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Exploring the integration of self-regulated learning into digital platforms to improve students’ achievement and performance

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This study aimed to explore the integration of self-regulated learning into digital platforms to improve students' achievement and performance. Moodle platform was used with additional modifications to integrate the features of self-regulated learning. An experimental design involving experimental and control groups with pre-post-tests was utilized. The ADDIE model stages were followed to develop and address the study variables. The study sample included 70 students from the faculty of education at Suez University in Egypt, who were divided into two groups. The first group studied using the instructional approach that integrates self-regulated learning and digital platforms, whereas the second group studied using the traditional method in computer lab. After data collection, SPSS software was used to analyze and process the results through a t-test, and calculated effect size using eta square (η2). The results showed significant differences in the mean scores of the two groups, favoring the first group. Moreover, the integration of self-regulated learning into online platforms had a positive impact on the improvement of students’ achievement and performance related to digital competencies, this finding attributed to the features of self-regulation within the online learning platform.
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Discover Education
Research
Exploring theintegration ofself‑regulated learning intodigital
platforms toimprove students’ achievement andperformance
AhmedElmabaredy1· NurgunGencel2
Received: 31 March 2024 / Accepted: 21 August 2024
© The Author(s) 2024 OPEN
Abstract
This study aimed to explore the integration of self-regulated learning into digital platforms to improve students’ achieve-
ment and performance. Moodle platform was used with additional modications to integrate the features of self-regu-
lated learning. An experimental design involving experimental and control groups with pre-post-tests was utilized. The
ADDIE model stages were followed to develop and address the study variables. The study sample included 70 students
from the faculty of education at Suez University in Egypt, who were divided into two groups. The rst group studied using
the instructional approach that integrates self-regulated learning and digital platforms, whereas the second group stud-
ied using the traditional method in computer lab. After data collection, SPSS software was used to analyze and process
the results through a t-test, and calculated eect size using eta square (η2). The results showed signicant dierences
in the mean scores of the two groups, favoring the rst group. Moreover, the integration of self-regulated learning into
online platforms had a positive impact on the improvement of students’ achievement and performance related to digital
competencies, this nding attributed to the features of self-regulation within the online learning platform.
Keywords Self-regulated learning· Digital learning platforms· Academic achievement· Digital competencies
performance
1 Introduction
E-learning using platforms will be the best solution in the future to develop and improve the competencies and skills of
students and teachers [1]. It is worth mentioning that platforms were the best way to learn during the Covid19 pandemic.
Schools and universities worldwide have used them as an alternative to traditional learning to complete their educational
programs online. Moreover, digital platforms provide students with a more structured and exible learning environment.
Digital platforms refer to systems of learning management. Furthermore, they use computers and the internet to man-
age distance learning; they provide tools that support learning activities, such as discussions, questions, exercises, and
tests, whether synchronous or non-synchronous [2]. That is by registration and scheduling, monitoring of participating
students, delivery of content, and tracking of the learning process, as well as the design of tests, discussion, activities,
and distance communication [3]. Distance learning management systems include free and open-source systems such
as ATutor and Moodle, and commercial systems such as WebCT and Blackboard.
Digital and distance learning using Moodle improved students’ online learning activities without being restricted by
space [4]. Moreover, other studies [3, 5] have also indicated that the Moodle platform is one of the most widely used
* Ahmed Elmabaredy, ahmed.elmabaredy.edu19@suezuni.edu.eg | 1Department ofEducational Technology, Faculty ofEducation, Suez
University, Suez, Egypt. 2Ministry ofNational Education, Bartin, Turkey.
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and eective systems for distance learning. On the other hand, the use of Blackboard features such as blogs, breakout
sessions, and video conferencing will help promote local and international educational practices [6].
The development of eective digital learning requires freedom for self-regulation [7]. Self-regulated learning (SRL) is
dened as a constructive interactive process, learners set the learning goals, and then try to organize, monitor, and control
knowledge, behavior, and motivations, which are directed and inuenced by their goals and environmental manifesta-
tions [8]. In this context, SRL refers to the ongoing process that students engage in to acquire academic skills, including
setting goals, reviewing, and selecting strategies and eective self-monitoring [9]. Previous studies [8, 10, 11] have
emphasized the role of self-regulation learning in helping students organize their learning and complete required tasks.
There is a set of characteristics and qualities that distinguish self-regulated students, as they use certain strategies,
such as cognitive and metacognitive strategies, that guide their behavior during planning, implementing, and evaluating
various learning processes. Schunk and Zimmerman [12] compared self-regulation learning between high-performing
and low-performing students. The ndings indicated that high-performing students set better learning goals, imple-
ment instructional strategies, create a more productive environment, track and assess goal progress, and seek help
when necessary.
Self-regulation of learning has its origins in the theory of social cognitive, which was founded by social psychologist
Albert Bandura. Bandura emphasized the existence of three intertwined determinants or inuences within the SRL:
personal, environmental, and behavioral. He assumed the existence of a triple causality between these determinants of
learning self-regulation [13]. According to Pintrich model, self- regulated learning includes three basic strategies: cogni-
tive, metacognitive, and resource management [8].
Acquiring and appropriately employing digital competencies helps students and teachers to organize their work plans,
enhance content design, and use instructional strategies eciently. It also allows for individualized education and the
attainment of high levels of thinking and creativity [14]. Digital competencies refer to the eective use of a full range of
digital information technology and communication technologies in solving problems [15]. Moreover, digital competen-
cies include several dimensions, the educational dimension, which involves converting information into knowledge and
acquiring it; the media dimension, which involves gathering, evaluating, and processing information in digital environ-
ments; the communicative dimension, which involves social communication; and the technological dimension, which
includes technological literacy [16].
Several studies [1720] have shown a weakness among higher education students in performing digital competencies.
Although digital technology has become increasingly important in academic and practical elds, some students still
struggle to use it eciently. In this context, Hassounah [21] identied the digital competencies required for the twenty-
rst century teacher in the use of Microsoft oce software to support teaching, the creating and editing of digital audio,
using of digital images, video, infographic, blogs, and social networking sites.
This study seeks to develop an instructional approach based on integration self-regulation into digital learning plat-
forms. It aims to overcome the constraints of conventional platforms by integrating tailored features and strategies
that empower students to take control of their learning process. By providing an interactive learning environment, the
platform fosters students’ autonomy, self-motivation, and metacognitive skills. Furthermore, this study aims to enhance
students’ achievement and performance in digital competencies to prepare them to keep up with the ongoing digital
transformation.
2 Literature review
2.1 Digital learning platforms
Ippakayala and El-Ocla [22] proposed a digital learning management platform that provides the ability to control digi-
tal content, integrates with social activities, and includes technology for recording lectures. Results suggested that the
platform helped teachers and students manage lectures, assignments, events, and discussions remotely. Alzahrani [23]
measured the eect of online learning using platforms on student achievement at Hail University in the Kingdom of Saudi
Arabia. Results showed that the Blackboard platform had a signicant impact on enhancing students’ achievement and
their attitude towards distance learning. On the other hand, Nadeak [24] analyzed the eectiveness of distance learning
using social platforms during Covid-19 pandemic. The results found that social learning platforms are only eective in
theoretical learning programs. In a comparison of the eectiveness of educational platforms, Almoeather [25] investi-
gated the eects of Blackboard Edmodo on self-regulated learning and the satisfaction in education among students.
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The participants included (148) students and were randomly distributed into two experimental groups. The ndings
indicated that there were no signicant dierences between the mean scores of the experimental groups.
Gunawan etal. [2] developed a Model-based system to enhance the creativity of teachers. The results indicated that
the developed system successfully contributed to the development of creativity among teachers. Also, Simanullang and
Rajagukguk’s [4] utilized the Moodle distance learning management system and showed its eectiveness in improving
students’ online learning activity. On the other hand, Al Shammari [26] investigated the digital platform preferences of
English students during the emergency remote education due to the COVID-19 pandemic. A Survey was designed to
answer the questions of the study. A total of 300 students from both male and female participated in the study. The
results showed that students preferred the Zoom to Blackboard. The ndings also indicated gender disparities in reasons
of preferences.
Study by Shemy [27] aimed to evaluate the use of a digital platform to enable Omani teachers to create e-learning
materials. A questionnaire was distributed to 100 Omani teachers to assess ease of use, accessibility, and ecacy of the
platform. Results showed that 88% of teachers found the platform easy to use and benecial, indicating a strong interest
and readiness among educators to utilize it for enhancing the learning process. Aldaghri and Oraif [28] investigate the
eect of using Blackboard for online teaching on the engagement of EFL college students in writing. The study sample
consists of 148 students. The ndings suggested that the utilization of Blackboard had a positive impact on the engage-
ment of EFL learners.
Ibrahim [29] investigated the eect of a digital learning program on developing communicative speaking and atti-
tudes towards digital learning among faculty of education students in Egypt. Results showed high dierences on the
pre-post measures of the communicative speaking test and the attitude scale, favoring the post measure. Also, Alenezi
[30] discusses the characteristics of digital learning in higher education. Moreover, how can grasp digital transforma-
tion and address the challenges brought about by the fourth industrial revolution. Pires and Fortes [31] identied the
determinants of students’ use online platforms in higher education institutions. The results showed that 60.1% of the
students expressed the use of online platforms.
After reviewing the literature related to digital learning platforms, there is a signicant interest in studies that focus on
the use of platforms for managing e-learning and facilitating distance learning. These studies have consistently shown
the positive impact of online platforms on improving learning outcomes.
2.2 Self‑regulated learning
Boekaerts [32] presented a model of SRL, based on adaptive learning through three systems: self-organization, organi-
zation of learning processing, and organization of information processing methods. However, Zimmerman [33] pro-
posed his model, based on three sequential stages that constitute SRL, the rst stage is contemplation, followed by the
performance stage, and then the stage of self-reection. Winne and Perry [34] compare two types of measures of SRL.
The rst type is aptitude measures, which dene students’ characteristics and enable the prediction of future behavior.
Examples include self-reports questionnaires and structured interviews. The second type is process measures, which
assess self-regulation as it occurs. Examples include tracking methodologies and performance observation. One of the
most popular measures of SRL is the Pintrich Scale (MSLQ) [35].
Mullen [36] explored differences in the use of self-regulated learning strategies among students. The participants
included 125 students. The Motivated Strategies for Learning Questionnaire (MSLQ) was applied to the study group,
and the results showed that the students used SRL strategies in learning. Narciss etal. [37] conducted a study aimed
to promote self-regulation learning into online learning environments. The study found that electronic environ-
ments support SRL by providing interactive interfaces and tools that support free browsing and active participation.
McLoughlin and Lee [38] examined personal learning and SRL methods in a Web 2 environment. The results found
that students were able to select and customize learning tools and electronic content across the web environment.
In a study conducted by Ocak and Yamac [39] to examine the relationship between self-regulated learning styles,
attitudes, and achievement. The study found that students who self-regulate their learning use a range of cogni-
tive methods, including recitation, details, and organization, as well as behavioral methods such as asking for help,
managing time and the environment, and motivational elements that play an important role in this process, includ-
ing self-efficacy, internal and external goals, and task value. Lehmann etal. [7] concluded that directed preflective
prompts work best for novice learners.
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Omar [40] proposed a strategy based on self-regulated mobile learning according to the Zimmerman socio-cognitive
model to develop self-regulatory learning skills and dimensions of m-learning acceptances for secondary school stu-
dents. The study sample included 53 students from secondary schools in Riyadh, Kingdom of Saudi Arabia; the results
showed the eectiveness of the proposed strategy based on self-regulated mobile learning according to the Zimmerman
social model. Study by Yahia etal. [41] aimed to investigate the impact of employment SRL with learning management
tools to improve student teachers’ creative writing skills. The study adopted a pre-post experimental one-group design.
It involved 30 student teachers from the Faculty of Women Arts and Education, Ain Shams University in Egypt. A pre-
posttest was administered. Students showed signicant improvement in their creative writing (short story) after being
trained through the suggested online self-regulated creative writing program.
Khiat and Vogel [42] conducted a study to examine the eect of the practice of SRL in an online environment. The
researchers developed an LMS based on self-regulation learning. The ndings suggested that the utilization of self-
regulation in learning management system helped and supported students in engaging in more ecient SRL behaviors,
which had an impact on learning motivation and metacognitive reection. In the study conducted by Zheng etal. [43]
an examination was undertaken to compare online self-regulation and engagement across three distinct groups of sec-
ondary students. These groups comprised students from both a metropolitan city and a rural area, encompassing a mix
of ethnicities. The ndings from the analysis of variance demonstrated noteworthy distinctions between the rural and
urban student cohorts, as well as disparities between the rural ethnic group and the urban non-ethnic group.
2.3 Digital competencies performance
In the framework of presenting the literature related to digital competencies, Yelubay etal. [1] indicated that digital
competencies are requirements for the future success of teachers, therefore they need to develop their digital skills in
teaching. In the same context, Hassounah [21] explored the degree to which computer and technology teachers integrate
the competencies associated with a 21stcentury educator. Study sample included 51 computer and technology teach-
ers in the directorate of education in the west of Gaza in Palestine. The results concluded that there is a shortcoming of
teachers in the application of digital competencies. Fernandez etal. [16] suggested an instructional design to facilitate
the handling of ICTs. After applying it to a group of undergraduate students, the results showed the eectiveness of the
proposed design in improving the dimensions of students’ digital competencies.
Guillén-Gámez etal. [44] revealed dierences between teachers’ knowledge and use of digital tools and skills; espe-
cially about Web 2.0 tools. On the other hand, Ukah [14] has developed a Digital Competency Acquisition Assessment
Questionnaire (DIRCETQ). The results found that the acquisition of digital teaching resources does not have a signicant
impact on the eectiveness of teachers’ teaching. Basantes-Andrade etal. [17] analyzed teachers’ digital Competencies.
He noted that in addition to beneting from the tools and helps that information technologies provide to teachers;
they also need pedagogical and social skills that allow them to generate an environment of collaboration and inclusive
digital learning.
Isrokatun etal. [45] study focused on the digital literacy competency among students at primary school teacher depart-
ment as the demands of 21stcentury learning, study employed a qualitative method of research design with a study case.
The results indicate that digital skills are crucial for everyday work, students are expected to possess and master digital
literacy skills in preparation for their future roles in education. In a study conducted by Koyuncuoglu [46] examined the
digital and technology competencies of students across various faculties. The results indicated that students exhibited
high levels of digital competence and technology skills in certain dimensions. Furthermore, the study showed variations
in the digital competencies among the students, depending on their grade level and academic achievement status.
El-Sayary [47] investigated the use of a training program to develop digital competence for teachers. A sequential
mixed-method approach using quantitative and qualitative data was used. The results indicated to the training program
developed digital competence among the teachers where they construct knowledge and skills. In the same context, a
study conducted by Ahmed [48] aimed to investigate the eect of the proposed program on developing achievement
and digital competencies among student teachers. The research sample consisted of one group of 60 students from Ain
Shams University in Egypt. The results indicated that the program had a positive impact on enhancing both the students’
academic achievement and their digital competencies.
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2.4 Research problem andquestions
The primary research problem revolves around deficiencies in current digital learning platforms concerning distance
and self-learning. The deficiencies in these platforms became particularly obvious during the COVID-19 pandemic.
Therefore, there is a critical need to address this gap by developing a digital educational system that integrates self-
regulated learning features with digital learning platforms. This study recognizes the importance of addressing this
issue and aims to contribute to the advancement of digital learning platforms that align with the fundamentals of
SRL, ultimately empowering students to become independent, motivated, and lifelong learners in the digital age.
In this context, Broadbent and Poon [49] indicate that with the increasing enrollment in online learning, it is
essential to comprehend how students can effectively utilize self-regulation strategies to attain success within digital
learning. Practicing self-regulation in learning is essential in a learning environment [42]. However, Currently, there
are only a few systems specifically designed for students to practice the complete range of SRL strategies. Xu etal.
[50] recommended that research on self-regulated learning strategies in online learning contexts is urgently needed,
and most of the available research did not focus on these strategies.
Regarding improving students’ digital competencies performance, many previous studies have indicated the
weakness of programs related to training students in digital competencies. Yue [51] notes that university education
institutions must change their educational programs and innovate new curricula based on 21stcentury skills. In the
same context, the Ukah study [14] recommended sufficient training for students and teachers in digital competen-
cies, especially the skills of using digital educational resources. Accordingly, this study seeks to answer the following
questions:
RQ1: How does the integration of self-regulated learning into digital platform impact students’ academic achievement?
RQ2: How does the integration of self-regulated learning into digital platform impact students performance in
digital competencies?
2.5 Research hypotheses
H1: Integrating self-regulated learning into digital platforms significantly improves students’ academic
achievement.
H2: Integrating self-regulated learning into digital platforms significantly enhances students’ performance in
digital competencies.
Figure1 shows the expected effects of integrating self-regulated learning into digital platforms on students’ aca-
demic achievement and their performance in digital competencies.
The rst hypothesis (H1) directly responds to the rst research question by predicting a positive impact of self-reg-
ulated learning on academic achievement. It suggests that the use of self-regulated learning strategies within digital
platforms will lead to measurable improvements in students grades or overall academic performance. While the second
hypothesis addresses the second research question by predicting a positive eect of self-regulated learning on students’
Fig. 1 Impact the integration system on academic achievement and digital competencies
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prociency in digital skills. It implies that students who use self-regulated learning strategies on digital platforms will
show improved abilities and performance in digital competencies compared to those who do not use these strategies.
3 Methodology
This study employs an experimental approach to investigate the eect of integration between SRL and digital platforms
on students’ achievement and performance, compared with traditional teaching methods. Achieving the research objec-
tive requires a direct experimental test that measures dierences in academic achievement and performance among
students. The experimental approach controls variables and identies causal relationships between the proposed model
and educational outcomes. This is achieved by dividing participants into two groups: an experimental group and a control
group. This approach isolates the impact of the proposed integration system from any external inuences or factors that
may aect the accuracy of the results. Such control of external variables ensures that any dierences in outcomes can
be directly attributed to the experimental intervention. The experimental approach provides precise, quantiable data
that can be statistically analyzed. By measuring the performance of both groups (experimental and control) based on
predened criteria, the eects can be accurately analyzed to determine the impact of the proposed integration model.
According to Rahman and Rabiul Islam [52]; Michiel and Rose [53] experimental design involves the researcher’s com-
plete control over potential extraneous variables and allows for predicting the eect of an independent variable on a
dependent variable with statistical signicance test. Therefore, it is the most suitable method for explanatory research
that involves measuring physical objects. It provides a high level of accurate observation and measurement.
To analyze and interpret the results, statistical analyses will be employed, including t-tests, to evaluate the dier-
ences between the experimental and control groups. These analyses will be able to assess whether the dierences in
performance between the two groups are statistically signicant and validate the eectiveness of the integration model.
3.1 Participants
The target population consisted of all students enrolled in various programs and specializations within the College of
Education at Suez University. This included programs such as science teacher preparation, mathematics teacher prepara-
tion, and chemistry teacher preparation. The sample size was determined to be 70 students. To ensure unbiased selec-
tion, a random sampling method was employed using a list of student names as the sampling frame. From this list, 70
students were randomly chosen using a random number generator. We carefully selected the research sample from the
same educational level and strived to include age groups as similar as possible. Moreover, we ensured that all participants
possessed basic skills in using computers and the basic software.
The selected students were then randomly divided into two equal groups of 35 students each. One group was des-
ignated as the experimental group, receiving learning content through the integration of self-regulated learning (SRL)
with digital learning platforms. The other group served as the control group, utilizing traditional study methods. Table1
shows the participants’ demographic characteristics.
The demographic table presents a clear overview of the sample characteristics of the experimental and control groups.
The participants’ ages ranged from 21 to 23years. Gender distribution was 10 males (33.33%) and 20 females (66.66%)
in the rst group and 12 males (40%) and 18 females (60%) in the second group. In terms of eld of study, most of the
Table 1 The participants’
demographic characteristics Demographic data Experimental group (n = 30) Control group
(n = 30)
n % n %
Gender Male 10 33.33% 12 40%
Female 20 66.66% 18 60%
Age (years) 21–23 30 100% 30 100%
Field of study Chemistry teacher 12 40% 11 36.66%
Science teacher 10 33.33% 10 33.33%
Math teacher 8 26.66% 9 30%
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participants in both groups were chemistry teacher preparation, with 12 (40%) in the experimental group and 11 (36.66%)
in the control group. Other elds of study included science and mathematics teacher preparation.
Detailed information about the study, including its purpose, procedures, and benets, was provided to the students.
We ensured that all students fully understood what participation in the study entailed. We emphasized our commitment
to maintaining the condentiality and privacy of the students’ personal information, and that the data would be used
solely for research purposes.
3.2 Instruments
To measure the students’ achievement, we prepared an achievement test consisting of 30 multiple-choice questions.
All questions were reviewed by specialized experts, and the reliability coecient of Cronbach’s Alpha was 0.80. The
questions were programed electronically using Google forms. Additionally, an observation checklist was developed to
assess students’ performance in digital competencies. This checklist consisted of four main dimensions, including text
editing skills, production of educational voice-over, image processing skills, and editing of educational videos. Each main
dimension included statements reecting the assessed digital competencies.
3.3 Research design
The study employed an experimental design with two experimental and control groups, with pre- and post-tests. As
illustrated in Fig.2.
In the experimental design, we divided the participants into two groups: experimental and control. Pre-tests were
conducted using instruments to ensure that the study groups were equivalent. Next, experimental processing was
applied. The participants in the rst group (experimental) were taught content using the integration model. On the other
hand, the participants in the second group (control) were taught exclusively through the traditional methods in the
computer lab. After all participants nished studying the content, a post-test was conducted on both the experimental
and control groups.
3.4 Design theintegration betweenSRL anddigital learning platform
As part of this study, we used Moodle as an open-source online platform. Moodle provided a range of tools and features
that were essential for our study, including the ability to create course content, track student progress, and enable self-
regulation features. Moodle platform provides easy-to-use tools such as assignments, forums, wikis, workshops, tests,
pages, and other tools [2, 5]. The analysis, design, development, implementation, and evaluation [ADDIE] model was
followed to design the integration system. As in Fig.3.
Fig. 2 The experimental design of the study
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1- Analysis phase
This stage included analyzing the characteristics of the participants and identifying the characteristics of students
who self-regulate learning. In addition, the general and behavioral goals were identied and analyzed in the light of the
Audience, Behavior, Condition, and Degree [ABCD] model. To identify the educational needs of students, digital compe-
tencies were analyzed into major and sub-competencies.
2- Design phase
In the second phase, the scenario of the integration system was designed, and the initial concept was prepared. The
content was organized into ve educational lessons, and learning strategies were dened according to SRL. In addition,
learning and multimedia resources were designed, including texts, instructional videos, images, and infographics. These
multimedia resources were carefully designed to enhance the learning experience and provide students with a com-
prehensive understanding of digital skills. Videos were included to demonstrate practical applications of digital skills,
while texts were used to provide theoretical knowledge and explanations. Images and infographics were employed to
illustrate complex concepts and present information in a more visually engaging format. The use of multimedia in the
platform created a more interactive and dynamic learning environment that encourages eective participation and
Fig. 3 ADDIE model
Fig. 4 Online learning platform
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knowledge retention. By using various multimedia resources, the platform could provide students with a well-rounded
and eective education in digital performance.
3- Development phase
In the development phase, electronic content was written in view of the scenario, produced, and uploaded to the
Moodle platform. Learning resources and multimedia were designed, including activities and assignments, and electronic
tests were created. Figure4 presents a scene from the online platform.
Self-regulated learning is a key feature of this platform, where students are encouraged to take an eective role in their
own learning process. This includes setting goals, monitoring progress, and engaging in learning practices. To support
SRL, Moodle platform provides a range of tools and resources, including personalized learning, self-assessment quizzes,
and progress tracking tools. Students can use these tools to identify their strengths and weaknesses, set achievable goals,
and track their progress over time. Therefore, students can develop skills and knowledge in this way.
4- Implementation phase
The implementation phase included registering students to participate in the online platform and providing a learn-
ing guide and instructions. Then, the students were taught using the online platform, applied digital competencies, and
submitted assignments.
5- Evaluation phase
The evaluation phase included two types: a formative evaluation that accompanied all the previous stages and a nal
evaluation using measurement tools to measure the eect of the online platform on improving students’ learning and
developing their achievement and digital competencies.
4 Data collection
Before implementing the experimental application, a pre-test was conducted. Both the experimental and control groups
underwent an achievement test and were evaluated using observation checklists. The pre-test results showed no statisti-
cally signicant dierences in the average scores between the groups. The pre-test results conrmed the equivalence
of the research groups in terms of learning aspects before the experiment. This equivalence indicates that any observed
eects post-experiment is attributable to the experimental treatment rather than any external factors.
The study experiment was implemented in the computer lab of the Faculty of Education. We ensured that all neces-
sary conditions for student learning were met, including the provision of appropriate devices, tools, and applications.
Additionally, we provided a wireless internet network to facilitate students’ access to the learning environment.
At the beginning of the experimental treatment, an introductory interview was conducted with the participants.
The purpose of this interview was to motivate and encourage participation, and to provide them with guidance on the
learning process using self-regulation fundamentals that can be integrated into a digital platform. To promote SRL on
the Moodle platform, the following actions were implemented:
A comprehensive digital library was made available, providing resources and educational media. These resources
encompass didactic videos, informative texts, infographics, and imagery, all meticulously crafted to optimize the
acquisition of knowledge.
A personalized learning plan was established for each student, considering their unique requirements and prefer-
ences. Moreover, students were encouraged to set specic goals that aligned with their interests and needs.
Self-assessment tools, such as quizzes, self-reection prompts, and rubrics, enable learners to monitor their progress
and evaluate their learning.
Self-reection was encouraged on the online platform, as learners were prompted to reect on their learning experi-
ences, identify their strengths and weaknesses. By engaging in this process, learners were able to take ownership of
their learning, develop their skills and knowledge, and make progress toward achieving their learning goals.
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Provided peer support: oer learners opportunities to collaborate and provide feedback to one another, as well as
access to peer support networks and resources.
Opportunities for feedback and support have been provided throughout the learning journey, including peer feed-
back, and mentorship.
Each student began the process of self-regulating their learning by establishing personal goals, devising plans to
acquire the necessary competencies, organizing their learning based on their individual requirements, and engaging in
self-assessment of their progress. Moreover, the students eectively interacted with the learning content, underwent
training to enhance their digital competencies, monitored their activities, completed assigned tasks, and submitted their
assignments. Throughout this process, the researchers closely monitored the students activities and oered support and
assistance whenever necessary. After completing the experiment, the post-test was performed. The instruments were
re-applied to both groups. The scores were extracted, then statistical analysis was performed using the SPSS software
to analyze the data and obtain the results.
5 Results
The results were presented by answering the research questions as follows:
5.1 Results ofanswering thefirst research question
To address the rst research question, how does the integration of self-regulated learning into digital platform impact
students’ academic achievement? The descriptive statistics and t-test were calculated using software. Table2 shows the
statistics for the results of the achievement test:
Table 2 Statistics of the
achievement results Achievement N Mean Std. deviation
Group 1 (experimental) 35 19.29 1.8
Group 2 (control) 35 15.00 1.9
Fig. 5 The average scores of
both groups in the achieve-
ment
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In Table2, the mean scores for the experimental group in the achievement test were 19.29, with a standard deviation
of 1.8. whereas the mean scores for the control group were 15, with a standard deviation of 1.9. Figure5 presents a graph
displaying the mean scores of both the experimental and control groups on the achievement test.
Table3 shows the signicance of the dierences between the mean scores of the experimental and control groups
on the achievement test.
Table3 shows the dierence in achievement between the mean scores of the experimental and control groups. The
value of “t was 5.5, and the experimental group had the highest mean score. Accordingly, we accept the rst hypothesis
of the research, which states: There are statistically signicant dierences between the average scores of the experi-
mental and control groups in the post-measurement of achievement, favoring the students of the experimental group.
Furthermore, the eect size was calculated using eta square (η2), and its value was 0.30, indicating a signicant eect of
the integration between SRL and Moodle platform on enhancing student achievement.
5.2 Results ofanswering thesecond research question
The second research question: How does the integration of self-regulated learning into digital platform impact students’
performance in digital competencies? To address this question, descriptive statistics and a t-test were performed. Table4
shows the statistics for the performance checklist:
Table 3 Signicance of
dierences between the mean
scores of the groups in the
achievement test
p < 0.05
Post-test group n mean t df p value
Achievement Experimental 35 19.29 5.5 68 0.000
Control 35 15.00
Table 4 Descriptive statistics
for the results of applying the
performance checklist
Observation checklist N Mean Std. deviation
Group 1 (experimental) 35 223.66 2.0
Group 2 (control) 35 185.51 2.2
Fig. 6 The average scores
of both groups in the digital
competencies’ performance
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In Table4, the average scores of the experimental students in the digital performance checklist were 223.66, with a std.
deviation is 2.0. The mean scores for the control group were 185.51, with a standard deviation of 2.2. Figure6 presents
a graph showing the average score of the two groups on the digital competencies’ checklist.
Table5 shows the results of the dierences between the mean scores of the experimental and control groups on the
performance of digital competencies using t-test.
Table5 reveals a signicant dierence between the scores of both groups in the post-test of the digital competen-
cies’ performance. The t-value was reported to be 7.22, suggesting a substantial dierence between the two groups.
Moreover, the p-value was found to be 0.00 at (p < 0.05), indicating that the results are highly signicant. This dierence
favored the second group (experimental). Accordingly, we accept the second hypothesis of the research, which states:
“There are statistically signicant dierences between the average scores of the experimental and control groups in the
post-measurement of digital competencies, favoring the students of the experimental group”. In addition, the eect size
of the integration system in developing digital performance for students was calculated using eta square (η2), and the
calculated value was 0.43, indicating a signicant impact size.
6 Discussion
The study findings revealed that the integration between SRL and Moodle platform has a significant impact on
enhancing students’ achievement and performance. The integration system has positively influenced students
learning outcomes in both cognitive and digital competence domains. The integration system plays a crucial role
in employing SRL strategies, enabling students to organize their learning by setting their own goals, planning their
learning, interacting with content, and self-evaluating their learning. Consequently, students take responsibility for
their learning, which increases their motivation to acquire cognitive aspects and master digital competencies.
The study results can be attributed to various factors. For instance, when designing the integration system, the
characteristics of SRL were considered, which stimulated students’ interest and motivated them to pursue their edu-
cational objectives. Furthermore, the organization and cohesion of the lessons within the platform. Additionally, the
blend of interactive multimedia content and the provision of enriching educational resources through the internet
improved students’ cognitive learning and their ability to apply digital competencies. The inclusion of videos within
the digital learning platform played a crucial role in facilitating students’ learning of digital competencies. The videos
provided simulations of skills performance, allowing students to observe and learn how to effectively navigate and
use digital tools and resources. By providing these visual demonstrations, students could imitate and implement
the demonstrated skills, thereby enhancing their learning experience and acquisition of digital competencies. The
researchers believe that the Moodle platform played an effective role in facilitating online learning at any time
and from anywhere. It provided self-learning and individualization for each student according to their speed and
self-development, making the learning environment more flexible. Linking the content with practical activities and
applications encouraged students to engage in the practice of digital competencies and their application in real-life
situations.
The findings confirm the fundamentals of connectivism theory, which emphasizes that learning involves the pro-
cess of linking various online resources. The hyperlink design of the educational lesson elements within the online
platform, and the provision of enriching web links helped students acquire information and improve their perfor-
mance. Furthermore, in line with the principles of social learning theory (learning by observation), the presentation
of skills in interactive videos had a significant impact on improving students’ digital competencies.
These results are consistent with the findings of Narciss etal. [37], who suggested that digital learning platforms
support self-regulated learning by including interactive interfaces and tools that support free browsing and effective
participation. In addition, the results are consistent with the results of Schunk and Zimmerman [12], who showed that
students with self-regulation skills apply effective learning strategies. The results of this research also support the
Table 5 Signicance of
dierences between the mean
scores of the groups in the
competencies’ checklist
p < 0.05
Post-test Group n Mean t df p value
Observation checklist Experimental 35 223.66 7.22 68 0.000
Control 35 185.51
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findings of Yelubay etal. [1], who stated that learning through online platforms is the best solution for developing
and improving digital competencies for students and teachers. The results of this research are also consistent with
the findings of other studies [2, 3, 5, 23, 42].
7 Conclusion andrecommendations
In conclusion, prioritizing the use advancements of the digital revolution in education is essential to equip students
with the skills and competencies required in the digital age, enabling them to thrive and succeed in an increasingly
interconnected and technology-driven world. This study integrated SRL into a digital learning platform and its eect
on enhancing achievement and digital competencies performance among students in higher education. Moodle was
used as the foundation for the development of this learning platform, and SRL characteristics were integrated into its
design. The results showed that the integration system had a positive impact on student achievement and performance.
We conclude that digital learning platforms that integrate SRL can play an important role in improving learning
outcomes in higher education by developing students’ achievement and performance related to the competencies.
These findings may contribute to the development of educational programs in higher education and provide a model
for leveraging information and communication technology to promote digital education. Based on the results of this
study, several recommendations can be made to enhance student learning experiences and outcomes:
Adoption of digital learning platforms with self-regulation: Academic institutions should consider adopting digital
platforms that integrate self-regulated learning components.
Blending multimedia elements and interactive interfaces: Incorporating multimedia elements, interactive interfaces,
and practical applications within online platforms can be benecial. This approach can facilitate the improvement of
digital competencies among students.
Expanding the study: This study should be expanded to include other student groups, such as those with dierent
grade levels or diverse demographic backgrounds.
Developing a framework: Developing a framework specically focused on developing students’ performance through
SRL platforms. This framework can provide guidance to educators and institutions on designing and implementing
eective strategies for fostering digital skills and abilities.
Acknowledgements The authors would like to express their gratitude to all Faculty of Education students who participated in this work. Also,
we thank all experts who reviewed the study instruments.
Author contributions Both authors contributed to the study of conception and design. Material preparation, data collection and results
discussion were performed by AE. The rst draft of the manuscript was written by NG. Review and edit the manuscript and conclusion were
performed by AE. Both authors read and approved the nal manuscript.
Data availability The data can be requested from the corresponding author for a reasonable purpose.
Declarations
Ethics approval and consent to participate Approval was obtained from the ethics committee of Suez University. The procedures used in this
study adhere to the tenets of the declaration of Helsinki.
Consent for publication Informed consent was obtained from all students whose data was used for the purpose of writing this study. All
personal information that may link the data to individual participants was kept condential.
Competing interests The authors declare no competing interests.
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which
permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to
the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modied the licensed material. You
do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party
material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If
material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds
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the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco
mmons. org/ licen ses/ by- nc- nd/4. 0/.
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