Two skills that need improvement during the university stage are self-regulated learning (SRL) and the reading of scientific texts. The objective of this study is to assess SRL, the profile of scientific reading, and the relationship between these variables in a sample of 1,253 students pursuing a Bachelor’s degree in Early Childhood and Primary Education. A descriptive and cross-sectional selective study was designed. A digital questionnaire was administered, including socio-demographic data, the range of scientific articles read in a semester, and the adapted SRSI-SR instrument to measure SRL. The results revealed significant differences in the mean SRL score in favour of women but not by the degree studied or the academic year. The range of scientific readings was less than three scientific articles per semester for more than half of the sample, with better results in women and second-year students. All scores on the adapted SRSI-SR scale improved with an increase in scientific reading. These findings suggest that increasing scientific reading in education students can enhance their self-regulated learning skills, also promoting critical thinking and voluntary selection of scientific readings by students.
Article Details
How to Cite
Torrijos-Muelas, M., González-Víllora, S., & Bodoque-Osma, A.-R. (2024). Self-regulated learning and scientific reading in pre-service teachers. An exploratory study. Ocnos. Journal of reading research, 23(2). https://doi.org/10.18239/ocnos_2024.23.2.421
Torrijos-Muelas, Bodoque-Osma, and González-Víllora: Self-regulated Learning and Scientific Reading in Pre-service Teachers. An Exploratory
Study
Introduction
Higher Education represents a significant change in the cognition of those who pursue
it, as the development of independent, self-directed and self-regulated learning skills
is required to achieve academic success (). In contrast to secondary education, where the use of one textbook per subject is
common, university subjects usually offer extensive lists of bibliographical references,
including numerous scientific articles. This change requires university students to
acquire a new reading profile that enables them to read academic texts fluently and
regularly, and to take charge of their own learning.
Self-regulated learning (SRL) refers to cognitive, metacognitive, motivational and
emotional processes that students initiate themselves to achieve their learning goals
(). This approach involves setting and adjusting goals, planning and monitoring the
learning process, evaluating performance and using adaptive strategies to improve
learning outcomes. In the university context, SRL is intended to lead to meaningful
and sustainable learning beyond the academy, becoming a lifelong process throughout
students’ professional lives ().
SRL is presented as a critical element for academic success and scientific activities
such as research, problem solving and reasoning (). Trainees must not only monitor and regulate their learning process, but also set
goals, choose strategies, and monitor their performance and goals (). Improving self-regulation of the learning process contributes to the development
of metacognitive skills, academic performance, reflective processes, self-assessment
and student motivation (). Furthermore, proficiency in self-regulated learning has been associated with lower
levels of anxiety and burnout in university students ().
On the other hand, reading scientific articles is an important challenge for future
teachers in their learning process. Although reading skills have been developed since
primary school, engaging with academic texts requires familiarity with technical terminology
and sophisticated analysis of results (; ). Academic reading goes beyond the mere reception of information; it requires an
active stance to analyse, reflect and interpret data, thus contributing to students’
scientific literacy process ().
Despite the importance of academic reading, future teachers have been shown to be
immature readers, with a preference for novels, fiction and commercial works, and
little commitment to academic reading, except in the area of social networks (; ; ; ). While social media can be effective in encouraging reading, it does not develop
the same skills needed to interact with scientific articles. For example, life science
students have difficulty understanding the structure and technical language of these
texts and focus on superficial information compared to more experienced students (). In this way, scientific literacy becomes a key process for strengthening the critical
capacity needed to understand and analyse texts specific to the field of study (). Furthermore, students tend to rely on the interpretation provided in scientific
texts rather than seeking and analysing evidence for themselves ().
Reading habits create a different pattern of attitudes between readers and non-readers,
reflecting greater reading comprehension and analytical skills in the former (). However, data on the frequency and reading habits of higher education students
show inconsistent patterns, with low percentages of regular readers and a greater
preference for occasional reading or even no reading habits (; ). In terms of reading scientific texts, the engagement of university students is
generally limited (). In addition, it is necessary not only to increase the frequency of reading, but
also to deepen the understanding of expository texts. Research focusing on scientific
thinking and literacy highlights the importance of developing scientific literacy
during teacher training in faculties of education ().
Objectives
Scientific reading should be an indispensable part of the academic curriculum, especially
in the case of education students, who will be trainers and transmitters of scientific
knowledge. This knowledge is complemented by the autonomous learning outcomes expected
of those completing a stage of higher education. It is from this combination that
this article derives its main objectives:
- To describe the learning self-regulation skills of a sample of Bachelor of Education
students and to explore this characteristic in relation to the socio-demographic data
of the participants.
- To find out the range of scientific reading done by Bachelor of Education students
during a four-month period, by comparing the sample in groups according to the socio-demographic
information collected.
- To explore whether there is a difference in the ability to self-regulate learning
according to the range of scientific reading over a four-month period in the research
sample.
Method
Design of the research
According to , this research proposes a non-experimental study using a selective descriptive strategy,
in this particular case recording the behaviour of the sample studied. In terms of
the methodological component, the research is descriptive in that it seeks to detail
specific characteristics of the target population through the estimation of sample
parameters (). As the variables were measured at a single point in time and in a group of participants
with common characteristics (degree studied and university), but it is unknown whether
the study variables are correlated, the design is cross-sectional (; ).
Participants
The sample consisted of 1,253 students from a Spanish public university enrolled in
a Bachelor's degree in Early Infant Education (32.7%) and a Bachelor’s degree in Primary
Education (67.3%). Participation in research represents 34.12% of the total number
of students in these programmes at the sampled university. The Bachelor's degree in
Primary Education has more than twice as many groups as the Bachelor’s degree in Infant
Education and 50% more enrolments. The mean age of the participants is 20.78 years
(range 18-49 years; SD = 3.257). Men accounted for 24.3% of those surveyed, while
74.9% said they were women. These data correspond to the gender ratio of the population
in these grades, where 71.45% are female and 28.54% are male. Although the university
does not provide information on other gender identifications, the survey includes
options such as 'prefer not to answer' and 'other gender', with a low percentage of
responses received that were excluded from further analysis due to lack of representativeness.
Almost 60% of the sample entered university with a bachelor's degree in social sciences
or humanities, and less than 1% of the prospective teachers had a previous university
degree (table 1).
Table 1Characteristics of the sample
Variable
Options
%
Gender identified
Woman
74.9
Man
24.3
I would rather not answer
.8
Transgender
.1
Grade
Infant education
32.7
Primary education
67.3
Year
First year
40.2
Second year
29.9
Third year
20.4
Fourth year
9.4
Previous studies leading to admission to the university
GCE
Social Science
39.5
Humanities
19.2
Technology
4.5
Health Sciences
17.4
Arts
1.8
Music
.1
Higher level training cycle
15.7
Admission exam >25 years
.7
Admission exam >45 years
.1
3-year bachelor’s degree
.3
Year
.4
Other Older Schemes
.2
Procedure
In this study, the main variables were the number of articles read in the previous
semester and the self-regulation learning skills of education students. Data collection
was deliberately conducted in the second semester to ensure that first year students
would provide data on their university reading. Despite the fact that final year students
complete the final year dissertation, the faculties surveyed schedule this subject
in the second semester, thus avoiding a distortion of the scientific reading data
related to the completion of the theoretical framework of the final year dissertation.
Participants were selected by convenience sampling during compulsory classes in the
first two weeks of the second semester. Consent was obtained from the responsible
teacher to use 20 minutes of the session, and equipment with internet access was provided
to ensure equal access to participation. Ethical approval was obtained prior to data
collection under reference CEIS-631156-N6M6, and participants gave informed consent.
The online survey was securely stored on university servers, and those who chose not
to participate remained in the classroom without written consent.
Instrument
An electronic questionnaire (appendix A) was designed to collect data using internet-connected devices. The tool began by
emphasising that participation was voluntary and anonymous, and asked again for permission
to start the survey. Socio-demographic data were collected, including gender, level
of education (early childhood or primary), years since first enrolling in the level
(hereinafter “year”), and previous studies that allowed access to university.
Participants were then asked to specify the number of scientific articles they had
read in the previous four months, choosing from six options: none, one or two, three
or four, five to seven, eight to ten and more than ten articles. This closed choice
was based on previous literature (Alcocer-Vázquez & Zapata-González, 2018, ). In addition, scientific reading may be considered irrelevant by respondents, resulting
in inaccurate responses to an open-ended question (). The decision to include six response options is intended to avoid central tendency
response bias ().
Finally, the questionnaire included Spanish adaptation for university students of the Self-Regulation Strategy Inventory−Self-Report (SRSI-SR)) data-toggle="popover" data-trigger="hover" data-reff="#ref11-421" title="Cleary, 2006" class="type-bibr">Cleary, 2006). The adapted SRSI-SR is a valid measure for assessing students' self-regulation
learning strategies, which has already been used in the context of higher education
(). The tool (appendix A), with an adaptive subscale with three factors (Factor II: Organisation of the environment;
Factor III: Information seeking; Factor IV: Task organisation) and a maladaptive subscale
with only one factor (Factor I: Inadequate regulation habits), assesses self-regulation
strategies for learning. The 18 items are answered on a Likert-type frequency scale
(never, rarely, almost always, always). The result of the inventory can be used as
an indicator of the general learning self-regulation ability of education students
with good reliability indices (FI: inappropriate regulation habits [ = .725]; FII: organisation of the environment [ = .816]; FIII: information seeking [ = .791]; FIV: task organisation [ = .775]; total scale Cronbach’s alpha of .81) ().
Data analysis
Non-parametric tests for data analysis were performed using the SPSS statistical package
(v.29).
SRL scores were calculated on the SRSI-SR scale, adapted from . A scale of zero to ten points was established for both the total scale score and
for the maladaptive (FI) and adaptive (FII, FIII and FIV) subscales in order to conduct
a descriptive exploration of the variable.
Average SRL scores were compared according to groups defined by socio-demographic
variables. The variables gender (male and female values) and grade (infant & primary
education values) were examined using the Mann-Whitney test. The data for the variable
year (values: first, second, third and fourth) were analysed using the Kruskall-Wallis
test.
As with the previous variable, the range of scientific articles was examined descriptively
using contingency tables with the percentages observed for each range of articles
read per categorical demographic variable (gender, year and class). The hypothesis
of independence of the variables was then tested using Pearson’s test. The comparison of the range of articles read with the socio-demographic variables
was made using the same statistical tests described for the comparison with SRL.
Finally, possible differences in SRL scale scores were examined as a function of the
range of scientific articles read by the participants. As this was a comparison of
six independent groups (each level of the variable ‘range of articles read’), Kruskall-Wallis
one-factor ANOVA was used.
To assess the effect size in analyses showing significant differences involving a
dichotomous categorical variable that creates two independent groups (gender, grade),
the A statistics proposed by Vargha et al. was used. (2000). This approach makes it possible
to estimate the magnitude of the effect without assuming normal distributions or equality
of variances and is characterised by its intuitive interpretation: the closer it is
to 1, the greater the effect of the variable under consideration. It should be noted
that this A statistic corresponds to the area under the COR curve provided in the SPSS statistical package ) data-toggle="popover" data-trigger="hover" data-reff="#ref26-421" title="Pardo & San-Martín, 2015" class="type-bibr">Pardo & San-Martín, 2015). To use this statistic when analyses are significant but involve non-dichotomous
categorical variables, post-hoc pairwise comparison tests were used to create the dichotomy with that pair.
A correlation test between the variable self-regulation of learning and scientific
reading is also included.
Results
The database containing the original results collected, an extended and expanded analysis
of them, and the appendix to this publication can be found in the open science repository
Zenodo (https://zenodo.org) at: https://doi.org/10.5281/zenodo.10512218.
Self-regulated learning (SRL)
Table 2 shows the means for the total sample of Bachelor of Teacher Education students for
the three possible scores offered by the adapted SRSI-SR scale.
Table 2Mean SRL factor scores for the sample of N = 1253
Note: *FI was converted to its inverse values as it is a maladaptive factor. FI = Inadequate
regulatory habits (maladaptive subscale); FII: Organisation of the environment; FIII:
Information seeking; FIV = Organisation of the activity; Adaptive subscale = FII,
FIII, FIV. M = mean. SD = Standard deviation.
Table 3 shows the descriptive analysis of the socio-demographic variables in relation to
the score of each factor and subscale in SRL according to the adapted SRSI-SR instrument.
Table 3.Descriptive statistics in SRL (adapted SRSI-SR) by socio-demographic variables
Gender
Grade
Year
Male N =304
Female N = 938
Infant education N = 408
Primary education N = 834
Year 1 N = 501
Year 2 N = 370
Year 3 N = 254
Year 4 N = 117
Punctuation
M
DT
M
DT
M
DT
M
DT
M
DT
M
DT
M
DT
M
DT
Total
6.32
.896
6.68
.902
6.63
.949
6.57
.895
6.59
.878
6.59
.892
6.62
.959
6.5
1.026
Maladaptive subscale
4.64
1.127
4.45
1.181
4.44
1.203
4.52
1.153
4.45
1.178
4.46
1.136
4.57
1.156
4.66
1.261
Adaptive subscale
6.88
1.001
7.42
1.002
7.35
1.073
7.26
1.01
7.31
.976
7.31
1.024
7.31
1.098
7.11
1.111
FII
7.76
1.180
8.15
1.150
8.11
1.235
8.03
1.135
8.1
1.125
8.15
1.139
8.00
1.234
7.75
1.258
FIII
5.98
1.502
6.35
1.514
6.27
1.558
6.26
1.500
6.33
1.444
6.16
1.503
6.26
1.651
6.25
1.577
FIV
6.89
1.470
7.76
1.411
7.69
1.444
7.48
1.483
7.5
1.422
7.62
1.477
7.66
1.484
7.33
1.631
Note: FI = Inadequate regulatory habits (maladaptive subscale); FII: Organisation of the
environment; FIII: Information seeking; FIV = Organisation of the activity; Adaptive
subscale = FII, FIII, FIV. M = ; SD = Standard deviation.
Significant group differences were found for the gender variable for all scores provided
by the adapted SRSI-SR scale. All differences have moderate effect sizes ranging from
A = .548 to A = .665 (table 4).
Table 4Mann-Whitney test between SRL scores (SRSI-SR) and socio-demographic variables
Punctuation
Variable
Mann-Whitney U test
Next
A
Total
Gender
109432.500
<.001
.616
Year
163533.000
.266
Maladaptive subscale
Gender
129019.000
.012
.548
Year
162734.000
.209
Adaptive subscale
Yender
99266.000
<.001
.652
Year
159488.000
.073
FII
Gender
113840.500
<.001
.601
Year
160150.500
.851
FIII
Gender
123957.500
<.001
.565
Year
169040.000
.851
FIV
Gender
95505.500
<.001
.665
Year
156619.500
.022
.540
Note: Maladaptive subscale = FI (inappropriate regulatory habits); FII: Organisation of
the environment; FIII: Information seeking; FIV = Organisation of the activity; Adaptive
subscale = FII, FIII, FIV; Significant results are shown in bold. For significant
results, only the effect size (A) was calculated
When the sample was examined for the course variable (table 5), a significant difference was only found for the FII (p = .014). The pairwise comparison
shows that this difference is between the first year group and the fourth year group
(p = .029) and between the fourth year group and the second year group (p = .011).
Both differences show a moderate effect size with values of .586 and .592 for the
A statistics (table 6).
Table 5Kruskal-Wallis test (grouping variable: course)
SRL score (SRSI-SR)
M
lf
Next
Total
.668
3
.881
Maladaptive subscale
4.695
3
.196
Adaptive subscale
2.662
3
.447
FII
10.679
3
.014
FIII
2.109
3
.550
FIV
4.345
3
.227
Note: Maladaptive subscale = FI (inappropriate regulatory habits); Adaptive subscale =
FII, FIII, FIV; FII: Organisation of the environment; FIII: Information search; IVF
= Organisation of the activity
Note: *Significance level adjusted by the Bonferroni correction was used. For significant
results, only the effect size (A) was calculated.
Scientific reading in teacher education students
The response percentages found for the variable range of articles read by the sample
of prospective teachers were obtained (figure 1).
Figure 1Percentage response to a variable range of articles read in the last four months
The comparison of the groups generated from the responses to the socio-demographic
variables (table 7) does not show significant differences in science reading by grade studied (early
childhood vs. primary education) but does show significant differences by gender (p = .015), with a moderate effect size (A = .545) in favour of females. Similarly, the Kruskal-Wallis analysis revealed significant
differences in reading range according to the grade studied (p < .001). Post-hoc pairwise tests show differences between first year students and their peers in the
next year (p = .000) and between second year students and third year students (p = .000). Both differences have a moderate effect size (table 8).
Table 7Tests for difference in rank of articles read by socio-demographic variables
Variable
N
Statistics
lf
Next
A
Mann-Whitney U test
Chi-square (Kruskal-Walis)
Gender
1242
129608.000
.015
.545
Grade
1253
165300.000
--
--
.203
--
Year
1253
--
56.068
3
<.001
Note: Statistics from two different tests are combined to simplify the presentation of
results; empty boxes do not apply to the variable analysed. Only the effect size (A)
was calculated for the statistically significant outcome.
Note: *Significance values adjusted by Bonferroni correction are used. Only the effect
size (A) was calculated for significant comparisons.
Self-regulated learning in relation to the range of articles read
The analysis of the means of the individual subscales of the SRSI-SR shows significant
differences in all of them (table 9).
Table 9Results of the Kruskal-Wallis test between SRL and the number of articles read.
Punctuation
N
Test statistics
lf
Next
Total
1253
54.9128
5
<.001
Maladaptive subscale
1253
26.536
5
<.001
Adaptive subscale
1253
50.896
5
<.001
FII
1253
12.147
5
.033
FIII
1253
47.310
5
<.001
FIV
1253
32.501
5
<.001
Note: Maladaptive subscale = FI (inappropriate regulatory habits); Adaptive subscale =
FII, FIII, FIV; FII: Organisation of the environment; FIII: Information search; IVF
= Organisation of the activity
The subsequent pairwise comparison shows which reading ranges on each scale of the
adapted SRSI-SR instrument show significant differences (table 10).
Table 10Post-hoc pairwise comparisons
SRL score (adapted SRSI-SR)
Total
Maladaptive
Adaptive
FII
FIII
FIV
Comparisons
Stat.
Next
A
Stat.
Next
A
Stat.
Next
A
Stat.
Next
A
Stat.
Next
A
Stat.
Next
A
None – 1-2
-82.173
.300
-47.009
1.000
-77.931
.410
-48.257
1.000
-59.646
1.000
-90.746
.147
None – 3-4
-157.234
.000
.626
-92.447
.134
.574
-152.784
.000
.621
-91.371
.146
.572
-140.625
.001
.614
-117.553
.014
.595
None – 5-7
-172.860
.000
.639
-81.595
.469
-175.181
.000
.640
-81.032
.486
-177.337
.000
.642
-141.671
.003
.614
None – 8-10
-179.482
.001
.644
-155.934
.007
.621
-152.031
.011
.625
-71.062
1.000
-136.320
.031
.606
-151.562
.010
.619
None – > 10
-257.343
.000
.697
-167.074
.000
.630
-246.397
.000
.687
-120.635
.027
.593
-217.971
.000
.671
-208.525
.000
.661
1-2 – 3-4
-75.061
.172
-45.438
1.000
-74.853
.176
-43.114
1.000
-80.980
.085
-26.808
1.000
1-2 – 5-7
-90.687
.084
-34.585
1.000
-97.250
.044
.581
-32.775
1.000
-117.692
.004
.594
-50.925
1.000
1-2 – 8-10
-97.309
.239
-108.925
.098
-74.100
.997
-22.805
1.000
-76.675
.812
-60.817
1.000
1-2 – > 10
-175.171
.000
.639
-120-065
.005
.597
-168.466
.000
.632
-72.378
.451
-158.325
.000
.625
-117.779
.007
.593
3-4 – 5-7
-15.626
1.000
10.852
1.000
-22.397
1.000
10.339
1.000
-36.712
1.000
-24.118
1.000
3-4 – 8-10
-22.248
1.000
-63.487
1.000
.753
1.000
20.309
1.000
4.305
1.000
-34.009
1.000
3-4 – > 10
-100.110
.049
.582
-74.627
.404
-93.613
.089
-29.264
1.000
-77.345
.317
-90.971
.108
5-7 – 8-10
-6.622
1.000
-74.339
1.000
23.150
1.000
9.970
1.000
41.017
1.000
-9.891
1.000
5-7 – > 10
-84.483
.319
-85.480
.281
-71.216
.783
-39.603
1.000
-40.634
1.000
-66.854
1.000
8-10 – > 10
-77.861
1.000
-11.140
1.000
-94.366
.459
-49.574
1.000
-81.650
.867
-56.962
1.000
Note: Statistics = Test statistics for pairwise comparisons; Next = Significance values
adjusted by Bonferroni correction are used.; Only the effect size (A) was calculated
for significant comparisons. Significant results are shown in bold.
Discussion
The present study focused data collection on two main variables: self-regulated learning
skills (SRL) and the reading of academic articles and texts by university students
preparing to become teachers.
Self-regulated learning (SRL)
In the context of the first proposed objective, the assessment of SRL in Infant or
Primary Education teacher students, the scores on the adapted SRSI-SR instrument range
from six to eight on a scale of zero to ten, reflecting medium to high scores. The
maladaptive subscale shows lower scores that do not reach the pass mark. The total
score is slightly lower than the previous validation by , with an average of 4.5 compared to 5.4 previously recorded. However, in the organisation
of the environment factor (FII), the current study shows an average of 8.05, exceeding
the 6.9 of . Repeat study, a factor present in the previous study, was not considered, which
may explain some of the differences found in the sample.
The trainee teachers surveyed show excellent performance on the adaptive subscale
and good environmental and task organisation strategies. However, their inadequate
habits for self-regulation of learning result in a lower overall SRL score than described
by the data of . Students surveyed need to improve their understanding of complex topics, ask their
teachers when they don't understand something and avoid distractions while studying
to improve their overall SRL scores.
On all SRL scores with the SRSI-SR scale, female students significantly outperform
their male peers. The findings are consistent with previous research highlighting
the superior ability of female student teachers to manage their own learning (; ). At the overall SRL level, similar to previous research (), there are no differences between infant and primary education, although in detail
the sample studied shows a significant difference in the organisation of the task,
with infant students performing slightly better than primary students.
Differences in self-regulation of learning between students in different years of
the Bachelor of Education programme are minimal in this study. Fourth year students
show significantly less organisation of the learning environment than first and second
year students. These findings contradict previous literature suggesting better self-regulated
learning scores for students in their final years of undergraduate study (; ). This discrepancy could be due to differences in the sample sizes of the courses
analysed, with final year students accounting for the smallest proportion of participants.
Scientific reading in teacher education students
The second objective was to examine the readership profile of university students
in scientific publications. Both men and women tend to have read one or two articles.
In terms of studies, students of Infant Education teacher are more likely to have
read three or four articles, while primary students are more likely to have read one
or two. Regarding Masters’ students, only the first year students mainly choose the
option ‘one or two items’, while in the following three years the preference shifts
to three or four items.
There are no differences in science reading between infant and primary education teacher
students. However, there are significant gender differences in student teachers, with
a moderate effect in favour of women. According to previous literature, university
students have limited time to read, which makes it difficult to consolidate a reading
habit. They prefer to read literary or self-help texts rather than scientific texts
related to their education. In this sense, their contact with informative texts is
reduced to those that are compulsory and essential to pass the subjects in the curriculum,
using the reading of informative texts as an instrument (; ; ). A study conducted at the University of Delhi (India) found that social science
students tend to read for academic purposes, compared to technology students who seek
to acquire more knowledge ().
Another important finding of this study is that students read less during the first
four months of the first year of these programmes, with most students choosing not
to read any articles at all. This finding is consistent with the underdeveloped reading
habit described by among incoming students in various Colombian university programmes. The data also
show that - comparatively - more reading takes place in the second year than in the
first and third year, so it cannot be said that there is an increase in the scholarly
reading profile of prospective teachers towards the end of their initial training.
Self-regulated learning in relation to scientific reading in trainee teachers
The final research objective was to investigate whether there were differences in
self-regulated learning according to the range of scientific articles read over a
four-month period. The data confirm significant differences on all scales of the adapted
SRSI-SR questionnaire. The mean scores for the SRL, the Adaptive Scale, and the information
search and organisation of the activity factors have worse mean scores in the 'no
articles' range compared to all other options except ‘one or two articles’ read per
semester. The largest effect is found when comparing those who read no articles with
those who read more than ten. In general, the ability to self-regulate learning improves
with increased scientific reading. There are no significant differences between those
who read no articles and those who read one or two, with improvements found from three
articles per semester.
Although there are mixed results in the literature on the relationship between SRL
and academic performance (; ), the data from this study confirm that reading scientific articles can explain the
improvement in SRL scores of the sample of prospective teachers analysed. In fact,
the lack of academic reading habits in the data collected correlates with a low level
of SRL skill development, which negatively affects the ability to engage in critical
reading and thus the development of critical thinking in university students.
Encouraging the practice of academic reading has been suggested to improve the SEL
performance of future teachers (; ), as reading scientific articles is important for academic success and the ability
to read these types of texts improves with practice and continued exposure ().
Conclusions
This research highlights that increasing scientific reading in infant and primary
education teacher students can improve their self-regulated learning skills, which
contributes to the development of critical thinking (; ). It emphasises the importance of an approach that promotes students’ choices in
reading, integrating intrinsic motivation to foster multiple skills and competences
(; ).
The positive relationship between science reading comprehension performance and executive
function, analogical reasoning, and positive attitudes towards reading is supported
by evidence (; ). It is proposed to replicate studies using eye tracking in Spanish students to assess
the relationship between visual behaviour and cognitive structures, applying neurodidactic
strategies (; ).
The influence of teachers’ reading habits on their teaching practice highlights the
need for active and critical teachers to promote the importance of reading as a tool
for learning (; ). Adapting scientific texts and using group readings and infographics can make it
easier to teach scientific content ().
It is suggested that future research should focus on the didactic use of science reading
adapted to schoolchildren in order to prevent preconceived ideas and foster a passion
for science. Limitations such as the representativeness of the sample or the individual
and exclusively quantitative focus of the study suggest directions for future research
to overcome these limitations. A relational approach with self-reported measures of
scientific reading and assessment of SRL before and after specific educational interventions
is recommended.
In conclusion, despite the challenges in educational research, the findings provide
an opportunity to promote scientific reading and evidence-based teaching models to
improve the self-regulated learning skills of future teachers ().
Authors’ contributions
Marta Torrijos-Muelas: Formal Analysis; Data curation; Writing – original draft; Writing – review & editing;
Investigation; Methodology; Software; Validation; Visualization.
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Appendix
Sample of participation survey
This model is an approximation of the digital survey used to collect data for the
study it accompanies. Some features of the questions and answers may not be accurate
because the digital format used cannot be reproduced on paper.
I declare that I have read the “Participant Information Sheet” and agree to take part
in the study.
I have access to the “Participant Information Sheet” and “Informed Consent”. The characteristics
and purpose of the study and the potential benefits and risks of my participation
have been explained to me.
I was able to ask questions in good time and they were all answered to my satisfaction.
I have been assured of the confidentiality of my data.
I give my consent voluntarily and understand that I am free to withdraw from the study
at any time without prejudice.
To give your consent and start your participation, click on “YES”.
To withdraw your consent and end your participation, click on “NO”.
Socio-demographic data
Age: ____________.
What are you currently studying? ___________________________________
In which year did you first enrol in this degree? __________________
Gender you identify with:
Female / Male / Prefer not to answer / Other (specify)
From what studies did you enter university?
Baccalaureate of Arts
Baccalaureate of science, health sciences option
Bachelor of science, technology option
Baccalaureate in the humanities
Baccalaureate in social sciences
How many scientific or magazine articles did you read last semester?
None
1 - 2
3 - 4
5 - 7
8 - 10
> 10
For the following statements, choose the answer that best fits your reality. Remember
that there are no right or wrong answers, only your own perception of yourself and
the frequency with which you perform the suggested actions.
I make sure that no one distracts me when I am studying.
FII
2
I avoid asking questions in class if I do not understand the subject.
FI
3
I use a method to keep my teaching materials in order.
FIV
4
If I do not understand something, I ask the teachera.
FI
5
I carry out additional literature searches to help me understand class topics.
FIII
6
I plan the order in which I will carry out my academic activities.
FIV
7
I give up easily when I do not understand something.
FI
8
I coordinate my time according to the academic activities assigned to me.
FIV
9
I make a timetable to organise my study time.
FIV
10
Before I start studying, I think about the best way to do it.
FIV
11
I finish all my academic activities before I start other activities.
FII
12
I do research when I do not understand something about the tasks I am given.
FIII
13
When I study, I ignore subjects that are difficult to understand.
FI
14
I try to study in a place without distractions (noise, people talking...).
FII
15
I am easily distracted when studying.
FI
16
I am looking for material to supplement the topics covered in class.
FIII
17
I try to study in a quiet place.
FII
18
I allow people to interrupt me when I am studyinga.
FII
Note: a = reverse item in your score.
* The factor to which each item belongs is added here, but the information in this
column was not given to the participants when they completed the questionnaire. FI
= Factor I; FII = Factor II; FIII = Factor III; FIV = Factor IV. Factor I forms the
maladaptive scale, while the other three are agglomerated and correspond to the adaptive
scale of the questionnaire.