flr-365	76	35	the	the	DET
flr-365	76	36	corresponding	corresponding	ADJ
flr-365	76	37	106	106	NUM
flr-365	76	38	answers	answer	NOUN
flr-365	76	39	to	to	ADP
flr-365	76	40	the	the	DET
flr-365	76	41	graph	graph	NOUN
flr-365	76	42	question	question	NOUN
flr-365	76	43	(	(	PUNCT
flr-365	76	44	the	the	DET
flr-365	76	45	outputs	output	NOUN
flr-365	76	46	)	)	PUNCT
flr-365	76	47	,	,	PUNCT
flr-365	76	48	were	be	AUX
flr-365	76	49	categorised	categorise	VERB
flr-365	76	50	as	as	ADP
flr-365	76	51	correct	correct	ADJ
flr-365	76	52	(	(	PUNCT
flr-365	76	53	1	1	NUM
flr-365	76	54	)	)	PUNCT
flr-365	76	55	or	or	CCONJ
flr-365	76	56	incorrect	incorrect	ADJ
flr-365	76	57	(	(	PUNCT
flr-365	76	58	0	0	NUM
flr-365	76	59	)	)	PUNCT
flr-365	76	60	.	.	PUNCT
flr-365	77	1	the	the	DET
flr-365	77	2	data	data	NOUN
flr-365	77	3	sequences	sequence	NOUN
flr-365	77	4	(	(	PUNCT
flr-365	77	5	sequences	sequence	NOUN
flr-365	77	6	of	of	ADP
flr-365	77	7	aoi	aoi	NOUN
flr-365	77	8	names	name	NOUN
flr-365	77	9	)	)	PUNCT
flr-365	77	10	could	could	AUX
flr-365	77	11	thus	thus	ADV
flr-365	77	12	be	be	AUX
flr-365	77	13	grouped	group	VERB
flr-365	77	14	into	into	ADP
flr-365	77	15	two	two	NUM
flr-365	77	16	classes	class	NOUN
flr-365	77	17	,	,	PUNCT
flr-365	77	18	one	one	NUM
flr-365	77	19	being	be	AUX
flr-365	77	20	the	the	DET
flr-365	77	21	sequences	sequence	NOUN
flr-365	77	22	of	of	ADP
flr-365	77	23	children	child	NOUN
flr-365	77	24	who	who	PRON
flr-365	77	25	responded	respond	VERB
flr-365	77	26	correctly	correctly	ADV
flr-365	77	27	to	to	ADP
flr-365	77	28	the	the	DET
flr-365	77	29	task	task	NOUN
flr-365	77	30	,	,	PUNCT
flr-365	77	31	and	and	CCONJ
flr-365	77	32	the	the	DET
flr-365	77	33	other	other	ADJ
flr-365	77	34	being	be	AUX
flr-365	77	35	the	the	DET
flr-365	77	36	sequences	sequence	NOUN
flr-365	77	37	of	of	ADP
flr-365	77	38	children	child	NOUN
flr-365	77	39	who	who	PRON
flr-365	77	40	responded	respond	VERB
flr-365	77	41	incorrectly	incorrectly	ADV
flr-365	77	42	.	.	PUNCT
flr-365	78	1	2.5	2.5	NUM
flr-365	78	2	machine	machine	NOUN
flr-365	78	3	learning	learn	VERB
flr-365	78	4	techniques	technique	NOUN
flr-365	78	5	machine	machine	NOUN
flr-365	78	6	learning	learning	NOUN
flr-365	78	7	approaches	approach	NOUN
flr-365	78	8	were	be	AUX
flr-365	78	9	used	use	VERB
flr-365	78	10	to	to	PART
flr-365	78	11	find	find	VERB
flr-365	78	12	a	a	DET
flr-365	78	13	representative	representative	ADJ
flr-365	78	14	sequence	sequence	NOUN
flr-365	78	15	of	of	ADP
flr-365	78	16	aois	aois	NOUN
flr-365	78	17	that	that	PRON
flr-365	78	18	would	would	AUX
flr-365	78	19	provide	provide	VERB
flr-365	78	20	qualitative	qualitative	ADJ
flr-365	78	21	information	information	NOUN
flr-365	78	22	about	about	ADP
flr-365	78	23	the	the	DET
flr-365	78	24	visual	visual	ADJ
flr-365	78	25	cognitive	cognitive	ADJ
flr-365	78	26	characteristics	characteristic	NOUN
flr-365	78	27	associated	associate	VERB
flr-365	78	28	with	with	ADP
flr-365	78	29	task	task	NOUN
flr-365	78	30	performance	performance	NOUN
flr-365	78	31	.	.	PUNCT
flr-365	79	1	two	two	NUM
flr-365	79	2	methods	method	NOUN
flr-365	79	3	are	be	AUX
flr-365	79	4	described	describe	VERB
flr-365	79	5	that	that	SCONJ
flr-365	79	6	provide	provide	VERB
flr-365	79	7	means	mean	NOUN
flr-365	79	8	by	by	ADP
flr-365	79	9	which	which	PRON
flr-365	79	10	an	an	DET
flr-365	79	11	average	average	ADJ
flr-365	79	12	scanpath	scanpath	NOUN
flr-365	79	13	can	can	AUX
flr-365	79	14	be	be	AUX
flr-365	79	15	extracted	extract	VERB
flr-365	79	16	from	from	ADP
flr-365	79	17	a	a	DET
flr-365	79	18	set	set	NOUN
flr-365	79	19	of	of	ADP
flr-365	79	20	multiple	multiple	ADJ
flr-365	79	21	sequences	sequence	NOUN
flr-365	79	22	or	or	CCONJ
flr-365	79	23	scanpaths	scanpath	NOUN
flr-365	79	24	obtained	obtain	VERB
flr-365	79	25	from	from	ADP
flr-365	79	26	children	child	NOUN
flr-365	79	27	performing	perform	VERB
flr-365	79	28	the	the	DET
flr-365	79	29	same	same	ADJ
flr-365	79	30	task	task	NOUN
flr-365	79	31	.	.	PUNCT
flr-365	80	1	method	method	PROPN
flr-365	80	2	one	one	NOUN
flr-365	80	3	applies	apply	VERB
flr-365	80	4	a	a	DET
flr-365	80	5	naïve	naïve	ADJ
flr-365	80	6	bayesian	bayesian	NOUN
flr-365	80	7	approach	approach	NOUN
flr-365	80	8	to	to	PART
flr-365	80	9	calculate	calculate	VERB
flr-365	80	10	the	the	DET
flr-365	80	11	most	most	ADV
flr-365	80	12	probable	probable	ADJ
flr-365	80	13	vector	vector	NOUN
flr-365	80	14	for	for	ADP
flr-365	80	15	each	each	DET
flr-365	80	16	class	class	NOUN
flr-365	80	17	(	(	PUNCT
flr-365	80	18	using	use	VERB
flr-365	80	19	two	two	NUM
flr-365	80	20	possible	possible	ADJ
flr-365	80	21	alternatives	alternative	NOUN
flr-365	80	22	to	to	ADP
flr-365	80	23	managing	manage	VERB
flr-365	80	24	variable	variable	ADJ
flr-365	80	25	feature	feature	NOUN
flr-365	80	26	vector	vector	NOUN
flr-365	80	27	length	length	NOUN
flr-365	80	28	)	)	PUNCT
flr-365	80	29	,	,	PUNCT
flr-365	80	30	and	and	CCONJ
flr-365	80	31	method	method	VERB
flr-365	80	32	two	two	NUM
flr-365	80	33	applies	apply	VERB
flr-365	80	34	a	a	DET
flr-365	80	35	single	single	ADJ
flr-365	80	36	iteration	iteration	NOUN
flr-365	80	37	of	of	ADP
flr-365	80	38	a	a	DET
flr-365	80	39	k	k	NOUN
flr-365	80	40	-	-	PUNCT
flr-365	80	41	means	means	NOUN
flr-365	80	42	approach	approach	NOUN
flr-365	80	43	to	to	PART
flr-365	80	44	calculate	calculate	VERB
flr-365	80	45	the	the	DET
flr-365	80	46	central	central	ADJ
flr-365	80	47	vector	vector	NOUN
flr-365	80	48	for	for	ADP
flr-365	80	49	each	each	DET
flr-365	80	50	class	class	NOUN
flr-365	80	51	using	use	VERB
flr-365	80	52	an	an	DET
flr-365	80	53	edit	edit	NOUN
flr-365	80	54	distance	distance	NOUN
flr-365	80	55	metric	metric	NOUN
flr-365	80	56	.	.	PUNCT
flr-365	81	1	the	the	DET
flr-365	81	2	use	use	NOUN
flr-365	81	3	of	of	ADP
flr-365	81	4	these	these	DET
flr-365	81	5	techniques	technique	NOUN
flr-365	81	6	will	will	AUX
flr-365	81	7	form	form	VERB
flr-365	81	8	the	the	DET
flr-365	81	9	basis	basis	NOUN
flr-365	81	10	for	for	ADP
flr-365	81	11	future	future	ADJ
flr-365	81	12	research	research	NOUN
flr-365	81	13	that	that	PRON
flr-365	81	14	characterises	characterise	VERB
flr-365	81	15	the	the	DET
flr-365	81	16	relevant	relevant	ADJ
flr-365	81	17	scanpaths	scanpath	NOUN
flr-365	81	18	of	of	ADP
flr-365	81	19	children	child	NOUN
flr-365	81	20	to	to	PART
flr-365	81	21	potentially	potentially	ADV
flr-365	81	22	guide	guide	VERB
flr-365	81	23	identification	identification	NOUN
flr-365	81	24	of	of	ADP
flr-365	81	25	their	their	PRON
flr-365	81	26	ability	ability	NOUN
flr-365	81	27	to	to	PART
flr-365	81	28	effectively	effectively	ADV
flr-365	81	29	perform	perform	VERB
flr-365	81	30	graph	graph	NOUN
flr-365	81	31	tasks	task	NOUN
flr-365	81	32	.	.	PUNCT
flr-365	82	1	2.5.1	2.5.1	NUM
flr-365	82	2	method	method	NOUN
flr-365	82	3	one	one	NUM
flr-365	82	4	–	–	PUNCT
flr-365	82	5	most	most	ADV
flr-365	82	6	probable	probable	ADJ
flr-365	82	7	vector	vector	NOUN
flr-365	82	8	for	for	ADP
flr-365	82	9	each	each	DET
flr-365	82	10	class	class	NOUN
flr-365	82	11	the	the	DET
flr-365	82	12	naïve	naïve	ADJ
flr-365	82	13	bayes	bayes	NOUN
flr-365	82	14	model	model	NOUN
flr-365	82	15	or	or	CCONJ
flr-365	82	16	classifier	classifier	NOUN
flr-365	82	17	“	"	PUNCT
flr-365	82	18	learns	learns	PROPN
flr-365	82	19	”	"	PUNCT
flr-365	82	20	from	from	ADP
flr-365	82	21	the	the	DET
flr-365	82	22	data	datum	NOUN
flr-365	82	23	sequences	sequence	NOUN
flr-365	82	24	,	,	PUNCT
flr-365	82	25	which	which	PRON
flr-365	82	26	are	be	AUX
flr-365	82	27	known	know	VERB
flr-365	82	28	as	as	ADP
flr-365	82	29	feature	feature	NOUN
flr-365	82	30	vectors	vector	NOUN
flr-365	82	31	,	,	PUNCT
flr-365	82	32	which	which	PRON
flr-365	82	33	is	be	AUX
flr-365	82	34	a	a	DET
flr-365	82	35	commonly	commonly	ADV
flr-365	82	36	used	use	VERB
flr-365	82	37	term	term	NOUN
flr-365	82	38	in	in	ADP
flr-365	82	39	the	the	DET
flr-365	82	40	machine	machine	NOUN
flr-365	82	41	learning	learn	VERB
flr-365	82	42	literature	literature	PROPN
flr-365	82	43	(	(	PUNCT
flr-365	82	44	murphy	murphy	PROPN
flr-365	82	45	,	,	PUNCT
flr-365	82	46	2012	2012	NUM
flr-365	82	47	)	)	PUNCT
flr-365	82	48	.	.	PUNCT
flr-365	83	1	a	a	DET
flr-365	83	2	data	data	NOUN
flr-365	83	3	sequence	sequence	NOUN
flr-365	83	4	can	can	AUX
flr-365	83	5	be	be	AUX
flr-365	83	6	defined	define	VERB
flr-365	83	7	as	as	ADP
flr-365	83	8	a	a	DET
flr-365	83	9	finite	finite	ADJ
flr-365	83	10	list	list	NOUN
flr-365	83	11	of	of	ADP
flr-365	83	12	representational	representational	ADJ
flr-365	83	13	feature	feature	NOUN
flr-365	83	14	objects	object	NOUN
flr-365	83	15	or	or	CCONJ
flr-365	83	16	values	value	NOUN
flr-365	83	17	,	,	PUNCT
flr-365	83	18	which	which	PRON
flr-365	83	19	can	can	AUX
flr-365	83	20	be	be	AUX
flr-365	83	21	names	name	NOUN
flr-365	83	22	,	,	PUNCT
flr-365	83	23	numbers	number	NOUN
flr-365	83	24	or	or	CCONJ
flr-365	83	25	symbols	symbol	NOUN
flr-365	83	26	,	,	PUNCT
flr-365	83	27	as	as	ADV
flr-365	83	28	long	long	ADV
flr-365	83	29	as	as	SCONJ
flr-365	83	30	the	the	DET
flr-365	83	31	possible	possible	ADJ
flr-365	83	32	set	set	NOUN
flr-365	83	33	of	of	ADP
flr-365	83	34	representational	representational	ADJ
flr-365	83	35	names	name	NOUN
flr-365	83	36	or	or	CCONJ
flr-365	83	37	values	value	NOUN
flr-365	83	38	is	be	AUX
flr-365	83	39	finite	finite	ADJ
flr-365	83	40	.	.	PUNCT
flr-365	84	1	in	in	ADP
flr-365	84	2	the	the	DET
flr-365	84	3	case	case	NOUN
flr-365	84	4	of	of	ADP
flr-365	84	5	scanpaths	scanpath	NOUN
flr-365	84	6	,	,	PUNCT
flr-365	84	7	the	the	DET
flr-365	84	8	feature	feature	NOUN
flr-365	84	9	values	value	NOUN
flr-365	84	10	are	be	AUX
flr-365	84	11	the	the	DET
flr-365	84	12	aoi	aoi	NOUN
flr-365	84	13	names	name	NOUN
flr-365	84	14	.	.	PUNCT
flr-365	85	1	the	the	DET
flr-365	85	2	classes	class	NOUN
flr-365	85	3	in	in	ADP
flr-365	85	4	the	the	DET
flr-365	85	5	model	model	NOUN
flr-365	85	6	are	be	AUX
flr-365	85	7	the	the	DET
flr-365	85	8	children	child	NOUN
flr-365	85	9	who	who	PRON
flr-365	85	10	either	either	CCONJ
flr-365	85	11	correctly	correctly	ADV
flr-365	85	12	or	or	CCONJ
flr-365	85	13	incorrectly	incorrectly	ADV
flr-365	85	14	completed	complete	VERB
flr-365	85	15	the	the	DET
flr-365	85	16	graph	graph	NOUN
flr-365	85	17	task	task	NOUN
flr-365	85	18	.	.	PUNCT
flr-365	86	1	learning	learn	VERB
flr-365	86	2	a	a	DET
flr-365	86	3	naïve	naïve	ADJ
flr-365	86	4	bayes	bayes	NOUN
flr-365	86	5	model	model	NOUN
flr-365	86	6	consists	consist	VERB
flr-365	86	7	of	of	ADP
flr-365	86	8	calculating	calculate	VERB
flr-365	86	9	the	the	DET
flr-365	86	10	class	class	NOUN
flr-365	86	11	conditional	conditional	ADJ
flr-365	86	12	probabilities	probability	NOUN
flr-365	86	13	of	of	ADP
flr-365	86	14	the	the	DET
flr-365	86	15	feature	feature	NOUN
flr-365	86	16	values	value	NOUN
flr-365	86	17	.	.	PUNCT
flr-365	87	1	for	for	ADP
flr-365	87	2	each	each	DET
flr-365	87	3	class	class	NOUN
flr-365	87	4	and	and	CCONJ
flr-365	87	5	each	each	DET
flr-365	87	6	feature	feature	NOUN
flr-365	87	7	,	,	PUNCT
flr-365	87	8	the	the	DET
flr-365	87	9	number	number	NOUN
flr-365	87	10	of	of	ADP
flr-365	87	11	occurrences	occurrence	NOUN
flr-365	87	12	of	of	ADP
flr-365	87	13	the	the	DET
flr-365	87	14	feature	feature	NOUN
flr-365	87	15	value	value	NOUN
flr-365	87	16	is	be	AUX
flr-365	87	17	divided	divide	VERB
flr-365	87	18	by	by	ADP
flr-365	87	19	the	the	DET
flr-365	87	20	number	number	NOUN
flr-365	87	21	of	of	ADP
flr-365	87	22	feature	feature	NOUN
flr-365	87	23	vectors	vector	NOUN
flr-365	87	24	in	in	ADP
flr-365	87	25	the	the	DET
flr-365	87	26	class	class	NOUN
flr-365	87	27	(	(	PUNCT
flr-365	87	28	whether	whether	SCONJ
flr-365	87	29	the	the	DET
flr-365	87	30	child	child	NOUN
flr-365	87	31	completed	complete	VERB
flr-365	87	32	the	the	DET
flr-365	87	33	task	task	NOUN
flr-365	87	34	correctly	correctly	ADV
flr-365	87	35	or	or	CCONJ
flr-365	87	36	incorrectly	incorrectly	ADV
flr-365	87	37	)	)	PUNCT
flr-365	87	38	in	in	ADP
flr-365	87	39	question	question	NOUN
flr-365	87	40	.	.	PUNCT
flr-365	88	1	this	this	PRON
flr-365	88	2	yields	yield	VERB
flr-365	88	3	the	the	DET
flr-365	88	4	class	class	NOUN
flr-365	88	5	conditional	conditional	ADJ
flr-365	88	6	probability	probability	NOUN
flr-365	88	7	for	for	ADP
flr-365	88	8	the	the	DET
flr-365	88	9	possible	possible	ADJ
flr-365	88	10	values	value	NOUN
flr-365	88	11	of	of	ADP
flr-365	88	12	a	a	DET
flr-365	88	13	given	give	VERB
flr-365	88	14	feature	feature	NOUN
flr-365	88	15	in	in	ADP
flr-365	88	16	the	the	DET
flr-365	88	17	given	give	VERB
flr-365	88	18	class	class	NOUN
flr-365	88	19	.	.	PUNCT
flr-365	89	1	the	the	DET
flr-365	89	2	“	"	PUNCT
flr-365	89	3	classifier	classifier	NOUN
flr-365	89	4	”	"	PUNCT
flr-365	89	5	obtained	obtain	VERB
flr-365	89	6	from	from	ADP
flr-365	89	7	the	the	DET
flr-365	89	8	model	model	NOUN
flr-365	89	9	consists	consist	VERB
flr-365	89	10	of	of	ADP
flr-365	89	11	probability	probability	NOUN
flr-365	89	12	distributions	distribution	NOUN
flr-365	89	13	of	of	ADP
flr-365	89	14	the	the	DET
flr-365	89	15	feature	feature	NOUN
flr-365	89	16	values	value	NOUN
flr-365	89	17	determined	determine	VERB
flr-365	89	18	by	by	ADP
flr-365	89	19	the	the	DET
flr-365	89	20	class	class	NOUN
flr-365	89	21	conditional	conditional	ADJ
flr-365	89	22	probabilities	probability	NOUN
flr-365	89	23	for	for	ADP
flr-365	89	24	the	the	DET
flr-365	89	25	values	value	NOUN
flr-365	89	26	of	of	ADP
flr-365	89	27	each	each	DET
flr-365	89	28	feature	feature	NOUN
flr-365	89	29	in	in	ADP
flr-365	89	30	each	each	DET
flr-365	89	31	class	class	NOUN
flr-365	89	32	.	.	PUNCT
flr-365	90	1	for	for	ADP
flr-365	90	2	example	example	NOUN
flr-365	90	3	,	,	PUNCT
flr-365	90	4	suppose	suppose	VERB
flr-365	90	5	that	that	SCONJ
flr-365	90	6	we	we	PRON
flr-365	90	7	have	have	VERB
flr-365	90	8	feature	feature	NOUN
flr-365	90	9	vectors	vector	NOUN
flr-365	90	10	(	(	PUNCT
flr-365	90	11	each	each	DET
flr-365	90	12	one	one	NUM
flr-365	90	13	in	in	ADP
flr-365	90	14	brackets	bracket	NOUN
flr-365	90	15	)	)	PUNCT
flr-365	90	16	in	in	ADP
flr-365	90	17	a	a	DET
flr-365	90	18	class	class	NOUN
flr-365	90	19	:	:	PUNCT
flr-365	90	20	(	(	PUNCT
flr-365	90	21	a	a	PRON
flr-365	90	22	,	,	PUNCT
flr-365	90	23	b	b	NOUN
flr-365	90	24	,	,	PUNCT
flr-365	90	25	c	c	NOUN
flr-365	90	26	,	,	PUNCT
flr-365	90	27	a	a	DET
flr-365	90	28	,	,	PUNCT
flr-365	90	29	b	b	NOUN
flr-365	90	30	)	)	PUNCT
flr-365	90	31	,	,	PUNCT
flr-365	90	32	(	(	PUNCT
flr-365	90	33	b	b	X
flr-365	90	34	,	,	PUNCT
flr-365	90	35	b	b	PROPN
flr-365	90	36	,	,	PUNCT
flr-365	90	37	c	c	NOUN
flr-365	90	38	,	,	PUNCT
flr-365	90	39	c	c	X
flr-365	90	40	,	,	PUNCT
flr-365	90	41	b	b	NOUN
flr-365	90	42	)	)	PUNCT
flr-365	90	43	,	,	PUNCT
flr-365	90	44	and	and	CCONJ
flr-365	90	45	(	(	PUNCT
flr-365	90	46	c	c	X
flr-365	90	47	,	,	PUNCT
flr-365	90	48	a	a	DET
flr-365	90	49	,	,	PUNCT
flr-365	90	50	b	b	NOUN
flr-365	90	51	,	,	PUNCT
flr-365	90	52	c	c	NOUN
flr-365	90	53	,	,	PUNCT
flr-365	90	54	a	a	PRON
flr-365	90	55	)	)	PUNCT
flr-365	90	56	.	.	PUNCT
flr-365	91	1	then	then	ADV
flr-365	91	2	,	,	PUNCT
flr-365	91	3	the	the	DET
flr-365	91	4	class	class	NOUN
flr-365	91	5	conditional	conditional	ADJ
flr-365	91	6	probabilities	probability	NOUN
flr-365	91	7	for	for	ADP
flr-365	91	8	the	the	DET
flr-365	91	9	second	second	ADJ
flr-365	91	10	feature	feature	NOUN
flr-365	91	11	value	value	NOUN
flr-365	91	12	(	(	PUNCT
flr-365	91	13	in	in	ADP
flr-365	91	14	bold	bold	ADJ
flr-365	91	15	)	)	PUNCT
flr-365	91	16	of	of	ADP
flr-365	91	17	this	this	DET
flr-365	91	18	class	class	NOUN
flr-365	91	19	are	be	AUX
flr-365	91	20	,	,	PUNCT
flr-365	91	21	for	for	ADP
flr-365	91	22	feature	feature	NOUN
flr-365	91	23	value	value	NOUN
flr-365	91	24	a	a	DET
flr-365	91	25	,	,	PUNCT
flr-365	91	26	1/3	1/3	NUM
flr-365	91	27	;	;	PUNCT
flr-365	91	28	for	for	ADP
flr-365	91	29	feature	feature	NOUN
flr-365	91	30	value	value	NOUN
flr-365	91	31	b	b	NOUN
flr-365	91	32	,	,	PUNCT
flr-365	91	33	2/3	2/3	NUM
flr-365	91	34	;	;	PUNCT
flr-365	91	35	and	and	CCONJ
flr-365	91	36	for	for	ADP
flr-365	91	37	feature	feature	NOUN
flr-365	91	38	value	value	NOUN
flr-365	91	39	c	c	NOUN
flr-365	91	40	,	,	PUNCT
flr-365	91	41	0	0	NUM
flr-365	91	42	because	because	SCONJ
flr-365	91	43	it	it	PRON
flr-365	91	44	does	do	AUX
flr-365	91	45	not	not	PART
flr-365	91	46	appear	appear	VERB
flr-365	91	47	in	in	ADP
flr-365	91	48	the	the	DET
flr-365	91	49	second	second	ADJ
flr-365	91	50	feature	feature	NOUN
flr-365	91	51	position	position	NOUN
flr-365	91	52	.	.	PUNCT
flr-365	92	1	for	for	ADP
flr-365	92	2	a	a	DET
flr-365	92	3	given	give	VERB
flr-365	92	4	sequence	sequence	NOUN
flr-365	92	5	or	or	CCONJ
flr-365	92	6	feature	feature	NOUN
flr-365	92	7	vector	vector	NOUN
flr-365	92	8	in	in	ADP
flr-365	92	9	a	a	DET
flr-365	92	10	given	give	VERB
flr-365	92	11	class	class	NOUN
flr-365	92	12	,	,	PUNCT
flr-365	92	13	all	all	DET
flr-365	92	14	the	the	DET
flr-365	92	15	class	class	NOUN
flr-365	92	16	conditional	conditional	ADJ
flr-365	92	17	probabilities	probability	NOUN
flr-365	92	18	are	be	AUX
flr-365	92	19	multiplied	multiply	VERB
flr-365	92	20	and	and	CCONJ
flr-365	92	21	the	the	DET
flr-365	92	22	product	product	NOUN
flr-365	92	23	is	be	AUX
flr-365	92	24	multiplied	multiply	VERB
flr-365	92	25	by	by	ADP
flr-365	92	26	the	the	DET
flr-365	92	27	class	class	NOUN
flr-365	92	28	prior	prior	ADJ
flr-365	92	29	probability	probability	NOUN
flr-365	92	30	.	.	PUNCT
flr-365	93	1	in	in	ADP
flr-365	93	2	our	our	PRON
flr-365	93	3	analysis	analysis	NOUN
flr-365	93	4	we	we	PRON
flr-365	93	5	assumed	assume	VERB
flr-365	93	6	what	what	PRON
flr-365	93	7	is	be	AUX
flr-365	93	8	called	call	VERB
flr-365	93	9	a	a	DET
flr-365	93	10	uniform	uniform	NOUN
flr-365	93	11	prior	prior	ADV
flr-365	93	12	,	,	PUNCT
flr-365	93	13	that	that	ADV
flr-365	93	14	is	is	ADV
flr-365	93	15	,	,	PUNCT
flr-365	93	16	a	a	DET
flr-365	93	17	prior	prior	ADJ
flr-365	93	18	probability	probability	NOUN
flr-365	93	19	value	value	NOUN
flr-365	93	20	of	of	ADP
flr-365	93	21	½	½	NOUN
flr-365	93	22	for	for	ADP
flr-365	93	23	each	each	DET
flr-365	93	24	class	class	NOUN
flr-365	93	25	.	.	PUNCT
flr-365	94	1	the	the	DET
flr-365	94	2	final	final	ADJ
flr-365	94	3	products	product	NOUN
flr-365	94	4	,	,	PUNCT
flr-365	94	5	one	one	NUM
flr-365	94	6	for	for	ADP
flr-365	94	7	each	each	DET
flr-365	94	8	class	class	NOUN
flr-365	94	9	,	,	PUNCT
flr-365	94	10	are	be	AUX
flr-365	94	11	the	the	DET
flr-365	94	12	joint	joint	ADJ
flr-365	94	13	probabilities	probability	NOUN
flr-365	94	14	.	.	PUNCT
flr-365	95	1	to	to	PART
flr-365	95	2	obtain	obtain	VERB
flr-365	95	3	the	the	DET
flr-365	95	4	most	most	ADV
flr-365	95	5	probable	probable	ADJ
flr-365	95	6	feature	feature	NOUN
flr-365	95	7	vector	vector	NOUN
flr-365	95	8	for	for	ADP
flr-365	95	9	a	a	DET
flr-365	95	10	class	class	NOUN
flr-365	95	11	(	(	PUNCT
flr-365	95	12	i.e.	i.e.	X
flr-365	95	13	,	,	PUNCT
flr-365	95	14	the	the	DET
flr-365	95	15	most	most	ADV
flr-365	95	16	probable	probable	ADJ
flr-365	95	17	or	or	CCONJ
flr-365	95	18	average	average	ADJ
flr-365	95	19	scanpath	scanpath	NOUN
flr-365	95	20	or	or	CCONJ
flr-365	95	21	data	datum	NOUN
flr-365	95	22	sequence	sequence	NOUN
flr-365	95	23	for	for	ADP
flr-365	95	24	the	the	DET
flr-365	95	25	given	give	VERB
flr-365	95	26	class	class	NOUN
flr-365	95	27	)	)	PUNCT
flr-365	95	28	the	the	DET
flr-365	95	29	feature	feature	NOUN
flr-365	95	30	value	value	NOUN
flr-365	95	31	that	that	PRON
flr-365	95	32	has	have	VERB
flr-365	95	33	the	the	DET
flr-365	95	34	highest	high	ADJ
flr-365	95	35	probability	probability	NOUN
flr-365	95	36	of	of	ADP
flr-365	95	37	occurring	occur	VERB
flr-365	95	38	in	in	ADP
flr-365	95	39	a	a	DET
flr-365	95	40	feature	feature	NOUN
flr-365	95	41	and	and	CCONJ
flr-365	95	42	class	class	NOUN
flr-365	95	43	,	,	PUNCT
flr-365	95	44	as	as	SCONJ
flr-365	95	45	given	give	VERB
flr-365	95	46	by	by	ADP
flr-365	95	47	the	the	DET
flr-365	95	48	class	class	NOUN
flr-365	95	49	conditional	conditional	ADJ
flr-365	95	50	probabilities	probability	NOUN
flr-365	95	51	,	,	PUNCT
flr-365	95	52	is	be	AUX
flr-365	95	53	selected	select	VERB
flr-365	95	54	for	for	ADP
flr-365	95	55	each	each	DET
flr-365	95	56	feature	feature	NOUN
flr-365	95	57	and	and	CCONJ
flr-365	95	58	class	class	NOUN
flr-365	95	59	.	.	PUNCT
flr-365	96	1	in	in	ADP
flr-365	96	2	the	the	DET
flr-365	96	3	above	above	ADJ
flr-365	96	4	example	example	NOUN
flr-365	96	5	,	,	PUNCT
flr-365	96	6	the	the	DET
flr-365	96	7	resulting	result	VERB
flr-365	96	8	vector	vector	NOUN
flr-365	96	9	would	would	AUX
flr-365	96	10	be	be	AUX
flr-365	96	11	(	(	PUNCT
flr-365	96	12	a	a	DET
flr-365	96	13	,	,	PUNCT
flr-365	96	14	b	b	NOUN
flr-365	96	15	,	,	PUNCT
flr-365	96	16	c	c	NOUN
flr-365	96	17	,	,	PUNCT
flr-365	96	18	c	c	X
flr-365	96	19	,	,	PUNCT
flr-365	96	20	b	b	NOUN
flr-365	96	21	)	)	PUNCT
flr-365	96	22	.	.	PUNCT
flr-365	97	1	in	in	ADP
flr-365	97	2	the	the	DET
flr-365	97	3	first	first	ADJ
flr-365	97	4	position	position	NOUN
flr-365	97	5	,	,	PUNCT
flr-365	97	6	all	all	DET
flr-365	97	7	values	value	NOUN
flr-365	97	8	have	have	VERB
flr-365	97	9	probability	probability	NOUN
flr-365	97	10	1/3	1/3	NUM
flr-365	97	11	so	so	CCONJ
flr-365	97	12	we	we	PRON
flr-365	97	13	pick	pick	VERB
flr-365	97	14	one	one	NUM
flr-365	97	15	at	at	ADP
flr-365	97	16	random	random	ADJ
flr-365	97	17	,	,	PUNCT
flr-365	97	18	say	say	VERB
flr-365	97	19	a.	a.	NOUN
flr-365	97	20	in	in	ADP
flr-365	97	21	the	the	DET
flr-365	97	22	second	second	ADJ
flr-365	97	23	through	through	ADP
flr-365	97	24	fifth	fifth	ADJ
flr-365	97	25	positions	position	NOUN
flr-365	97	26	,	,	PUNCT
flr-365	97	27	b	b	X
flr-365	97	28	,	,	PUNCT
flr-365	97	29	c	c	NOUN
flr-365	97	30	,	,	PUNCT
flr-365	97	31	c	c	NOUN
flr-365	97	32	,	,	PUNCT
flr-365	97	33	and	and	CCONJ
flr-365	97	34	b	b	X
flr-365	97	35	have	have	VERB
flr-365	97	36	probability	probability	NOUN
flr-365	97	37	2/3	2/3	NUM
flr-365	97	38	whereas	whereas	SCONJ
flr-365	97	39	the	the	DET
flr-365	97	40	other	other	ADJ
flr-365	97	41	symbols	symbol	NOUN
flr-365	97	42	in	in	ADP
flr-365	97	43	each	each	DET
flr-365	97	44	position	position	NOUN
flr-365	97	45	have	have	VERB
flr-365	97	46	probability	probability	NOUN
flr-365	97	47	1/3	1/3	NUM
flr-365	97	48	or	or	CCONJ
flr-365	97	49	0	0	NUM
flr-365	97	50	.	.	PUNCT
flr-365	98	1	the	the	DET
flr-365	98	2	resulting	result	VERB
flr-365	98	3	list	list	NOUN
flr-365	98	4	,	,	PUNCT
flr-365	98	5	or	or	CCONJ
flr-365	98	6	vector	vector	NOUN
flr-365	98	7	,	,	PUNCT
flr-365	98	8	of	of	ADP
flr-365	98	9	most	most	ADJ
flr-365	98	10	probable	probable	ADJ
flr-365	98	11	feature	feature	NOUN
flr-365	98	12	values	value	NOUN
flr-365	98	13	is	be	AUX
flr-365	98	14	the	the	DET
flr-365	98	15	most	most	ADV
flr-365	98	16	probable	probable	ADJ
flr-365	98	17	feature	feature	NOUN
flr-365	98	18	vector	vector	NOUN
flr-365	98	19	(	(	PUNCT
flr-365	98	20	or	or	CCONJ
flr-365	98	21	average	average	ADJ
flr-365	98	22	scanpath	scanpath	NOUN
flr-365	98	23	or	or	CCONJ
flr-365	98	24	data	data	NOUN
flr-365	98	25	sequence	sequence	NOUN
flr-365	98	26	)	)	PUNCT
flr-365	98	27	for	for	ADP
flr-365	98	28	that	that	DET
flr-365	98	29	class	class	NOUN
flr-365	98	30	.	.	PUNCT
flr-365	99	1	the	the	DET
flr-365	99	2	vectors	vector	NOUN
flr-365	99	3	obtained	obtain	VERB
flr-365	99	4	for	for	ADP
flr-365	99	5	each	each	DET
flr-365	99	6	class	class	NOUN
flr-365	99	7	provide	provide	VERB
flr-365	99	8	qualitative	qualitative	ADJ
flr-365	99	9	information	information	NOUN
flr-365	99	10	regarding	regard	VERB
flr-365	99	11	the	the	DET
flr-365	99	12	children	child	NOUN
flr-365	99	13	’s	’s	PART
flr-365	99	14	task	task	NOUN
flr-365	99	15	performance	performance	NOUN
flr-365	99	16	according	accord	VERB
flr-365	99	17	to	to	ADP
flr-365	99	18	the	the	DET
flr-365	99	19	previously	previously	ADV
flr-365	99	20	established	establish	VERB
flr-365	99	21	criterion	criterion	NOUN
flr-365	99	22	,	,	PUNCT
flr-365	99	23	which	which	PRON
flr-365	99	24	indicates	indicate	VERB
flr-365	99	25	whether	whether	SCONJ
flr-365	99	26	the	the	DET
flr-365	99	27	graph	graph	NOUN
flr-365	99	28	task	task	NOUN
flr-365	99	29	was	be	AUX
flr-365	99	30	completed	complete	VERB
flr-365	99	31	correctly	correctly	ADV
flr-365	99	32	or	or	CCONJ
flr-365	99	33	incorrectly	incorrectly	ADV
flr-365	99	34	.	.	PUNCT
flr-365	100	1	the	the	DET
flr-365	100	2	feature	feature	NOUN
flr-365	100	3	vectors	vector	NOUN
flr-365	100	4	can	can	AUX
flr-365	100	5	have	have	VERB
flr-365	100	6	different	different	ADJ
flr-365	100	7	lengths	length	NOUN
flr-365	100	8	,	,	PUNCT
flr-365	100	9	which	which	PRON
flr-365	100	10	can	can	AUX
flr-365	100	11	lead	lead	VERB
flr-365	100	12	to	to	ADP
flr-365	100	13	biases	bias	NOUN
flr-365	100	14	;	;	PUNCT
flr-365	100	15	there	there	PRON
flr-365	100	16	are	be	VERB
flr-365	100	17	two	two	NUM
flr-365	100	18	alternatives	alternative	NOUN
flr-365	100	19	for	for	ADP
flr-365	100	20	managing	manage	VERB
flr-365	100	21	variable	variable	ADJ
flr-365	100	22	feature	feature	NOUN
flr-365	100	23	vector	vector	NOUN
flr-365	100	24	lengths	length	NOUN
flr-365	100	25	.	.	PUNCT
flr-365	101	1	the	the	DET
flr-365	101	2	first	first	ADJ
flr-365	101	3	way	way	NOUN
flr-365	101	4	to	to	PART
flr-365	101	5	deal	deal	VERB
flr-365	101	6	with	with	ADP
flr-365	101	7	this	this	DET
flr-365	101	8	length	length	NOUN
flr-365	101	9	variability	variability	NOUN
flr-365	101	10	is	be	AUX
flr-365	101	11	to	to	PART
flr-365	101	12	consider	consider	VERB
flr-365	101	13	those	those	DET
flr-365	101	14	feature	feature	NOUN
flr-365	101	15	vectors	vector	NOUN
flr-365	101	16	in	in	ADP
flr-365	101	17	a	a	DET
flr-365	101	18	class	class	NOUN
flr-365	101	19	which	which	PRON
flr-365	101	20	are	be	AUX
flr-365	101	21	shorter	short	ADJ
flr-365	101	22	than	than	ADP
flr-365	101	23	the	the	DET
flr-365	101	24	longest	long	ADJ
flr-365	101	25	one	one	NOUN
flr-365	101	26	in	in	ADP
flr-365	101	27	that	that	DET
flr-365	101	28	class	class	NOUN
flr-365	101	29	,	,	PUNCT
flr-365	101	30	as	as	ADP
flr-365	101	31	feature	feature	NOUN
flr-365	101	32	vectors	vector	NOUN
flr-365	101	33	containing	contain	VERB
flr-365	101	34	missing	miss	VERB
flr-365	101	35	data	datum	NOUN
flr-365	101	36	.	.	PUNCT
flr-365	102	1	the	the	DET
flr-365	102	2	class	class	NOUN
flr-365	102	3	conditional	conditional	ADJ
flr-365	102	4	probabilities	probability	NOUN
flr-365	102	5	are	be	AUX
flr-365	102	6	calculated	calculate	VERB
flr-365	102	7	as	as	SCONJ
flr-365	102	8	outlined	outline	VERB
flr-365	102	9	in	in	ADP
flr-365	102	10	the	the	DET
flr-365	102	11	example	example	NOUN
flr-365	102	12	.	.	PUNCT
flr-365	103	1	if	if	SCONJ
flr-365	103	2	a	a	DET
flr-365	103	3	feature	feature	NOUN
flr-365	103	4	is	be	AUX
flr-365	103	5	considered	consider	VERB
flr-365	103	6	as	as	ADP
flr-365	103	7	a	a	DET
flr-365	103	8	coordinate	coordinate	NOUN
flr-365	103	9	or	or	CCONJ
flr-365	103	10	location	location	NOUN
flr-365	103	11	in	in	ADP
flr-365	103	12	a	a	DET
flr-365	103	13	vector	vector	NOUN
flr-365	103	14	,	,	PUNCT
flr-365	103	15	for	for	ADP
flr-365	103	16	a	a	DET
flr-365	103	17	given	give	VERB
flr-365	103	18	feature	feature	NOUN
flr-365	103	19	and	and	CCONJ
flr-365	103	20	class	class	NOUN
flr-365	103	21	,	,	PUNCT
flr-365	103	22	the	the	DET
flr-365	103	23	probability	probability	NOUN
flr-365	103	24	of	of	ADP
flr-365	103	25	a	a	DET
flr-365	103	26	feature	feature	NOUN
flr-365	103	27	value	value	NOUN
flr-365	103	28	is	be	AUX
flr-365	103	29	the	the	DET
flr-365	103	30	number	number	NOUN
flr-365	103	31	of	of	ADP
flr-365	103	32	times	time	NOUN
flr-365	103	33	that	that	DET
flr-365	103	34	value	value	NOUN
flr-365	103	35	occurs	occur	VERB
flr-365	103	36	in	in	ADP
flr-365	103	37	any	any	PRON
flr-365	103	38	of	of	ADP
flr-365	103	39	the	the	DET
flr-365	103	40	feature	feature	NOUN
flr-365	103	41	vectors	vector	NOUN
flr-365	103	42	,	,	PUNCT
flr-365	103	43	at	at	ADP
flr-365	103	44	the	the	DET
flr-365	103	45	given	give	VERB
flr-365	103	46	location	location	NOUN
flr-365	103	47	,	,	PUNCT
flr-365	103	48	divided	divide	VERB
flr-365	103	49	by	by	ADP
flr-365	103	50	the	the	DET
flr-365	103	51	total	total	ADJ
flr-365	103	52	number	number	NOUN
flr-365	103	53	of	of	ADP
flr-365	103	54	feature	feature	NOUN
flr-365	103	55	vectors	vector	NOUN
flr-365	103	56	in	in	ADP
flr-365	103	57	the	the	DET
flr-365	103	58	given	give	VERB
flr-365	103	59	class	class	NOUN
flr-365	103	60	.	.	PUNCT
flr-365	104	1	if	if	SCONJ
flr-365	104	2	a	a	DET
flr-365	104	3	feature	feature	NOUN
flr-365	104	4	vector	vector	NOUN
flr-365	104	5	is	be	AUX
flr-365	104	6	too	too	ADV
flr-365	104	7	short	short	ADJ
flr-365	104	8	to	to	PART
flr-365	104	9	contain	contain	VERB
flr-365	104	10	any	any	DET
flr-365	104	11	feature	feature	NOUN
flr-365	104	12	values	value	NOUN
flr-365	104	13	,	,	PUNCT
flr-365	104	14	then	then	ADV
flr-365	104	15	it	it	PRON
flr-365	104	16	will	will	AUX
flr-365	104	17	not	not	PART
flr-365	104	18	contribute	contribute	VERB
flr-365	104	19	to	to	ADP
flr-365	104	20	the	the	DET
flr-365	104	21	numerator	numerator	NOUN
flr-365	104	22	of	of	ADP
flr-365	104	23	the	the	DET
flr-365	104	24	preceding	precede	VERB
flr-365	104	25	quantity	quantity	NOUN
flr-365	104	26	,	,	PUNCT
flr-365	104	27	as	as	ADP
flr-365	104	28	in	in	ADP
flr-365	104	29	the	the	DET
flr-365	104	30	example	example	NOUN
flr-365	104	31	above	above	ADV
flr-365	104	32	.	.	PUNCT
flr-365	105	1	the	the	DET
flr-365	105	2	alternative	alternative	ADJ
flr-365	105	3	approach	approach	NOUN
flr-365	105	4	to	to	ADP
flr-365	105	5	handling	handle	VERB
flr-365	105	6	the	the	DET
flr-365	105	7	length	length	NOUN
flr-365	105	8	variability	variability	NOUN
flr-365	105	9	is	be	AUX
flr-365	105	10	to	to	PART
flr-365	105	11	turn	turn	VERB
flr-365	105	12	all	all	DET
flr-365	105	13	the	the	DET
flr-365	105	14	feature	feature	NOUN
flr-365	105	15	vectors	vector	NOUN
flr-365	105	16	in	in	ADP
flr-365	105	17	a	a	DET
flr-365	105	18	given	give	VERB
flr-365	105	19	class	class	NOUN
flr-365	105	20	into	into	ADP
flr-365	105	21	vectors	vector	NOUN
flr-365	105	22	of	of	ADP
flr-365	105	23	the	the	DET
flr-365	105	24	same	same	ADJ
flr-365	105	25	length	length	NOUN
flr-365	105	26	by	by	ADP
flr-365	105	27	“	"	PUNCT
flr-365	105	28	padding	padding	NOUN
flr-365	105	29	”	"	PUNCT
flr-365	105	30	the	the	DET
flr-365	105	31	shorter	short	ADJ
flr-365	105	32	vectors	vector	NOUN
flr-365	105	33	in	in	ADP
flr-365	105	34	the	the	DET
flr-365	105	35	class	class	NOUN
flr-365	105	36	with	with	ADP
flr-365	105	37	a	a	DET
flr-365	105	38	dummy	dummy	ADJ
flr-365	105	39	value	value	NOUN
flr-365	105	40	to	to	ADP
flr-365	105	41	the	the	DET
flr-365	105	42	right	right	NOUN
flr-365	105	43	,	,	PUNCT
flr-365	105	44	up	up	ADP
flr-365	105	45	to	to	ADP
flr-365	105	46	the	the	DET
flr-365	105	47	length	length	NOUN
flr-365	105	48	of	of	ADP
flr-365	105	49	the	the	DET
flr-365	105	50	longest	long	ADJ
flr-365	105	51	feature	feature	NOUN
flr-365	105	52	vector	vector	NOUN
flr-365	105	53	in	in	ADP
flr-365	105	54	the	the	DET
flr-365	105	55	class	class	NOUN
flr-365	105	56	.	.	PUNCT
flr-365	106	1	padding	pad	VERB
flr-365	106	2	a	a	DET
flr-365	106	3	short	short	ADJ
flr-365	106	4	vector	vector	NOUN
flr-365	106	5	to	to	ADP
flr-365	106	6	the	the	DET
flr-365	106	7	right	right	NOUN
flr-365	106	8	means	mean	VERB
flr-365	106	9	that	that	SCONJ
flr-365	106	10	,	,	PUNCT
flr-365	106	11	after	after	ADP
flr-365	106	12	the	the	DET
flr-365	106	13	last	last	ADJ
flr-365	106	14	value	value	NOUN
flr-365	106	15	of	of	ADP
flr-365	106	16	the	the	DET
flr-365	106	17	short	short	ADJ
flr-365	106	18	feature	feature	NOUN
flr-365	106	19	vector	vector	NOUN
flr-365	106	20	,	,	PUNCT
flr-365	106	21	a	a	DET
flr-365	106	22	new	new	ADJ
flr-365	106	23	padded	padded	ADJ
flr-365	106	24	value	value	NOUN
flr-365	106	25	is	be	AUX
flr-365	106	26	added	add	VERB
flr-365	106	27	to	to	ADP
flr-365	106	28	the	the	DET
flr-365	106	29	end	end	NOUN
flr-365	106	30	of	of	ADP
flr-365	106	31	the	the	DET
flr-365	106	32	list	list	NOUN
flr-365	106	33	of	of	ADP
flr-365	106	34	feature	feature	NOUN
flr-365	106	35	values	value	NOUN
flr-365	106	36	until	until	SCONJ
flr-365	106	37	it	it	PRON
flr-365	106	38	is	be	AUX
flr-365	106	39	the	the	DET
flr-365	106	40	same	same	ADJ
flr-365	106	41	length	length	NOUN
flr-365	106	42	as	as	ADP
flr-365	106	43	the	the	DET
flr-365	106	44	longest	long	ADJ
flr-365	106	45	feature	feature	NOUN
flr-365	106	46	vector	vector	NOUN
flr-365	106	47	in	in	ADP
flr-365	106	48	the	the	DET
flr-365	106	49	class	class	NOUN
flr-365	106	50	.	.	PUNCT
flr-365	107	1	the	the	DET
flr-365	107	2	“	"	PUNCT
flr-365	107	3	padding	padding	NOUN
flr-365	107	4	feature	feature	NOUN
flr-365	107	5	value	value	NOUN
flr-365	107	6	”	"	PUNCT
flr-365	107	7	instances	instance	NOUN
flr-365	107	8	are	be	AUX
flr-365	107	9	different	different	ADJ
flr-365	107	10	to	to	ADP
flr-365	107	11	all	all	DET
flr-365	107	12	original	original	ADJ
flr-365	107	13	feature	feature	NOUN
flr-365	107	14	values	value	NOUN
flr-365	107	15	occurring	occur	VERB
flr-365	107	16	in	in	ADP
flr-365	107	17	the	the	DET
flr-365	107	18	data	data	NOUN
flr-365	107	19	feature	feature	NOUN
flr-365	107	20	vectors	vector	NOUN
flr-365	107	21	.	.	PUNCT
flr-365	108	1	as	as	ADP
flr-365	108	2	an	an	DET
flr-365	108	3	example	example	NOUN
flr-365	108	4	,	,	PUNCT
flr-365	108	5	if	if	SCONJ
flr-365	108	6	the	the	DET
flr-365	108	7	longest	long	ADJ
flr-365	108	8	feature	feature	NOUN
flr-365	108	9	vector	vector	NOUN
flr-365	108	10	has	have	VERB
flr-365	108	11	a	a	DET
flr-365	108	12	length	length	NOUN
flr-365	108	13	of	of	ADP
flr-365	108	14	5	5	NUM
flr-365	108	15	(	(	PUNCT
flr-365	108	16	a	a	PRON
flr-365	108	17	,	,	PUNCT
flr-365	108	18	b	b	NOUN
flr-365	108	19	,	,	PUNCT
flr-365	108	20	a	a	PRON
flr-365	108	21	,	,	PUNCT
flr-365	108	22	c	c	NOUN
flr-365	108	23	,	,	PUNCT
flr-365	108	24	a	a	NOUN
flr-365	108	25	)	)	PUNCT
flr-365	108	26	,	,	PUNCT
flr-365	108	27	and	and	CCONJ
flr-365	108	28	we	we	PRON
flr-365	108	29	have	have	VERB
flr-365	108	30	a	a	DET
flr-365	108	31	feature	feature	NOUN
flr-365	108	32	vector	vector	NOUN
flr-365	108	33	of	of	ADP
flr-365	108	34	a	a	DET
flr-365	108	35	length	length	NOUN
flr-365	108	36	of	of	ADP
flr-365	108	37	3	3	NUM
flr-365	108	38	(	(	PUNCT
flr-365	108	39	a	a	PRON
flr-365	108	40	,	,	PUNCT
flr-365	108	41	b	b	NOUN
flr-365	108	42	,	,	PUNCT
flr-365	108	43	c	c	NOUN
flr-365	108	44	)	)	PUNCT
flr-365	108	45	,	,	PUNCT
flr-365	108	46	then	then	ADV
flr-365	108	47	,	,	PUNCT
flr-365	108	48	in	in	ADP
flr-365	108	49	positions	position	NOUN
flr-365	108	50	4	4	NUM
flr-365	108	51	and	and	CCONJ
flr-365	108	52	5	5	NUM
flr-365	108	53	of	of	ADP
flr-365	108	54	the	the	DET
flr-365	108	55	short	short	ADJ
flr-365	108	56	feature	feature	NOUN
flr-365	108	57	vector	vector	NOUN
flr-365	108	58	we	we	PRON
flr-365	108	59	introduce	introduce	VERB
flr-365	108	60	the	the	DET
flr-365	108	61	padding	padding	NOUN
flr-365	108	62	feature	feature	NOUN
flr-365	108	63	value	value	NOUN
flr-365	108	64	,	,	PUNCT
flr-365	108	65	say	say	VERB
flr-365	108	66	x	x	NOUN
flr-365	108	67	,	,	PUNCT
flr-365	108	68	so	so	SCONJ
flr-365	108	69	that	that	SCONJ
flr-365	108	70	instead	instead	ADV
flr-365	108	71	of	of	ADP
flr-365	108	72	(	(	PUNCT
flr-365	108	73	a	a	DET
flr-365	108	74	,	,	PUNCT
flr-365	108	75	b	b	NOUN
flr-365	108	76	,	,	PUNCT
flr-365	108	77	c	c	X
flr-365	108	78	)	)	PUNCT
flr-365	108	79	we	we	PRON
flr-365	108	80	end	end	VERB
flr-365	108	81	up	up	ADP
flr-365	108	82	with	with	ADP
flr-365	108	83	(	(	PUNCT
flr-365	108	84	a	a	PRON
flr-365	108	85	,	,	PUNCT
flr-365	108	86	b	b	NOUN
flr-365	108	87	,	,	PUNCT
flr-365	108	88	c	c	NOUN
flr-365	108	89	,	,	PUNCT
flr-365	108	90	x	x	NOUN
flr-365	108	91	,	,	PUNCT
flr-365	108	92	x	x	NOUN
flr-365	108	93	)	)	PUNCT
flr-365	108	94	.	.	PUNCT
flr-365	109	1	the	the	DET
flr-365	109	2	class	class	NOUN
flr-365	109	3	conditional	conditional	ADJ
flr-365	109	4	probabilities	probability	NOUN
flr-365	109	5	are	be	AUX
flr-365	109	6	calculated	calculate	VERB
flr-365	109	7	as	as	ADP
flr-365	109	8	before	before	ADV
flr-365	109	9	,	,	PUNCT
flr-365	109	10	noting	note	VERB
flr-365	109	11	that	that	SCONJ
flr-365	109	12	in	in	ADP
flr-365	109	13	some	some	DET
flr-365	109	14	cases	case	NOUN
flr-365	109	15	,	,	PUNCT
flr-365	109	16	the	the	DET
flr-365	109	17	most	most	ADV
flr-365	109	18	probable	probable	ADJ
flr-365	109	19	feature	feature	NOUN
flr-365	109	20	value	value	NOUN
flr-365	109	21	might	might	AUX
flr-365	109	22	turn	turn	VERB
flr-365	109	23	out	out	ADP
flr-365	109	24	to	to	PART
flr-365	109	25	be	be	AUX
flr-365	109	26	the	the	DET
flr-365	109	27	padding	padding	NOUN
flr-365	109	28	feature	feature	NOUN
flr-365	109	29	value	value	NOUN
flr-365	109	30	.	.	PUNCT
flr-365	110	1	in	in	ADP
flr-365	110	2	the	the	DET
flr-365	110	3	case	case	NOUN
flr-365	110	4	of	of	ADP
flr-365	110	5	our	our	PRON
flr-365	110	6	analysis	analysis	NOUN
flr-365	110	7	we	we	PRON
flr-365	110	8	used	use	VERB
flr-365	110	9	the	the	DET
flr-365	110	10	first	first	ADJ
flr-365	110	11	method	method	NOUN
flr-365	110	12	to	to	PART
flr-365	110	13	deal	deal	VERB
flr-365	110	14	with	with	ADP
flr-365	110	15	length	length	NOUN
flr-365	110	16	variability	variability	NOUN
flr-365	110	17	because	because	SCONJ
flr-365	110	18	,	,	PUNCT
flr-365	110	19	among	among	ADP
flr-365	110	20	other	other	ADJ
flr-365	110	21	more	more	ADV
flr-365	110	22	technical	technical	ADJ
flr-365	110	23	reasons	reason	NOUN
flr-365	110	24	,	,	PUNCT
flr-365	110	25	it	it	PRON
flr-365	110	26	allowed	allow	VERB
flr-365	110	27	us	we	PRON
flr-365	110	28	to	to	PART
flr-365	110	29	have	have	VERB
flr-365	110	30	strings	string	NOUN
flr-365	110	31	that	that	PRON
flr-365	110	32	contain	contain	VERB
flr-365	110	33	only	only	ADV
flr-365	110	34	aoi	aoi	NOUN
flr-365	110	35	names	name	NOUN
flr-365	110	36	.	.	PUNCT
flr-365	111	1	2.5.2	2.5.2	NUM
flr-365	111	2	.	.	PUNCT
flr-365	111	3	method	method	PROPN
flr-365	111	4	two	two	NUM
flr-365	111	5	–	–	PUNCT
flr-365	111	6	the	the	DET
flr-365	111	7	central	central	ADJ
flr-365	111	8	vector	vector	NOUN
flr-365	111	9	for	for	ADP
flr-365	111	10	each	each	DET
flr-365	111	11	class	class	NOUN
flr-365	111	12	the	the	DET
flr-365	111	13	second	second	ADJ
flr-365	111	14	overall	overall	ADJ
flr-365	111	15	method	method	NOUN
flr-365	111	16	of	of	ADP
flr-365	111	17	analysis	analysis	NOUN
flr-365	111	18	involves	involve	VERB
flr-365	111	19	taking	take	VERB
flr-365	111	20	a	a	DET
flr-365	111	21	measure	measure	NOUN
flr-365	111	22	of	of	ADP
flr-365	111	23	the	the	DET
flr-365	111	24	“	"	PUNCT
flr-365	111	25	distance	distance	NOUN
flr-365	111	26	”	"	PUNCT
flr-365	111	27	between	between	ADP
flr-365	111	28	one	one	NUM
flr-365	111	29	feature	feature	NOUN
flr-365	111	30	vector	vector	NOUN
flr-365	111	31	and	and	CCONJ
flr-365	111	32	another	another	DET
flr-365	111	33	one	one	NOUN
flr-365	111	34	with	with	ADP
flr-365	111	35	the	the	DET
flr-365	111	36	levenshtein	levenshtein	PROPN
flr-365	111	37	edit	edit	PROPN
flr-365	111	38	distance	distance	NOUN
flr-365	111	39	metric	metric	NOUN
flr-365	111	40	.	.	PUNCT
flr-365	112	1	the	the	DET
flr-365	112	2	edit	edit	NOUN
flr-365	112	3	distance	distance	NOUN
flr-365	112	4	between	between	ADP
flr-365	112	5	two	two	NUM
flr-365	112	6	feature	feature	NOUN
flr-365	112	7	vectors	vector	NOUN
flr-365	112	8	is	be	AUX
flr-365	112	9	given	give	VERB
flr-365	112	10	as	as	ADP
flr-365	112	11	the	the	DET
flr-365	112	12	number	number	NOUN
flr-365	112	13	of	of	ADP
flr-365	112	14	feature	feature	NOUN
flr-365	112	15	deletions	deletion	NOUN
flr-365	112	16	,	,	PUNCT
flr-365	112	17	insertions	insertion	NOUN
flr-365	112	18	,	,	PUNCT
flr-365	112	19	and	and	CCONJ
flr-365	112	20	replacements	replacement	NOUN
flr-365	112	21	that	that	PRON
flr-365	112	22	are	be	AUX
flr-365	112	23	required	require	VERB
flr-365	112	24	to	to	PART
flr-365	112	25	transform	transform	VERB
flr-365	112	26	one	one	NUM
flr-365	112	27	of	of	ADP
flr-365	112	28	the	the	DET
flr-365	112	29	vectors	vector	NOUN
flr-365	112	30	into	into	ADP
flr-365	112	31	the	the	DET
flr-365	112	32	other	other	ADJ
flr-365	112	33	one	one	NUM
flr-365	112	34	.	.	PUNCT
flr-365	113	1	the	the	DET
flr-365	113	2	method	method	NOUN
flr-365	113	3	then	then	ADV
flr-365	113	4	works	work	VERB
flr-365	113	5	by	by	ADP
flr-365	113	6	finding	find	VERB
flr-365	113	7	a	a	DET
flr-365	113	8	feature	feature	NOUN
flr-365	113	9	vector	vector	NOUN
flr-365	113	10	,	,	PUNCT
flr-365	113	11	which	which	PRON
flr-365	113	12	is	be	AUX
flr-365	113	13	called	call	VERB
flr-365	113	14	a	a	DET
flr-365	113	15	central	central	ADJ
flr-365	113	16	feature	feature	NOUN
flr-365	113	17	vector	vector	NOUN
flr-365	113	18	,	,	PUNCT
flr-365	113	19	that	that	PRON
flr-365	113	20	minimises	minimise	VERB
flr-365	113	21	the	the	DET
flr-365	113	22	total	total	ADJ
flr-365	113	23	edit	edit	NOUN
flr-365	113	24	distance	distance	NOUN
flr-365	113	25	between	between	ADP
flr-365	113	26	the	the	DET
flr-365	113	27	central	central	ADJ
flr-365	113	28	feature	feature	NOUN
flr-365	113	29	vector	vector	NOUN
flr-365	113	30	and	and	CCONJ
flr-365	113	31	each	each	PRON
flr-365	113	32	of	of	ADP
flr-365	113	33	the	the	DET
flr-365	113	34	other	other	ADJ
flr-365	113	35	feature	feature	NOUN
flr-365	113	36	vectors	vector	NOUN
flr-365	113	37	.	.	PUNCT
flr-365	114	1	methods	method	NOUN
flr-365	114	2	to	to	PART
flr-365	114	3	compute	compute	VERB
flr-365	114	4	edit	edit	NOUN
flr-365	114	5	distance	distance	NOUN
flr-365	114	6	and	and	CCONJ
flr-365	114	7	thus	thus	ADV
flr-365	114	8	a	a	DET
flr-365	114	9	central	central	ADJ
flr-365	114	10	feature	feature	NOUN
flr-365	114	11	vector	vector	NOUN
flr-365	114	12	are	be	AUX
flr-365	114	13	well	well	ADV
flr-365	114	14	understood	understand	VERB
flr-365	114	15	in	in	ADP
flr-365	114	16	the	the	DET
flr-365	114	17	computer	computer	NOUN
flr-365	114	18	science	science	NOUN
flr-365	114	19	or	or	CCONJ
flr-365	114	20	mathematics	mathematics	NOUN
flr-365	114	21	literature	literature	NOUN
flr-365	114	22	(	(	PUNCT
flr-365	114	23	see	see	VERB
flr-365	114	24	skiena	skiena	ADJ
flr-365	114	25	,	,	PUNCT
flr-365	114	26	2010	2010	NUM
flr-365	114	27	for	for	ADP
flr-365	114	28	a	a	DET
flr-365	114	29	review	review	NOUN
flr-365	114	30	)	)	PUNCT
flr-365	114	31	.	.	PUNCT
flr-365	115	1	these	these	DET
flr-365	115	2	central	central	ADJ
flr-365	115	3	feature	feature	NOUN
flr-365	115	4	vectors	vector	NOUN
flr-365	115	5	also	also	ADV
flr-365	115	6	reflect	reflect	VERB
flr-365	115	7	,	,	PUNCT
flr-365	115	8	on	on	ADP
flr-365	115	9	average	average	ADJ
flr-365	115	10	,	,	PUNCT
flr-365	115	11	what	what	PRON
flr-365	115	12	is	be	AUX
flr-365	115	13	happening	happen	VERB
flr-365	115	14	with	with	ADP
flr-365	115	15	all	all	DET
flr-365	115	16	the	the	DET
flr-365	115	17	sequences	sequence	NOUN
flr-365	115	18	,	,	PUNCT
flr-365	115	19	and	and	CCONJ
flr-365	115	20	should	should	AUX
flr-365	115	21	be	be	AUX
flr-365	115	22	generally	generally	ADV
flr-365	115	23	similar	similar	ADJ
flr-365	115	24	to	to	ADP
flr-365	115	25	those	those	PRON
flr-365	115	26	obtained	obtain	VERB
flr-365	115	27	with	with	ADP
flr-365	115	28	method	method	NOUN
flr-365	115	29	one	one	NUM
flr-365	115	30	the	the	DET
flr-365	115	31	most	most	ADV
flr-365	115	32	probable	probable	ADJ
flr-365	115	33	vector	vector	NOUN
flr-365	115	34	.	.	PUNCT
flr-365	116	1	3	3	X
flr-365	116	2	.	.	NOUN
flr-365	116	3	results	result	VERB
flr-365	116	4	the	the	DET
flr-365	116	5	results	result	NOUN
flr-365	116	6	of	of	ADP
flr-365	116	7	method	method	NOUN
flr-365	116	8	one	one	NUM
flr-365	116	9	show	show	VERB
flr-365	116	10	that	that	SCONJ
flr-365	116	11	classifying	classify	VERB
flr-365	116	12	multiple	multiple	ADJ
flr-365	116	13	scanpaths	scanpath	NOUN
flr-365	116	14	,	,	PUNCT
flr-365	116	15	particularly	particularly	ADV
flr-365	116	16	,	,	PUNCT
flr-365	116	17	dwell	dwell	NOUN
flr-365	116	18	area	area	NOUN
flr-365	116	19	of	of	ADP
flr-365	116	20	interest	interest	NOUN
flr-365	116	21	(	(	PUNCT
flr-365	116	22	daoi	daoi	ADJ
flr-365	116	23	)	)	PUNCT
flr-365	116	24	sequences	sequence	NOUN
flr-365	116	25	with	with	ADP
flr-365	116	26	naïve	naïve	ADJ
flr-365	116	27	bayes	bayes	NOUN
flr-365	116	28	works	work	VERB
flr-365	116	29	extremely	extremely	ADV
flr-365	116	30	well	well	ADV
flr-365	116	31	(	(	PUNCT
flr-365	116	32	where	where	SCONJ
flr-365	116	33	a	a	DET
flr-365	116	34	dwell	dwell	NOUN
flr-365	116	35	is	be	AUX
flr-365	116	36	a	a	DET
flr-365	116	37	continuous	continuous	ADJ
flr-365	116	38	series	series	NOUN
flr-365	116	39	of	of	ADP
flr-365	116	40	fixations	fixation	NOUN
flr-365	116	41	within	within	ADP
flr-365	116	42	the	the	DET
flr-365	116	43	same	same	ADJ
flr-365	116	44	aoi	aoi	NOUN
flr-365	116	45	)	)	PUNCT
flr-365	116	46	.	.	PUNCT
flr-365	117	1	this	this	PRON
flr-365	117	2	in	in	ADP
flr-365	117	3	itself	itself	PRON
flr-365	117	4	is	be	AUX
flr-365	117	5	informative	informative	ADJ
flr-365	117	6	,	,	PUNCT
flr-365	117	7	as	as	SCONJ
flr-365	117	8	it	it	PRON
flr-365	117	9	means	mean	VERB
flr-365	117	10	that	that	SCONJ
flr-365	117	11	the	the	DET
flr-365	117	12	elements	element	NOUN
flr-365	117	13	of	of	ADP
flr-365	117	14	a	a	DET
flr-365	117	15	daoi	daoi	ADJ
flr-365	117	16	sequence	sequence	NOUN
flr-365	117	17	are	be	AUX
flr-365	117	18	not	not	PART
flr-365	117	19	necessarily	necessarily	ADV
flr-365	117	20	correlated	correlate	VERB
flr-365	117	21	,	,	PUNCT
flr-365	117	22	that	that	ADV
flr-365	117	23	is	is	ADV
flr-365	117	24	,	,	PUNCT
flr-365	117	25	after	after	ADP
flr-365	117	26	looking	look	VERB
flr-365	117	27	at	at	ADP
flr-365	117	28	any	any	DET
flr-365	117	29	one	one	NUM
flr-365	117	30	particular	particular	ADJ
flr-365	117	31	aoi	aoi	NOUN
flr-365	117	32	,	,	PUNCT
flr-365	117	33	the	the	DET
flr-365	117	34	observer	observer	NOUN
flr-365	117	35	may	may	AUX
flr-365	117	36	look	look	VERB
flr-365	117	37	at	at	ADP
flr-365	117	38	any	any	DET
flr-365	117	39	other	other	ADJ
flr-365	117	40	aoi	aoi	NOUN
flr-365	117	41	with	with	ADP
flr-365	117	42	equal	equal	ADJ
flr-365	117	43	likelihood	likelihood	NOUN
flr-365	117	44	.	.	PUNCT
flr-365	118	1	both	both	PRON
flr-365	118	2	method	method	VERB
flr-365	118	3	one	one	NUM
flr-365	118	4	and	and	CCONJ
flr-365	118	5	method	method	VERB
flr-365	118	6	two	two	NUM
flr-365	118	7	allowed	allow	VERB
flr-365	118	8	us	we	PRON
flr-365	118	9	to	to	PART
flr-365	118	10	produce	produce	VERB
flr-365	118	11	“	"	PUNCT
flr-365	118	12	virtual	virtual	ADJ
flr-365	118	13	scanpaths	scanpath	NOUN
flr-365	118	14	”	"	PUNCT
flr-365	118	15	(	(	PUNCT
flr-365	118	16	the	the	DET
flr-365	118	17	most	most	ADV
flr-365	118	18	probable	probable	ADJ
flr-365	118	19	vector	vector	NOUN
flr-365	118	20	and	and	CCONJ
flr-365	118	21	the	the	DET
flr-365	118	22	central	central	ADJ
flr-365	118	23	vector	vector	NOUN
flr-365	118	24	scanpaths	scanpath	NOUN
flr-365	118	25	)	)	PUNCT
flr-365	118	26	that	that	PRON
flr-365	118	27	demonstrate	demonstrate	VERB
flr-365	118	28	what	what	PRON
flr-365	118	29	children	child	NOUN
flr-365	118	30	are	be	AUX
flr-365	118	31	doing	do	VERB
flr-365	118	32	when	when	SCONJ
flr-365	118	33	they	they	PRON
flr-365	118	34	are	be	AUX
flr-365	118	35	solving	solve	VERB
flr-365	118	36	the	the	DET
flr-365	118	37	problem	problem	NOUN
flr-365	118	38	correctly	correctly	ADV
flr-365	118	39	or	or	CCONJ
flr-365	118	40	incorrectly	incorrectly	ADV
flr-365	118	41	.	.	PUNCT
flr-365	119	1	3.1	3.1	NUM
flr-365	119	2	using	use	VERB
flr-365	119	3	a	a	DET
flr-365	119	4	naïve	naïve	ADJ
flr-365	119	5	bayes	bayes	NOUN
flr-365	119	6	classifier	classifier	NOUN
flr-365	119	7	to	to	PART
flr-365	119	8	obtain	obtain	VERB
flr-365	119	9	most	most	ADV
flr-365	119	10	probable	probable	ADJ
flr-365	119	11	vectors	vector	NOUN
flr-365	119	12	using	use	VERB
flr-365	119	13	a	a	DET
flr-365	119	14	naïve	naïve	ADJ
flr-365	119	15	bayes	bayes	NOUN
flr-365	119	16	classifier	classifier	NOUN
flr-365	119	17	we	we	PRON
flr-365	119	18	were	be	AUX
flr-365	119	19	able	able	ADJ
flr-365	119	20	to	to	PART
flr-365	119	21	get	get	VERB
flr-365	119	22	a	a	DET
flr-365	119	23	perfect	perfect	ADJ
flr-365	119	24	classification	classification	NOUN
flr-365	119	25	,	,	PUNCT
flr-365	119	26	where	where	SCONJ
flr-365	119	27	our	our	PRON
flr-365	119	28	training	training	NOUN
flr-365	119	29	error	error	NOUN
flr-365	119	30	rate	rate	NOUN
flr-365	119	31	was	be	AUX
flr-365	119	32	zero	zero	NUM
flr-365	119	33	.	.	PUNCT
flr-365	120	1	since	since	SCONJ
flr-365	120	2	predictive	predictive	ADJ
flr-365	120	3	analyses	analysis	NOUN
flr-365	120	4	was	be	AUX
flr-365	120	5	not	not	PART
flr-365	120	6	our	our	PRON
flr-365	120	7	goal	goal	NOUN
flr-365	120	8	,	,	PUNCT
flr-365	120	9	we	we	PRON
flr-365	120	10	did	do	AUX
flr-365	120	11	not	not	PART
flr-365	120	12	write	write	VERB
flr-365	120	13	our	our	PRON
flr-365	120	14	own	own	ADJ
flr-365	120	15	cross	cross	NOUN
flr-365	120	16	validation	validation	NOUN
flr-365	120	17	routine	routine	NOUN
flr-365	120	18	.	.	PUNCT
flr-365	121	1	however	however	ADV
flr-365	121	2	,	,	PUNCT
flr-365	121	3	with	with	ADP
flr-365	121	4	a	a	DET
flr-365	121	5	commercial	commercial	ADJ
flr-365	121	6	package	package	NOUN
flr-365	121	7	that	that	PRON
flr-365	121	8	handles	handle	VERB
flr-365	121	9	missing	miss	VERB
flr-365	121	10	data	datum	NOUN
flr-365	121	11	very	very	ADV
flr-365	121	12	differently	differently	ADV
flr-365	121	13	(	(	PUNCT
flr-365	121	14	mathematica	mathematica	PROPN
flr-365	121	15	,	,	PUNCT
flr-365	121	16	wolfram	wolfram	PROPN
flr-365	121	17	research	research	PROPN
flr-365	121	18	)	)	PUNCT
flr-365	121	19	,	,	PUNCT
flr-365	121	20	we	we	PRON
flr-365	121	21	obtained	obtain	VERB
flr-365	121	22	a	a	DET
flr-365	121	23	training	training	NOUN
flr-365	121	24	error	error	NOUN
flr-365	121	25	rate	rate	NOUN
flr-365	121	26	of	of	ADP
flr-365	121	27	.15	.15	NUM
flr-365	121	28	and	and	CCONJ
flr-365	121	29	a	a	DET
flr-365	121	30	“	"	PUNCT
flr-365	121	31	leave	leave	VERB
flr-365	121	32	one	one	NUM
flr-365	121	33	out	out	ADP
flr-365	121	34	”	"	PUNCT
flr-365	121	35	cross	cross	NOUN
flr-365	121	36	validation	validation	NOUN
flr-365	121	37	error	error	NOUN
flr-365	121	38	rate	rate	NOUN
flr-365	121	39	of	of	ADP
flr-365	121	40	.27	.27	NUM
flr-365	121	41	.	.	PUNCT
flr-365	122	1	this	this	PRON
flr-365	122	2	suggested	suggest	VERB
flr-365	122	3	that	that	SCONJ
flr-365	122	4	the	the	DET
flr-365	122	5	aois	aois	NOUN
flr-365	122	6	in	in	ADP
flr-365	122	7	the	the	DET
flr-365	122	8	gaze	gaze	NOUN
flr-365	122	9	sequences	sequence	NOUN
flr-365	122	10	are	be	AUX
flr-365	122	11	uncorrelated	uncorrelate	VERB
flr-365	122	12	along	along	ADP
flr-365	122	13	the	the	DET
flr-365	122	14	sequences	sequence	NOUN
flr-365	122	15	and	and	CCONJ
flr-365	122	16	obey	obey	VERB
flr-365	122	17	the	the	DET
flr-365	122	18	naïve	naïve	ADJ
flr-365	122	19	bayes	bayes	NOUN
flr-365	122	20	assumption	assumption	NOUN
flr-365	122	21	.	.	PUNCT
flr-365	123	1	what	what	PRON
flr-365	123	2	makes	make	VERB
flr-365	123	3	the	the	DET
flr-365	123	4	use	use	NOUN
flr-365	123	5	of	of	ADP
flr-365	123	6	a	a	DET
flr-365	123	7	naïve	naïve	ADJ
flr-365	123	8	bayes	bayes	NOUN
flr-365	123	9	classifier	classifier	NOUN
flr-365	123	10	attractive	attractive	ADJ
flr-365	123	11	to	to	ADP
flr-365	123	12	us	we	PRON
flr-365	123	13	is	be	AUX
flr-365	123	14	the	the	DET
flr-365	123	15	possibility	possibility	NOUN
flr-365	123	16	of	of	ADP
flr-365	123	17	generating	generate	VERB
flr-365	123	18	“	"	PUNCT
flr-365	123	19	virtual	virtual	ADJ
flr-365	123	20	scanpaths	scanpath	NOUN
flr-365	123	21	”	"	PUNCT
flr-365	123	22	that	that	PRON
flr-365	123	23	are	be	AUX
flr-365	123	24	“	"	PUNCT
flr-365	123	25	most	most	ADV
flr-365	123	26	probable	probable	ADJ
flr-365	123	27	”	"	PUNCT
flr-365	123	28	.	.	PUNCT
flr-365	124	1	since	since	SCONJ
flr-365	124	2	for	for	ADP
flr-365	124	3	each	each	DET
flr-365	124	4	feature	feature	NOUN
flr-365	124	5	(	(	PUNCT
flr-365	124	6	each	each	DET
flr-365	124	7	coordinate	coordinate	NOUN
flr-365	124	8	of	of	ADP
flr-365	124	9	the	the	DET
flr-365	124	10	scanpath	scanpath	NOUN
flr-365	124	11	sequences	sequence	NOUN
flr-365	124	12	)	)	PUNCT
flr-365	124	13	and	and	CCONJ
flr-365	124	14	for	for	ADP
flr-365	124	15	each	each	DET
flr-365	124	16	class	class	NOUN
flr-365	124	17	we	we	PRON
flr-365	124	18	obtain	obtain	VERB
flr-365	124	19	a	a	DET
flr-365	124	20	probability	probability	NOUN
flr-365	124	21	distribution	distribution	NOUN
flr-365	124	22	of	of	ADP
flr-365	124	23	the	the	DET
flr-365	124	24	possible	possible	ADJ
flr-365	124	25	aois	aois	NOUN
flr-365	124	26	,	,	PUNCT
flr-365	124	27	the	the	DET
flr-365	124	28	most	most	ADV
flr-365	124	29	probable	probable	ADJ
flr-365	124	30	one	one	PRON
flr-365	124	31	can	can	AUX
flr-365	124	32	be	be	AUX
flr-365	124	33	selected	select	VERB
flr-365	124	34	.	.	PUNCT
flr-365	125	1	this	this	PRON
flr-365	125	2	provides	provide	VERB
flr-365	125	3	us	we	PRON
flr-365	125	4	with	with	ADP
flr-365	125	5	an	an	DET
flr-365	125	6	exemplary	exemplary	ADJ
flr-365	125	7	sequence	sequence	NOUN
flr-365	125	8	that	that	PRON
flr-365	125	9	provides	provide	VERB
flr-365	125	10	good	good	ADJ
flr-365	125	11	qualitative	qualitative	ADJ
flr-365	125	12	data	datum	NOUN
flr-365	125	13	regarding	regard	VERB
flr-365	125	14	what	what	PRON
flr-365	125	15	the	the	DET
flr-365	125	16	children	child	NOUN
flr-365	125	17	are	be	AUX
flr-365	125	18	doing	do	VERB
flr-365	125	19	while	while	SCONJ
flr-365	125	20	they	they	PRON
flr-365	125	21	solve	solve	VERB
flr-365	125	22	the	the	DET
flr-365	125	23	task	task	NOUN
flr-365	125	24	,	,	PUNCT
flr-365	125	25	depending	depend	VERB
flr-365	125	26	on	on	ADP
flr-365	125	27	whether	whether	SCONJ
flr-365	125	28	they	they	PRON
flr-365	125	29	do	do	AUX
flr-365	125	30	so	so	ADV
flr-365	125	31	correctly	correctly	ADV
flr-365	125	32	or	or	CCONJ
flr-365	125	33	incorrectly	incorrectly	ADV
flr-365	125	34	.	.	PUNCT
flr-365	126	1	on	on	ADP
flr-365	126	2	average	average	ADJ
flr-365	126	3	,	,	PUNCT
flr-365	126	4	the	the	DET
flr-365	126	5	lengths	length	NOUN
flr-365	126	6	of	of	ADP
flr-365	126	7	the	the	DET
flr-365	126	8	scanpaths	scanpath	NOUN
flr-365	126	9	of	of	ADP
flr-365	126	10	children	child	NOUN
flr-365	126	11	in	in	ADP
flr-365	126	12	either	either	DET
flr-365	126	13	group	group	NOUN
flr-365	126	14	are	be	AUX
flr-365	126	15	largely	largely	ADV
flr-365	126	16	similar	similar	ADJ
flr-365	126	17	(	(	PUNCT
flr-365	126	18	69	69	NUM
flr-365	126	19	±	±	NUM
flr-365	126	20	31	31	NUM
flr-365	126	21	aois	aois	NOUN
flr-365	126	22	for	for	ADP
flr-365	126	23	children	child	NOUN
flr-365	126	24	who	who	PRON
flr-365	126	25	responded	respond	VERB
flr-365	126	26	correctly	correctly	ADV
flr-365	126	27	,	,	PUNCT
flr-365	126	28	vs	vs	ADP
flr-365	126	29	77	77	NUM
flr-365	126	30	±	±	NUM
flr-365	126	31	39	39	NUM
flr-365	126	32	for	for	ADP
flr-365	126	33	children	child	NOUN
flr-365	126	34	who	who	PRON
flr-365	126	35	responded	respond	VERB
flr-365	126	36	incorrectly	incorrectly	ADV
flr-365	126	37	)	)	PUNCT
flr-365	126	38	,	,	PUNCT
flr-365	126	39	although	although	SCONJ
flr-365	126	40	they	they	PRON
flr-365	126	41	are	be	AUX
flr-365	126	42	slightly	slightly	ADV
flr-365	126	43	shorter	short	ADJ
flr-365	126	44	for	for	ADP
flr-365	126	45	children	child	NOUN
flr-365	126	46	who	who	PRON
flr-365	126	47	completed	complete	VERB
flr-365	126	48	the	the	DET
flr-365	126	49	task	task	NOUN
flr-365	126	50	correctly	correctly	ADV
flr-365	126	51	.	.	PUNCT
flr-365	127	1	the	the	DET
flr-365	127	2	qualitative	qualitative	ADJ
flr-365	127	3	information	information	NOUN
flr-365	127	4	provided	provide	VERB
flr-365	127	5	by	by	ADP
flr-365	127	6	the	the	DET
flr-365	127	7	average	average	ADJ
flr-365	127	8	scanpaths	scanpath	NOUN
flr-365	127	9	becomes	become	VERB
flr-365	127	10	even	even	ADV
flr-365	127	11	more	more	ADV
flr-365	127	12	evident	evident	ADJ
flr-365	127	13	with	with	ADP
flr-365	127	14	further	further	ADJ
flr-365	127	15	manipulation	manipulation	NOUN
flr-365	127	16	and	and	CCONJ
flr-365	127	17	post	post	NOUN
flr-365	127	18	-	-	ADJ
flr-365	127	19	processing	processing	NOUN
flr-365	127	20	of	of	ADP
flr-365	127	21	the	the	DET
flr-365	127	22	average	average	ADJ
flr-365	127	23	scanpaths	scanpath	NOUN
flr-365	127	24	.	.	PUNCT
flr-365	128	1	if	if	SCONJ
flr-365	128	2	we	we	PRON
flr-365	128	3	merge	merge	VERB
flr-365	128	4	the	the	DET
flr-365	128	5	aois	aois	NOUN
flr-365	128	6	which	which	PRON
flr-365	128	7	are	be	AUX
flr-365	128	8	contiguous	contiguous	ADJ
flr-365	128	9	and	and	CCONJ
flr-365	128	10	identical	identical	ADJ
flr-365	128	11	in	in	ADP
flr-365	128	12	the	the	DET
flr-365	128	13	average	average	ADJ
flr-365	128	14	scanpath	scanpath	NOUN
flr-365	128	15	into	into	ADP
flr-365	128	16	a	a	DET
flr-365	128	17	single	single	ADJ
flr-365	128	18	instance	instance	NOUN
flr-365	128	19	,	,	PUNCT
flr-365	128	20	and	and	CCONJ
flr-365	128	21	remove	remove	VERB
flr-365	128	22	dwells	dwell	NOUN
flr-365	128	23	on	on	ADP
flr-365	128	24	blank	blank	ADJ
flr-365	128	25	spaces	space	NOUN
flr-365	128	26	,	,	PUNCT
flr-365	128	27	the	the	DET
flr-365	128	28	average	average	ADJ
flr-365	128	29	scanpaths	scanpath	NOUN
flr-365	128	30	become	become	VERB
flr-365	128	31	much	much	ADV
flr-365	128	32	shorter	short	ADJ
flr-365	128	33	,	,	PUNCT
flr-365	128	34	and	and	CCONJ
flr-365	128	35	this	this	PRON
flr-365	128	36	varies	vary	VERB
flr-365	128	37	between	between	ADP
flr-365	128	38	the	the	DET
flr-365	128	39	two	two	NUM
flr-365	128	40	classes	class	NOUN
flr-365	128	41	.	.	PUNCT
flr-365	129	1	the	the	DET
flr-365	129	2	correct	correct	ADJ
flr-365	129	3	children	child	NOUN
flr-365	129	4	’s	’s	PART
flr-365	129	5	post	post	NOUN
flr-365	129	6	processed	process	VERB
flr-365	129	7	(	(	PUNCT
flr-365	129	8	merged	merged	ADJ
flr-365	129	9	)	)	PUNCT
flr-365	129	10	average	average	ADJ
flr-365	129	11	scanpath	scanpath	NOUN
flr-365	129	12	is	be	AUX
flr-365	129	13	as	as	SCONJ
flr-365	129	14	follows	follow	VERB
flr-365	129	15	:	:	PUNCT
flr-365	129	16	{	{	PUNCT
flr-365	129	17	c1,b1,a1,b2,a2,b2,a2,a3,b2,a3,b2,a3,a1,a3,a1,a3,a1,a2,a1,a3,a1,a3,a1	c1,b1,a1,b2,a2,b2,a2,a3,b2,a3,b2,a3,a1,a3,a1,a3,a1,a2,a1,a3,a1,a3,a1	X
flr-365	129	18	}	}	PUNCT
flr-365	129	19	and	and	CCONJ
flr-365	129	20	the	the	DET
flr-365	129	21	incorrect	incorrect	ADJ
flr-365	129	22	children	child	NOUN
flr-365	129	23	’s	’s	PART
flr-365	129	24	post	post	NOUN
flr-365	129	25	processed	process	VERB
flr-365	129	26	(	(	PUNCT
flr-365	129	27	merged	merged	ADJ
flr-365	129	28	)	)	PUNCT
flr-365	129	29	average	average	ADJ
flr-365	129	30	scanpath	scanpath	NOUN
flr-365	129	31	is	be	AUX
flr-365	129	32	as	as	SCONJ
flr-365	129	33	follows	follow	VERB
flr-365	129	34	:	:	PUNCT
flr-365	129	35	{	{	PUNCT
flr-365	129	36	c2,c1,b1,a1,b1,a1,b1,b2,b1,b2,a1,b2,c2,b2,a1,c2,b2,a3,b2,c2,a3,a1,a3,a1,c1,c2,b2,a2,a3,b2,a1	c2,c1,b1,a1,b1,a1,b1,b2,b1,b2,a1,b2,c2,b2,a1,c2,b2,a3,b2,c2,a3,a1,a3,a1,c1,c2,b2,a2,a3,b2,a1	X
flr-365	129	37	,	,	PUNCT
flr-365	129	38	b2,a1,a3,c2,b3,c2,b2,a3,a2	b2,a1,a3,c2,b3,c2,b2,a3,a2	NUM
flr-365	129	39	}	}	PUNCT
flr-365	129	40	as	as	SCONJ
flr-365	129	41	can	can	AUX
flr-365	129	42	be	be	AUX
flr-365	129	43	observed	observe	VERB
flr-365	129	44	,	,	PUNCT
flr-365	129	45	the	the	DET
flr-365	129	46	incorrect	incorrect	ADJ
flr-365	129	47	children	child	NOUN
flr-365	129	48	’s	’s	PART
flr-365	129	49	merged	merge	VERB
flr-365	129	50	average	average	ADJ
flr-365	129	51	scanpath	scanpath	NOUN
flr-365	129	52	is	be	AUX
flr-365	129	53	almost	almost	ADV
flr-365	129	54	twice	twice	ADV
flr-365	129	55	as	as	ADV
flr-365	129	56	long	long	ADJ
flr-365	129	57	(	(	PUNCT
flr-365	129	58	40	40	NUM
flr-365	129	59	aois	aois	NOUN
flr-365	129	60	)	)	PUNCT
flr-365	129	61	as	as	ADP
flr-365	129	62	that	that	PRON
flr-365	129	63	of	of	ADP
flr-365	129	64	correct	correct	ADJ
flr-365	129	65	children	child	NOUN
flr-365	129	66	(	(	PUNCT
flr-365	129	67	23	23	NUM
flr-365	129	68	aois	aois	NOUN
flr-365	129	69	)	)	PUNCT
flr-365	129	70	.	.	PUNCT
flr-365	130	1	it	it	PRON
flr-365	130	2	is	be	AUX
flr-365	130	3	notable	notable	ADJ
flr-365	130	4	that	that	SCONJ
flr-365	130	5	a4	a4	NOUN
flr-365	130	6	does	do	AUX
flr-365	130	7	not	not	PART
flr-365	130	8	feature	feature	VERB
flr-365	130	9	in	in	ADP
flr-365	130	10	the	the	DET
flr-365	130	11	merged	merged	ADJ
flr-365	130	12	average	average	ADJ
flr-365	130	13	scanpath	scanpath	NOUN
flr-365	130	14	for	for	ADP
flr-365	130	15	either	either	CCONJ
flr-365	130	16	the	the	DET
flr-365	130	17	correct	correct	ADJ
flr-365	130	18	or	or	CCONJ
flr-365	130	19	incorrect	incorrect	ADJ
flr-365	130	20	children	child	NOUN
flr-365	130	21	.	.	PUNCT
flr-365	131	1	this	this	PRON
flr-365	131	2	is	be	AUX
flr-365	131	3	likely	likely	ADJ
flr-365	131	4	to	to	PART
flr-365	131	5	indicate	indicate	VERB
flr-365	131	6	that	that	SCONJ
flr-365	131	7	while	while	SCONJ
flr-365	131	8	children	child	NOUN
flr-365	131	9	may	may	AUX
flr-365	131	10	have	have	AUX
flr-365	131	11	accessed	access	VERB
flr-365	131	12	a4	a4	NOUN
flr-365	131	13	in	in	ADP
flr-365	131	14	their	their	PRON
flr-365	131	15	scanpath	scanpath	NOUN
flr-365	131	16	,	,	PUNCT
flr-365	131	17	there	there	PRON
flr-365	131	18	is	be	VERB
flr-365	131	19	not	not	PART
flr-365	131	20	one	one	NUM
flr-365	131	21	clear	clear	ADJ
flr-365	131	22	position	position	NOUN
flr-365	131	23	in	in	ADP
flr-365	131	24	the	the	DET
flr-365	131	25	participants	participant	NOUN
flr-365	131	26	’	'	PUNCT
flr-365	131	27	sequences	sequence	NOUN
flr-365	131	28	where	where	SCONJ
flr-365	131	29	a4	a4	NOUN
flr-365	131	30	features	feature	VERB
flr-365	131	31	,	,	PUNCT
flr-365	131	32	therefore	therefore	ADV
flr-365	131	33	it	it	PRON
flr-365	131	34	does	do	AUX
flr-365	131	35	not	not	PART
flr-365	131	36	appear	appear	VERB
flr-365	131	37	in	in	ADP
flr-365	131	38	the	the	DET
flr-365	131	39	average	average	ADJ
flr-365	131	40	scanpath	scanpath	NOUN
flr-365	131	41	.	.	PUNCT
flr-365	132	1	the	the	DET
flr-365	132	2	percentage	percentage	NOUN
flr-365	132	3	of	of	ADP
flr-365	132	4	overall	overall	ADJ
flr-365	132	5	aoi	aoi	NOUN
flr-365	132	6	accessed	access	VERB
flr-365	132	7	in	in	ADP
flr-365	132	8	the	the	DET
flr-365	132	9	merged	merge	VERB
flr-365	132	10	average	average	ADJ
flr-365	132	11	scanpath	scanpath	NOUN
flr-365	132	12	are	be	AUX
flr-365	132	13	presented	present	VERB
flr-365	132	14	in	in	ADP
flr-365	132	15	figure	figure	NOUN
flr-365	132	16	2	2	NUM
flr-365	132	17	.	.	PUNCT
flr-365	133	1	this	this	PRON
flr-365	133	2	shows	show	VERB
flr-365	133	3	that	that	SCONJ
flr-365	133	4	the	the	DET
flr-365	133	5	gaze	gaze	NOUN
flr-365	133	6	of	of	ADP
flr-365	133	7	the	the	DET
flr-365	133	8	incorrect	incorrect	ADJ
flr-365	133	9	children	child	NOUN
flr-365	133	10	wandered	wander	VERB
flr-365	133	11	more	more	ADJ
flr-365	133	12	than	than	ADP
flr-365	133	13	the	the	DET
flr-365	133	14	gaze	gaze	NOUN
flr-365	133	15	of	of	ADP
flr-365	133	16	correct	correct	ADJ
flr-365	133	17	children	child	NOUN
flr-365	133	18	.	.	PUNCT
flr-365	134	1	it	it	PRON
flr-365	134	2	is	be	AUX
flr-365	134	3	also	also	ADV
flr-365	134	4	interesting	interesting	ADJ
flr-365	134	5	to	to	PART
flr-365	134	6	note	note	VERB
flr-365	134	7	that	that	SCONJ
flr-365	134	8	the	the	DET
flr-365	134	9	incorrect	incorrect	ADJ
flr-365	134	10	children	child	NOUN
flr-365	134	11	spread	spread	VERB
flr-365	134	12	their	their	PRON
flr-365	134	13	attention	attention	NOUN
flr-365	134	14	relatively	relatively	ADV
flr-365	134	15	evenly	evenly	ADV
flr-365	134	16	across	across	ADP
flr-365	134	17	the	the	DET
flr-365	134	18	a	a	NOUN
flr-365	134	19	,	,	PUNCT
flr-365	134	20	b	b	NOUN
flr-365	134	21	,	,	PUNCT
flr-365	134	22	and	and	CCONJ
flr-365	134	23	c	c	NOUN
flr-365	134	24	areas	area	NOUN
flr-365	134	25	,	,	PUNCT
flr-365	134	26	whereas	whereas	SCONJ
flr-365	134	27	the	the	DET
flr-365	134	28	correct	correct	ADJ
flr-365	134	29	children	child	NOUN
flr-365	134	30	exhibited	exhibit	VERB
flr-365	134	31	greater	great	ADJ
flr-365	134	32	visual	visual	ADJ
flr-365	134	33	attention	attention	NOUN
flr-365	134	34	(	(	PUNCT
flr-365	134	35	i.e.	i.e.	X
flr-365	134	36	highest	high	ADJ
flr-365	134	37	percentage	percentage	NOUN
flr-365	134	38	of	of	ADP
flr-365	134	39	dwells	dwell	NOUN
flr-365	134	40	)	)	PUNCT
flr-365	134	41	on	on	ADP
flr-365	134	42	the	the	DET
flr-365	134	43	more	more	ADV
flr-365	134	44	critical	critical	ADJ
flr-365	134	45	a	a	DET
flr-365	134	46	areas	area	NOUN
flr-365	134	47	.	.	PUNCT
flr-365	135	1	figure	figure	VERB
flr-365	135	2	2	2	NUM
flr-365	135	3	.	.	NOUN
flr-365	135	4	percentage	percentage	NOUN
flr-365	135	5	of	of	ADP
flr-365	135	6	aoi	aoi	NOUN
flr-365	135	7	access	access	NOUN
flr-365	135	8	in	in	ADP
flr-365	135	9	the	the	DET
flr-365	135	10	merged	merged	ADJ
flr-365	135	11	average	average	ADJ
flr-365	135	12	scanpath	scanpath	NOUN
flr-365	135	13	,	,	PUNCT
flr-365	135	14	comparing	compare	VERB
flr-365	135	15	correct	correct	ADJ
flr-365	135	16	and	and	CCONJ
flr-365	135	17	incorrect	incorrect	ADJ
flr-365	135	18	children	child	NOUN
flr-365	135	19	.	.	PUNCT
flr-365	136	1	a	a	DET
flr-365	136	2	aois	aois	NOUN
flr-365	136	3	:	:	PUNCT
flr-365	136	4	most	most	ADV
flr-365	136	5	critical	critical	ADJ
flr-365	136	6	,	,	PUNCT
flr-365	136	7	b	b	NOUN
flr-365	136	8	aois	aois	NOUN
flr-365	136	9	:	:	PUNCT
flr-365	136	10	somewhat	somewhat	ADV
flr-365	136	11	critical	critical	ADJ
flr-365	136	12	,	,	PUNCT
flr-365	136	13	c	c	PROPN
flr-365	136	14	aois	aois	PROPN
flr-365	136	15	:	:	PUNCT
flr-365	136	16	less	less	ADV
flr-365	136	17	critical	critical	ADJ
flr-365	136	18	.	.	PUNCT
flr-365	137	1	examining	examine	VERB
flr-365	137	2	the	the	DET
flr-365	137	3	merged	merged	ADJ
flr-365	137	4	average	average	ADJ
flr-365	137	5	scanpath	scanpath	NOUN
flr-365	137	6	as	as	ADP
flr-365	137	7	a	a	DET
flr-365	137	8	sequence	sequence	NOUN
flr-365	137	9	of	of	ADP
flr-365	137	10	dwells	dwell	NOUN
flr-365	137	11	in	in	ADP
flr-365	137	12	areas	area	NOUN
flr-365	137	13	a	a	PRON
flr-365	137	14	,	,	PUNCT
flr-365	137	15	b	b	PROPN
flr-365	137	16	and	and	CCONJ
flr-365	137	17	c	c	NOUN
flr-365	137	18	,	,	PUNCT
flr-365	137	19	demonstrates	demonstrate	VERB
flr-365	137	20	a	a	DET
flr-365	137	21	more	more	ADV
flr-365	137	22	detailed	detailed	ADJ
flr-365	137	23	characterisation	characterisation	NOUN
flr-365	137	24	of	of	ADP
flr-365	137	25	the	the	DET
flr-365	137	26	visual	visual	ADJ
flr-365	137	27	cognitive	cognitive	ADJ
flr-365	137	28	behaviours	behaviour	NOUN
flr-365	137	29	(	(	PUNCT
flr-365	137	30	figure	figure	NOUN
flr-365	137	31	3	3	NUM
flr-365	137	32	)	)	PUNCT
flr-365	137	33	.	.	PUNCT
flr-365	138	1	correct	correct	ADJ
flr-365	138	2	children	child	NOUN
flr-365	138	3	more	more	ADV
flr-365	138	4	rapidly	rapidly	ADV
flr-365	138	5	accessed	access	VERB
flr-365	138	6	and	and	CCONJ
flr-365	138	7	maintained	maintain	VERB
flr-365	138	8	attention	attention	NOUN
flr-365	138	9	on	on	ADP
flr-365	138	10	the	the	DET
flr-365	138	11	a	a	DET
flr-365	138	12	areas	area	NOUN
flr-365	138	13	.	.	PUNCT
flr-365	139	1	whereas	whereas	SCONJ
flr-365	139	2	children	child	NOUN
flr-365	139	3	who	who	PRON
flr-365	139	4	were	be	AUX
flr-365	139	5	incorrect	incorrect	ADJ
flr-365	139	6	did	do	AUX
flr-365	139	7	not	not	PART
flr-365	139	8	exhibit	exhibit	VERB
flr-365	139	9	the	the	DET
flr-365	139	10	same	same	ADJ
flr-365	139	11	rate	rate	NOUN
flr-365	139	12	of	of	ADP
flr-365	139	13	attention	attention	NOUN
flr-365	139	14	on	on	ADP
flr-365	139	15	a	a	DET
flr-365	139	16	areas	area	NOUN
flr-365	139	17	,	,	PUNCT
flr-365	139	18	but	but	CCONJ
flr-365	139	19	rather	rather	ADV
flr-365	139	20	appeared	appear	VERB
flr-365	139	21	to	to	PART
flr-365	139	22	be	be	AUX
flr-365	139	23	uncertain	uncertain	ADJ
flr-365	139	24	as	as	ADP
flr-365	139	25	to	to	ADP
flr-365	139	26	where	where	SCONJ
flr-365	139	27	to	to	PART
flr-365	139	28	focus	focus	VERB
flr-365	139	29	their	their	PRON
flr-365	139	30	visual	visual	ADJ
flr-365	139	31	attention	attention	NOUN
flr-365	139	32	,	,	PUNCT
flr-365	139	33	with	with	ADP
flr-365	139	34	many	many	ADJ
flr-365	139	35	shifts	shift	NOUN
flr-365	139	36	between	between	ADP
flr-365	139	37	a	a	DET
flr-365	139	38	,	,	PUNCT
flr-365	139	39	b	b	NOUN
flr-365	139	40	and	and	CCONJ
flr-365	139	41	c	c	PROPN
flr-365	139	42	areas	area	NOUN
flr-365	139	43	with	with	ADP
flr-365	139	44	a	a	DET
flr-365	139	45	larger	large	ADJ
flr-365	139	46	number	number	NOUN
flr-365	139	47	of	of	ADP
flr-365	139	48	dwells	dwell	NOUN
flr-365	139	49	.	.	PUNCT
flr-365	140	1	figure	figure	NOUN
flr-365	140	2	3	3	NUM
flr-365	140	3	.	.	NUM
flr-365	140	4	merged	merge	VERB
flr-365	140	5	average	average	ADJ
flr-365	140	6	scanpath	scanpath	NOUN
flr-365	140	7	,	,	PUNCT
flr-365	140	8	showing	show	VERB
flr-365	140	9	which	which	PRON
flr-365	140	10	aoi	aoi	NOUN
flr-365	140	11	were	be	AUX
flr-365	140	12	accessed	access	VERB
flr-365	140	13	by	by	ADP
flr-365	140	14	correct	correct	ADJ
flr-365	140	15	and	and	CCONJ
flr-365	140	16	incorrect	incorrect	ADJ
flr-365	140	17	children	child	NOUN
flr-365	140	18	over	over	ADP
flr-365	140	19	time	time	NOUN
flr-365	140	20	.	.	PUNCT
flr-365	141	1	3.2	3.2	NUM
flr-365	141	2	finding	find	VERB
flr-365	141	3	the	the	DET
flr-365	141	4	central	central	ADJ
flr-365	141	5	data	datum	NOUN
flr-365	141	6	item	item	NOUN
flr-365	141	7	in	in	ADP
flr-365	141	8	each	each	DET
flr-365	141	9	class	class	NOUN
flr-365	141	10	and	and	CCONJ
flr-365	141	11	what	what	PRON
flr-365	141	12	it	it	PRON
flr-365	141	13	reveals	reveal	VERB
flr-365	141	14	the	the	DET
flr-365	141	15	average	average	ADJ
flr-365	141	16	scanpath	scanpath	NOUN
flr-365	141	17	derived	derive	VERB
flr-365	141	18	by	by	ADP
flr-365	141	19	method	method	NOUN
flr-365	141	20	two	two	NUM
flr-365	141	21	(	(	PUNCT
flr-365	141	22	central	central	ADJ
flr-365	141	23	data	datum	NOUN
flr-365	141	24	item	item	NOUN
flr-365	141	25	)	)	PUNCT
flr-365	141	26	determined	determine	VERB
flr-365	141	27	that	that	SCONJ
flr-365	141	28	correct	correct	ADJ
flr-365	141	29	children	child	NOUN
flr-365	141	30	had	have	VERB
flr-365	141	31	the	the	DET
flr-365	141	32	following	follow	VERB
flr-365	141	33	sequence	sequence	NOUN
flr-365	141	34	:	:	PUNCT
flr-365	141	35	{	{	PUNCT
flr-365	141	36	a1,b5,b1,b1,b1,a1,a1,a1,c2,a1,b2,b2,b2,b2,a2,b2,a2,a2,a1,b3,c2,c1,a3,a3,a1,a3,b3,a4,a3,a4,a3,a3,b2,a2,a1,a1	a1,b5,b1,b1,b1,a1,a1,a1,c2,a1,b2,b2,b2,b2,a2,b2,a2,a2,a1,b3,c2,c1,a3,a3,a1,a3,b3,a4,a3,a4,a3,a3,b2,a2,a1,a1	NOUN
flr-365	141	37	}	}	PUNCT
flr-365	141	38	while	while	SCONJ
flr-365	141	39	the	the	DET
flr-365	141	40	sequence	sequence	NOUN
flr-365	141	41	for	for	ADP
flr-365	141	42	incorrect	incorrect	ADJ
flr-365	141	43	children	child	NOUN
flr-365	141	44	was	be	AUX
flr-365	141	45	as	as	SCONJ
flr-365	141	46	follows	follow	VERB
flr-365	141	47	:	:	PUNCT
flr-365	141	48	{	{	PUNCT
flr-365	141	49	c1,b1,b1,a1,a1,b2,b2,b2,b2,b2,b2,b2,a3,c1,c2,b3,a3,a4,c1,b5,b2,a2,b2,b2,b2,b2,a2,c3,c1,a4,c2,a3,b1	c1,b1,b1,a1,a1,b2,b2,b2,b2,b2,b2,b2,a3,c1,c2,b3,a3,a4,c1,b5,b2,a2,b2,b2,b2,b2,a2,c3,c1,a4,c2,a3,b1	NOUN
flr-365	141	50	,	,	PUNCT
flr-365	141	51	a1,a2,a1	a1,a2,a1	VERB
flr-365	141	52	}	}	PUNCT
flr-365	141	53	the	the	DET
flr-365	141	54	average	average	ADJ
flr-365	141	55	scanpath	scanpath	NOUN
flr-365	141	56	sequences	sequence	NOUN
flr-365	141	57	for	for	ADP
flr-365	141	58	correct	correct	ADJ
flr-365	141	59	and	and	CCONJ
flr-365	141	60	incorrect	incorrect	ADJ
flr-365	141	61	children	child	NOUN
flr-365	141	62	have	have	VERB
flr-365	141	63	the	the	DET
flr-365	141	64	same	same	ADJ
flr-365	141	65	sequence	sequence	NOUN
flr-365	141	66	length	length	NOUN
flr-365	141	67	(	(	PUNCT
flr-365	141	68	36	36	NUM
flr-365	141	69	values	value	NOUN
flr-365	141	70	)	)	PUNCT
flr-365	141	71	.	.	PUNCT
flr-365	142	1	in	in	ADP
flr-365	142	2	terms	term	NOUN
flr-365	142	3	of	of	ADP
flr-365	142	4	percentage	percentage	NOUN
flr-365	142	5	of	of	ADP
flr-365	142	6	dwells	dwell	NOUN
flr-365	142	7	in	in	ADP
flr-365	142	8	the	the	DET
flr-365	142	9	most	most	ADV
flr-365	142	10	critical	critical	ADJ
flr-365	142	11	areas	area	NOUN
flr-365	142	12	,	,	PUNCT
flr-365	142	13	incorrect	incorrect	ADJ
flr-365	142	14	children	child	NOUN
flr-365	142	15	,	,	PUNCT
flr-365	142	16	in	in	ADP
flr-365	142	17	contrast	contrast	NOUN
flr-365	142	18	to	to	ADP
flr-365	142	19	the	the	DET
flr-365	142	20	correct	correct	ADJ
flr-365	142	21	children	child	NOUN
flr-365	142	22	,	,	PUNCT
flr-365	142	23	spent	spend	VERB
flr-365	142	24	a	a	DET
flr-365	142	25	lot	lot	NOUN
flr-365	142	26	of	of	ADP
flr-365	142	27	time	time	NOUN
flr-365	142	28	looking	look	VERB
flr-365	142	29	at	at	ADP
flr-365	142	30	the	the	DET
flr-365	142	31	less	less	ADV
flr-365	142	32	critical	critical	ADJ
flr-365	142	33	areas	area	NOUN
flr-365	142	34	(	(	PUNCT
flr-365	142	35	b	b	NOUN
flr-365	142	36	and	and	CCONJ
flr-365	142	37	c	c	NOUN
flr-365	142	38	)	)	PUNCT
flr-365	142	39	(	(	PUNCT
flr-365	142	40	figure	figure	NOUN
flr-365	142	41	4	4	NUM
flr-365	142	42	)	)	PUNCT
flr-365	142	43	,	,	PUNCT
flr-365	142	44	which	which	PRON
flr-365	142	45	is	be	AUX
flr-365	142	46	similar	similar	ADJ
flr-365	142	47	to	to	ADP
flr-365	142	48	the	the	DET
flr-365	142	49	results	result	NOUN
flr-365	142	50	of	of	ADP
flr-365	142	51	method	method	NOUN
flr-365	142	52	one	one	NUM
flr-365	142	53	(	(	PUNCT
flr-365	142	54	the	the	DET
flr-365	142	55	most	most	ADV
flr-365	142	56	probable	probable	ADJ
flr-365	142	57	vector	vector	NOUN
flr-365	142	58	)	)	PUNCT
flr-365	142	59	.	.	PUNCT
flr-365	143	1	figure	figure	VERB
flr-365	143	2	4	4	NUM
flr-365	143	3	.	.	PUNCT
flr-365	143	4	percentage	percentage	NOUN
flr-365	143	5	of	of	ADP
flr-365	143	6	aoi	aoi	NOUN
flr-365	143	7	access	access	NOUN
flr-365	143	8	using	use	VERB
flr-365	143	9	the	the	DET
flr-365	143	10	central	central	ADJ
flr-365	143	11	feature	feature	NOUN
flr-365	143	12	vector	vector	NOUN
flr-365	143	13	,	,	PUNCT
flr-365	143	14	comparing	compare	VERB
flr-365	143	15	correct	correct	ADJ
flr-365	143	16	and	and	CCONJ
flr-365	143	17	incorrect	incorrect	ADJ
flr-365	143	18	children	child	NOUN
flr-365	143	19	.	.	PUNCT
flr-365	144	1	a	a	DET
flr-365	144	2	aois	aois	NOUN
flr-365	144	3	:	:	PUNCT
flr-365	144	4	most	most	ADV
flr-365	144	5	critical	critical	ADJ
flr-365	144	6	,	,	PUNCT
flr-365	144	7	b	b	NOUN
flr-365	144	8	aois	aois	NOUN
flr-365	144	9	:	:	PUNCT
flr-365	144	10	somewhat	somewhat	ADV
flr-365	144	11	critical	critical	ADJ
flr-365	144	12	,	,	PUNCT
flr-365	144	13	c	c	PROPN
flr-365	144	14	aois	aois	PROPN
flr-365	144	15	:	:	PUNCT
flr-365	144	16	less	less	ADV
flr-365	144	17	critical	critical	ADJ
flr-365	144	18	.	.	PUNCT
flr-365	145	1	the	the	DET
flr-365	145	2	central	central	ADJ
flr-365	145	3	feature	feature	NOUN
flr-365	145	4	vectors	vector	NOUN
flr-365	145	5	allowed	allow	VERB
flr-365	145	6	us	we	PRON
flr-365	145	7	to	to	PART
flr-365	145	8	learn	learn	VERB
flr-365	145	9	how	how	SCONJ
flr-365	145	10	the	the	DET
flr-365	145	11	critical	critical	ADJ
flr-365	145	12	areas	area	NOUN
flr-365	145	13	were	be	AUX
flr-365	145	14	accessed	access	VERB
flr-365	145	15	.	.	PUNCT
flr-365	146	1	if	if	SCONJ
flr-365	146	2	we	we	PRON
flr-365	146	3	remove	remove	VERB
flr-365	146	4	all	all	PRON
flr-365	146	5	of	of	ADP
flr-365	146	6	the	the	DET
flr-365	146	7	non	non	ADJ
flr-365	146	8	-	-	ADJ
flr-365	146	9	critical	critical	ADJ
flr-365	146	10	(	(	PUNCT
flr-365	146	11	b	b	NOUN
flr-365	146	12	and	and	CCONJ
flr-365	146	13	c	c	NOUN
flr-365	146	14	)	)	PUNCT
flr-365	146	15	areas	area	NOUN
flr-365	146	16	,	,	PUNCT
flr-365	146	17	leaving	leave	VERB
flr-365	146	18	only	only	ADV
flr-365	146	19	the	the	DET
flr-365	146	20	a	a	DET
flr-365	146	21	areas	area	NOUN
flr-365	146	22	,	,	PUNCT
flr-365	146	23	a	a	DET
flr-365	146	24	distinction	distinction	NOUN
flr-365	146	25	between	between	ADP
flr-365	146	26	the	the	DET
flr-365	146	27	two	two	NUM
flr-365	146	28	vectors	vector	NOUN
flr-365	146	29	which	which	PRON
flr-365	146	30	is	be	AUX
flr-365	146	31	crucial	crucial	ADJ
flr-365	146	32	to	to	ADP
flr-365	146	33	our	our	PRON
flr-365	146	34	understanding	understanding	NOUN
flr-365	146	35	of	of	ADP
flr-365	146	36	the	the	DET
flr-365	146	37	children	child	NOUN
flr-365	146	38	’s	’s	PART
flr-365	146	39	task	task	NOUN
flr-365	146	40	behavior	behavior	NOUN
flr-365	146	41	becomes	become	VERB
flr-365	146	42	evident	evident	ADJ
flr-365	146	43	.	.	PUNCT
flr-365	147	1	following	follow	VERB
flr-365	147	2	this	this	DET
flr-365	147	3	step	step	NOUN
flr-365	147	4	,	,	PUNCT
flr-365	147	5	we	we	PRON
flr-365	147	6	obtained	obtain	VERB
flr-365	147	7	the	the	DET
flr-365	147	8	following	follow	VERB
flr-365	147	9	correct	correct	ADJ
flr-365	147	10	sequence	sequence	NOUN
flr-365	147	11	:	:	PUNCT
flr-365	147	12	or	or	CCONJ
flr-365	147	13	more	more	ADV
flr-365	147	14	simply	simply	ADV
flr-365	147	15	,	,	PUNCT
flr-365	147	16	without	without	ADP
flr-365	147	17	the	the	DET
flr-365	147	18	non	non	ADJ
flr-365	147	19	-	-	ADJ
flr-365	147	20	critical	critical	ADJ
flr-365	147	21	areas	area	NOUN
flr-365	147	22	:	:	PUNCT
flr-365	147	23	correct	correct	ADJ
flr-365	147	24	response	response	NOUN
flr-365	147	25	sequence	sequence	NOUN
flr-365	147	26	:	:	PUNCT
flr-365	147	27	{	{	PUNCT
flr-365	147	28	a1,a1,a1,a1,a1,a2,a2,a2,a1,a3,a3,a1,a3,a4,a3,a4,a3,a3,a2,a1,a1	a1,a1,a1,a1,a1,a2,a2,a2,a1,a3,a3,a1,a3,a4,a3,a4,a3,a3,a2,a1,a1	VERB
flr-365	147	29	}	}	PUNCT
flr-365	147	30	and	and	CCONJ
flr-365	147	31	,	,	PUNCT
flr-365	147	32	the	the	DET
flr-365	147	33	incorrect	incorrect	ADJ
flr-365	147	34	response	response	NOUN
flr-365	147	35	sequence	sequence	NOUN
flr-365	147	36	:	:	PUNCT
flr-365	147	37	{	{	PUNCT
flr-365	147	38	a1,a1,a3,a3,a4,a2,a2,a4,a3,a1,a2,a1	a1,a1,a3,a3,a4,a2,a2,a4,a3,a1,a2,a1	X
flr-365	147	39	}	}	PUNCT
flr-365	147	40	.	.	PUNCT
flr-365	148	1	figure	figure	NOUN
flr-365	148	2	5	5	NUM
flr-365	148	3	summarises	summarise	NOUN
flr-365	148	4	the	the	DET
flr-365	148	5	sequence	sequence	NOUN
flr-365	148	6	of	of	ADP
flr-365	148	7	dwells	dwell	NOUN
flr-365	148	8	on	on	ADP
flr-365	148	9	most	most	ADV
flr-365	148	10	critical	critical	ADJ
flr-365	148	11	areas	area	NOUN
flr-365	148	12	(	(	PUNCT
flr-365	148	13	a1	a1	NOUN
flr-365	148	14	-	-	PUNCT
flr-365	148	15	a4	a4	NOUN
flr-365	148	16	)	)	PUNCT
flr-365	148	17	and	and	CCONJ
flr-365	148	18	other	other	ADJ
flr-365	148	19	non	non	ADJ
flr-365	148	20	-	-	ADJ
flr-365	148	21	critical	critical	ADJ
flr-365	148	22	areas	area	NOUN
flr-365	148	23	(	(	PUNCT
flr-365	148	24	b	b	X
flr-365	148	25	-	-	PUNCT
flr-365	148	26	c	c	NOUN
flr-365	148	27	)	)	PUNCT
flr-365	148	28	for	for	ADP
flr-365	148	29	the	the	DET
flr-365	148	30	modified	modify	VERB
flr-365	148	31	sequences	sequence	NOUN
flr-365	148	32	.	.	PUNCT
flr-365	149	1	looking	look	VERB
flr-365	149	2	at	at	ADP
flr-365	149	3	the	the	DET
flr-365	149	4	modified	modify	VERB
flr-365	149	5	sequences	sequence	NOUN
flr-365	149	6	,	,	PUNCT
flr-365	149	7	it	it	PRON
flr-365	149	8	is	be	AUX
flr-365	149	9	evident	evident	ADJ
flr-365	149	10	that	that	SCONJ
flr-365	149	11	area	area	NOUN
flr-365	149	12	a4	a4	PROPN
flr-365	149	13	,	,	PUNCT
flr-365	149	14	which	which	PRON
flr-365	149	15	includes	include	VERB
flr-365	149	16	the	the	DET
flr-365	149	17	values	value	NOUN
flr-365	149	18	along	along	ADP
flr-365	149	19	the	the	DET
flr-365	149	20	y	y	NOUN
flr-365	149	21	-	-	PUNCT
flr-365	149	22	axis	axis	NOUN
flr-365	149	23	of	of	ADP
flr-365	149	24	the	the	DET
flr-365	149	25	task	task	NOUN
flr-365	149	26	graph	graph	NOUN
flr-365	149	27	,	,	PUNCT
flr-365	149	28	is	be	AUX
flr-365	149	29	infrequently	infrequently	ADV
flr-365	149	30	visited	visit	VERB
flr-365	149	31	by	by	ADP
flr-365	149	32	incorrect	incorrect	ADJ
flr-365	149	33	children	child	NOUN
flr-365	149	34	,	,	PUNCT
flr-365	149	35	and	and	CCONJ
flr-365	149	36	,	,	PUNCT
flr-365	149	37	as	as	SCONJ
flr-365	149	38	anybody	anybody	PRON
flr-365	149	39	who	who	PRON
flr-365	149	40	learns	learn	VERB
flr-365	149	41	math	math	NOUN
flr-365	149	42	as	as	ADP
flr-365	149	43	a	a	DET
flr-365	149	44	student	student	NOUN
flr-365	149	45	or	or	CCONJ
flr-365	149	46	as	as	SCONJ
flr-365	149	47	a	a	DET
flr-365	149	48	professional	professional	NOUN
flr-365	149	49	is	be	AUX
flr-365	149	50	aware	aware	ADJ
flr-365	149	51	,	,	PUNCT
flr-365	149	52	knowing	know	VERB
flr-365	149	53	what	what	PRON
flr-365	149	54	is	be	AUX
flr-365	149	55	being	be	AUX
flr-365	149	56	counted	count	VERB
flr-365	149	57	is	be	AUX
flr-365	149	58	critical	critical	ADJ
flr-365	149	59	to	to	ADP
flr-365	149	60	understanding	understanding	NOUN
flr-365	149	61	and	and	CCONJ
flr-365	149	62	solving	solve	VERB
flr-365	149	63	graph	graph	NOUN
flr-365	149	64	problems	problem	NOUN
flr-365	149	65	correctly	correctly	ADV
flr-365	149	66	.	.	PUNCT
flr-365	150	1	moreover	moreover	ADV
flr-365	150	2	,	,	PUNCT
flr-365	150	3	the	the	DET
flr-365	150	4	correct	correct	ADJ
flr-365	150	5	children	child	NOUN
flr-365	150	6	’s	’s	PART
flr-365	150	7	inspection	inspection	NOUN
flr-365	150	8	of	of	ADP
flr-365	150	9	the	the	DET
flr-365	150	10	most	most	ADV
flr-365	150	11	critical	critical	ADJ
flr-365	150	12	areas	area	NOUN
flr-365	150	13	is	be	AUX
flr-365	150	14	in	in	ADP
flr-365	150	15	a	a	DET
flr-365	150	16	predictable	predictable	ADJ
flr-365	150	17	order	order	NOUN
flr-365	150	18	(	(	PUNCT
flr-365	150	19	a1	a1	NOUN
flr-365	150	20	,	,	PUNCT
flr-365	150	21	a2	a2	PROPN
flr-365	150	22	,	,	PUNCT
flr-365	150	23	a3	a3	NOUN
flr-365	150	24	,	,	PUNCT
flr-365	150	25	a4	a4	NOUN
flr-365	150	26	)	)	PUNCT
flr-365	150	27	.	.	PUNCT
flr-365	151	1	conversely	conversely	ADV
flr-365	151	2	,	,	PUNCT
flr-365	151	3	a	a	DET
flr-365	151	4	less	less	ADV
flr-365	151	5	predictable	predictable	ADJ
flr-365	151	6	order	order	NOUN
flr-365	151	7	was	be	AUX
flr-365	151	8	evident	evident	ADJ
flr-365	151	9	in	in	ADP
flr-365	151	10	the	the	DET
flr-365	151	11	modified	modify	VERB
flr-365	151	12	sequence	sequence	NOUN
flr-365	151	13	of	of	ADP
flr-365	151	14	the	the	DET
flr-365	151	15	incorrect	incorrect	ADJ
flr-365	151	16	children	child	NOUN
flr-365	151	17	.	.	PUNCT
flr-365	152	1	figure	figure	VERB
flr-365	152	2	5	5	NUM
flr-365	152	3	.	.	PUNCT
flr-365	152	4	modified	modify	VERB
flr-365	152	5	average	average	ADJ
flr-365	152	6	scanpath	scanpath	NOUN
flr-365	152	7	,	,	PUNCT
flr-365	152	8	showing	show	VERB
flr-365	152	9	the	the	DET
flr-365	152	10	sequence	sequence	NOUN
flr-365	152	11	in	in	ADP
flr-365	152	12	which	which	PRON
flr-365	152	13	the	the	DET
flr-365	152	14	most	most	ADV
flr-365	152	15	critical	critical	ADJ
flr-365	152	16	aois	aois	NOUN
flr-365	152	17	(	(	PUNCT
flr-365	152	18	a1	a1	NOUN
flr-365	152	19	-	-	PUNCT
flr-365	152	20	a4	a4	NOUN
flr-365	152	21	)	)	PUNCT
flr-365	152	22	and	and	CCONJ
flr-365	152	23	other	other	ADJ
flr-365	152	24	non	non	ADJ
flr-365	152	25	-	-	ADJ
flr-365	152	26	critical	critical	ADJ
flr-365	152	27	areas	area	NOUN
flr-365	152	28	(	(	PUNCT
flr-365	152	29	b	b	X
flr-365	152	30	-	-	PUNCT
flr-365	152	31	c	c	NOUN
flr-365	152	32	)	)	PUNCT
flr-365	152	33	were	be	AUX
flr-365	152	34	accessed	access	VERB
flr-365	152	35	by	by	ADP
flr-365	152	36	correct	correct	ADJ
flr-365	152	37	and	and	CCONJ
flr-365	152	38	incorrect	incorrect	ADJ
flr-365	152	39	children	child	NOUN
flr-365	152	40	over	over	ADP
flr-365	152	41	time	time	NOUN
flr-365	152	42	.	.	PUNCT
flr-365	153	1	discussion	discussion	NOUN
flr-365	153	2	in	in	ADP
flr-365	153	3	this	this	DET
flr-365	153	4	paper	paper	NOUN
flr-365	153	5	we	we	PRON
flr-365	153	6	discuss	discuss	VERB
flr-365	153	7	two	two	NUM
flr-365	153	8	novel	novel	ADJ
flr-365	153	9	methods	method	NOUN
flr-365	153	10	of	of	ADP
flr-365	153	11	analysing	analyse	VERB
flr-365	153	12	eye	eye	NOUN
flr-365	153	13	tracking	tracking	NOUN
flr-365	153	14	data	datum	NOUN
flr-365	153	15	to	to	PART
flr-365	153	16	better	well	ADV
flr-365	153	17	understand	understand	VERB
flr-365	153	18	the	the	DET
flr-365	153	19	visual	visual	ADJ
flr-365	153	20	and	and	CCONJ
flr-365	153	21	cognitive	cognitive	ADJ
flr-365	153	22	behaviours	behaviour	NOUN
flr-365	153	23	associated	associate	VERB
flr-365	153	24	with	with	ADP
flr-365	153	25	completion	completion	NOUN
flr-365	153	26	of	of	ADP
flr-365	153	27	a	a	DET
flr-365	153	28	graph	graph	NOUN
flr-365	153	29	task	task	NOUN
flr-365	153	30	in	in	ADP
flr-365	153	31	a	a	DET
flr-365	153	32	sample	sample	NOUN
flr-365	153	33	of	of	ADP
flr-365	153	34	children	child	NOUN
flr-365	153	35	in	in	ADP
flr-365	153	36	year	year	NOUN
flr-365	153	37	3	3	NUM
flr-365	153	38	.	.	PUNCT
flr-365	154	1	each	each	DET
flr-365	154	2	method	method	NOUN
flr-365	154	3	produced	produce	VERB
flr-365	154	4	two	two	NUM
flr-365	154	5	strings	string	NOUN
flr-365	154	6	(	(	PUNCT
flr-365	154	7	one	one	NUM
flr-365	154	8	for	for	ADP
flr-365	154	9	the	the	DET
flr-365	154	10	correct	correct	ADJ
flr-365	154	11	children	child	NOUN
flr-365	154	12	and	and	CCONJ
flr-365	154	13	one	one	NUM
flr-365	154	14	for	for	ADP
flr-365	154	15	the	the	DET
flr-365	154	16	incorrect	incorrect	NOUN
flr-365	154	17	)	)	PUNCT
flr-365	154	18	which	which	PRON
flr-365	154	19	were	be	AUX
flr-365	154	20	compared	compare	VERB
flr-365	154	21	.	.	PUNCT
flr-365	155	1	the	the	DET
flr-365	155	2	initial	initial	ADJ
flr-365	155	3	findings	finding	NOUN
flr-365	155	4	are	be	AUX
flr-365	155	5	significant	significant	ADJ
flr-365	155	6	because	because	SCONJ
flr-365	155	7	they	they	PRON
flr-365	155	8	demonstrate	demonstrate	VERB
flr-365	155	9	how	how	SCONJ
flr-365	155	10	the	the	DET
flr-365	155	11	methods	method	NOUN
flr-365	155	12	developed	develop	VERB
flr-365	155	13	by	by	ADP
flr-365	155	14	our	our	PRON
flr-365	155	15	research	research	NOUN
flr-365	155	16	group	group	NOUN
flr-365	155	17	can	can	AUX
flr-365	155	18	assist	assist	VERB
flr-365	155	19	in	in	ADP
flr-365	155	20	characterising	characterise	VERB
flr-365	155	21	the	the	DET
flr-365	155	22	visual	visual	ADJ
flr-365	155	23	behaviour	behaviour	NOUN
flr-365	155	24	of	of	ADP
flr-365	155	25	children	child	NOUN
flr-365	155	26	who	who	PRON
flr-365	155	27	correctly	correctly	ADV
flr-365	155	28	or	or	CCONJ
flr-365	155	29	incorrectly	incorrectly	ADV
flr-365	155	30	answered	answer	VERB
flr-365	155	31	the	the	DET
flr-365	155	32	graph	graph	NOUN
flr-365	155	33	task	task	NOUN
flr-365	155	34	.	.	PUNCT
flr-365	156	1	the	the	DET
flr-365	156	2	results	result	NOUN
flr-365	156	3	of	of	ADP
flr-365	156	4	both	both	DET
flr-365	156	5	methods	method	NOUN
flr-365	156	6	of	of	ADP
flr-365	156	7	analysis	analysis	NOUN
flr-365	156	8	reveal	reveal	VERB
flr-365	156	9	differences	difference	NOUN
flr-365	156	10	in	in	ADP
flr-365	156	11	gaze	gaze	NOUN
flr-365	156	12	patterns	pattern	NOUN
flr-365	156	13	between	between	ADP
flr-365	156	14	the	the	DET
flr-365	156	15	correct	correct	ADJ
flr-365	156	16	and	and	CCONJ
flr-365	156	17	incorrect	incorrect	ADJ
flr-365	156	18	groups	group	NOUN
flr-365	156	19	.	.	PUNCT
flr-365	157	1	this	this	DET
flr-365	157	2	discussion	discussion	NOUN
flr-365	157	3	will	will	AUX
flr-365	157	4	summarise	summarise	VERB
flr-365	157	5	the	the	DET
flr-365	157	6	key	key	ADJ
flr-365	157	7	findings	finding	NOUN
flr-365	157	8	for	for	ADP
flr-365	157	9	each	each	DET
flr-365	157	10	method	method	NOUN
flr-365	157	11	,	,	PUNCT
flr-365	157	12	compare	compare	VERB
flr-365	157	13	the	the	DET
flr-365	157	14	different	different	ADJ
flr-365	157	15	analytic	analytic	ADJ
flr-365	157	16	approaches	approach	NOUN
flr-365	157	17	and	and	CCONJ
flr-365	157	18	characterise	characterise	VERB
flr-365	157	19	the	the	DET
flr-365	157	20	visual	visual	ADJ
flr-365	157	21	cognitive	cognitive	ADJ
flr-365	157	22	behaviours	behaviour	NOUN
flr-365	157	23	identified	identify	VERB
flr-365	157	24	.	.	PUNCT
flr-365	158	1	method	method	PROPN
flr-365	158	2	one	one	NUM
flr-365	158	3	used	use	VERB
flr-365	158	4	a	a	DET
flr-365	158	5	naïve	naïve	ADJ
flr-365	158	6	bayes	bayes	NOUN
flr-365	158	7	classifier	classifier	NOUN
flr-365	158	8	to	to	PART
flr-365	158	9	obtain	obtain	VERB
flr-365	158	10	most	most	ADV
flr-365	158	11	probable	probable	ADJ
flr-365	158	12	vectors	vector	NOUN
flr-365	158	13	.	.	PUNCT
flr-365	159	1	the	the	DET
flr-365	159	2	perfect	perfect	ADJ
flr-365	159	3	classification	classification	NOUN
flr-365	159	4	training	training	NOUN
flr-365	159	5	rate	rate	NOUN
flr-365	159	6	with	with	ADP
flr-365	159	7	our	our	PRON
flr-365	159	8	software	software	NOUN
flr-365	159	9	of	of	ADP
flr-365	159	10	100	100	NUM
flr-365	159	11	%	%	NOUN
flr-365	159	12	suggests	suggest	VERB
flr-365	159	13	that	that	SCONJ
flr-365	159	14	the	the	DET
flr-365	159	15	eye	eye	NOUN
flr-365	159	16	tracking	track	VERB
flr-365	159	17	data	datum	NOUN
flr-365	159	18	for	for	ADP
flr-365	159	19	this	this	DET
flr-365	159	20	task	task	NOUN
flr-365	159	21	obeyed	obey	VERB
flr-365	159	22	the	the	DET
flr-365	159	23	naïve	naïve	ADJ
flr-365	159	24	bayes	bayes	NOUN
flr-365	159	25	assumption	assumption	NOUN
flr-365	159	26	,	,	PUNCT
flr-365	159	27	and	and	CCONJ
flr-365	159	28	that	that	SCONJ
flr-365	159	29	the	the	DET
flr-365	159	30	aois	aois	NOUN
flr-365	159	31	in	in	ADP
flr-365	159	32	the	the	DET
flr-365	159	33	scanpath	scanpath	NOUN
flr-365	159	34	were	be	AUX
flr-365	159	35	uncorrelated	uncorrelate	VERB
flr-365	159	36	,	,	PUNCT
flr-365	159	37	and	and	CCONJ
flr-365	159	38	an	an	DET
flr-365	159	39	average	average	ADJ
flr-365	159	40	scanpath	scanpath	NOUN
flr-365	159	41	can	can	AUX
flr-365	159	42	plausibly	plausibly	ADV
flr-365	159	43	be	be	AUX
flr-365	159	44	determined	determine	VERB
flr-365	159	45	.	.	PUNCT
flr-365	160	1	we	we	PRON
flr-365	160	2	believe	believe	VERB
flr-365	160	3	that	that	SCONJ
flr-365	160	4	this	this	PRON
flr-365	160	5	is	be	AUX
flr-365	160	6	likely	likely	ADJ
flr-365	160	7	to	to	PART
flr-365	160	8	be	be	AUX
flr-365	160	9	task	task	NOUN
flr-365	160	10	dependent	dependent	ADJ
flr-365	160	11	,	,	PUNCT
flr-365	160	12	however	however	ADV
flr-365	160	13	,	,	PUNCT
flr-365	160	14	further	further	ADJ
flr-365	160	15	research	research	NOUN
flr-365	160	16	is	be	AUX
flr-365	160	17	required	require	VERB
flr-365	160	18	in	in	ADP
flr-365	160	19	order	order	NOUN
flr-365	160	20	to	to	PART
flr-365	160	21	fully	fully	ADV
flr-365	160	22	understand	understand	VERB
flr-365	160	23	this	this	DET
flr-365	160	24	issue	issue	NOUN
flr-365	160	25	.	.	PUNCT
flr-365	161	1	we	we	PRON
flr-365	161	2	did	do	AUX
flr-365	161	3	not	not	PART
flr-365	161	4	do	do	VERB
flr-365	161	5	cross	cross	NOUN
flr-365	161	6	-	-	NOUN
flr-365	161	7	validation	validation	NOUN
flr-365	161	8	with	with	ADP
flr-365	161	9	our	our	PRON
flr-365	161	10	software	software	NOUN
flr-365	161	11	,	,	PUNCT
flr-365	161	12	but	but	CCONJ
flr-365	161	13	used	use	VERB
flr-365	161	14	a	a	DET
flr-365	161	15	commercial	commercial	ADJ
flr-365	161	16	package	package	NOUN
flr-365	161	17	(	(	PUNCT
flr-365	161	18	mathematica	mathematica	PROPN
flr-365	161	19	,	,	PUNCT
flr-365	161	20	wolfram	wolfram	PROPN
flr-365	161	21	research	research	PROPN
flr-365	161	22	)	)	PUNCT
flr-365	161	23	which	which	PRON
flr-365	161	24	showed	show	VERB
flr-365	161	25	a	a	DET
flr-365	161	26	training	training	NOUN
flr-365	161	27	error	error	NOUN
flr-365	161	28	rate	rate	NOUN
flr-365	161	29	of	of	ADP
flr-365	161	30	.15	.15	NUM
flr-365	161	31	and	and	CCONJ
flr-365	161	32	a	a	DET
flr-365	161	33	leave	leave	NOUN
flr-365	161	34	one	one	NUM
flr-365	161	35	out	out	ADP
flr-365	161	36	cross	cross	NOUN
flr-365	161	37	validation	validation	NOUN
flr-365	161	38	of	of	ADP
flr-365	161	39	.27	.27	NUM
flr-365	161	40	,	,	PUNCT
flr-365	161	41	which	which	PRON
flr-365	161	42	given	give	VERB
flr-365	161	43	the	the	DET
flr-365	161	44	small	small	ADJ
flr-365	161	45	amount	amount	NOUN
flr-365	161	46	data	datum	NOUN
flr-365	161	47	and	and	CCONJ
flr-365	161	48	relatively	relatively	ADV
flr-365	161	49	large	large	ADJ
flr-365	161	50	number	number	NOUN
flr-365	161	51	of	of	ADP
flr-365	161	52	features	feature	NOUN
flr-365	161	53	,	,	PUNCT
flr-365	161	54	is	be	AUX
flr-365	161	55	still	still	ADV
flr-365	161	56	very	very	ADV
flr-365	161	57	good	good	ADJ
flr-365	161	58	.	.	PUNCT
flr-365	162	1	we	we	PRON
flr-365	162	2	are	be	AUX
flr-365	162	3	optimistic	optimistic	ADJ
flr-365	162	4	that	that	SCONJ
flr-365	162	5	with	with	ADP
flr-365	162	6	more	more	ADJ
flr-365	162	7	data	datum	NOUN
flr-365	162	8	,	,	PUNCT
flr-365	162	9	this	this	DET
flr-365	162	10	rate	rate	NOUN
flr-365	162	11	would	would	AUX
flr-365	162	12	drop	drop	VERB
flr-365	162	13	.	.	PUNCT
flr-365	163	1	with	with	ADP
flr-365	163	2	method	method	NOUN
flr-365	163	3	one	one	NUM
flr-365	163	4	,	,	PUNCT
flr-365	163	5	comparisons	comparison	NOUN
flr-365	163	6	of	of	ADP
flr-365	163	7	the	the	DET
flr-365	163	8	average	average	ADJ
flr-365	163	9	number	number	NOUN
flr-365	163	10	of	of	ADP
flr-365	163	11	dwells	dwell	NOUN
flr-365	163	12	in	in	ADP
flr-365	163	13	the	the	DET
flr-365	163	14	sequences	sequence	NOUN
flr-365	163	15	of	of	ADP
flr-365	163	16	each	each	DET
flr-365	163	17	class	class	NOUN
flr-365	163	18	identified	identify	VERB
flr-365	163	19	a	a	DET
flr-365	163	20	slightly	slightly	ADV
flr-365	163	21	higher	high	ADJ
flr-365	163	22	number	number	NOUN
flr-365	163	23	of	of	ADP
flr-365	163	24	dwells	dwell	NOUN
flr-365	163	25	for	for	ADP
flr-365	163	26	the	the	DET
flr-365	163	27	incorrect	incorrect	ADJ
flr-365	163	28	children	child	NOUN
flr-365	163	29	,	,	PUNCT
flr-365	163	30	compared	compare	VERB
flr-365	163	31	to	to	ADP
flr-365	163	32	the	the	DET
flr-365	163	33	correct	correct	ADJ
flr-365	163	34	children	child	NOUN
flr-365	163	35	(	(	PUNCT
flr-365	163	36	77	77	NUM
flr-365	163	37	vs	vs	ADP
flr-365	163	38	69	69	NUM
flr-365	163	39	aois	aois	NOUN
flr-365	163	40	,	,	PUNCT
flr-365	163	41	respectively	respectively	ADV
flr-365	163	42	)	)	PUNCT
flr-365	163	43	.	.	PUNCT
flr-365	164	1	this	this	DET
flr-365	164	2	higher	high	ADJ
flr-365	164	3	number	number	NOUN
flr-365	164	4	of	of	ADP
flr-365	164	5	dwells	dwell	NOUN
flr-365	164	6	for	for	ADP
flr-365	164	7	the	the	DET
flr-365	164	8	incorrect	incorrect	ADJ
flr-365	164	9	children	child	NOUN
flr-365	164	10	is	be	AUX
flr-365	164	11	in	in	ADP
flr-365	164	12	accord	accord	NOUN
flr-365	164	13	with	with	ADP
flr-365	164	14	the	the	DET
flr-365	164	15	findings	finding	NOUN
flr-365	164	16	of	of	ADP
flr-365	164	17	kim	kim	PROPN
flr-365	164	18	et	et	PROPN
flr-365	164	19	al	al	PROPN
flr-365	164	20	.	.	PROPN
flr-365	165	1	(	(	PUNCT
flr-365	165	2	2014	2014	NUM
flr-365	165	3	)	)	PUNCT
flr-365	165	4	who	who	PRON
flr-365	165	5	found	find	VERB
flr-365	165	6	that	that	SCONJ
flr-365	165	7	novices	novice	NOUN
flr-365	165	8	display	display	VERB
flr-365	165	9	significantly	significantly	ADV
flr-365	165	10	more	more	ADJ
flr-365	165	11	shifts	shift	NOUN
flr-365	165	12	in	in	ADP
flr-365	165	13	visual	visual	ADJ
flr-365	165	14	attention	attention	NOUN
flr-365	165	15	than	than	ADP
flr-365	165	16	experts	expert	NOUN
flr-365	165	17	and	and	CCONJ
flr-365	165	18	have	have	AUX
flr-365	165	19	longer	long	ADJ
flr-365	165	20	gaze	gaze	VERB
flr-365	165	21	sequences	sequence	NOUN
flr-365	165	22	(	(	PUNCT
flr-365	165	23	or	or	CCONJ
flr-365	165	24	scanpaths	scanpath	NOUN
flr-365	165	25	)	)	PUNCT
flr-365	165	26	for	for	ADP
flr-365	165	27	a	a	DET
flr-365	165	28	given	give	VERB
flr-365	165	29	problem	problem	NOUN
flr-365	165	30	-	-	PUNCT
flr-365	165	31	solving	solve	VERB
flr-365	165	32	task	task	NOUN
flr-365	165	33	,	,	PUNCT
flr-365	165	34	than	than	ADP
flr-365	165	35	their	their	PRON
flr-365	165	36	more	more	ADV
flr-365	165	37	experienced	experienced	ADJ
flr-365	165	38	counterparts	counterpart	NOUN
flr-365	165	39	.	.	PUNCT
flr-365	166	1	in	in	ADP
flr-365	166	2	our	our	PRON
flr-365	166	3	study	study	NOUN
flr-365	166	4	,	,	PUNCT
flr-365	166	5	the	the	DET
flr-365	166	6	correct	correct	ADJ
flr-365	166	7	children	child	NOUN
flr-365	166	8	exhibited	exhibit	VERB
flr-365	166	9	fewer	few	ADJ
flr-365	166	10	dwells	dwell	NOUN
flr-365	166	11	and	and	CCONJ
flr-365	166	12	fewer	few	ADJ
flr-365	166	13	shifts	shift	NOUN
flr-365	166	14	in	in	ADP
flr-365	166	15	visual	visual	ADJ
flr-365	166	16	attention	attention	NOUN
flr-365	166	17	than	than	ADP
flr-365	166	18	their	their	PRON
flr-365	166	19	counterparts	counterpart	NOUN
flr-365	166	20	who	who	PRON
flr-365	166	21	were	be	AUX
flr-365	166	22	incorrect	incorrect	ADJ
flr-365	166	23	.	.	PUNCT
flr-365	167	1	this	this	PRON
flr-365	167	2	is	be	AUX
flr-365	167	3	further	far	ADV
flr-365	167	4	evidenced	evidence	VERB
flr-365	167	5	in	in	ADP
flr-365	167	6	the	the	DET
flr-365	167	7	merged	merged	ADJ
flr-365	167	8	average	average	ADJ
flr-365	167	9	scanpath	scanpath	NOUN
flr-365	167	10	,	,	PUNCT
flr-365	167	11	where	where	SCONJ
flr-365	167	12	correct	correct	ADJ
flr-365	167	13	children	child	NOUN
flr-365	167	14	had	have	VERB
flr-365	167	15	a	a	DET
flr-365	167	16	higher	high	ADJ
flr-365	167	17	percentage	percentage	NOUN
flr-365	167	18	of	of	ADP
flr-365	167	19	dwells	dwell	NOUN
flr-365	167	20	in	in	ADP
flr-365	167	21	the	the	DET
flr-365	167	22	most	most	ADV
flr-365	167	23	critical	critical	ADJ
flr-365	167	24	a	a	DET
flr-365	167	25	areas	area	NOUN
flr-365	167	26	,	,	PUNCT
flr-365	167	27	whereas	whereas	SCONJ
flr-365	167	28	the	the	DET
flr-365	167	29	incorrect	incorrect	ADJ
flr-365	167	30	children	child	NOUN
flr-365	167	31	had	have	VERB
flr-365	167	32	dwells	dwell	NOUN
flr-365	167	33	distributed	distribute	VERB
flr-365	167	34	across	across	ADP
flr-365	167	35	the	the	DET
flr-365	167	36	most	most	ADV
flr-365	167	37	critical	critical	ADJ
flr-365	167	38	and	and	CCONJ
flr-365	167	39	less	less	ADV
flr-365	167	40	critical	critical	ADJ
flr-365	167	41	(	(	PUNCT
flr-365	167	42	a	a	DET
flr-365	167	43	-	-	PUNCT
flr-365	167	44	c	c	NOUN
flr-365	167	45	)	)	PUNCT
flr-365	167	46	areas	area	NOUN
flr-365	167	47	.	.	PUNCT
flr-365	168	1	interestingly	interestingly	ADV
flr-365	168	2	,	,	PUNCT
flr-365	168	3	these	these	DET
flr-365	168	4	patterns	pattern	NOUN
flr-365	168	5	reflect	reflect	VERB
flr-365	168	6	those	those	PRON
flr-365	168	7	of	of	ADP
flr-365	168	8	gegenfurtner	gegenfurtner	NOUN
flr-365	168	9	,	,	PUNCT
flr-365	168	10	et	et	PROPN
flr-365	168	11	al	al	PROPN
flr-365	168	12	.	.	PROPN
flr-365	168	13	,	,	PUNCT
flr-365	168	14	(	(	PUNCT
flr-365	168	15	2011	2011	NUM
flr-365	168	16	)	)	PUNCT
flr-365	168	17	and	and	CCONJ
flr-365	168	18	tsai	tsai	PROPN
flr-365	168	19	,	,	PUNCT
flr-365	168	20	et	et	PROPN
flr-365	168	21	al	al	PROPN
flr-365	168	22	.	.	PROPN
flr-365	168	23	,	,	PUNCT
flr-365	168	24	(	(	PUNCT
flr-365	168	25	2012	2012	NUM
flr-365	168	26	)	)	PUNCT
flr-365	168	27	regarding	regard	VERB
flr-365	168	28	the	the	DET
flr-365	168	29	behaviours	behaviour	NOUN
flr-365	168	30	of	of	ADP
flr-365	168	31	more	more	ADV
flr-365	168	32	experienced	experienced	ADJ
flr-365	168	33	problem	problem	NOUN
flr-365	168	34	solvers	solver	NOUN
flr-365	168	35	who	who	PRON
flr-365	168	36	were	be	AUX
flr-365	168	37	shown	show	VERB
flr-365	168	38	to	to	PART
flr-365	168	39	identify	identify	VERB
flr-365	168	40	task	task	NOUN
flr-365	168	41	relevant	relevant	ADJ
flr-365	168	42	features	feature	NOUN
flr-365	168	43	of	of	ADP
flr-365	168	44	visual	visual	ADJ
flr-365	168	45	information	information	NOUN
flr-365	168	46	more	more	ADV
flr-365	168	47	rapidly	rapidly	ADV
flr-365	168	48	than	than	ADP
flr-365	168	49	less	less	ADV
flr-365	168	50	experienced	experienced	ADJ
flr-365	168	51	individuals	individual	NOUN
flr-365	168	52	,	,	PUNCT
flr-365	168	53	and	and	CCONJ
flr-365	168	54	their	their	PRON
flr-365	168	55	visual	visual	ADJ
flr-365	168	56	attention	attention	NOUN
flr-365	168	57	focused	focus	VERB
flr-365	168	58	more	more	ADV
flr-365	168	59	on	on	ADP
flr-365	168	60	relevant	relevant	ADJ
flr-365	168	61	than	than	ADP
flr-365	168	62	irrelevant	irrelevant	ADJ
flr-365	168	63	regions	region	NOUN
flr-365	168	64	of	of	ADP
flr-365	168	65	the	the	DET
flr-365	168	66	visual	visual	ADJ
flr-365	168	67	stimulus	stimulus	NOUN
flr-365	168	68	.	.	PUNCT
flr-365	169	1	our	our	PRON
flr-365	169	2	research	research	NOUN
flr-365	169	3	was	be	AUX
flr-365	169	4	also	also	ADV
flr-365	169	5	able	able	ADJ
flr-365	169	6	to	to	PART
flr-365	169	7	characterise	characterise	VERB
flr-365	169	8	the	the	DET
flr-365	169	9	sequence	sequence	NOUN
flr-365	169	10	of	of	ADP
flr-365	169	11	rapid	rapid	ADJ
flr-365	169	12	dwells	dwell	NOUN
flr-365	169	13	on	on	ADP
flr-365	169	14	relevant	relevant	ADJ
flr-365	169	15	/	/	SYM
flr-365	169	16	critical	critical	ADJ
flr-365	169	17	areas	area	NOUN
flr-365	169	18	in	in	ADP
flr-365	169	19	the	the	DET
flr-365	169	20	children	child	NOUN
flr-365	169	21	who	who	PRON
flr-365	169	22	completed	complete	VERB
flr-365	169	23	the	the	DET
flr-365	169	24	graph	graph	NOUN
flr-365	169	25	task	task	NOUN
flr-365	169	26	correctly	correctly	ADV
flr-365	169	27	,	,	PUNCT
flr-365	169	28	as	as	SCONJ
flr-365	169	29	shown	show	VERB
flr-365	169	30	in	in	ADP
flr-365	169	31	figure	figure	NOUN
flr-365	169	32	3	3	NUM
flr-365	169	33	.	.	PUNCT
flr-365	169	34	method	method	PROPN
flr-365	169	35	two	two	NUM
flr-365	169	36	used	use	VERB
flr-365	169	37	the	the	DET
flr-365	169	38	central	central	ADJ
flr-365	169	39	data	datum	NOUN
flr-365	169	40	item	item	NOUN
flr-365	169	41	to	to	PART
flr-365	169	42	determine	determine	VERB
flr-365	169	43	the	the	DET
flr-365	169	44	average	average	ADJ
flr-365	169	45	scanpath	scanpath	NOUN
flr-365	169	46	,	,	PUNCT
flr-365	169	47	as	as	ADV
flr-365	169	48	well	well	ADV
flr-365	169	49	as	as	ADP
flr-365	169	50	a	a	DET
flr-365	169	51	procedure	procedure	NOUN
flr-365	169	52	to	to	PART
flr-365	169	53	isolate	isolate	VERB
flr-365	169	54	the	the	DET
flr-365	169	55	sequence	sequence	NOUN
flr-365	169	56	of	of	ADP
flr-365	169	57	dwells	dwell	NOUN
flr-365	169	58	on	on	ADP
flr-365	169	59	the	the	DET
flr-365	169	60	most	most	ADV
flr-365	169	61	critical	critical	ADJ
flr-365	169	62	a	a	DET
flr-365	169	63	areas	area	NOUN
flr-365	169	64	.	.	PUNCT
flr-365	170	1	this	this	DET
flr-365	170	2	isolation	isolation	NOUN
flr-365	170	3	of	of	ADP
flr-365	170	4	the	the	DET
flr-365	170	5	sequence	sequence	NOUN
flr-365	170	6	of	of	ADP
flr-365	170	7	dwells	dwell	NOUN
flr-365	170	8	on	on	ADP
flr-365	170	9	a	a	DET
flr-365	170	10	areas	area	NOUN
flr-365	170	11	was	be	AUX
flr-365	170	12	revealing	reveal	VERB
flr-365	170	13	in	in	ADP
flr-365	170	14	terms	term	NOUN
flr-365	170	15	of	of	ADP
flr-365	170	16	understanding	understanding	NOUN
flr-365	170	17	whether	whether	SCONJ
flr-365	170	18	there	there	PRON
flr-365	170	19	was	be	VERB
flr-365	170	20	a	a	DET
flr-365	170	21	logical	logical	ADJ
flr-365	170	22	sequence	sequence	NOUN
flr-365	170	23	in	in	ADP
flr-365	170	24	accessing	access	VERB
flr-365	170	25	the	the	DET
flr-365	170	26	most	most	ADV
flr-365	170	27	critical	critical	ADJ
flr-365	170	28	information	information	NOUN
flr-365	170	29	.	.	PUNCT
flr-365	171	1	the	the	DET
flr-365	171	2	children	child	NOUN
flr-365	171	3	who	who	PRON
flr-365	171	4	responded	respond	VERB
flr-365	171	5	correctly	correctly	ADV
flr-365	171	6	followed	follow	VERB
flr-365	171	7	a	a	DET
flr-365	171	8	logical	logical	ADJ
flr-365	171	9	sequence	sequence	NOUN
flr-365	171	10	of	of	ADP
flr-365	171	11	dwells	dwell	NOUN
flr-365	171	12	(	(	PUNCT
flr-365	171	13	based	base	VERB
flr-365	171	14	on	on	ADP
flr-365	171	15	our	our	PRON
flr-365	171	16	initial	initial	ADJ
flr-365	171	17	categorisation	categorisation	NOUN
flr-365	171	18	of	of	ADP
flr-365	171	19	which	which	PRON
flr-365	171	20	areas	area	NOUN
flr-365	171	21	were	be	AUX
flr-365	171	22	most	most	ADV
flr-365	171	23	or	or	CCONJ
flr-365	171	24	least	least	ADV
flr-365	171	25	critical	critical	ADJ
flr-365	171	26	)	)	PUNCT
flr-365	171	27	,	,	PUNCT
flr-365	171	28	that	that	PRON
flr-365	171	29	progresses	progress	VERB
flr-365	171	30	from	from	ADP
flr-365	171	31	a1	a1	NOUN
flr-365	171	32	to	to	ADP
flr-365	171	33	a2	a2	PROPN
flr-365	171	34	to	to	PART
flr-365	171	35	a3	a3	VERB
flr-365	171	36	,	,	PUNCT
flr-365	171	37	then	then	ADV
flr-365	171	38	a4	a4	INTJ
flr-365	171	39	(	(	PUNCT
flr-365	171	40	figure	figure	NOUN
flr-365	171	41	5	5	NUM
flr-365	171	42	)	)	PUNCT
flr-365	171	43	.	.	PUNCT
flr-365	172	1	conversely	conversely	ADV
flr-365	172	2	,	,	PUNCT
flr-365	172	3	the	the	DET
flr-365	172	4	children	child	NOUN
flr-365	172	5	who	who	PRON
flr-365	172	6	responded	respond	VERB
flr-365	172	7	incorrectly	incorrectly	ADV
flr-365	172	8	,	,	PUNCT
flr-365	172	9	accessed	access	VERB
flr-365	172	10	a2	a2	NOUN
flr-365	172	11	relatively	relatively	ADV
flr-365	172	12	late	late	ADV
flr-365	172	13	in	in	ADP
flr-365	172	14	the	the	DET
flr-365	172	15	sequence	sequence	NOUN
flr-365	172	16	.	.	PUNCT
flr-365	173	1	a2	a2	PROPN
flr-365	173	2	represented	represent	VERB
flr-365	173	3	the	the	DET
flr-365	173	4	area	area	NOUN
flr-365	173	5	surrounding	surround	VERB
flr-365	173	6	the	the	DET
flr-365	173	7	main	main	ADJ
flr-365	173	8	question	question	NOUN
flr-365	173	9	‘	'	PUNCT
flr-365	173	10	how	how	SCONJ
flr-365	173	11	much	much	ADJ
flr-365	173	12	did	do	AUX
flr-365	173	13	she	she	PRON
flr-365	173	14	earn	earn	VERB
flr-365	173	15	in	in	ADP
flr-365	173	16	week	week	NOUN
flr-365	173	17	3	3	NUM
flr-365	173	18	?	?	PUNCT
flr-365	173	19	’	'	PUNCT
flr-365	173	20	with	with	ADP
flr-365	173	21	a2	a2	PROPN
flr-365	173	22	specifically	specifically	ADV
flr-365	173	23	representing	represent	VERB
flr-365	173	24	‘	'	PUNCT
flr-365	173	25	week	week	NOUN
flr-365	173	26	3	3	NUM
flr-365	173	27	’	'	PUNCT
flr-365	173	28	.	.	PUNCT
flr-365	174	1	delays	delay	NOUN
flr-365	174	2	in	in	ADP
flr-365	174	3	accessing	access	VERB
flr-365	174	4	this	this	DET
flr-365	174	5	information	information	NOUN
flr-365	174	6	may	may	AUX
flr-365	174	7	result	result	VERB
flr-365	174	8	in	in	ADP
flr-365	174	9	poorly	poorly	ADV
flr-365	174	10	focused	focus	VERB
flr-365	174	11	attention	attention	NOUN
flr-365	174	12	to	to	ADP
flr-365	174	13	the	the	DET
flr-365	174	14	relevant	relevant	ADJ
flr-365	174	15	aspects	aspect	NOUN
flr-365	174	16	of	of	ADP
flr-365	174	17	the	the	DET
flr-365	174	18	graph	graph	NOUN
flr-365	174	19	,	,	PUNCT
flr-365	174	20	resulting	result	VERB
flr-365	174	21	in	in	ADP
flr-365	174	22	the	the	DET
flr-365	174	23	child	child	NOUN
flr-365	174	24	not	not	PART
flr-365	174	25	knowing	know	VERB
flr-365	174	26	which	which	DET
flr-365	174	27	bar	bar	NOUN
flr-365	174	28	they	they	PRON
flr-365	174	29	should	should	AUX
flr-365	174	30	be	be	AUX
flr-365	174	31	using	use	VERB
flr-365	174	32	in	in	ADP
flr-365	174	33	their	their	PRON
flr-365	174	34	calculation	calculation	NOUN
flr-365	174	35	.	.	PUNCT
flr-365	175	1	relating	relate	VERB
flr-365	175	2	this	this	PRON
flr-365	175	3	to	to	PART
flr-365	175	4	curcio	curcio	VERB
flr-365	175	5	’s	’s	PART
flr-365	175	6	(	(	PUNCT
flr-365	175	7	2010	2010	NUM
flr-365	175	8	)	)	PUNCT
flr-365	175	9	framework	framework	NOUN
flr-365	175	10	it	it	PRON
flr-365	175	11	is	be	AUX
flr-365	175	12	the	the	DET
flr-365	175	13	first	first	ADJ
flr-365	175	14	level	level	NOUN
flr-365	175	15	in	in	ADP
flr-365	175	16	the	the	DET
flr-365	175	17	data	data	NOUN
flr-365	175	18	comprehension	comprehension	NOUN
flr-365	175	19	that	that	PRON
flr-365	175	20	is	be	AUX
flr-365	175	21	delayed	delay	VERB
flr-365	175	22	,	,	PUNCT
flr-365	175	23	or	or	CCONJ
flr-365	175	24	out	out	ADP
flr-365	175	25	of	of	ADP
flr-365	175	26	sequence	sequence	NOUN
flr-365	175	27	for	for	ADP
flr-365	175	28	the	the	DET
flr-365	175	29	children	child	NOUN
flr-365	175	30	who	who	PRON
flr-365	175	31	responded	respond	VERB
flr-365	175	32	incorrectly	incorrectly	ADV
flr-365	175	33	.	.	PUNCT
flr-365	176	1	the	the	DET
flr-365	176	2	initial	initial	ADJ
flr-365	176	3	understanding	understanding	NOUN
flr-365	176	4	and	and	CCONJ
flr-365	176	5	reading	reading	NOUN
flr-365	176	6	of	of	ADP
flr-365	176	7	information	information	NOUN
flr-365	176	8	in	in	ADP
flr-365	176	9	a	a	DET
flr-365	176	10	logical	logical	ADJ
flr-365	176	11	sequence	sequence	NOUN
flr-365	176	12	is	be	AUX
flr-365	176	13	the	the	DET
flr-365	176	14	essential	essential	ADJ
flr-365	176	15	foundation	foundation	NOUN
flr-365	176	16	to	to	PART
flr-365	176	17	guide	guide	VERB
flr-365	176	18	subsequent	subsequent	ADJ
flr-365	176	19	visual	visual	ADJ
flr-365	176	20	attention	attention	NOUN
flr-365	176	21	for	for	ADP
flr-365	176	22	interpreting	interpret	VERB
flr-365	176	23	and	and	CCONJ
flr-365	176	24	integrating	integrate	VERB
flr-365	176	25	the	the	DET
flr-365	176	26	relevant	relevant	ADJ
flr-365	176	27	graphical	graphical	ADJ
flr-365	176	28	information	information	NOUN
flr-365	176	29	and	and	CCONJ
flr-365	176	30	successfully	successfully	ADV
flr-365	176	31	completing	complete	VERB
flr-365	176	32	the	the	DET
flr-365	176	33	task	task	NOUN
flr-365	176	34	.	.	PUNCT
flr-365	177	1	this	this	DET
flr-365	177	2	finding	finding	NOUN
flr-365	177	3	is	be	AUX
flr-365	177	4	consistent	consistent	ADJ
flr-365	177	5	with	with	ADP
flr-365	177	6	kotsopoulos	kotsopoulo	NOUN
flr-365	177	7	and	and	CCONJ
flr-365	177	8	lee	lee	PROPN
flr-365	177	9	(	(	PUNCT
flr-365	177	10	2012	2012	NUM
flr-365	177	11	)	)	PUNCT
flr-365	177	12	,	,	PUNCT
flr-365	177	13	who	who	PRON
flr-365	177	14	reported	report	VERB
flr-365	177	15	that	that	PRON
flr-365	177	16	student	student	NOUN
flr-365	177	17	problem	problem	NOUN
flr-365	177	18	-	-	PUNCT
flr-365	177	19	solving	solving	NOUN
flr-365	177	20	most	most	ADV
flr-365	177	21	often	often	ADV
flr-365	177	22	broke	break	VERB
flr-365	177	23	down	down	ADP
flr-365	177	24	in	in	ADP
flr-365	177	25	the	the	DET
flr-365	177	26	early	early	ADJ
flr-365	177	27	stages	stage	NOUN
flr-365	177	28	of	of	ADP
flr-365	177	29	understanding	understand	VERB
flr-365	177	30	a	a	DET
flr-365	177	31	mathematics	mathematic	NOUN
flr-365	177	32	problem	problem	NOUN
flr-365	177	33	-	-	PUNCT
flr-365	177	34	solving	solve	VERB
flr-365	177	35	task	task	NOUN
flr-365	177	36	.	.	PUNCT
flr-365	178	1	it	it	PRON
flr-365	178	2	may	may	AUX
flr-365	178	3	be	be	AUX
flr-365	178	4	that	that	SCONJ
flr-365	178	5	if	if	SCONJ
flr-365	178	6	initial	initial	ADJ
flr-365	178	7	understanding	understanding	NOUN
flr-365	178	8	or	or	CCONJ
flr-365	178	9	orientation	orientation	NOUN
flr-365	178	10	is	be	AUX
flr-365	178	11	not	not	PART
flr-365	178	12	achieved	achieve	VERB
flr-365	178	13	early	early	ADV
flr-365	178	14	,	,	PUNCT
flr-365	178	15	the	the	DET
flr-365	178	16	visual	visual	ADJ
flr-365	178	17	dwells	dwell	NOUN
flr-365	178	18	become	become	VERB
flr-365	178	19	more	more	ADV
flr-365	178	20	frequent	frequent	ADJ
flr-365	178	21	and	and	CCONJ
flr-365	178	22	variable	variable	NOUN
flr-365	178	23	in	in	ADP
flr-365	178	24	location	location	NOUN
flr-365	178	25	,	,	PUNCT
flr-365	178	26	where	where	SCONJ
flr-365	178	27	children	child	NOUN
flr-365	178	28	may	may	AUX
flr-365	178	29	be	be	AUX
flr-365	178	30	looking	look	VERB
flr-365	178	31	for	for	ADP
flr-365	178	32	information	information	NOUN
flr-365	178	33	to	to	PART
flr-365	178	34	help	help	VERB
flr-365	178	35	them	they	PRON
flr-365	178	36	understand	understand	VERB
flr-365	178	37	the	the	DET
flr-365	178	38	requirements	requirement	NOUN
flr-365	178	39	of	of	ADP
flr-365	178	40	the	the	DET
flr-365	178	41	task	task	NOUN
flr-365	178	42	.	.	PUNCT
flr-365	179	1	it	it	PRON
flr-365	179	2	may	may	AUX
flr-365	179	3	also	also	ADV
flr-365	179	4	be	be	AUX
flr-365	179	5	that	that	SCONJ
flr-365	179	6	the	the	DET
flr-365	179	7	positioning	positioning	NOUN
flr-365	179	8	of	of	ADP
flr-365	179	9	the	the	DET
flr-365	179	10	question	question	NOUN
flr-365	179	11	,	,	PUNCT
flr-365	179	12	either	either	CCONJ
flr-365	179	13	above	above	ADP
flr-365	179	14	or	or	CCONJ
flr-365	179	15	below	below	ADP
flr-365	179	16	the	the	DET
flr-365	179	17	graph	graph	NOUN
flr-365	179	18	,	,	PUNCT
flr-365	179	19	would	would	AUX
flr-365	179	20	impact	impact	VERB
flr-365	179	21	on	on	ADP
flr-365	179	22	the	the	DET
flr-365	179	23	visual	visual	ADJ
flr-365	179	24	behaviours	behaviour	NOUN
flr-365	179	25	and	and	CCONJ
flr-365	179	26	task	task	NOUN
flr-365	179	27	response	response	NOUN
flr-365	179	28	.	.	PUNCT
flr-365	180	1	in	in	ADP
flr-365	180	2	comparing	compare	VERB
flr-365	180	3	the	the	DET
flr-365	180	4	results	result	NOUN
flr-365	180	5	of	of	ADP
flr-365	180	6	method	method	NOUN
flr-365	180	7	one	one	NUM
flr-365	180	8	and	and	CCONJ
flr-365	180	9	method	method	NOUN
flr-365	180	10	two	two	NUM
flr-365	180	11	,	,	PUNCT
flr-365	180	12	there	there	PRON
flr-365	180	13	are	be	VERB
flr-365	180	14	similarities	similarity	NOUN
flr-365	180	15	and	and	CCONJ
flr-365	180	16	differences	difference	NOUN
flr-365	180	17	.	.	PUNCT
flr-365	181	1	both	both	DET
flr-365	181	2	methods	method	NOUN
flr-365	181	3	produce	produce	VERB
flr-365	181	4	an	an	DET
flr-365	181	5	average	average	ADJ
flr-365	181	6	scanpath	scanpath	NOUN
flr-365	181	7	where	where	SCONJ
flr-365	181	8	the	the	DET
flr-365	181	9	correct	correct	ADJ
flr-365	181	10	children	child	NOUN
flr-365	181	11	have	have	VERB
flr-365	181	12	a	a	DET
flr-365	181	13	larger	large	ADJ
flr-365	181	14	percentage	percentage	NOUN
flr-365	181	15	access	access	NOUN
flr-365	181	16	of	of	ADP
flr-365	181	17	a	a	DET
flr-365	181	18	areas	area	NOUN
flr-365	181	19	,	,	PUNCT
flr-365	181	20	whereas	whereas	SCONJ
flr-365	181	21	incorrect	incorrect	ADJ
flr-365	181	22	children	child	NOUN
flr-365	181	23	distribute	distribute	VERB
flr-365	181	24	their	their	PRON
flr-365	181	25	dwells	dwell	NOUN
flr-365	181	26	across	across	ADP
flr-365	181	27	a	a	DET
flr-365	181	28	,	,	PUNCT
flr-365	181	29	b	b	PROPN
flr-365	181	30	and	and	CCONJ
flr-365	181	31	c	c	PROPN
flr-365	181	32	areas	area	NOUN
flr-365	181	33	,	,	PUNCT
flr-365	181	34	demonstrating	demonstrate	VERB
flr-365	181	35	that	that	SCONJ
flr-365	181	36	they	they	PRON
flr-365	181	37	may	may	AUX
flr-365	181	38	not	not	PART
flr-365	181	39	be	be	AUX
flr-365	181	40	identifying	identify	VERB
flr-365	181	41	the	the	DET
flr-365	181	42	most	most	ADV
flr-365	181	43	critical	critical	ADJ
flr-365	181	44	areas	area	NOUN
flr-365	181	45	.	.	PUNCT
flr-365	182	1	the	the	DET
flr-365	182	2	average	average	ADJ
flr-365	182	3	scanpath	scanpath	NOUN
flr-365	182	4	derived	derive	VERB
flr-365	182	5	using	use	VERB
flr-365	182	6	the	the	DET
flr-365	182	7	most	most	ADV
flr-365	182	8	probable	probable	ADJ
flr-365	182	9	vector	vector	NOUN
flr-365	182	10	indicated	indicate	VERB
flr-365	182	11	that	that	SCONJ
flr-365	182	12	children	child	NOUN
flr-365	182	13	who	who	PRON
flr-365	182	14	provided	provide	VERB
flr-365	182	15	correct	correct	ADJ
flr-365	182	16	responses	response	NOUN
flr-365	182	17	had	have	VERB
flr-365	182	18	a	a	DET
flr-365	182	19	slightly	slightly	ADV
flr-365	182	20	shorter	short	ADJ
flr-365	182	21	average	average	ADJ
flr-365	182	22	scanpath	scanpath	NOUN
flr-365	182	23	(	(	PUNCT
flr-365	182	24	69	69	NUM
flr-365	182	25	aois	aois	NOUN
flr-365	182	26	)	)	PUNCT
flr-365	182	27	compared	compare	VERB
flr-365	182	28	to	to	ADP
flr-365	182	29	the	the	DET
flr-365	182	30	children	child	NOUN
flr-365	182	31	who	who	PRON
flr-365	182	32	were	be	AUX
flr-365	182	33	incorrect	incorrect	ADJ
flr-365	182	34	(	(	PUNCT
flr-365	182	35	77	77	NUM
flr-365	182	36	aois	aois	NOUN
flr-365	182	37	)	)	PUNCT
flr-365	182	38	.	.	PUNCT
flr-365	183	1	this	this	DET
flr-365	183	2	distinction	distinction	NOUN
flr-365	183	3	was	be	AUX
flr-365	183	4	not	not	PART
flr-365	183	5	evident	evident	ADJ
flr-365	183	6	in	in	ADP
flr-365	183	7	the	the	DET
flr-365	183	8	average	average	ADJ
flr-365	183	9	scanpath	scanpath	NOUN
flr-365	183	10	derived	derive	VERB
flr-365	183	11	using	use	VERB
flr-365	183	12	the	the	DET
flr-365	183	13	central	central	ADJ
flr-365	183	14	data	datum	NOUN
flr-365	183	15	item	item	NOUN
flr-365	183	16	,	,	PUNCT
flr-365	183	17	both	both	DET
flr-365	183	18	groups	group	NOUN
flr-365	183	19	had	have	VERB
flr-365	183	20	an	an	DET
flr-365	183	21	average	average	ADJ
flr-365	183	22	scanpath	scanpath	NOUN
flr-365	183	23	of	of	ADP
flr-365	183	24	36	36	NUM
flr-365	183	25	aois	aois	NOUN
flr-365	183	26	.	.	PUNCT
flr-365	184	1	a	a	DET
flr-365	184	2	further	further	ADJ
flr-365	184	3	difference	difference	NOUN
flr-365	184	4	between	between	ADP
flr-365	184	5	the	the	DET
flr-365	184	6	two	two	NUM
flr-365	184	7	methods	method	NOUN
flr-365	184	8	was	be	AUX
flr-365	184	9	associated	associate	VERB
flr-365	184	10	with	with	ADP
flr-365	184	11	dwells	dwell	NOUN
flr-365	184	12	on	on	ADP
flr-365	184	13	a1	a1	NOUN
flr-365	184	14	-	-	PUNCT
flr-365	184	15	a4	a4	NOUN
flr-365	184	16	aois	aois	NOUN
flr-365	184	17	.	.	PUNCT
flr-365	185	1	the	the	DET
flr-365	185	2	average	average	ADJ
flr-365	185	3	scanpath	scanpath	NOUN
flr-365	185	4	(	(	PUNCT
flr-365	185	5	central	central	ADJ
flr-365	185	6	vector	vector	NOUN
flr-365	185	7	)	)	PUNCT
flr-365	185	8	included	include	VERB
flr-365	185	9	dwells	dwell	NOUN
flr-365	185	10	on	on	ADP
flr-365	185	11	all	all	PRON
flr-365	185	12	of	of	ADP
flr-365	185	13	the	the	DET
flr-365	185	14	most	most	ADV
flr-365	185	15	critical	critical	ADJ
flr-365	185	16	areas	area	NOUN
flr-365	185	17	(	(	PUNCT
flr-365	185	18	a1	a1	NOUN
flr-365	185	19	-	-	PUNCT
flr-365	185	20	a4	a4	NOUN
flr-365	185	21	)	)	PUNCT
flr-365	185	22	and	and	CCONJ
flr-365	185	23	implied	imply	VERB
flr-365	185	24	a	a	DET
flr-365	185	25	logical	logical	ADJ
flr-365	185	26	dwell	dwell	NOUN
flr-365	185	27	sequence	sequence	NOUN
flr-365	185	28	,	,	PUNCT
flr-365	185	29	whereas	whereas	SCONJ
flr-365	185	30	the	the	DET
flr-365	185	31	average	average	ADJ
flr-365	185	32	scanpath	scanpath	NOUN
flr-365	185	33	(	(	PUNCT
flr-365	185	34	most	most	ADV
flr-365	185	35	probable	probable	ADJ
flr-365	185	36	vector	vector	NOUN
flr-365	185	37	)	)	PUNCT
flr-365	185	38	did	do	AUX
flr-365	185	39	not	not	PART
flr-365	185	40	include	include	VERB
flr-365	185	41	an	an	DET
flr-365	185	42	a4	a4	NOUN
flr-365	185	43	dwell	dwell	NOUN
flr-365	185	44	.	.	PUNCT
flr-365	186	1	as	as	SCONJ
flr-365	186	2	noted	note	VERB
flr-365	186	3	in	in	ADP
flr-365	186	4	the	the	DET
flr-365	186	5	results	result	NOUN
flr-365	186	6	for	for	ADP
flr-365	186	7	method	method	NOUN
flr-365	186	8	one	one	NUM
flr-365	186	9	(	(	PUNCT
flr-365	186	10	most	most	ADV
flr-365	186	11	probable	probable	ADJ
flr-365	186	12	vector	vector	NOUN
flr-365	186	13	)	)	PUNCT
flr-365	186	14	,	,	PUNCT
flr-365	186	15	the	the	DET
flr-365	186	16	omission	omission	NOUN
flr-365	186	17	of	of	ADP
flr-365	186	18	a4	a4	NOUN
flr-365	186	19	from	from	ADP
flr-365	186	20	the	the	DET
flr-365	186	21	average	average	ADJ
flr-365	186	22	scanpath	scanpath	NOUN
flr-365	186	23	could	could	AUX
flr-365	186	24	be	be	AUX
flr-365	186	25	an	an	DET
flr-365	186	26	indicator	indicator	NOUN
flr-365	186	27	of	of	ADP
flr-365	186	28	variation	variation	NOUN
flr-365	186	29	in	in	ADP
flr-365	186	30	how	how	SCONJ
flr-365	186	31	children	child	NOUN
flr-365	186	32	accessed	access	VERB
flr-365	186	33	this	this	DET
flr-365	186	34	scale	scale	NOUN
flr-365	186	35	information	information	NOUN
flr-365	186	36	,	,	PUNCT
flr-365	186	37	so	so	CCONJ
flr-365	186	38	it	it	PRON
flr-365	186	39	did	do	AUX
flr-365	186	40	not	not	PART
flr-365	186	41	appear	appear	VERB
flr-365	186	42	using	use	VERB
flr-365	186	43	the	the	DET
flr-365	186	44	most	most	ADV
flr-365	186	45	probable	probable	ADJ
flr-365	186	46	vector	vector	NOUN
flr-365	186	47	method	method	NOUN
flr-365	186	48	.	.	PUNCT
flr-365	187	1	for	for	ADP
flr-365	187	2	example	example	NOUN
flr-365	187	3	,	,	PUNCT
flr-365	187	4	children	child	NOUN
flr-365	187	5	may	may	AUX
flr-365	187	6	have	have	AUX
flr-365	187	7	counted	count	VERB
flr-365	187	8	up	up	ADP
flr-365	187	9	the	the	DET
flr-365	187	10	gridlines	gridline	NOUN
flr-365	187	11	within	within	ADP
flr-365	187	12	the	the	DET
flr-365	187	13	body	body	NOUN
flr-365	187	14	of	of	ADP
flr-365	187	15	the	the	DET
flr-365	187	16	graph	graph	NOUN
flr-365	187	17	to	to	PART
flr-365	187	18	determine	determine	VERB
flr-365	187	19	the	the	DET
flr-365	187	20	two	two	NUM
flr-365	187	21	hours	hour	NOUN
flr-365	187	22	worked	work	VERB
flr-365	187	23	in	in	ADP
flr-365	187	24	week	week	NOUN
flr-365	187	25	3	3	NUM
flr-365	187	26	.	.	NOUN
flr-365	187	27	or	or	CCONJ
flr-365	187	28	alternatively	alternatively	ADV
flr-365	187	29	,	,	PUNCT
flr-365	187	30	children	child	NOUN
flr-365	187	31	may	may	AUX
flr-365	187	32	have	have	AUX
flr-365	187	33	looked	look	VERB
flr-365	187	34	more	more	ADV
flr-365	187	35	generally	generally	ADV
flr-365	187	36	at	at	ADP
flr-365	187	37	the	the	DET
flr-365	187	38	scale	scale	NOUN
flr-365	187	39	of	of	ADP
flr-365	187	40	the	the	DET
flr-365	187	41	y	y	NOUN
flr-365	187	42	-	-	PUNCT
flr-365	187	43	axis	axis	NOUN
flr-365	187	44	,	,	PUNCT
flr-365	187	45	but	but	CCONJ
flr-365	187	46	not	not	PART
flr-365	187	47	necessarily	necessarily	ADV
flr-365	187	48	specifically	specifically	ADV
flr-365	187	49	at	at	ADP
flr-365	187	50	a4	a4	NUM
flr-365	187	51	.	.	PUNCT
flr-365	188	1	the	the	DET
flr-365	188	2	source	source	NOUN
flr-365	188	3	of	of	ADP
flr-365	188	4	this	this	DET
flr-365	188	5	variation	variation	NOUN
flr-365	188	6	would	would	AUX
flr-365	188	7	need	need	VERB
flr-365	188	8	to	to	PART
flr-365	188	9	be	be	AUX
flr-365	188	10	investigated	investigate	VERB
flr-365	188	11	with	with	ADP
flr-365	188	12	eye	eye	NOUN
flr-365	188	13	tracking	tracking	NOUN
flr-365	188	14	data	datum	NOUN
flr-365	188	15	from	from	ADP
flr-365	188	16	another	another	DET
flr-365	188	17	task	task	NOUN
flr-365	188	18	.	.	PUNCT
flr-365	189	1	there	there	PRON
flr-365	189	2	are	be	VERB
flr-365	189	3	limitations	limitation	NOUN
flr-365	189	4	to	to	ADP
flr-365	189	5	both	both	DET
flr-365	189	6	methods	method	NOUN
flr-365	189	7	and	and	CCONJ
flr-365	189	8	in	in	ADP
flr-365	189	9	the	the	DET
flr-365	189	10	characterisation	characterisation	NOUN
flr-365	189	11	of	of	ADP
flr-365	189	12	the	the	DET
flr-365	189	13	average	average	ADJ
flr-365	189	14	scanpath	scanpath	NOUN
flr-365	189	15	for	for	ADP
flr-365	189	16	children	child	NOUN
flr-365	189	17	who	who	PRON
flr-365	189	18	responded	respond	VERB
flr-365	189	19	correctly	correctly	ADV
flr-365	189	20	and	and	CCONJ
flr-365	189	21	incorrectly	incorrectly	ADV
flr-365	189	22	.	.	PUNCT
flr-365	190	1	as	as	ADP
flr-365	190	2	with	with	ADP
flr-365	190	3	all	all	DET
flr-365	190	4	averaging	average	VERB
flr-365	190	5	procedures	procedure	NOUN
flr-365	190	6	,	,	PUNCT
flr-365	190	7	there	there	PRON
flr-365	190	8	is	be	VERB
flr-365	190	9	some	some	DET
flr-365	190	10	loss	loss	NOUN
flr-365	190	11	of	of	ADP
flr-365	190	12	individual	individual	ADJ
flr-365	190	13	detail	detail	NOUN
flr-365	190	14	,	,	PUNCT
flr-365	190	15	however	however	ADV
flr-365	190	16	,	,	PUNCT
flr-365	190	17	the	the	DET
flr-365	190	18	aim	aim	NOUN
flr-365	190	19	of	of	ADP
flr-365	190	20	this	this	DET
flr-365	190	21	study	study	NOUN
flr-365	190	22	was	be	AUX
flr-365	190	23	to	to	PART
flr-365	190	24	characterise	characterise	VERB
flr-365	190	25	the	the	DET
flr-365	190	26	visual	visual	ADJ
flr-365	190	27	cognitive	cognitive	ADJ
flr-365	190	28	behaviours	behaviour	NOUN
flr-365	190	29	of	of	ADP
flr-365	190	30	those	those	DET
flr-365	190	31	children	child	NOUN
flr-365	190	32	who	who	PRON
flr-365	190	33	completed	complete	VERB
flr-365	190	34	the	the	DET
flr-365	190	35	task	task	NOUN
flr-365	190	36	correctly	correctly	ADV
flr-365	190	37	versus	versus	ADP
flr-365	190	38	those	those	DET
flr-365	190	39	children	child	NOUN
flr-365	190	40	who	who	PRON
flr-365	190	41	were	be	AUX
flr-365	190	42	incorrect	incorrect	ADJ
flr-365	190	43	.	.	PUNCT
flr-365	191	1	method	method	PROPN
flr-365	191	2	one	one	NUM
flr-365	191	3	,	,	PUNCT
flr-365	191	4	using	use	VERB
flr-365	191	5	a	a	DET
flr-365	191	6	naïve	naïve	ADJ
flr-365	191	7	bayes	bayes	NOUN
flr-365	191	8	classifier	classifier	NOUN
flr-365	191	9	to	to	PART
flr-365	191	10	determine	determine	VERB
flr-365	191	11	the	the	DET
flr-365	191	12	most	most	ADV
flr-365	191	13	probable	probable	ADJ
flr-365	191	14	vector	vector	NOUN
flr-365	191	15	,	,	PUNCT
flr-365	191	16	might	might	AUX
flr-365	191	17	be	be	AUX
flr-365	191	18	limited	limit	VERB
flr-365	191	19	by	by	ADP
flr-365	191	20	the	the	DET
flr-365	191	21	data	datum	NOUN
flr-365	191	22	used	use	VERB
flr-365	191	23	in	in	ADP
flr-365	191	24	the	the	DET
flr-365	191	25	analysis	analysis	NOUN
flr-365	191	26	unless	unless	SCONJ
flr-365	191	27	,	,	PUNCT
flr-365	191	28	as	as	SCONJ
flr-365	191	29	was	be	AUX
flr-365	191	30	the	the	DET
flr-365	191	31	case	case	NOUN
flr-365	191	32	in	in	ADP
flr-365	191	33	our	our	PRON
flr-365	191	34	study	study	NOUN
flr-365	191	35	,	,	PUNCT
flr-365	191	36	the	the	DET
flr-365	191	37	eye	eye	NOUN
flr-365	191	38	tracking	track	VERB
flr-365	191	39	data	datum	NOUN
flr-365	191	40	obeys	obey	VERB
flr-365	191	41	the	the	DET
flr-365	191	42	naïve	naïve	ADJ
flr-365	191	43	bayes	bayes	NOUN
flr-365	191	44	assumption	assumption	NOUN
flr-365	191	45	of	of	ADP
flr-365	191	46	an	an	DET
flr-365	191	47	uncorrelated	uncorrelated	ADJ
flr-365	191	48	aoi	aoi	NOUN
flr-365	191	49	sequence	sequence	NOUN
flr-365	191	50	.	.	PUNCT
flr-365	192	1	future	future	ADJ
flr-365	192	2	research	research	NOUN
flr-365	192	3	should	should	AUX
flr-365	192	4	replicate	replicate	VERB
flr-365	192	5	this	this	DET
flr-365	192	6	task	task	NOUN
flr-365	192	7	,	,	PUNCT
flr-365	192	8	or	or	CCONJ
flr-365	192	9	a	a	DET
flr-365	192	10	close	close	ADJ
flr-365	192	11	variant	variant	NOUN
flr-365	192	12	,	,	PUNCT
flr-365	192	13	in	in	ADP
flr-365	192	14	order	order	NOUN
flr-365	192	15	to	to	PART
flr-365	192	16	obtain	obtain	VERB
flr-365	192	17	test	test	NOUN
flr-365	192	18	data	datum	NOUN
flr-365	192	19	to	to	PART
flr-365	192	20	validate	validate	VERB
flr-365	192	21	the	the	DET
flr-365	192	22	models	model	NOUN
flr-365	192	23	produced	produce	VERB
flr-365	192	24	here	here	ADV
flr-365	192	25	.	.	PUNCT
flr-365	193	1	overall	overall	ADV
flr-365	193	2	,	,	PUNCT
flr-365	193	3	this	this	DET
flr-365	193	4	research	research	NOUN
flr-365	193	5	has	have	AUX
flr-365	193	6	applied	apply	VERB
flr-365	193	7	novel	novel	ADJ
flr-365	193	8	machine	machine	NOUN
flr-365	193	9	learning	learning	NOUN
flr-365	193	10	and	and	CCONJ
flr-365	193	11	mathematical	mathematical	ADJ
flr-365	193	12	analyses	analysis	NOUN
flr-365	193	13	to	to	PART
flr-365	193	14	characterise	characterise	VERB
flr-365	193	15	the	the	DET
flr-365	193	16	visual	visual	ADJ
flr-365	193	17	cognitive	cognitive	ADJ
flr-365	193	18	behaviours	behaviour	NOUN
flr-365	193	19	of	of	ADP
flr-365	193	20	year	year	NOUN
flr-365	193	21	3	3	NUM
flr-365	193	22	children	child	NOUN
flr-365	193	23	engaged	engage	VERB
flr-365	193	24	in	in	ADP
flr-365	193	25	a	a	DET
flr-365	193	26	mathematics	mathematics	NOUN
flr-365	193	27	graph	graph	NOUN
flr-365	193	28	task	task	NOUN
flr-365	193	29	.	.	PUNCT
flr-365	194	1	the	the	DET
flr-365	194	2	resulting	result	VERB
flr-365	194	3	characterisations	characterisation	NOUN
flr-365	194	4	support	support	VERB
flr-365	194	5	the	the	DET
flr-365	194	6	importance	importance	NOUN
flr-365	194	7	of	of	ADP
flr-365	194	8	initial	initial	ADJ
flr-365	194	9	understanding	understanding	NOUN
flr-365	194	10	of	of	ADP
flr-365	194	11	the	the	DET
flr-365	194	12	presented	present	VERB
flr-365	194	13	task	task	NOUN
flr-365	194	14	and	and	CCONJ
flr-365	194	15	identification	identification	NOUN
flr-365	194	16	of	of	ADP
flr-365	194	17	the	the	DET
flr-365	194	18	most	most	ADV
flr-365	194	19	critical	critical	ADJ
flr-365	194	20	information	information	NOUN
flr-365	194	21	.	.	PUNCT
flr-365	195	1	while	while	SCONJ
flr-365	195	2	identification	identification	NOUN
flr-365	195	3	of	of	ADP
flr-365	195	4	the	the	DET
flr-365	195	5	most	most	ADV
flr-365	195	6	critical	critical	ADJ
flr-365	195	7	information	information	NOUN
flr-365	195	8	may	may	AUX
flr-365	195	9	be	be	AUX
flr-365	195	10	part	part	NOUN
flr-365	195	11	of	of	ADP
flr-365	195	12	a	a	DET
flr-365	195	13	typical	typical	ADJ
flr-365	195	14	classroom	classroom	NOUN
flr-365	195	15	practice	practice	NOUN
flr-365	195	16	,	,	PUNCT
flr-365	195	17	this	this	DET
flr-365	195	18	reinforcement	reinforcement	NOUN
flr-365	195	19	,	,	PUNCT
flr-365	195	20	and	and	CCONJ
flr-365	195	21	the	the	DET
flr-365	195	22	logical	logical	ADJ
flr-365	195	23	sequence	sequence	NOUN
flr-365	195	24	of	of	ADP
flr-365	195	25	visual	visual	ADJ
flr-365	195	26	access	access	NOUN
flr-365	195	27	of	of	ADP
flr-365	195	28	the	the	DET
flr-365	195	29	most	most	ADV
flr-365	195	30	critical	critical	ADJ
flr-365	195	31	information	information	NOUN
flr-365	195	32	,	,	PUNCT
flr-365	195	33	may	may	AUX
flr-365	195	34	be	be	AUX
flr-365	195	35	beneficial	beneficial	ADJ
flr-365	195	36	for	for	ADP
flr-365	195	37	children	child	NOUN
flr-365	195	38	who	who	PRON
flr-365	195	39	feel	feel	VERB
flr-365	195	40	less	less	ADV
flr-365	195	41	confident	confident	ADJ
flr-365	195	42	.	.	PUNCT
flr-365	196	1	keypoints	keypoint	NOUN
flr-365	196	2	machine	machine	NOUN
flr-365	196	3	learning	learn	VERB
flr-365	196	4	techniques	technique	NOUN
flr-365	196	5	take	take	VERB
flr-365	196	6	the	the	DET
flr-365	196	7	analysis	analysis	NOUN
flr-365	196	8	of	of	ADP
flr-365	196	9	eye	eye	NOUN
flr-365	196	10	tracking	track	VERB
flr-365	196	11	data	datum	NOUN
flr-365	196	12	to	to	ADP
flr-365	196	13	a	a	DET
flr-365	196	14	new	new	ADJ
flr-365	196	15	level	level	NOUN
flr-365	196	16	.	.	PUNCT
flr-365	197	1	in	in	ADP
flr-365	197	2	particular	particular	ADJ
flr-365	197	3	,	,	PUNCT
flr-365	197	4	they	they	PRON
flr-365	197	5	allow	allow	VERB
flr-365	197	6	for	for	ADP
flr-365	197	7	understanding	understanding	NOUN
flr-365	197	8	of	of	ADP
flr-365	197	9	phenomena	phenomenon	NOUN
flr-365	197	10	in	in	ADP
flr-365	197	11	the	the	DET
flr-365	197	12	dimension	dimension	NOUN
flr-365	197	13	of	of	ADP
flr-365	197	14	time	time	NOUN
flr-365	197	15	in	in	ADP
flr-365	197	16	relation	relation	NOUN
flr-365	197	17	to	to	ADP
flr-365	197	18	the	the	DET
flr-365	197	19	order	order	NOUN
flr-365	197	20	structure	structure	NOUN
flr-365	197	21	of	of	ADP
flr-365	197	22	data	datum	NOUN
flr-365	197	23	.	.	PUNCT
flr-365	198	1	spending	spending	NOUN
flr-365	198	2	time	time	NOUN
flr-365	198	3	looking	look	VERB
flr-365	198	4	at	at	ADP
flr-365	198	5	critical	critical	ADJ
flr-365	198	6	areas	area	NOUN
flr-365	198	7	and	and	CCONJ
flr-365	198	8	accessing	access	VERB
flr-365	198	9	critical	critical	ADJ
flr-365	198	10	areas	area	NOUN
flr-365	198	11	in	in	ADP
flr-365	198	12	a	a	DET
flr-365	198	13	logical	logical	ADJ
flr-365	198	14	order	order	NOUN
flr-365	198	15	is	be	AUX
flr-365	198	16	important	important	ADJ
flr-365	198	17	for	for	ADP
flr-365	198	18	completing	complete	VERB
flr-365	198	19	the	the	DET
flr-365	198	20	task	task	NOUN
flr-365	198	21	successfully	successfully	ADV
flr-365	198	22	.	.	PUNCT
flr-365	199	1	spending	spend	VERB
flr-365	199	2	too	too	ADV
flr-365	199	3	much	much	ADJ
flr-365	199	4	time	time	NOUN
flr-365	199	5	looking	look	VERB
flr-365	199	6	at	at	ADP
flr-365	199	7	less	less	ADV
flr-365	199	8	critical	critical	ADJ
flr-365	199	9	areas	area	NOUN
flr-365	199	10	,	,	PUNCT
flr-365	199	11	and	and	CCONJ
flr-365	199	12	more	more	ADJ
flr-365	199	13	dwells	dwell	NOUN
flr-365	199	14	,	,	PUNCT
flr-365	199	15	is	be	AUX
flr-365	199	16	indicative	indicative	ADJ
flr-365	199	17	of	of	ADP
flr-365	199	18	probable	probable	ADJ
flr-365	199	19	failure	failure	NOUN
flr-365	199	20	to	to	PART
flr-365	199	21	successfully	successfully	ADV
flr-365	199	22	complete	complete	VERB
flr-365	199	23	the	the	DET
flr-365	199	24	task	task	NOUN
flr-365	199	25	.	.	PUNCT
flr-365	200	1	for	for	ADP
flr-365	200	2	teaching	teaching	NOUN
flr-365	200	3	purposes	purpose	NOUN
flr-365	200	4	,	,	PUNCT
flr-365	200	5	it	it	PRON
flr-365	200	6	is	be	AUX
flr-365	200	7	important	important	ADJ
flr-365	200	8	to	to	PART
flr-365	200	9	identify	identify	VERB
flr-365	200	10	critical	critical	ADJ
flr-365	200	11	areas	area	NOUN
flr-365	200	12	and	and	CCONJ
flr-365	200	13	to	to	PART
flr-365	200	14	break	break	VERB
flr-365	200	15	down	down	ADP
flr-365	200	16	the	the	DET
flr-365	200	17	process	process	NOUN
flr-365	200	18	of	of	ADP
flr-365	200	19	problem	problem	NOUN
flr-365	200	20	-	-	PUNCT
flr-365	200	21	solving	solving	NOUN
flr-365	200	22	into	into	ADP
flr-365	200	23	recognisable	recognisable	ADJ
flr-365	200	24	steps	step	NOUN
flr-365	200	25	which	which	PRON
flr-365	200	26	can	can	AUX
flr-365	200	27	be	be	AUX
flr-365	200	28	carried	carry	VERB
flr-365	200	29	out	out	ADP
flr-365	200	30	procedurally	procedurally	ADV
flr-365	200	31	.	.	PUNCT
flr-365	201	1	acknowledgments	acknowledgment	NOUN
flr-365	201	2	this	this	DET
flr-365	201	3	research	research	NOUN
flr-365	201	4	was	be	AUX
flr-365	201	5	financially	financially	ADV
flr-365	201	6	supported	support	VERB
flr-365	201	7	by	by	ADP
flr-365	201	8	the	the	DET
flr-365	201	9	ian	ian	PROPN
flr-365	201	10	potter	potter	PROPN
flr-365	201	11	foundation	foundation	PROPN
flr-365	201	12	(	(	PUNCT
flr-365	201	13	ref	ref	NOUN
flr-365	201	14	:	:	PUNCT
flr-365	201	15	20140415	20140415	NUM
flr-365	201	16	)	)	PUNCT
flr-365	201	17	.	.	PUNCT
flr-365	202	1	thank	thank	VERB
flr-365	202	2	you	you	PRON
flr-365	202	3	to	to	ADP
flr-365	202	4	the	the	DET
flr-365	202	5	schools	school	NOUN
flr-365	202	6	,	,	PUNCT
flr-365	202	7	teachers	teacher	NOUN
flr-365	202	8	,	,	PUNCT
flr-365	202	9	parents	parent	NOUN
flr-365	202	10	and	and	CCONJ
flr-365	202	11	children	child	NOUN
flr-365	202	12	for	for	ADP
flr-365	202	13	their	their	PRON
flr-365	202	14	interest	interest	NOUN
flr-365	202	15	and	and	CCONJ
flr-365	202	16	involvement	involvement	NOUN
flr-365	202	17	in	in	ADP
flr-365	202	18	this	this	DET
flr-365	202	19	research	research	NOUN
flr-365	202	20	.	.	PUNCT
flr-365	203	1	egme	egme	PROPN
flr-365	203	2	wishes	wish	VERB
flr-365	203	3	to	to	PART
flr-365	203	4	acknowledge	acknowledge	VERB
flr-365	203	5	the	the	DET
flr-365	203	6	on	on	ADP
flr-365	203	7	-	-	PUNCT
flr-365	203	8	going	go	VERB
flr-365	203	9	discussions	discussion	NOUN
flr-365	203	10	with	with	ADP
flr-365	203	11	nora	nora	PROPN
flr-365	203	12	mcintyre	mcintyre	PROPN
flr-365	203	13	,	,	PUNCT
flr-365	203	14	at	at	ADP
flr-365	203	15	psychology	psychology	NOUN
flr-365	203	16	in	in	ADP
flr-365	203	17	education	education	NOUN
flr-365	203	18	research	research	NOUN
flr-365	203	19	centre	centre	NOUN
flr-365	203	20	in	in	ADP
flr-365	203	21	the	the	DET
flr-365	203	22	university	university	PROPN
flr-365	203	23	of	of	ADP
flr-365	203	24	york	york	PROPN
flr-365	203	25	,	,	PUNCT
flr-365	203	26	with	with	ADP
flr-365	203	27	whom	whom	PRON
flr-365	203	28	valuable	valuable	ADJ
flr-365	203	29	discussions	discussion	NOUN
flr-365	203	30	ensued	ensue	VERB
flr-365	203	31	about	about	ADP
flr-365	203	32	the	the	DET
flr-365	203	33	possible	possible	ADJ
flr-365	203	34	measures	measure	NOUN
flr-365	203	35	discussed	discuss	VERB
flr-365	203	36	here	here	ADV
flr-365	203	37	,	,	PUNCT
flr-365	203	38	and	and	CCONJ
flr-365	203	39	about	about	ADP
flr-365	203	40	classifying	classify	VERB
flr-365	203	41	gaze	gaze	NOUN
flr-365	203	42	patterns	pattern	NOUN
flr-365	203	43	according	accord	VERB
flr-365	203	44	to	to	ADP
flr-365	203	45	the	the	DET
flr-365	203	46	subjects	subject	NOUN
flr-365	203	47	state	state	NOUN
flr-365	203	48	of	of	ADP
flr-365	203	49	mind	mind	NOUN
flr-365	203	50	;	;	PUNCT
flr-365	203	51	and	and	CCONJ
flr-365	203	52	the	the	DET
flr-365	203	53	ongoing	ongoing	ADJ
flr-365	203	54	support	support	NOUN
flr-365	203	55	of	of	ADP
flr-365	203	56	prof	prof	NOUN
flr-365	203	57	.	.	PUNCT
flr-365	204	1	markku	markku	PROPN
flr-365	204	2	s.	s.	PROPN
flr-365	204	3	hannula	hannula	PROPN
flr-365	204	4	at	at	ADP
flr-365	204	5	the	the	DET
flr-365	204	6	faculty	faculty	NOUN
flr-365	204	7	of	of	ADP
flr-365	204	8	educational	educational	ADJ
flr-365	204	9	sciences	science	NOUN
flr-365	204	10	of	of	ADP
flr-365	204	11	the	the	DET
flr-365	204	12	university	university	PROPN
flr-365	204	13	of	of	ADP
flr-365	204	14	helsinki	helsinki	PROPN
flr-365	204	15	during	during	ADP
flr-365	204	16	this	this	DET
flr-365	204	17	research	research	NOUN
flr-365	204	18	.	.	PUNCT
flr-365	205	1	sw	sw	PROPN
flr-365	205	2	was	be	AUX
flr-365	205	3	supported	support	VERB
flr-365	205	4	by	by	ADP
flr-365	205	5	an	an	DET
flr-365	205	6	australian	australian	ADJ
flr-365	205	7	research	research	NOUN
flr-365	205	8	council	council	NOUN
flr-365	205	9	decra	decra	NOUN
flr-365	205	10	(	(	PUNCT
flr-365	205	11	de160100830	de160100830	PROPN
flr-365	205	12	)	)	PUNCT
flr-365	205	13	during	during	ADP
flr-365	205	14	the	the	DET
flr-365	205	15	preparation	preparation	NOUN
flr-365	205	16	of	of	ADP
flr-365	205	17	this	this	DET
flr-365	205	18	manuscript	manuscript	NOUN
flr-365	205	19	.	.	PUNCT
flr-365	206	1	references	reference	NOUN
flr-365	206	2	australiancurriculum	australiancurriculum	PROPN
flr-365	206	3	,	,	PUNCT
flr-365	206	4	assessment	assessment	NOUN
flr-365	206	5	and	and	CCONJ
flr-365	206	6	reporting	reporting	NOUN
flr-365	206	7	authority	authority	NOUN
flr-365	206	8	(	(	PUNCT
flr-365	206	9	2016	2016	NUM
flr-365	206	10	)	)	PUNCT
flr-365	206	11	.	.	PUNCT
flr-365	207	1	the	the	DET
flr-365	207	2	australian	australian	ADJ
flr-365	207	3	curriculum	curriculum	NOUN
flr-365	207	4	:	:	PUNCT
flr-365	207	5	mathematics	mathematic	NOUN
flr-365	207	6	,	,	PUNCT
flr-365	207	7	v8.2.retrievedfrom	v8.2.retrievedfrom	ADP
flr-365	207	8	http://www.australiancurriculum.edu.au/	http://www.australiancurriculum.edu.au/	PROPN
flr-365	207	9	bochynska	bochynska	NOUN
flr-365	207	10	,	,	PUNCT
flr-365	207	11	a.	a.	PROPN
flr-365	207	12	,	,	PUNCT
flr-365	207	13	&	&	CCONJ
flr-365	207	14	laeng	laeng	PROPN
flr-365	207	15	,	,	PUNCT
flr-365	207	16	b.	b.	PROPN
flr-365	207	17	(	(	PUNCT
flr-365	207	18	2015).trackingdown	2015).trackingdown	NUM
flr-365	207	19	thepathofmemory	thepathofmemory	NOUN
flr-365	207	20	:	:	PUNCT
flr-365	207	21	eyescanpathsfacilitatetheretrievalofvisuospatialinformation	eyescanpathsfacilitatetheretrievalofvisuospatialinformation	NOUN
flr-365	207	22	.	.	PUNCT
flr-365	208	1	cognitiveprocessing,16(suppl	cognitiveprocessing,16(suppl	NOUN
flr-365	208	2	.	.	PUNCT
flr-365	209	1	1)159–163.doi:10.1007	1)159–163.doi:10.1007	NUM
flr-365	209	2	/	/	SYM
flr-365	209	3	s10339	s10339	PROPN
flr-365	209	4	-	-	PUNCT
flr-365	209	5	015	015	NUM
flr-365	209	6	-	-	PUNCT
flr-365	209	7	0690	0690	NUM
flr-365	209	8	-	-	PUNCT
flr-365	209	9	0	0	NUM
flr-365	209	10	curcio	curcio	NOUN
flr-365	209	11	,	,	PUNCT
flr-365	209	12	f.r.(2010).developingdata	f.r.(2010).developingdata	NOUN
flr-365	209	13	-	-	PUNCT
flr-365	209	14	graphcomprehensioningradesk-8	graphcomprehensioningradesk-8	NUM
flr-365	209	15	(	(	PUNCT
flr-365	209	16	3rdedition.).reston	3rdedition.).reston	PROPN
flr-365	209	17	,	,	PUNCT
flr-365	209	18	va	va	NOUN
flr-365	209	19	:	:	PUNCT
flr-365	209	20	thenationalcouncilofteachersofmathematics	thenationalcouncilofteachersofmathematic	NOUN
flr-365	209	21	.	.	PUNCT
flr-365	210	1	gegenfurtner	gegenfurtner	NOUN
flr-365	210	2	,	,	PUNCT
flr-365	210	3	a.	a.	PROPN
flr-365	210	4	,lehtinen	,lehtinen	PROPN
flr-365	210	5	,	,	PUNCT
flr-365	210	6	e.	e.	PROPN
flr-365	210	7	,&säljö	,&säljö	PROPN
flr-365	210	8	,	,	PUNCT
flr-365	210	9	r.(2011	r.(2011	NOUN
flr-365	210	10	)	)	PUNCT
flr-365	210	11	.	.	PUNCT
flr-365	211	1	expertisedifferencesinthecomprehensionofvisualizations	expertisedifferencesinthecomprehensionofvisualization	NOUN
flr-365	211	2	:	:	PUNCT
flr-365	211	3	ameta	ameta	ADJ
flr-365	211	4	-	-	PUNCT
flr-365	211	5	analysisofeye	analysisofeye	NOUN
flr-365	211	6	-	-	PUNCT
flr-365	211	7	trackingresearchinprofessionaldomains	trackingresearchinprofessionaldomain	NOUN
flr-365	211	8	.	.	PUNCT
flr-365	212	1	educationalpsychologyreview,23	educationalpsychologyreview,23	PROPN
flr-365	212	2	(	(	PUNCT
flr-365	212	3	4),523	4),523	NOUN
flr-365	212	4	-	-	SYM
flr-365	212	5	552.doi:10.1007	552.doi:10.1007	NUM
flr-365	212	6	/	/	SYM
flr-365	212	7	s10648	s10648	NOUN
flr-365	212	8	-	-	PUNCT
flr-365	212	9	011	011	NUM
flr-365	212	10	-	-	PUNCT
flr-365	212	11	9174	9174	NUM
flr-365	212	12	-	-	PUNCT
flr-365	212	13	7	7	NUM
flr-365	212	14	holmqvist	holmqvist	NOUN
flr-365	212	15	,	,	PUNCT
flr-365	212	16	k.	k.	PROPN
flr-365	212	17	,nystrom	,nystrom	PUNCT
flr-365	212	18	,	,	PUNCT
flr-365	212	19	m.	m.	NOUN
flr-365	212	20	,andersson	,andersson	PUNCT
flr-365	212	21	,	,	PUNCT
flr-365	212	22	r.	r.	PROPN
flr-365	212	23	,dewhurst	,dewhurst	PROPN
flr-365	212	24	,	,	PUNCT
flr-365	212	25	r.	r.	PROPN
flr-365	212	26	,jarodzka	,jarodzka	PROPN
flr-365	212	27	,	,	PUNCT
flr-365	212	28	h.	h.	PROPN
flr-365	212	29	,&vandeweijer	,&vandeweijer	PROPN
flr-365	212	30	,	,	PUNCT
flr-365	212	31	j.(2011	j.(2011	PROPN
flr-365	212	32	)	)	PUNCT
flr-365	212	33	.	.	PUNCT
flr-365	213	1	eyetracking	eyetracke	VERB
flr-365	213	2	:	:	PUNCT
flr-365	213	3	acomprehensiveguidetomethodsandmeasures	acomprehensiveguidetomethodsandmeasure	NOUN
flr-365	213	4	.newyork	.newyork	PROPN
flr-365	213	5	,	,	PUNCT
flr-365	213	6	ny	ny	NOUN
flr-365	213	7	:	:	PUNCT
flr-365	213	8	oxforduniversitypress	oxforduniversitypress	NOUN
flr-365	213	9	.	.	PUNCT
flr-365	214	1	kim	kim	PROPN
flr-365	214	2	,	,	PUNCT
flr-365	214	3	s.	s.	PROPN
flr-365	214	4	,aleven	,aleven	PROPN
flr-365	214	5	,	,	PUNCT
flr-365	214	6	v.	v.	ADP
flr-365	214	7	,&dey	,&dey	PUNCT
flr-365	214	8	,	,	PUNCT
flr-365	214	9	a.k.(2014,april	a.k.(2014,april	PROPN
flr-365	214	10	)	)	PUNCT
flr-365	214	11	.	.	PUNCT
flr-365	215	1	understandingexpert	understandingexpert	NOUN
flr-365	215	2	-	-	PUNCT
flr-365	215	3	novicedifferencesingeometryproblemsolvingtasks	novicedifferencesingeometryproblemsolvingtask	NOUN
flr-365	215	4	:	:	PUNCT
flr-365	215	5	asensor	asensor	NOUN
flr-365	215	6	-	-	PUNCT
flr-365	215	7	basedapproach	basedapproach	PROPN
flr-365	215	8	.paperpresentedatthechi'14extendedabstractsonhumanfactorsincomputingsystems	.paperpresentedatthechi'14extendedabstractsonhumanfactorsincomputingsystems	PROPN
flr-365	215	9	,	,	PUNCT
flr-365	215	10	toronto	toronto	PROPN
flr-365	215	11	,	,	PUNCT
flr-365	215	12	ontario	ontario	PROPN
flr-365	215	13	,	,	PUNCT
flr-365	215	14	canada.doi:10.1145/2559206.2581248	canada.doi:10.1145/2559206.2581248	PROPN
flr-365	215	15	knoblich	knoblich	PROPN
flr-365	215	16	,	,	PUNCT
flr-365	215	17	g.	g.	PROPN
flr-365	215	18	,ohlsson	,ohlsson	PROPN
flr-365	215	19	,	,	PUNCT
flr-365	215	20	s.	s.	PROPN
flr-365	215	21	,&raney	,&raney	PUNCT
flr-365	215	22	,	,	PUNCT
flr-365	215	23	g.e.(2001).aneyemovementstudyofinsightproblemsolving	g.e.(2001).aneyemovementstudyofinsightproblemsolve	VERB
flr-365	215	24	.	.	PUNCT
flr-365	216	1	memory&cognition,29(7),1000	memory&cognition,29(7),1000	ADJ
flr-365	216	2	-	-	PUNCT
flr-365	216	3	1009.doi:10.3758	1009.doi:10.3758	NUM
flr-365	216	4	/	/	SYM
flr-365	216	5	bf03195762	bf03195762	NOUN
flr-365	216	6	kotsopoulos	kotsopoulo	NOUN
flr-365	216	7	,	,	PUNCT
flr-365	216	8	d.	d.	PROPN
flr-365	216	9	,&lee	,&lee	PROPN
flr-365	216	10	,	,	PUNCT
flr-365	216	11	j.(2012).anaturalisticstudyofexecutivefunctionandmathematicalproblem	j.(2012).anaturalisticstudyofexecutivefunctionandmathematicalproblem	NOUN
flr-365	216	12	-	-	PUNCT
flr-365	216	13	solving	solving	NOUN
flr-365	216	14	.	.	PUNCT
flr-365	217	1	thejournalofmathematicalbehavior,31	thejournalofmathematicalbehavior,31	NOUN
flr-365	217	2	,	,	PUNCT
flr-365	217	3	196	196	NUM
flr-365	217	4	-	-	SYM
flr-365	217	5	208doi:10.1016	208doi:10.1016	NUM
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