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EXPLORATION OF PHRASAL VERBS IN ELT TEXTBOOKS: 
A CORPUS-BASED ANALYSIS OF LOWER SECONDARY 

LEVEL BANGLADESHI BOOKS 
 

Naywaz Sharif Shubha 

University of Dhaka, Dhaka, Bangladesh  
 

naywaz01sharif@gmail.com   
 

ABSTRACT 

The current study aims at exploring the usage of the Phrasal Verbs in the lower secondary 
Bangladeshi ELT textbooks which are prescribed by the Government of Bangladesh at 
national education levels. The methodological approach continues in this study based on the 
corpus tools and related analysis on the topic of Phrasal Verbs usage in those textbooks. The 
phrasal verbs that are found in the textbooks are extracted from the textbooks; their 
frequency distributions are analyzed, and finally checked with the two most authentic 
corpus of the English Language - The British National Corpus (BNC) and Corpus of 
Contemporary American English (COCA). Alongside, deriving the top fifteen Phrasal Verbs 
in the textbook corpus with their significant values; the relative positions to the two 
reference corpora and other corpus-related scores of the phrasal verbs are compared, with 
reference to the study of Liu (2011), which are also included in the advanced research of 
PHaVE List (2015). The results find that the Phrasal Verbs used in the selected textbooks are 
quite irrelevant to the two standard big corpora. Especially the corpus scores vary greatly 
when compared with the reference corpora. Finally, based on the findings some remarks and 
implications are prescribed for pedagogical purposes. The current study would be the first 
one that examines the Bangladeshi Lower Secondary ELT textbooks assisted by the corpus 
approach.  

Keywords: Bangladeshi Textbooks, Corpus Analysis, English Language Teaching, Lower-
Secondary, Phrasal Verbs.  

 

INTRODUCTION  

Multi-word verbs or PVs are found numerously in English language usage. Often it 
seems problematic for second language (L2) learners, and it needs extra effort and special 
focus. The underlying reasons can be derived from research studies about the difficulty in 
acquiring the Phrasal Verbs (hereon, PVS) in the L2, for example, exploring why PVs as 
morphological structures are difficult. In definitive terms- PVs are a group of words 
consisting of a verb that combines two adverbs or prepositions (Mayor, 2009). In regular 
grammar books, the PVs are defined as multi-word verbs (Quirk, 2010). The most effective 
identifying characteristics of PVs are that they combine a preposition or any article with the 
verb. PVs are defined by scholars as morphological structures carrying a verb and adverb 

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particle (Richards & Schmidt, 2013). Some others defined PVs in the same way consisting of 
a verb and adverb particles or prepositions (Broukal et al., 1990).  

Scholars even find that the PV sometimes becomes difficult to classify them into a 
definite morphological category and deciding their relation to the semantics (Cappelle et al., 
2010). In a broader overview, the PVs can be divided into three types of multi-word 
expressions or the verbs-the first one is PVs in general, the second category is the verbs 
which are called prepositional verbs, and the last one in the category of verbs that are both 
mixture of phrasal and prepositional verbs but used as a single category; also the term PV 
denotes three types altogether (Walter, 2008). Many other scholars have identified the 
different classification of multi-word PVs, mostly have derived three (Armstrong, 2004), and 
some others describe them as two types (Jackendoff, 2012). Most of these scholars have 
defined different classifications from each other based on the characteristics and the 
function of the verbs.  

Biber et al. (2002) differentiate among different kinds of PVs and also additionally 
explain the underlying reasons for the variance in patterns and meaning that brings the 
difference between them. Also, the PV might belong to other categories such as prepositions, 
words, or rather multi-word verbs, depending on the criteria that might include it in a 
separate category. But it has been also suggested that the differentiation between these 
categories arises due to grammatical characteristics (Gardner & Davies, 2007). In the English 
language, there exist different types of PVs, the first type has two parts in them, it’s a verb 
adjoined with adverb particles. These adverb particles are fixed in numbers and some 
scholars even included these smallest particles within a shortlist (MacGregor, 2006).  

The research area in the sector of multiple-expressions is thriving day by day (Gardner 
& Davies, 2007). In the English language, PVs are often found in common usage, and they are 
considered as a part of proficiency in the L2 acquisition process (Garnier & Schmitt, 2015). 
But this acquisition process of PVs for the L2 learners is often very difficult in the context of 
the English language (Siyanova & Schmitt, 2007).  

The importance of PVs and multi-word expressions in English SLA rises due to the high 
frequency in English (Darwin & Gray, 1999). It has been suggested that the L2  competency 
grows if a learner has stronger competence over the PVs which might help him achieve the 
target goals in the L2 acquisition (Garnier & Schmitt, 2015). Some researchers have 
suggested PVs are indicators of the lexical richness of a language (Gardner & Davies, 2007). 
This argument can also be regarded as the key point encountering the question of why PVs 
should be a core element to acquire native-like competence in the English language (Wray & 
Perkins, 2000).   

As already mentioned in the earlier paragraph that PV might become a problematic 
factor in the language acquisition of English. Some scholars like Siyanova and Schmitt, (2007) 
also suggest that in the L2 acquisition process, PVs can be framed as a problematic issue. The 
answer to the question of why the difficulty arises is because the PVs are very much 
recurrently used in the English language (White, 2012). Other researchers have found that 
in the L2 acquisition process PVs are found among the most difficult ones to learn and to 
teach. (Boers & Lindstromberg, 2008) As the problem of the PVs have made their existence 
as an obstacle to the learning process of the L2 learners, there have also been attempts to 

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explore the cause of the problem. Some research studies recently attempted to solve the 
problem of mixing teaching methods with cognitive linguistics (Lee, 2012). Some other 
researchers like White (2012), have also mixed not only the cognitive aspects but also the 
sociocultural framework with the teaching aspects.    

The important part is that not simply the difficulties, rather PVs are considered one of 
the most difficult aspects which can hinder the learning process (Gilquin, 2015). The 
evolution of the PVs might explain a reason for the difficulty because the existence of the PVs 
is conceptualized as the historical evolution of the IE (Indo European) language family. Some 
scholars suggest that multi-word verbs mainly exist for semantic relations (Claridge, 2000). 
Many researchers have selected and elaborated on some reasons why PVs in an L2 are quite 
difficult to learn, one of the important reasons is the distinctive variance found in the 
structures and semantics of the PVs (Kurtyka, 2001). Scholars have related meaning aspects 
to the PVs because many a time as idiomaticity arises from them (Claridge, 2000).    

Another reason and which is very much complicated is that the PV occurs with different 
words and expressions; after being separated from the multi-words’ original form. The 
nature of the PVs being combined with different types of words makes it difficult to be 
learned by L2 learners. And also, it confuses the L2 learners of English (Side, 1990). Li et al. 
(2003) have found that language learners from foreign countries often show a tendency in 
avoiding the usage of PVs. Because most of the time they might not be familiar with 
combinations and separation contexts of the multi-words usage. On the other hand, 
researchers also have suggested that native speakers continuously give rise to new PVs in 
their language usage, and it happens unconsciously (Armstrong, 2004). Some research 
studies are found stating that they found about 33% of the whole words are PVs (Li et al., 
2003).   

The trend of corpus-based studies is not something new in the study of linguistics and 
related research. Thus the importance of corpus-based studies cannot be denied in the L2 
acquisition process. Especially, the field of the corpus-based approach to L2 acquisition is 
broader than any other field. For example, it has been observed by several scholars finding 
out frequent verbs in different corpus analyzed with corpora tools. Some of the most 
authentic studies showed some hundred highest occurring PVs in the British National 
Corpus (BNC), which has been represented in a smaller list from the whole Corpus. Other 
studies included the COCA corpus as a reference corpus to find out the most frequent PVs. In 
applied fields, relating to these kinds of studies, many of the recent ones on the PVs 
cooperated with dictionary-making procedures, published for the L2 learners of English.  

Popular study materials found on PVs include a large number of entries, for example, 
about 5000 PVs are included in Longman and about 6000 PVs in Cambridge. The huge 
number of entries clearly shows that the process tried to include all the existing forms of the 
verbs, although, in reality, it's an impossible task. It is also not possible to enlist all the words 
that exist in a language.  

There have been recent studies on the PVs in the British National Corpus, finding PVs 
from both written and spoken sample text (both formal and informal usage) and found near 
about hundred and sixty PVs comprising 50% of the usage in the BNC and the usage list could 
be extended up to 100 verbs in BNC (Gardner & Davies, 2007). Liu (2011) gives 150 most 

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occurring PVs found in the COCA, in addition to BNC; showing that both British and American 
English share the same mostly used PVs in English.    

Both of these research studies have been criticized for finding similar frequency lists 
as they fall short of pedagogical implications, meaning the studies do not relate to the 
polysemous nature of the PVs (Garnier & Schmitt, 2015). Also, the researchers, Garnier & 
Schmitt (2015) added to their critical description that these 200 words relate to at least 700 
other semantic extensions and each of these carrying at least six different meanings on 
average, and these facts are very important for further implications. For example, the 
learning load of particular 200 PVs should be extensively emphasized over any other 
vocabulary or multi-word expressions in English (Garnier & Schmitt, 2015). More 
importantly,  these findings are more useful for designing proper schemes which can benefit 
the L2 learners and teachers. Garnier & Schmitt (2015) used the same verbs which were 
found (about 150) by Liu (2011) but added extensive meaning implications in the 
pedagogical aims. So, in their study, Garnier & Schmitt (2015) combined a list from previous 
research by Liu (2011) and Gardner & Davies (2007), and called it PHaVE list; adding 
different meaning senses to the verbs for L2 teaching purposes.     

Another study by Trebits (2009) derived the 25 PVs that were mostly used in the EU 
documents’ Corpus, however, half of these PVs in that list are missing in the PHaVE list 
(Garnier & Schmitt, 2015). The study by Trebits (2009) might not be conducive for the ESL 
learner context as most of those documents of EU had formal language usage, more 
specifically those official and secretariat language doesn’t relate to daily usage in real life.  

Many other studies have been done on the topic of multi-word verbs, on their 

structures, semantic explorations, patterns in the learners’ contexts etc. based on different 

methodologies and purposes (Abdolvahed Zarifi & Mukundan, 2012;  Abdolvahed Zarifi & 

Mukundan, 2013a; Abdolvahed Zarifi & Mukundan, 2013b; Abdolvahed Zarifi & Mukundan, 

2014; Abdolvahed Zarifi & Mukundan, 2014; Alavi & Rajabpoor, 2015; Abdul Rahman & Abid, 

2014; A Zarifi & Mukundan, 2015; El-Dakhs, 2016;  Jacobsen, 2013; Jahedi & Mukundan, 

2015; Ke, 2017; Tsai, 2015; YAMAMURA, 2015). Most of the studies on this topic are from 

the linguistic point of view or analysis, which were both done with basic research and 

intellectual efforts as well as involving different corpus methods and analysis. However, a 

larger number of studies on the PVs should have been more focused on pedagogical 

implications, for the convenience of L2 teaching purposes. But a relatively small number of 

studies are found on the topic of multi-word verbs or PVs in L2 acquisition, which focuses on 

exploring the difficulties in the acquisition of the target language. Additionally, research 

studies can also strongly suggest the elements and materials in L2 teaching and what to 

include or not in the syllabus design and curriculum. Thus the current study focuses on the 
textbooks PVs (on learning material) rather than directly on the learner’s contexts.   

  

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METHODS 

Method & Data Collection   

Two English Language Teaching (ELT) books published and distributed by the 

Government of Bangladesh were chosen for comparing the phrasal verbs with the past 

studies. The two books are mainly prescribed for the grade 6 and 7 in Bangladeshi High 

School Context. It is to mention that grade 6 and 7 is considered to be a junior grade at High 

School level. After the completion of the last stage of the primary levels at Grade 5, with the 
examination of PSC (Primary School Certificate Examination); the children are promoted to 

the junior secondary level in the high schools. Then after grades 6 and 7, in grade 8 another 

examination (Junior Secondary School Certificate Examination-JSC) is taken to take the 

students to senior Secondary School levels. So, in the context of Bangladesh, grades 6 and 7 

are the very first stage of the Secondary School stage, which comes after the PSC exam which 

means that they have successfully completed primary education. Thus the current study 

selected only the two books of the beginning High School level which starts soon after the 

completion of the primary levels.   

Collecting the Textbooks   

The selected two books needed to be in electronic format for the making of the corpus, 

as the corpus tools needed. Firstly, the two books were downloaded from the government 
website which provided free distribution of the electronic version of the books, freely 

available at http://nctb.gov.bd/site. The books started freely distributing in printed versions 

after 2010, and have been made available free on the internet since 2015.  

 These English literature books are prescribed for the education of the grade 6 and 7 in 

higher secondary levels. Both of these books are designed to teach English to non-native 

Bangla-speaking students of grades 6 and 7. The learning materials include different types 

of activities, selected English literary, historical, poetic texts, essays to read, comprehend and 

learn.  

Conversion of the Texts and Further Data Cleaning Process  

For the creation of the text corpus, the PDF versions of the textbooks were then 

transcribed into plain text format using an online software pdf2go (available online at 
https://www.pdf2go.com/pdf-to-text). This process included uploading the PDF to the 

server and then converting them into text formats. After the conversion was completed, the 

texts were downloaded to the local computer drive storage. The plain text version makes it 

easy to conduct searches with corpus tools.  

Primarily, the text versions of the books contained all the words and unidentifiable 

figures including the cover pages, introductory sections, and preface, commentary sections, 

headings on each page, back matter, etc. It is more reasonable that these unnecessary texts 

should not be included in the corpus; thus the broken text, unnecessary punctuation, 

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preliminary front matter texts, introductory sections, preface, and other unnecessary 

sections were excluded from the text data. This cleaning process greatly made the text 

clearer for the corpus to read and find the desirable patterns for the study.  

Corpus Software, Compilation, and Further Corpus Search  

With the plain text versions, the textbook corpus was then created using the Sketch 

Engine online software. Sketch Engine is a popular software program that is widely used in 

corpus linguistics. At present, it has got hundreds of users worldwide.  

With the available software, the previously downloaded texts were then compiled into 

a single corpus containing two separate text files (each of the whole books were converted 

into single plain text files). After the compilation, the corpus is ready to use for further 

analysis. The corpus had a total of 45,949 words and 57,010 token types. Additionally, it 

contained 4,690 lemmas and also had a total of 55 tags (POS and others).      

This current study would firstly find out what are the phrasal verbs that have been used 
in this corpus (along with particle distributions). The second step would be deriving the top 

15 lemmas of the PVs. Then the third step would find out if all the phrasal verbs in the 

textbook corpus come in the BNC, COCA (from the list of Liu, 2011) and match with the 

relative frequency in (COCA), Per million Word Measures (PMWs), etc. Then lastly the 

phrasal verbs used mostly would be compared to the list created by Garnier & Schmitt 

(2015). It would be clearer if the national curriculum planner of the textbooks has used any 

guidelines regarding the fact these books are designed for the EFL contexts.   

RESULTS & DISCUSSIONS  

Frequency Distribution of the lemma verbs and Particles  

The extensive search in the whole corpus availed us with a total of 127 Phrasal Verb 

occurrences found in the whole corpus. Out of these 127 PVs occurrences, about 120 phrasal 

verbs are the lexical verbs, which is 94% of the total phrasal verbs found in the current 

corpus. About 7 of the verbs (which is about 6%) here are not lexical verbs, which are of 

course PVs with functional category. These verbs (about 7 of the 127 PVs) are as the 

following- ‘is over’ occurs 4 times and ‘was/were over’ occurs 2 times, and additionally 

‘do’(+ing)+around comes in the list 1 time.    
In tables A and B, 120 phrasal verbs have been represented, which are only lexical of 

types. However, these 120 phrasal verbs are always found with certain adverbial particles 

or prepositions. In this present corpus search, the number of the adverbial particles is 

limited. The represented 120 phrasal verbs always occur with only 9 particles, which are- 

down, out, up, around, away, on, along, off, and across. These particles always adjoin with the 

lexical verb lemmas and are used as the phrasal verbs in the English language contexts. The 

results are presented in the following Table A and B separately.  

Table A. represents the 74 phrasal verbs from the total of 120 phrasal verbs, where 

each of the lemma and their corresponding verb particle has been separated into rows and 

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columns. Each of the tables A and B clearly shows how the different adverbial particles are 

distributed with the lemma verbs in the real language usage in the corpus. All the verbs in 

tables A and B are ordered in alphabetical order and the particles are ordered by frequency 

measures, from higher to lower frequency.   

Table 1. The frequency distribution of the Phrasal Verbs and related particles in the textbook corpus  

Part A. - The list of total used verbs found in the textbook’s corpus (Only Lexical verbs ) 

Verbs down out up around away  on along across Total  

 act  4       4 

 add   1      1 

 climb   1      1 

 come 5 2 1      8 

 cut 1        1 

 draw   1      1 

 fill  1 1      2 

 find  4       4 

 get   8      8 

 give   4  3    7 

 go 1 5 1 1 1 1   10 

 grow   1      1 

 heat   2      2 

 look 1 5 4      10 

 lump       1  1 

 make   1      1 

 pick   4      4 

 put   1   1  1 3 

 reach   1      1 

 read  1       1 

 run   1 1 1    3 

         Total 74 

Table A holds two important lexical lemma verbs. The verbs with the second-highest 

frequency are in this table, with the absolute hits (frequency) 10, for the verbs ‘go’ and ‘look’. 

Other high-frequency verbs are also found, with the frequency of 8 (‘come’ and ‘get’).  The 

second Table B. has also got some significant distributions. It contains the highest occurring 

verb ‘write down’ at a frequency of 11. Additionally, it has got numerous least occurring 
verbs with the frequency 1.     

The tables clearly show that the most used verb particle with all the phrasal verbs is 

‘up’, found the highest number of times occurring with the phrasal verb lemmas. After that, 

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the verb particle ‘out’ is used mostly according to distribution and counts. And in the 3rd 

position, the particle ‘down’ is used mostly, which is again apparent from the frequency 

distribution of the particles in both the tables. The least used for particles in the tables that 

are found include- along, across, and off. However, this table only helps to show the 

distribution and the particle usage with the lexical phrasal verbs, but for getting deeper 

insights into the textbook corpus, a more detailed representation is necessary.   

Table 2. The frequency distribution of the Phrasal Verbs and related particles in the textbook corpus   

Part B. - The list of total used verbs found in the textbook’s corpus (Only Lexical verbs )  

Verbs down out up around away  along off Total  

 set   6     6 

 sit 2  3     5 

 take  2      2 

 throw 1    1   2 

 wake   4     4 

 walk   1 1    2 

 warm   3     3 

 write 11       11 

calm  1       1 

burst   1      1 

jump   1      1 

shout   1      1 

play     1    1 

cool  1       1 

charge       1  1 

see        1 1 

issue   1      1 

stand    1     1 

stretch   1      1 

     Total 46 

Top 15 lexical phrasal Verbs  

The next search result was regarding the top 15 lexical phrasal verbs lemma in the corpus. This 

finding is a bit more important and more focused on statistical and numerical significance with the 

corpus data. The findings are represented in Table C., which represents the data regarding the 

Phrasal Verbs which are distributed into different categories like the number of hits, the number of 

hits per million tokens, percentage of the whole corpus, and lastly percentage amongst all the phrasal 

verbs in textbooks. These current findings clearly show which are the top 15 most frequent phrasal 

verbs in the textbook corpus.     

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Table 3. The top fifteen (15) lexical PVs (lemmas) and their data in the current textbook corpus  

Top 15 Lexical (Phrasal) Verbs (Lemma) in the Corpus 

Verbs     
Number of 

hits 

Number of 
hits per 
million 
tokens 

Per cent of 
the whole 

corpus 

Percentage 
amongst all the 
Phrasal Verbs 
in Textbooks 

 write 

+AdvP.  

 11 192.95 0.02% 8.73% 

 go  10 175.41 0.02% 7.94% 

 look  10 175.41 0.02% 7.94% 

 come  8 140.33 0.01% 6.35% 

 get  8 140.33 0.01% 6.35% 

 give  7 122.79 0.01% 5.56% 

 set  6 105.24 0.01% 4.76% 

 sit  5 87.7 0.01% 3.97% 

 act  4 70.16 0.01% 3.17% 

 find  4 70.16 0.01% 3.17% 

 pick  4 70.16 0.01% 3.17% 

 wake  4 70.16 0.01% 3.17% 

 put  3 52.62 0.01% 2.38% 

 run  3 52.62 0.01% 2.38% 

warm    3 52.62 0.01% 2.38% 

Total     90     71.43% 

In Table C., the most frequent phrasal verb lemma in the corpus found is “write”, which occurs 

11 times. The second and the third position is occupied by the verbs go and look.  All three phrasal 

verbs in the first three positions clearly show that the language-related verbs are of directive usage 

or related to commands. These three (3) phrasal verbs comprise 25% of all the occurrences of the 

phrasal verbs that are used in the whole textbook corpus.  other phrasal verbs coming just 

after these are- come, get, give, set and, sit. These lexical lemmas of the phrasal verbs 

combine with other particles that occur several times in the corpus and make a higher 

position than the rest ones.  

The top 15 most frequent phrasal verbs are found a total of 90 times in frequency, out 

of 120 lexical phrasal verbs. This means that these top 15 lexical phrasal verbs comprise 

almost 71% of all the phrasal verbs in the whole textbook corpus. (see, Table C) This also 

implies that the most frequent phrasal verbs are dominating the usage in real contexts.   

These top 15 most used PVs make a small number in the percentage of the whole 
corpus, for example, the top three (3) most frequent phrasal verbs take 0.02% of the whole 

corpus, and the rest of the lexical verbs takes 0.01%. If all the numbers in percentage are added 

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together, even then the most frequent phrasal verbs in this list take only 0.18% or approximately 

0.20% of the whole corpus. This means that even the highest frequent phrasal verbs take a very small 

portion of the whole corpus texts.   

It is to note that this table doesn't indicate which adverbial particles separately come 

with which of the lexical lemmas. Rather only the lexical verb lemmas with indefinite 

adverbial particles (with their exact number of hits) are represented in the table.   

PVs (separately) with particles and their inclusion in BNC and COCA   

The next search results are more crucial and give a clearer picture of the PVs that are 

used in the selected textbooks' corpus. In these findings, the phrasal verbs are separately 

represented with each of the adverbial particles, which means the results that we found 

earlier as the lemma verbs, would now be separately listed for each of the particles that were 

adjoined with those lemmas.  

Table D depicts the data of the current findings. It is to be noted that the phrasal verbs 
have been listed here without the measure of frequencies. Every phrasal verb that was found 

in different inflicted or passive forms in the earlier list now contains only the base form.  

Consequently, these current findings include only one form (for each PVs) from several 

occurrences of the phrasal verbs in the corpus texts.  

Table 4. The total PVs (58) in the current textbook corpus and their inclusion in two standard corpora  

All the PVs found in the textbooks 

a) PVs listed in COCA & BNC (27)  b. PVs not in COCA & BNC (31)  

 come down  go out   
 go away run away climb up  

 
come out come up 

 

 heat up  run up 
calm 
down  

 get up   go around put on   give away run around burst out  

 write down   made up put up  warm up  cut down jump out  

 look out  go down fill out    read out   put across  shout out  

 
lookup  go up stand up   walk-up  reach up  

play 
around  

 
look down   give up take out   walk around add up 

cool 
down  

 
sit down  wake up  go on  throw away draw up 

charge 
along  

 sit up  find out  pick up    throwdown lump along  see off  

 set up  grow up   act out  fill up  issue out  

 
   

 

  

stretch 
out  

note: This inclusion-exclusion are based on Liu’s list (2011)  

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It can be seen from Table D that the table is divided into two parts, one part containing the 

phrasal verbs listed in COCA and BNC, and the other containing the verbs that are not 

inserted in the COCA and BNC. This table contains only 58 lexical phrasal verbs which make 

the total 120 occurrences in different forms and shapes; because of the inflection or passive 

structures as already mentioned. So to be precise, the textbook corpus actually contains not 

more than 58 lexical phrasal verbs that are found in different contexts and frequencies.    

Out of these 58 phrasal verbs, 27 phrasal verbs (46.55%) are found in the COCA and 

BNC corpus, and the rest of the 31 verbs (53.45%) are not found in COCA and BNC. It is to be 

noted that the inclusion-exclusion in this table is based on Liu’s list (2011). These findings 

clearly show that there exists a large number of phrasal verbs (31), which is 64% of the 58 

PVs in the textbook corpus might be of less importance in academic contexts. Even this 

number points to the fact that there exist deficiencies in the textbook design. These findings 

might be utterly disappointing and also intriguing, which stimulates the study's interest to 

find even if the included phrasal verbs (46.55%) (in the BNC and COCA) have been correctly used in 

the language contexts. To find the results, the phrasal verbs in BNC&COCA have to be compared with 

exact positions to a reference corpus. The next interesting findings clearly can answer these queries.  

Comparison with COCA  

The next findings regarding the phrasal verbs were mainly comparison to a larger 

reference corpus, COCA. The reference corpus, COCA, is the short form used for the 

Contemporary Corpus of American English, and it's a large corpus containing millions of 

words. The reason for choosing this corpus (COCA) is referring to the study of Liu (2011), 

where 150 phrasal verbs with relative order to COCA, with their frequencies and position, 

are found.  

 As already the table D. lists the PVs that are included in both BNC and COCA, those 27 

PVs can be easily compared to find out the positions, frequencies, and per million tokens 

measures for the verbs. The current findings illustrate the following results in Table E.   

Table E clearly shows the phrasal verbs are chronologically ordered by frequency 

measures. The additional columns include positions and frequencies, and the rest columns 
come with the number of hits per million tokens in reference to COCA. Thus the special 

findings in this table are the specific numerical data extracted from COCA for the targeted 27 

phrasal verbs.   

Some significant results are found in this current table. The topmost occurring PVs in 

the textbook corpus-‘write down’ has got a very disappointing value in the number of hits 

per million tokens. In the textbook corpus, it is the most popular phrasal verb with a score 

of 192.95 (hits per million words), but very disappointingly it has got a poor score of 9.04 

(hits per million words) in COCA. This result is also supported by the position of the verb in 

both of the corpus- whereas it’s got the first position in the textbook corpus; it comes at the 

119th place in COCA (from the 150 PVs list by Liu (2011).   

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Other results’ in these findings are also disappointing. Only three phrasal verbs from 

the top ten list in COCA come in these 27 phrasal verbs, which are- go out, act out and come 

out. The only similarity found in both the corpus is for the PV ‘go out. It has got the sixth 

position in the textbook corpus, and it is also in the same position in COCA.   

However, for other PVs, comparing the positions does not match with the scores with 

the COCA at all. Even the numbers of hits per million tokens of the top five (5) phrasal verbs 

in the textbook corpus (Table- E.) are very dissimilar and disappointing.  

Table 5. The Comparison between the PVs of the Textbook and the COCA  

The Textbook Corpus COCA 

Position PVs Frequency 
Number of hits 

per million tokens 
Number of hits 

per million tokens 
Position 

1 write down    11 192.95 9.04 119 

2 get up   8 140.33 47.41 23 

3 set up  6 105.24 65.11 11 

4 Come down  5 87.7 34.58 31 

5 look out  5 87.7 23.97 46 

6 go out  5 87.7 70.77 8 

7 look up  4 70.16 50.24 20 

8 Give up  4 70.16 56 11 16 

9 pick up    4 70.16 89.95 2 

10 wake up   4 70.16 29.54 35 

11 find out  4 70.16 80.43 6 

13 sit up  3 52.62 12.83 93 

16 Come Out  2 35.08 72.51 7 

17 sit down  2 35.08 47.43 22 

19 take out   2 35.08 34.1 24 

20 Come Up  1 17.54 54.97 4 

21 look down   1 17.54 24.96 41 

22 go around 1 17.54 17.96 115 

24 go away 1 17.54 54.43 26 

25 go on 1 17.54 148.33 1 

26 go up 1 17.54 33.23 33 

30 grow up 1 17.54 69.36 10 

33 Made up 1 17.54 54.43 17 

39 Put On  1 17.54 14.08 87 

40 Put Up 1 17.54 24.49 43 

45  Fill out  1 17.54 8.46 121 

57 stand up  1 17.54 36.46 30 

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Even the results clearly show that the phrasal verbs which are positioned very later in 

the reference corpus- COCA, are mostly found in the textbook corpus at an early position, 

which can greatly harm the learners to be acquainted with the most useful phrasal verbs 

usage. The only pleasant finding in these results is that out of these 27 phrasal verbs in the 

textbook corpus, 81% of the verbs (22 PVs) come within the top 50 positions in COCA. 

Although this might not be fruitful in pedagogy, at least it asserts that these phrasal verbs 

would be of some use for ESL students.    

Table 6. The missing PVs in COCA and BNC with related corpus data      

Absolute Frequency & Frequency per Million tokens for PVs (31) (*not enlisted in the 
BNC and COCA) 

S. PVs f. nPMT S. PVs f. 
nPM
T 

S. PVs f. nPMT 

14 give away  3 52.62 
3
5 

run up 1 17.54 
4
9 

burst out  1 17.54 

15 warm up 3 52.62 
3
6 

run 
around 

1 17.54 
5
0 

jump out  1 17.54 

18 heat up 2 35.08 
3
7 

cut down 1 17.54 
5
1 

shout out  1 17.54 

23 go down 1 17.54 
3
8 

 put 
across  

1 17.54 
5
2 

play 
around  

1 17.54 

24 go away 1 17.54 
4
1 

 reach up  1 17.54 
5
3 

cool 
down  

1 17.54 

27  read out  1 17.54 
4
2 

add up 1 17.54 
5
4 

charge 
along  

1 17.54 

28 walk up 1 17.54 
4
3 

draw up 1 17.54 
5
5 

see off  1 17.54 

29 
walk 
around 

1 17.54 
4
4 

lump 
along  

1 17.54 
5
6 

issue out  1 17.54 

31 
throw 
away 

1 17.54 
4
6 

Fill up  1 17.54 
5
8 

strech 
out  

1 17.54 

32 
throw 
down 

1 17.54 
4
7 

Climb up  1 17.54     

34 run away 1 17.54 
4
8 

calm 
down  

1 17.54 
        

S.= Position in the Textbook Corpus, PVs= Phrasal Verbs, f.= Frequency, nPMT= number 
per million tokens 

Alongside these findings, some other findings were extracted from the corpus for the 
PVs that were missing in BNC and COCA previously. This was done to understand the 
remaining phrasal verb’s position and compare them with the standard reference corpus. 
The derived information and the related data have been summarized in Table F.  Some 

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significant numerical figures are found in Table F, especially in the score of nPMT (number 
per million tokens), at least three phrasal verbs (positions- 14,15,18) have significant scores. 
These words are not found in the previous list of Liu (2011) which had included a total of 
150 phrasal verbs in that list with positions to the BNC and COCA, but their scores show that 
they have been used in significant numbers in the current corpus texts. However, they are 
not so important according to the inclusion list of Liu (2011) in the two standard corpora.   

Lastly, the comparison of the textbook PVs was compared to the list made by Garnier 
& Schmitt (2015), which is also popularly known as the PHaVE list. It is quite evident from 
the comparison between Liu (2011)  and Garnier & Schmitt (2015) that both of the lists 
include the same verbs, thus there was no need to compare again. The PHaVE list had 
extensive exemplification of the verbs as an additional feature.  

CONCLUSION   

The current study discovers that a greater number of PVs used in the selected textbook 
corpus are not found in the standard BNC and COCA corpora. Additionally, the frequencies 
and per million measures for the PVs are also not satisfactory in terms of comparison with 
the standard values. Consequently, many unnecessary PVs are found in those textbooks, and 
also many important ones are missing. These findings can be implemented in the textbooks’ 
next editions and future designs, and the study can be broadened to greater extensions with 
further funding and research interests for implementation in the national education levels.    

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