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Psychology, 2018, 9, 2972-2983
http://www.scirp.org/journal/psych
ISSN Online: 2152-7199
ISSN Print: 2152-7180
Reading Comprehension and Eye-Tracking in
College Students: Comparison between Low-
and Middle-Skilled Readers
Alicia Abundis-Gutiérrez1,2, Víctor Hugo González-Becerra1*, Jahaziel Molina del Río1,3,
Mónica Almeida López4, Anaid Amira Villegas Ramírez1, Diana Ortiz Sánchez1,
José Rodolfo Alcázar Huerta4, Luis Alfonso Zepeda Capilla4
1Behavior and Health Research Center, University of Guadalajara-Valley’s University Center, Jalisco, México
2Laboratory of Human Behavior and Cognition, University of Guadalajara-Valley’s University Center, Jalisco, México
3Laboratory of Neuropsychology, University of Guadalajara-Valley’s University Center, Jalisco, México
4University of Guadalajara, Jalisco, México
Abstract
Efficient reading begins with text decoding and finish with comprehension.
When there is a lack of reading comprehension (RC), the person is likely un-
able to use the main information of a text in everyday life; something related
to non-functional literacy. Using eye-
tracking technique, some researchers
have found that regressions (return to previously read text) are a common
behavior during reading, and sometimes they are u
sed as a rereading strategy
to improve RC. However, the utility of regressions to improve RC depends on
the reader’s skills. Based on these data, the main purpose of this study was to
compare regressions and RC between low- and middle-skilled readers. Eigh-
teen college students completed a computerized version of a middle school
student’s RC test (ECOMPLEC-Sec) while their eye movements were record-
ed. We found a statistically marginal relation between regressions during
narrative text and text-based RC on low-skilled
readers. However, our results
indicated no relation between number of regressions and RC regardless of
level of reading competency. The necessity of new research to increase the
knowledge of RC using eye-tracking parameters was discussed.
Keywords
Eye-Tracking, Reading Comprehension, Regressions, Literacy, Educational
Psychology
1. Introduction
When someone read without comprehension (s)he could be unable to use the
How to cite this paper:
Abundis-Gutiérrez,
A
., González-Becerra, V. H., del Río, J. M.
,
López
, M. A., Ramírez, A. A. V., Sánchez,
D
. O., Huerta, J. R. A., & Capilla, L. A. Z.
(201
8). Reading Comprehen
sion and
Eye
-Tracking in College Students: Com-
pa
rison between Low- and Middle-
Skilled
Readers
.
Psychology, 9,
2972-2983.
https://doi.org/10.4236/psych.2018.915172
Received:
November 20, 2018
Accepted:
December 22, 2018
Published:
December 25, 2018
Copyright © 20
18 by authors and
Scientific
Research Publishing Inc.
This work is licensed under the Creative
Commons Attribution International
License (CC BY
4.0).
http://creativecommons.org/licenses/by/4.0/
Open Access
DOI: 10.4236/psych.2018.915172 Dec. 25, 2018 2972 Psychology
A. Abundis-Gutiérrez et al.
main information of a text in her/his own life, something related to
non-functional literacy. Illiteracy was one of the biggest world educational chal-
lenges some decades ago, however, nowadays functional literacy is one of the
main subjects in industrialized countries (UNESCO, 2005). In this regard,
México is still facing both problems: in 2010, six million of the Mexican popula-
tion were illiterate (Narro & Moctezuma, 2012) and in 2015, more than 50% of
15 years students showed a low performance in RC, mathematics and science
skills in the Program for International Student Assessment (PISA) (INEE, 2017).
Concerning reading comprehension (RC), the National Institute of Education
Assessment (INEE, initials in Spanish) found that more than 60% of the students
in last grade of elementary and middle school achieved a level related to poor RC
performance (INEE, 2016). A similar problem is found in many countries
around the world, even in countries with high level of economy and culture
(OECD, 2015).
There are different analytical alternatives in the study of reading that could
involve both simple and complex parameters in the assessment process (e.g.,
Adams & Wu, 2003; Kintsch & van Dijk, 1978; León, Escudero, & Olmos, 2012;
Rayner, 1990; Ribes, Ibáñez, & Pérez, 2014). From an overall outlook, reading
development begins with text decoding skills and finish with comprehension.
Concerning RC, almost all the analytical alternatives claim that the complexity
of readers’ skills improves from textual (literal) to inferential, as shown by read-
ers’ accuracy to answer questions about text content. The simplest skill of RC is
textual comprehension, shown when a reader is able to retrieve explicit informa-
tion from a text, for instance, answering how many dwarfs are in Snow White
Tale. In the other hand, a reader shows inferential comprehension when (s)he
finds some implicit link between the information given in various sites of the
text either by analogy, syllogism, relation cause-effect and any other cognitive
skill that support it (León, Escudero, & Olmos, 2012; OECD, 2015).
Narrative texts are the most used reading material format to teach decoding
and RC at schools. Therefore, it is to be expected that students of different edu-
cational level showed better performance in narrative comprehension than other
type of texts (Best, Floyd, & Mcnamara, 2008; Fuentes, 2009; González-Becerra,
García, Almeida, Navarro, Molina, & Ramos, 2015; Sáenz & Fuchs, 2002). Non-
etheless, it is necessary that children and youth are able to comprehend other
sources of information, like continuous texts with other literary styles (i.e., expo-
sitory, argumentative) and non-continuous texts (i.e., lists, forms, graphs, dia-
grams) (OECD, 2001).
Before eye-tracking technology, researchers ignored that some eye-movement
behavior during reading are related to text decoding and comprehending. For
instance, readers go back (his) her gaze during reading about 10% to 15% of the
time (regressions) and their average of fixation time in a word and saccade
length vary in relation to words functions (i.e., novelty, familiarity, oddity, am-
biguity, relevancy) (Rayner, 1993). Concerning these parameters of eye-movement,
readers are classified as: 1) proactive (long saccades, many regressions), and 2)
DOI: 10.4236/psych.2018.915172 2973 Psychology
A. Abundis-Gutiérrez et al.
conservative (short saccades, few regressions); the reading strategies used by
both are related to low or high level of reading experience, respectively (Koorn-
neef & Mulders, 2017; Vorstius, Radach, & Lonigan, 2014).
Booth and Weger (2013) conducted three experiments with university stu-
dents to find evidence about the role of regressions during reading. In each ex-
periment, RC and eye movement were evaluated while students read sentences
presented in different tasks. After the students read or heard a sentence, this one
remained, disappeared and/or was replaced by other stimuli (i.e., points, letters,
words with other meanings). The regressions to the remaining sentence were re-
lated to a strategy of rereading; moreover, when the regression was to a substi-
tuted sentence it was assumed that students used a deictic strategy (improve-
ment of memory by word location). Results showed that rereading strategy re-
lated to RC, suggesting that readers made regressions when they needed infor-
mation to improve their comprehension. Instead, regressions to word locations
in substituted sentences did not improve comprehension; opposite evidence to
the assumptions of deictic strategy. However, RC was higher when students did
not make regressions. Apparently, regressions help to improve RC, but they are
not a necessary condition (Barnes & Kim, 2016; Koornneef & Mulders, 2017;
Vorstius, Radach, & Lonigan, 2014).
Most of the eye-tracking research on reading is focused on textual (literal)
comprehension, and it is usually evaluated by reading sentences (Barnes & Kim,
2016; Booth & Weger, 2013; Rayner, 1993; Vorstius, Radach, & Lonigan, 2014).
On the other hand, long texts (i.e., tales, scientific reports) and inferential ques-
tions are also used for the study of RC (Koornneef & Mulders, 2017). But proac-
tive readers show higher RC than conservative readers despite the text’s length
(short or long) and the question’s complexity (literal/textual or inferential).
Regarding that, Krstić, Šoškić, Ković, & Holmqvist (2018) conducted a study
to evaluate RC with PISA test, and also the eye-movement during reading in
15-year-old students with low and high reading skills. Scores in reading speed
(words read per minute; WPM) and RC were used to classify reading skills. The
students read continuous and noncontinuous texts that were available while
questions (textual and inferential) appeared on a screen. These authors found
that students with high reading skills performed better than students with low
skills in textual and inferential comprehension questions, on both continuous
and non-continuous texts. Saccade amplitude (length) and percentage of regres-
sions were higher in students with high reading skills, as found in other studies
(Koornneef & Mulders, 2017). Difference between groups concerning their
eye-movement patterns increased in relation to complexity of questions, from
textual to inferential comprehension. Besides, readers with low skills showed
more variability in eye-movement because they tracked the whole text instead of
the parts with relevant information.
As mentioned before, most of the studies in this field record eye movement
during single sentence presentation. The main purpose of the present study was
to compare regressions and RC between low- and middle-skilled readers during
DOI: 10.4236/psych.2018.915172 2974 Psychology
A. Abundis-Gutiérrez et al.
non-stop text reading, as well as the association between these two measures.
Readers’ skills were determined by RC assessment based on PISA (León, Escu-
dero, & Olmos, 2012).
2. Method
2.1. Participants
Eighteen college students participated in the present study (4 males, mean age =
20.9 years, SD= 1.7 years). Participants were volunteers and received no com-
pensation to participate. All students came from a University Campus within a
rural area. The participants were assigned to two groups according to their level
of RC, namely: low-RC (LRC) and Middle-RC (MRC) group.
2.2. Task
To assess RC participants completed a computerized version of the
ECOMPLEC-Sec test (León, Escudero, & Olmos, 2012). The ECOMPLEC-Sec
was designed for middle school students (aged 13 - 15-years), it includes three
types of text: narrative (leisure reading), expository (acquisition of scientific of
academic knowledge), and discontinuous (search for graphic information). After
reading each text, participants completed a multiple-choice questionnaire con-
cerning the content of the text previously read, and two metacognitive questions
about the perceived difficulty of the text and the questionnaire. The narrative
text is by Julio Cortázar (1956), “Continuidad de los parques” (“Continuity of
Parks”) (541 words, 27 questions); the expository text, “Los árboles estrangula-
dores” (“Strangler trees”) (500 words, 25 questions), taken from an academic
textbook, and the discontinuous text, “Ocio” (“Leisure”), is a text with graphs
and figures regarding the young Spaniards’ leisure habits (22 questions).
In order to guarantee a good quality eye movement registration during read-
ing, the texts of the ECOMPLEC-Sec were segmented into various presentations
consisted in three text lines (calibri font size 35, line spacing of 3 cm.) written in
white font on a black background in a 15 inches laptop screen. After reading
each segment, participants were instructed to press a key to pass to the next
segment in order to continue reading until they finished the text. During ques-
tionnaire completion, the whole text was available to participants: questions ap-
peared, one by one, at the left side of the screen and the text was at the right side.
Participants reported their answers on a paper format. ECOMPLEC-Sec comple-
tion took approximately 20 minutes per participant.
As far as we know, there is no a standardized test for Mexican population in
Spanish to appraise RC in adults. Previous studies (unpublished), using the
ECOMPLEC-Sec, have shown that the same population of our sample have low
RC, despite being assessed by a test intended for 13 - 15-year-olds. Based on
these results, we consider the ECOMPLEC-Sec could be a suitable instrument to
evaluate RC on rural college students.
DOI: 10.4236/psych.2018.915172 2975 Psychology
A. Abundis-Gutiérrez et al.
2.3. Procedure
Participants completed the ECOMPLEC-Sec in the Research Center for Behavior
and Health of the University of Guadalajara. Participants were seated at ap-
proximately 60 cm from a laptop, and approximately 50 cm from a Gazepoint
GP3 eye tracker (60 Hz sampling rate; accuracy between 0.5 and 1˚). Luminance,
temperature and noise kept similar in all experimental sessions. Experimenter
explained the task and the importance to keep the posture and distance towards
the screen in order to properly register eye movements. Experimenter was
present throughout the session to visually inspect participants’ eye movement
recording in a separate screen; if needed, experimenter requested participants to
adjusts their posture until their eyes were captured by the eye tracker again. All
participants completed a 9-point calibration phase using Gaze-point calibration
system. Participants were instructed to carefully read each of the three texts and
answer to the questions following. Presentation of the texts was in the following
order: narrative, expository and discontinuous.
3. Results
Two participants were excluded from the analysis due to a difference of 2 stan-
dard deviations from the sample mean in the Global Comprehension Index.
3.1. Performance Measures
ECOMPLEC-Sec provides different scores that reflect both global and specific
aspects of RC. The global reading comprehension (RC-Global) indicates general
reading competency, but it gives no information regarding specific abilities or
difficulties during RC. ECOMPLEC-Sec uses a typical score based on a mean of
50 and SD of 20. The results reported in this study are the typical scores, based
on percentiles. Participants with Low-Reading-Comprehension (LRC) obtained
a mean RC-Global of 24.87 (SD 3.27) and Middle-Reading-Comprehension
(MRC) participants obtained 41.87 (SD 6.87). According to ECOMPLEC-Sec
qualitative ranges, these scores indicate a low-medium and a medium reading
competency for LRC and MRC groups, respectively. It is necessary to detach that
participants reading performance were compared to middle school students,
which suggests that the skills required to fully comprehend narrative, expository
and discontinuous texts are not fully developed in our sample. This is also re-
flected in the scores obtained in narrative (mean = 32.00, SD = 12.45 for
LCR-group; mean = 46.75, SD = 10.63 for MCR-group) and expository (mean =
34.37, SD = 12.02 for LCR-group; mean = 43.87, SD = 11.90 for MCR-group)
texts, which are also within a middle school medium-low range. All RC compar-
isons between LRC and MRC groups were statistically significant (see Figure 1
and Table 1).
Regarding the level of representation, MRC and LRC groups showed a signif-
icant difference between the RC Inferential and RC Textual (
t-test, p
< 0.05).
The RC Inferential score reflects mental representation skills, as well as the skill
DOI: 10.4236/psych.2018.915172 2976 Psychology
A. Abundis-Gutiérrez et al.
Figure 1. Reading Comprehension of college students using the yardstick
for students of 5th grade of middle school. Note: RC = Reading Comprehen-
sion, LRC = Low Reading Comprehension Group, MRC = Middle Reading
Comprehension Group.
Table 1. Statistical differences of LCR-Group and MCR-Group of percentiles of Reading
Comprehension and frequency of regressions during reading.
LRC
MRC
Mean
SD
Mean
SD
t
p
Global Comprehension index
24.87 3.27 41.87 6.87 −6.31 0.000
RC Narrative
32.00 12.45 46.75 10.63 −2.54 0.023
RC Expository
34.37 12.02 43.87 11.90 −1.58 0.135
RC Inferential
29.25 7.75 52.75 13.43 −4.28 0.001
RC Textual
23.50 4.17 34.25 6.73 −3.83 0.002
Narrative Regressions
33.37 16.36 52.50 26.20 −1.75 0.102
Expository Regressions
30.00 14.36 43.50 14.36 −1.88 0.081
Note: RC = Reading Comprehension, LRC = Low Reading Comprehension Group, MRC = Middle Reading
Comprehension Group.
to make inferences based on previous knowledge, and effectively integrate the
new information into previous knowledge system. On the other hand, RC Tex-
tual reflects the level of representation based on the text, which implies the use of
explicit information. Low range of this level of representation suggests a diffi-
culty in the reproduction of explicit information and lack of knowledge that ob-
struct semantic connections, causal connections and the use of information to
formulate and support arguments (León, Escudero, & Olmos, 2012). It is impor-
Reading Performance per Group
Reading Comprehension Dimensions
RC-Global
RC-Narrative
RC-Expos itive
RC-Inferential
RC-Textual
Reading Comprehension Percentil
0
20
40
60
80
100
LRC
MRC
Low
Level
Middle
Level
High
Level
DOI: 10.4236/psych.2018.915172 2977 Psychology
A. Abundis-Gutiérrez et al.
tant to note that a low scoring could also indicate a lack of interest or motiva-
tion. Differences between inferential and textual RC on narrative text were mar-
ginally significant (
t
test, p
< 0.09), and no difference was found on expository
text (see Figure 1 and Table 1).
LRC group obtained a low-medium range score in both narrative (mean = 32,
SD = 12.45) and expository (mean = 34.37, SD = 12.02) texts. For level of repre-
sentation, LRC obtained a low range on both RC Inferential (mean = 29.25, SD =
7.75) and RC textual (mean = 23.50, SD = 4.17). Besides, they showed similar
reading performance on narrative text about RC Inferential (mean = 36.5, SD =
17) and RC textual (mean = 33, SD = 10), as well as for expository RC Inferential
(mean = 37.6, SD = 15.7) and RC textual (mean = 35.2, SD = 12.7) scores. On the
other hand, MRC group obtained a medium range score on both narrative
(mean = 46.7, SD = 10.6) and expository (mean = 43.9, SD = 12) texts, as well as
on the RC Inferential (mean = 52.7, SD = 13.4) level of representation, and me-
dium-low range on RC textual (mean = 34.2, SD = 6.7) level of representation.
MRC showed a medium range for narrative RC Inferential (mean = 54.5, SD =
10.7) and medium-low for narrative RC textual (mean = 41, SD = 14.2), as well
as for expositive RC Inferential (mean = 41.6, SD = 15.4) and RC textual (mean
= 48.5, SD = 16.1) scores. Differences between global inferential and textual RC
scores were found (
t
= 3.570;
p
< 0.01), as well as a difference between narrative
inferential and textual RC scores (
t
= 2.433;
p
< 0.05).
3.2. Eye tracking Metrics: Number of Regressions
Regarding eye regression during reading, we found a mean of 39.5 (SD = 17.3) of
total regressions made during narrative (mean = 42.9, SD = 23.3) and expository
(mean = 36.7, SD = 15.5) texts reading. No differences were found between text
type (
t
= −1.613;
p
> 0.05).
LRC group made a total of 33.5 (SD = 15) regressions during narrative (mean =
33.4, SD = 16.4) and expository (mean = 30, SD = 14.4) texts reading. MRC
group made a total of 45.5 (SD = 18.2) regressions during narrative (mean =
52.5, SD = 26.2) and expository (mean = 43.5, SD = 14.4) texts reading. Marginal
difference in number of regressions during expositive text reading were found
between groups (
t
= −1.880;
p =
0.081) (see Table 2 and Figure 2).
No correlations were found between number of regressions made and
ECOMPLEC-Sec scores. Only a marginal correlation on the LRC group between
RC Textual and regressions during narrative text was found (r2 = 0.67;
p =
0.07).
4. Discussion
The main purpose of the study was to compare reading performance between
students with low reading comprehension (LRC) and middle reading compre-
hension (MRC). Reading comprehension (RC) level shown by both groups of
college students were low, and this fact is worthy of consideration because they
were assessed with an instrument designed for middle school students in their
DOI: 10.4236/psych.2018.915172 2978 Psychology
A. Abundis-Gutiérrez et al.
Table 2. Correlations of reading comprehension dimensions and types of regressions.
RC Global
Narrative Regression
Expository Regression
LRC MRC LRC MRC LRC MRC
RC Global −0.333 −0.100 −0.481 −0.205
RC Narrative 0.726* 0.377 −0.032 0.006 −0.272 0.074
RC Expository 0.245 0.649~ −0.342 0.338 −0.538 0.198
RC Inferential 0.654~ 0.839** −0.562 −0.013 −0.337 −0.167
RC Textual 0.371 0.556 0.668~ 0.074 0.438 0.105
RC Narrative Inferential 0.592 0.308 0.124 −0.465 0.023 -0.032
RC Narrative Textual 0.438 0.268 −0.219 0.319 −0.487 0.127
RC Expository Inferential 0.144 0.232 −0.519 0.571 −0.574 −0.057
RC Expository Textual 0.241 0.646~ 0.142 −0.021 −0.119 0.361
Note 1: RC = Reading Comprehension, LRC = Low Reading Comprehension Group, MRC = Middle Read-
ing Comprehension Group. Note 2: ~Marginal correlation at level 0.099; *Significant correlation at level
0.05; **Significant correlation at level 0.01.
Figure 2.
Frequency of regressions during reading per group in narrative
and expository texts. Note: LRC = Low Reading Comprehension Group,
MRC = Middle Reading Comprehension Group.
3rd grade. Significant differences between groups on Global RC, narrative RC,
and levels of representation were found. However, no relation between RC and
regression was found, regardless of level of RC competency.
Unfortunately, LRC on rural students of elementary and middle school, in
comparison to urban students, is a consequence of sociocultural disadvantages
(e.g., Backoff, 2009; Canales, 2012; Canales et al., 2014; González-Becerra et al.,
2015), something that seems to persist until university. The college students with
Regressions per Group
Regressi on-Narrative Regressi on-Expos it ory
Frequency of Regressions
0
20
40
60
80
100
LRC
MRC
DOI: 10.4236/psych.2018.915172 2979 Psychology
A. Abundis-Gutiérrez et al.
LRC and MRC of this study showed similar patterns of regressions as observed
on conservative and proactive readers, respectively (Booth & Weger, 2013;
Koornneef & Mulders, 2017; Krstić, Šoškić, Ković, & Holmqvist, 2018).
Comprehension of narrative text requires different modalities of knowledge:
conceptual, empathic, goal oriented, and metacognitive, whereas, explicative text
comprehension demands conceptual, technical/scientific, and episodic know-
ledge (León et al., 2012). Low scoring is not necessary a lack of knowledge, ra-
ther the inability to manage the previous knowledge.
The first highlight in this study was that regressions and RC do not correlate,
despite the significant difference on RC found between LRC and MRC groups,
and the evidence in the literature that better readers made more regressions.
However, in some studies, regressions frequency did not correlate with RC; in-
stead there were found other eye-tracking parameters that correlate with RC: re-
gressions to specific words, time of fixations during regressions and regressions
patterns (e.g., Barnes & Kim, 2016; Inhoff, Weger, & Radach, 2005; Krstić,
Šoškić, Ković, & Holmqvist, 2018). Additionally, there is evidence related to a
negative correlation between regressions and RC, attributed to readers who did
not need reread the text because they comprehended it with only one gaze
(Booth & Weger, 2013; Hyönä & Olson 1995; Vorstius, Radach, & Lonigan, 2014).
Our results suggest that regressions have different functions and they may
change in relation to different variables. For instance, regressions could be used
as a tool to improve RC for readers with high reading skills or it could be related
to low RC when readers with low reading skills make many regressions without
success. The regression’s functions change regarding the skills of the reader.
About that, MRC group showed more regressions and more RC, in this case re-
gressions could have been used as a strategy to improve RC. On the other hand,
the function of regressions was different in LRC group because it did not help to
improve RC; instead it might be considered a sign of confusion. In this regard,
the negative correlations between regressions and RC (more regressions, less
RC) showed by LRC group in some RC dimensions could be related to confu-
sion, although these correlations were not significant. On the other hand, there
was only one marginal correlation, showed by LRC group, between RC textual
and regressions in narrative text, evidence that could indicate that regressions
function as a helper for low skilled readers only when it combines with other va-
riables. In this specific case, regressions could be effective because LCR group
had more familiarity reading narrative texts and answering textual questions re-
trieving the explicit information available on the text.
Barnes and Kim (2016) assessed the RC of statements and eye-tracking pat-
terns of children of elementary school and adults with low reading skills, finding
no differences between groups. Authors expected better performance for adults
because of their oral language development, but they showed short saccades and
similar regressions frequency as children. Concerning those results, the function
of the regressions frequency was not clear, because it could be a rereading strat-
egy to verify comprehension or a sign of poorer comprehension. However, there
DOI: 10.4236/psych.2018.915172 2980 Psychology
A. Abundis-Gutiérrez et al.
were found that other eye-tracking parameters could be related to RC, like the
total viewing time during regressions, instead of regressions frequency or gaze
duration in a word.
Using another methodology for RC assessment, Krstić et al. (2018) found that
regressions of low-skilled readers during reading of paragraphs were more vari-
able in frequency, trajectory and length than good readers. Readers who had
high-reading-skills used regressions to find specific information to answer tex-
tual or inferential questions. On the other hand, low-skilled readers made unor-
ganized saccades to different parts of the text, some of them with few tries and
some other with many, most of the time without success.
In summary, there are distinct parameters of regressions useful for the analy-
sis of RC, but the profiles of the readers must be taken into account. Regressions
are used for rereading information that readers have missed, forgotten, or are
unsure about (Booth & Weger, 2013). Nevertheless, functions of a regression are
not the same in high or low-skilled readers and patterns of regressions change in
relation of the reader profile (Krstić et al., 2018). Hence, one of the limitations of
this study was that only used regressions frequency in the analysis of RC, para-
meter insufficient for the assessment of functions of regressions.
Ultimately, contrary to what was expected, participants from both groups,
LRC and MRC, showed a higher RC level in inferential questions than in textual
questions. Theoretically it has been assumed that answering inferential questions
is more complex than answering literal questions (León, Escudero, & Olmos,
2012; OECD, 2001), and empirically it has been found that elementary, middle
and high school students are more likely to answer literal questions than infe-
rential questions (INNE, 2017; OECD, 2015). A possible explanation of this
counterintuitive fact is that both groups were low-skilled readers and used the
inferences to improve their RC instead retrieving key information using regres-
sions. Regrettably the eye-tracking assessment in this study was limited to re-
gressions frequency, perhaps whether the trajectory, fixation time and length of
regressions were measured the explanation would had been answered. It is dis-
cussed the necessity of new research to increase the knowledge of RC using
eye-tracking parameters.
Acknowledgements
Authors thank to The Mexican Secretariat of Public Education (SEP) for sup-
porting the research presented in this article through the grants: “Support for the
Strengthening of Academic Groups 2017” (Apoyo al Fortalecimiento de Cuerpos
Académicos 2017), granted to the CA-UDG-887, and “Support for the Incorpo-
ration of Full-time Professors” (Apoyo a la Incorporación de Profesores de
Tiempo Completo/F-PROMEP-38/Rev-04, SEP-23-005), granted to Dra. Alicia
Abundis Gutiérrez.
Conflicts of Interest
The authors declare no conflicts of interest regarding the publication of this paper.
DOI: 10.4236/psych.2018.915172 2981 Psychology
A. Abundis-Gutiérrez et al.
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