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Neurocommunicative methodologies: attention and

emotion of the audiovisual story in the classroom

Mario Rajas1, Vanessa Izquierdo2, María Luisa García3

1 Universidad Rey Juan Carlos, email: mario.rajas@urjc.es
2 Garrigues, email: vanessa.izquierdo@garrigues.com
3 Universidad Complutense de Madrid, email: mluisagarcia@ccinf.ucm.es

Abstract
Audiovisual content as a learning tool has been incorporated extensively into

lecture classes. Emotion-cognition is intrinsic to the functioning of the human

brain, and therefore can explain the acquisition of knowledge and

competencies in the educational field, and more specifically, the

transformative impact on digital natives. Advances in the study of the brain

have allowed for quantitative measurement of attentional (EDL) and

emotional (EDR) terms. The objective of this article is to analyze and

evaluate the correlation between attention and emotion during the viewing of

two videos shown in a classroom in the academic space of a university. The

method consisted of recording the electrodermal activity of various groups of

Audiovisual Communication and Advertising and Public Relations students

during the viewing of the two audiovisual stories. The main results and

conclusions link characteristics of the audiovisual narrative and technical-

expressive qualities and objectives of the videos with the levels of EDL and

EDR recorded by the device and establish advanced lines of research in the

field of neuroeducation and neurocommunication.

Keywords

Neuroeducation, Audiovisual didactic, Teaching methodology, Attention,

Emotion, Electrodermal activity, Story, Audiovisual language

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1. Introduction and status of the question

Educommunication integrates two disciplines of the social and human sciences that

historically have been developed in parallel, communication and education, to form

a new pedagogical paradigm (Freire, 1970). Recognized by UNESCO in 1979,

educommunication "includes all forms of study, learning and teaching, at all levels

and in all circumstances, the history, creation, use and evaluation of

communications media as practical arts and techniques” (Morduchowicz, 1997).

Masterman refers to the possibilities of education through audiovisual content

(Masterman, 1985). Aparici (2010), meanwhile, warns of the danger of digital

technologies repeating vertical and non-participatory pedagogical models, i.e., that

greater frequency of use of audiovisual resources does not assume a real change in

learning processes. Dejaeghere (2009) and Martinez-Rodrigo & Segura Garcia

(2011) link the use of digital communications media in education to socio-cultural

and personal-emotional transformations.

Analysis of the teaching and learning process through digital audiovisual media in

the classroom can be approached from very heterogeneous perspectives, such as a

study of the educational technology involved (Garcia Garcia & Rajas, 2011), the

procedures for acquiring competences (Ferres & Piscitelli, 2012; Perez-Rodriguez

& Delgado, 2012), media literacy in digital content (Perez-Tornero & Cerda, 2011),

or in the field in which this article is developed, the effectiveness of current

technology as a methodological tool in student learning (Aranda, Sanchez-Navarro

& Tabernero, 2009, Gabelas & Marta-Lazo, 2008, Garcia Garcia & Gertrudix,

2009, Caceres, Ruiz San Roman & Brandle, 2011, Area, 2012).

Digital technology has boosted the production and distribution of online

audiovisual content through the Internet and social networks (Gonzalez Valles &

Valderrama Santome, 2014). In this media context in which visual text and sound

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predominate, the videographic format acquires special relevance as audiovisual

content support. With quantitative and qualitative exponential growth, young

people invest hours of attention in viewing videos on the web. Written text gives

way to image and sound as the predominant expressive substances in the learning

process (Buckingham, 2003).

The search to optimize educational resources used in university classrooms has led

to analyzing the attention that audiovisual content awakens in students. Equally, the

interest in understanding, from rigorous scientific approaches, the quality of

audiovisual teaching methods has raised interest in new research tools that measure

the effects of the use of video in the classroom.

In this context, neuroeducation is a discipline that combines knowledge of

neuroscience, education and psychology with the objective of understanding

learning and teaching processes and their direct link with communication (Salas,

2013). It can be stated that "neuroscience allows for an approach that complements

traditional research methods. Qualitative research offers variety and depth through

interpretation, while the quantitative counterpart offers data” (Garcia Guardia &

Llorente Barroso, 2014).

Several authors have established the direct relationship between neuroscience and

education (Cacioppo, 2002, Battro, Fischer & Lena, 2008, Hardiman, Rinne,

Gregory & Yarmolinskaya, 2012), and specifically between emotion and learning

processes (Pekrun, 1992; Fernandez Abascal, 1995, Masson, 2015). Students, as

emotional beings, learn and memorize better that which involves them, that which

demands their sensory participation and that which they love. Information, before

being processed by the cerebral cortex, passes through the limbic or emotional

brain system, in whose areas of association neural networks are produced and

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distributed, creating the abstract, ideas and the basic elements of thought (Mora,

2013).

The action of paying attention is one of the processes that most concerns teaching

activities (Anderson, 2014). Without attention from the student, the communication

involved in any act of teaching-learning achieves satisfactory results, either because

it does not end, or because it does not even occur. Attentional, emotional and

motivational processes are closely linked to the achievement of learning objectives

(Carew & Magsamen, 2010).

This article provides an approach to analyzing the effects of audiovisual media on

student learning through a neuroscientific experiment: measuring the attention

(EDL) and emotion (EDR) that a series of audiovisual resources of a narrative

nature provoke in the classroom.

Based on research on electrodermal activity and measurement of EDL and EDR

levels (Ketterer & Smith, 1982, Tranel, 2000, Dawson, Schell & Filion, 2000,

Martinez Herrador, Garrido Martín, Valdunquillo Carlón & Macaya Sanchez, 2008;

Gomez, 2013) applied to audiovisual productions, an analysis was conducted to

determine if videographic content in a didactic context can reinforce attentional and

emotional levels; therefore, its use in the classroom merges the communicative-

didactic process which concludes successfully with the acquisition of knowledge

and competency by the student.

The study of audiovisual material in the classroom from this perspective is

pertinent since attention and emotion are two cognitive processes strongly related

to memory and consequently play a key role in learning.

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2. Material and methods

The general objective of this research is to understand the attentional and emotional

efficacy of the screening of audiovisual materials in university classrooms.

Specifically, if the screening of audiovisuals during a given classroom lesson

causes variation in attention and emotion during viewing that results in an increase

in the attentional and emotional development of the class as a whole. The specific

objectives are to test diverse audiovisual materials to compare the level of attention

and emotion of each, and secondly, to test their efficacy in the communicative flow

in relation to the audiovisual character of the lesson taught.

To achieve these objectives, we have chosen to conduct an experiment from applied

neuroscientific formulations (Sutil, 2013). We are aware that we are faced with

flexible and generic indicators (Ferres and Piscitelli, 2012) and that they must be

adapted to the applicable educational situation, depending on age, objectives and

competencies required by the curricular content; therefore particular attention has

been given to the design of the experiment for a specific situation. Media

communication depends to a large extent on reception spaces, therefore we have

implemented a neuroeducative approach for a specific environment and

experiment. In this specific case, a lecture was prepared to be taught by professors

of Audiovisual Communication and Advertising and Public Relations that included

the screening of a Video A and a Video B to determine which of the two videos was

more relevant in attentional and emotional terms for the students.

The two audiovisual materials were selected and validated by a committee of

experts in audiovisual narrative and emerging technologies consisting of 7 teacher-

researchers from a general sample of 20 audiovisual productions. The videos

address, in accordance with the above regarding emerging technologies and

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education, the digital society of social networks, and include images, animation

style motion graphics, voice over and different types of musical content. The image

presents strong chromatic contrasts and different playback or timewarp speeds.

The videos validated by the committee of experts and screened were The Social

Media Revolution by Evan Kutsko (2016) - Video A - and Socialnomics by Erik

Qualman ( 2014) - Video B - both broadcasted on the YouTube platform. The

screening of the materials began with Video A, longer in duration (4:25), followed

by Video B, shorter in duration (2:22). The sampling procedure chosen was

convenient, given the commitment the method offers in cost and reliability, since

the sample was non-random.

The sample chosen consisted of 54 people between 18 and 30 years old - the most

common age of enrollment in university studies - from both sexes in a similar

proportion (50%): 26 students - Degree in Audiovisual Communication and 28

students - Degree in Advertising and Public Relations, at the Complutense

University of Madrid. The size of the sample has been validated in accordance with

recent studies and can be considered correct and reliable with respect to the

neuroscientific method performed in this research in comparison with similar

research (Martinez Herrador, 2007; Vecchiato, Cherubino, Maglione et al. 2014;

Reimann, 2012; Karmarkar, Yoon & Plassman, 2015; Orzan, Zara & Purcarea,

2015; Tapia & Martín, 2016).

Field work was conducted in April 2017 at the Faculty of Information Sciences of

the Complutense University of Madrid. The participants in this study were

informed of the purpose of the research and subsequently provided the applicable

verbal consent.

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The procedure used for recording attention and emotion of the group was the

measurement of the electrodermal activity (EDA) of the subjects. Due to reliability

and efficiency of measurement, electrodermal activity is one of the most frequently

used methods in analogous experiments (Martinez Herrador, Monge Benito &

Valduquillo, 2012, Tapia, Martin & Puentes, 2016).

The technology used to observe electrodermal activity was developed by the

scientific marketing company, Sociograph (www.sociograph.es). The technology

consists of a wristband with two diodes placed on the index and middle fingers,

which measures electrodermal activity; subsequently, the devices send the

measurements to a central calculation unit for storage and processing (Aiger,

Palacín & Cornejo, 2013).

The technology measures two parameters:

1) Tonic activity: related to attention (EDL). The unit of measurement used is the

summation of the electrodermal resistance in kilo ohms (KΩ) of all the participants.

In this article, the inverted values are shown to facilitate reading.

2) Phasic activity: related to emotion (EDR). The unit of measurement is the

arithmetic mean of the electrodermal resistance in kilo ohms (KΩ) of all the

participants. As a note, the machine simply detects the presence and intensity of

emotion, but not the content or quality of it, research objectives that extend beyond

the methodological framework of this experiment.

For the use of results, cross-sectional statistical models and techniques applicable

to the study of time series were employed.

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Over the course of the class, the videos were screened separately to ensure each

viewing was independent of the other – Video A was broadcast first, and after a

sixty second pause, Video B was broadcast. The university professor taught a class

that developed the content related to the videographic materials before and after the

broadcasts, content that was part of the theme of the two subjects.

The sessions were also recorded with the objective of detecting potential deviations

in terms of instructions received by the students from the teacher, performance of

the task in general, correct broadcasting of the videos and development of the

session.

3. Analysis and results

First, in relation to the attentional function (EDL), it should be noted that the model

utilized demonstrates significant autocorrelation (0.838 in 16 delays, p value

0.000), which indicates the dependence of subsequent values on previous values.

However, this data is applicable to the study of attention (EDL), but not to the

study of emotion, as due to the sudden nature of emotion it does not demonstrate

dependence.

3.1. Analysis of attention (EDL)

The average attention level demonstrated during the screening of Video A, longer

in duration, maintained at an average attention measurement of -666.051 KΩ with a

standard deviation of 16.926 KΩ. For the screening of Video B, -671.400 KΩ with

a standard deviation of 5.488 KΩ. Given that the exposed value measures the

inverse resistance, it can be stated, firstly, that more attention was paid on average

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to the screening of the longer video than to the viewing of the shorter video.

However, it is important to emphasize that the attentional dispersion was much

higher in the case of longer video. I.e., more attention was paid during Video A on

average, but that attention showed more ups and downs, which could be a relevant

factor in the learning process. The difference was also statistically significant (T

test of difference between averages, p value 0.000 per p value in Levene Test

0.000).

However, an analysis of the structure of the attention during the screening, as can

be seen in the following figure (up to the red line of Video A, then Video B), allows

extraction of other significant data.

Figure 1. EDL recording (Attention) during broadcast of the videos (-ΣKΩ )

Source: compiled by the author

The broadcast of Video A maintains - with slight ups and downs - attention for the

first two minutes, at which time attention drops very intensely almost until the end -

four minutes -, where a turning point occurs during which it increases again but

without recovering the levels prior to the descent. I.e., during the broadcast of

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almost half of the video - from minute two to four -, the students paid a low level of

attention. Additionally, during this segment, the level of attention was significantly

lower than during the course of the screening of Video B.

However, the structure of the attention given to Video B demonstrates a different

evolution. It increases slightly during the first 20 seconds, notably declines during

the next 30 seconds, and increases again - up to minute 1:20 - until recovering and

maintaining the levels prior to the descent until the end of the screening.

Analysis of the attention of both videos must also be based on the study of the rate

of change of the variable. This data reveals moments of increase and decrease in

attention in response to the stimuli deployed.

The following figure shows the rate of change in EDL of the two pieces - equally,

Video A extends to the red line and then Video B begins.

Figure 2. Rate of Change in EDL (-KΩ)

Source: compiled by the author

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As shown, the recording of the rate of change in EDL demonstrates notable

attentional alterations which are described in detail in the following table.

Table 1. EDL increments in rate of change

Temporary

segment

∑KΩ Description

Video A

00:13-00:21 1.30 Audio: electronic music. Alters tones on a constant basis.

Image: on white background appears overlaid: “Welcome to the

revolution. Over 50% of the population is under 30 years old. 96%

of millennials have joined a social network.”

00:39-00:49 1.1480 Audio: electronic music continues.

Image: on white background appears overlaid: “Years to reach 50

millions users. Radio. 38 years. TV. 13 years. Internet. 4 years.”

00:59-01:10 2.0274 Audio: electronic music continues.

Image: on white background appears overlaid: “We don´t have a

choice on whether we do social media, the question is how well we

do it.”

01:34-01:43 1.4315 Audio: electronic music continues. A drum sample is added.

Image: appears overlaid: “Twitter. What´s happening? Ashton

Kutcher and Britney Spears have more Facebook followers than the

population of Sweden, Israel, Switzerland, Ireland, Norway and

Panama.”

02:28-02:34 1.2178 Audio: electronic music continues. A repetitive and unintelligible

voice sound is added.

Image: on white background appears overlaid: “If you were paid $1

for every article posted on Wikipedia you would earn $1,712.32 per

hour. There are over 200,000,000 blogs.”

03:18-03:23 1.5969 Audio: electronic music continues. The voice does not continue.

Image: on white background appears an image of a TV overlaid and

the text: “Only 18% of traditional TV campaigns generate a positive

ROI. 90% of people skip ads via TiVo/DVR.”

03:36-03:41 1.3615 Audio: electronic music continues. The same voice indicated above

is added.

Image: on a search box similar to that of Google appears the

writing: “We no longer search for the news. The news find us. We

no longer search for products and services.”

03:50-04:19 1.4053 Audio: electronic music continues. The voice does not continue.

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Image: on white background appears overlaid, “Successful

companies in social media act more like Dale Carnegie and less like

Mad Men. Listening first, selling second.”

Video B

00:09-00:13 0.9599 Audio: electronic music.

Image: on blue background appears overlaid: “World Population. 1.

China, 2. Facebook, 3. India, 4. Tencent, 5. WhastApp, 6. United

States, 7. Google+, 8. Indonesia, 9. LinkedIn, 10. Twitter.”

00:50-00:54 1.299 Audio: electronic music.

Image: on blue background appears overlaid: “1 in 5 divorces

involve Social Media. What happens in Vegas stays in Facebook.”

00:59-01:03 0.8391 Audio: electronic music.

Image: on blue background, an image of a mobile phone. On the

phone, an image of a group taking a selfie, and above in white text,

it reads, "Selfie is now a word in Webster."

01:10-01:14 0.7393 Audio: electronic music continues. A repetitive and unintelligible

voice is added.

Image: on white background appears various shields from American

universities.

01:56-02:22 0.6203 Audio: electronic music continues and the voice is repetitive and

unintelligible.

Image: on blue background Oreo cookies and traces of milk can be

seen. The text states: “Real time marketing and newsjacking are

becoming staples for savvy brands. Goodbye 4 Ps of marketing:

product, place, price promotion.”

Source: compiled by the author

Considering times when attentional increase occurs as a whole, a certain common

pattern can be seen. The background, whether white or blue, focuses attention on

the graphic overlay elements. The text on the image background stands out.

Regarding the text, large headings stood out with data that was surprising and

unknown to the audience a priori, and attracted attention due to showing very high

statistics in comparison with other numbers - for example, the relationship between

the population of certain countries and inhabitants of the social networks.

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8 attentional increases above 0.5 KΩ were detected during the screening of Video

A, and 5 during the course of Video B, which indicate on average an increase in

attention in the case of the first video every 33 seconds and in the case of the

second every 29 seconds.

3.2. Analysis of emotion (EDR)

The average level of emotion recorded during the broadcast of Video A was 0.1489

with a standard deviation of 0.08280. The average value for Video B was 0.1572

with a standard deviation of 0.08724. Therefore, it is important to note, in the first

instance, the similarity of the emotional values of both screenings. Therefore, this

indicates a similar display of average emotional intensity. Additionally, a T test of

difference between averages was conducted, which ruled out significant differences

- p value 0.352 with p value 0.282 in the Levene test for equality of variances.

However, the fact that there are no relevant differences in terms of average

intensity does not indicate the same homogeneity in emotional peaks. These are

moments in which, in response to a certain stimulus, the audience responded

suddenly with a peak of intensity.

The responses, as shown in the following figure, are produced on four occasions

during the screening of Video A, and also on four other occasions during Video B,

the difference being that in this case the peaks are much closer to one another.

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Figure 3. EDR of the screenings (KΩ)

Source: compiled by the author

The times indicated, of a sudden and independent character with respect to the

previous content, are described in the auditory and visual plan in the following

table.

Table 2. EDR increases (KΩ)

Temporary

segment

KΩ Description

Video A

01:07 0.3993 Audio: electronic music; a voice repeats: “Right here, right now.”

Image: a list appears in columns with the most populated

countries in black text with the following highlighted in blue text:

“3. Facebook.”

02:01 0.4436 Audio: electronic music; a repetitive voice, this time

unintelligible.

Image: on black background, white and blue text that states,

"Instead they are distributing: ereaders, ipads, tablets. The social

media revolution 2016.”

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03:19 1.0307 Audio: electronic music, this time without a voice.

Image: on white background, image of a TV and the text, "Only

18% of traditional TV campaigns generate a positive ROI."

Suddenly the text, "90% of people skip ads via TiVo/DVR,"

appears.

03:37 0.4556 Audio: electronic music; the same unintelligible voice as before is

added.

Image: "We no longer search for the news. The news finds us," is

written on a search box similar to that of Google.

Video B

00:10 0.3987 Audio: electronic music. There is the sound effect of a typewriter.

Image: a classification on blue background is displayed: “World

population. 1. China, 2. Facebook.”

00:51 0.413 Audio: electronic music. There is also a sound effect of broken

glass.

Image: on blue background appears an overlay: “1 in 5 divorces

involve Social Media.”

01:00 0.4745 Audio: electronic music. There is no voice or sound effect.

Image: on blue background, the image of a mobile phone is

formed; a group of people taking a selfie is seen. White text states,

"Selfie is now a Word in Webster."

01:06 0.4223 Audio: electronic music; a repetitive voice states, "Right here,

right now."

Image: on a white background, black text is shown that states,

"Every second 2 new members join LinkedIn."

Source: compiled by the author

As with attentional increases, emotional increases of a more sudden and brief

character are seen above the electronic music that keeps the viewer in a state of

alert, in this case more frequent use of voice and sound effects that highlight or

amplify the meaning of the image. The text is also shown as a large headline

intended to provoke surprise in the audience.

It is important to note also, coinciding with the above, that in the case of Video A,

two of the four times during which emotional content was generated took place in

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sections of increased attention. The same situation is found in three of the four

times during the screening of Video B.

Therefore, emotional content was generated more frequently in sections of

increased attention. However, a related issue is whether there is a significant

relationship between emotional and attentional increase, or formulated in another

way, if attentional increase indicates emotional increase or not – and vice versa.

The tests performed -Pearson correlations - do not allow for this relationship to be

significantly validated (p value 0.517), therefore this link is not emphasized as

significant.

3.3. Proposal for the development of an audiovisual performance factor.

As Mora (2013) emphasizes, attention and emotion are two fundamental cognitive

processes in the learning process. Following this approach, we propose the

establishment of a comparative performance index for audiovisual materials viewed

in the classroom.

To accomplish this, the average rate of change and the average EDR at N(0.1) are

normalized, as shown in the following table.

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Table 3. Average EDL rate of change and Average EDR normalized to N(0.1).

EDL (Average Rate of Change) EDR (Average EDR)

Data

Source

Standardized Rate

N(0.1)

Data

Source

Standardized Rate

N(0.1)

Video A

Average -0.1058 -0.0314 0.1489 -0.0348

Standard

Deviation 0.5163 0.9792 0.828 0.9812

Video B

Average -0.059 0.057 0.1572 0.0634

Standard

Deviation 0.5473 1.038 0.8724 1.0339

Source: compiled by the author

These indexes are considered in terms of attention and emotion equivalence.

Likewise, the value of the standard deviation is studied to indiscriminately consider

the intrinsic variation in the average values of each of the videos, the IPerformance

correlation coefficient.

IPerformance = EDL (Average + 2*Std. Dev.) + EDR (Average + 2*Std. Dev.).

In this way, the performance for Video A would obtain a value of 3.8546 and

4.2642 for Video B, which would indicate a higher general value for Video B.

Video B achieves a higher score in EDL - where it decreases, but less than Video A

-, and it also obtains a somewhat higher value in average EDR - although it also has

greater dispersion -, which definitively describes why Video B obtained a

significantly higher score.

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4. Conclusions

When comparing the attention (EDL) of students during a university class on two

videos, The Social Media Revolution by Evan Kutsko (2016) and Socialnomics by

Erik Qualman (2014), the following conclusions were drawn.

In relation to the objectives proposed in the research, in the sense of understanding

attentional and emotional efficacy of the screening of audiovisual materials in the

university classroom by comparing the levels of attention and emotion of the

different materials used, there is less attention regarding Video B, shorter in

duration, although the attentional dispersion was greater. Video A, longer in

duration, maintains attention with slight ups and downs during the first two

minutes. Subsequently, there is a moment in which attention decreases very

intensely until the end, with lower attention in the final two minutes than

throughout the course of Video B. This fact indicates that the order of the videos

and their total duration influenced the attention process, since they deal with two

subjects that are very similar in content and form, which excludes other audiovisual

language and narrative variables in the case of having used different recording or

post-production techniques.

On average, attentional increases differed depending on the duration of the video:

during the long duration video every 33 seconds and during the short duration

video every 29 seconds.

In particular, there is an overall increase in attention when text overlaid on an

image appears on a blue or white background. I.e., this type of expressive resource

increases the attention of the students, equal to what was observed in the tables

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above, a variety of surprising data due to the unsuspected nature both quantitatively

and qualitatively, producing the same result where more attention is concerned.

On the other hand, when analyzing emotion, the values of both screenings were

similar: the Pearson correlation with a value of 0.517 confirms that there is no

relationship between attention and emotion in the two videos.

Similar to that which occurred with attention, sudden and short increases in

emotion, which coincided with the use of electronic music, kept the students in a

state of alert, in this case the use of voice and sound effects was more common, as

explained in the experiment, to highlight the different informative and emotional

messages intended to reach the spectators through the story.

Finally, it is important to note that IPerformance demonstrates that Video B obtains

a higher value than Video A.

According to this data, it can be concluded that neuroeducational analysis can yield

significant results regarding which audiovisual materials may be the most effective

in provoking attention and emotion in the classroom, and when its efficacy or

measurement is positive or negative.

After comparing and contrasting the results of this research, we propose to open

discussion regarding the influence of the order of the screening of the videos by

performing an experiment which begins with the screening of Video B, shorter in

duration, followed by Video A, longer in duration, and likewise, if the merging of

different expressive substances - audiovisual resources that bring into play other

languages of image and sound - improves attention and emotion. Similarly, the

possibility of crossing data with other research methods will be assessed - in

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addition to video recording of the expressions made by the students - such as the

use of a survey or focus group and other neuroscientific measurement systems

including eye-tracking and microexpression analysis software.

The results obtained in this work refer to a given context, therefore it would be of

scientific interest to create the experience with other types of learners in other

knowledge areas, with different ages or other geographical environments, as well as

to measure the delivery of content type lecture classes given in conjunction with

audiovisual materials. This study presents relevant results given the lack of

previous analysis regarding this type of experiment with audiovisual content in

university classrooms, but its weakness is in the context; it is essential not to over

emphasize the results, and to propose new experiments that result in greater global

knowledge of the subject of study.

Therefore, neuroscientific experiments applied to the use of audiovisual resources

in the classroom is a field of study that can provide relevant data and interpretations

in the scope of teaching methodologies: attention and emotion are two fundamental

aspects of the process of teaching a classroom or virtual class, and knowledge and

use of these concepts can be applied to the development of audiovisual content and

to the improvement of the way in which the communicative act of teaching and

learning is produced and shared, the didactic story, ultimately.

Thus, for example, content analysis facilitates obtainment of valuable data when

evaluating the narrative and aesthetic structure of videos, or in another area of

equal interest, a comparison of EDL and EDR of the same content taught

exclusively orally -lecture-, with the support of visual presentations, or in

audiovisual form with a video, among other fascinating lines of research in the

interrelated field of education, communication and neuroscience.

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6. Key ideas

The study interrelates the use of audiovisual resources in the classroom with the

analysis of attention and emotion in a group of communication sciences

(Advertising and Public Relations and Audiovisual Communication) students. The

introduction of various visual and sound stimuli - such as key words in motion

graphics and specific references in the voice over -, as well as the temporal

construction of stimuli displayed by the videos produced significant changes in

EDL and EDR values.

Therefore, we highlight the possibility that neuroscientific experiments can be

applied to the use of audiovisual resources, in the narrative and aesthetic

construction of these materials to obtain higher levels of attention and emotion, as

well as in the integration in university classrooms with other types of content and

how it can provide relevant data and interpretations in the field of teaching

methodologies, both in the classroom and in virtual classes, with the intention of

improving the teaching-learning process in the era of digital content.