Differences In Self-regulated Learning Research Articles

Exploring SRL Differences: Science vs. Social Science Students in Soe, NTT

This study examines the differences in Self-Regulated Learning (SRL) skills between 3rd-grade science and social studies students at SMA X Soe City, South Central Timor Regency. The total population for this study was 386 students, with a sample of 196 students from SMA X Kota Soe, South Central Timor Regency, determined using the Slovin formula. The sample was further divided into 94 science class students and 104 social studies class students. The Self-Regulated Learning questionnaire comprises 39 question items that have undergone validity testing and have been deemed valid. The questionnaire has a high reliability coefficient of 0.955. Science students exhibit a mean value of 116.4255 for Self-Regulated Learning skills, which is higher than the mean value of social studies students, which is only 107.9510. The data analysis technique employed was Independent Sample T-Test. The results per aspect of Self-Regulated Learning (Motivation, Metacognition, Behavior) suggest that science students outperformed social studies students, indicating a difference in Self-Regulated Learning between the two classes. It can be concluded that the level of Self-Regulated Learning is higher in the science class than in the social studies class.

Unveiling the dynamics of self-regulated learning in project-based learning environments

Project-based learning (PBL) has been found to exert a positive influence on learners' academic achievements, while also fostering their intrinsic motivation and playing a crucial role in nurturing sustainable learning capacities. Understanding individual differences in self-regulated learning (SRL) within project-based foreign language learning can guide language teachers in delivering personalized instruction. This study utilized a blended learning management system to collect and analyze data on SRL from 95 learners enrolled in a project-based College English course. Through microanalysis, latent profile analysis (LPA), and epistemic network analysis (ENA), the study identified distinct learner profiles and traced their developmental trajectories in project-based language learning. The findings revealed that PBL facilitates the occurrence of SRL behaviors and strengthens connections across different regulation phases. Notably, learners with diverse profiles displayed variations in their SRL epistemic network structures and developmental trajectories. These results highlight the dynamic nature of SRL within the PBL context, underscoring the significance of considering individual differences and supporting learners’ evolving self-regulatory behaviors and strategies throughout their engagement in PBL activities. To enhance SRL in PBL, educators are encouraged to provide scaffolding support, promote help-seeking behaviors, and implement interventions targeting metacognitive processes and reflective practices.

DIFFERENCES IN SELF-REGULATED LEARNING AMONG STUDENTS IN TERMS OF GENDER

Self-regulated learningare important skills that enable students to control, manage and monitor their own learning. This research aims to determine the differences in self-regulated learning in male and female students. This research uses a comparative quantitative method with t-test analysis. Data was collected through a questionnaire based on a scale adapted from Lili Nur Indah Sari's 2013 Self-regulated Learning scale based on aspects of self-regulated learning by Zimmerman (1989). The sampling technique was proportionate random sampling, totaling 75 people consisting of 26 men and 49 women. The results show that there is a significant difference between the self-regulated learning of male and female students, namely that female students are higher.

Implementation of Electronic Module Based Multiple Representation on Buffer Solution Materials to Improve Students’ Self-Regulated Learning and Cognitive Learning Outcomes

This research aims to determine the differences between self-regulated learning (SRL) and cognitive learning outcomes (CLO) of students who use multiple representation-based e-modules with students who use other teaching materials without being based on multiple representations on buffer solution materials and to determine the percentage of effective contribution. The subjects of this study were students of class XI MIPA at one of the high schools in Yogyakarta. The sampling technique carried out is cluster random sampling with a quasi-experiment method by posttest-only control group design. The instruments used are questionnaires on self-regulated learning and cognitive learning outcomes. The data analysis technique used in the field test results used Hotelling's Trace test and the results of effective contribution were obtained from the Partial Eta Squared value. The results showed that the significance value of 0.000 < 0.05 so that H0 was rejected, which means that there are differences in SRL and CLO of students between students who use multiple representation-based e-modules and students who use other teaching materials without multiple representations based on buffer solution materials. The percentage of effective contribution of the use of e-modules to SRL by 16.5%, CLO by 11.8%, and SRL and CLO by 20.3%.

Differences in Self-Regulated Learning Between Gifted Students, Students with Special Needs and Other Students in Slovenian Schools

Differences in Self-Regulated Learning Between Gifted Students, Students with Special Needs and Other Students in Slovenian Schools

Effect of Electronic Modules on Self-regulated Learning and Cognitive Learning Outcomes on Chemical Bonding Material

This study aims to the effect of guided inquiry-based electronic modules on self-regulated learning and cognitive learning outcomes. The research design uses a quasi-experimental post-test only. This research was conducted on students of class X Natural Science in Yogyakarta using the cluster random sampling technique. The instrument used in this research is a self-regulated learning questionnaire and cognitive learning outcomes test. The data analysis technique uses Hotelling’s T-Test to test whether there are differences in self-regulated learning and cognitive learning outcomes with the implementation of electronic modules. The results show that the significance value is 0.002 < 0.05. This means that there is a difference in self-regulated learning and cognitive learning outcomes between students who use the guided inquiry-based electronic module and those who do not use the electronic module.

Leveraging complexity frameworks to refine theories of engagement: Advancing self‐regulated learning in the age of artificial intelligence

AbstractCapturing evidence for dynamic changes in self‐regulated learning (SRL) behaviours resulting from interventions is challenging for researchers. In the current study, we identified students who were likely to do poorly in a biology course and those who were likely to do well. Then, we randomly assigned a portion of the students predicted to perform poorly to a science of learning to learn intervention where they were taught SRL study strategies. Learning outcome and log data (257 K events) were collected from n = 226 students. We used a complex systems framework to model the differences in SRL including the amount, interrelatedness, density and regularity of engagement captured in digital trace data (ie, logs). Differences were compared between students who were predicted to (1) perform poorly (control, n = 48), (2) perform poorly and received intervention (treatment, n = 95) and (3) perform well (not flagged, n = 83). Results indicated that the regularity of students' engagement was predictive of course grade, and that the intervention group exhibited increased regularity in engagement over the control group immediately after the intervention and maintained that increase over the course of the semester. We discuss the implications of these findings in relation to the future of artificial intelligence and potential uses for monitoring student learning in online environments. Practitioner notesWhat is already known about this topic Self‐regulated learning (SRL) knowledge and skills are strong predictors of postsecondary STEM student success. SRL is a dynamic, temporal process that leads to purposeful student engagement. Methods and metrics for measuring dynamic SRL behaviours in learning contexts are needed. What this paper adds A Markov process for measuring dynamic SRL processes using log data. Evidence that dynamic, interaction‐dominant aspects of SRL predict student achievement. Evidence that SRL processes can be meaningfully impacted through educational intervention. Implications for theory and practice Complexity approaches inform theory and measurement of dynamic SRL processes. Static representations of dynamic SRL processes are promising learning analytics metrics. Engineered features of LMS usage are valuable contributions to AI models.

Self-regulated learning of primary school teachers, reviewed from external factors

This study aims to examine the overview and differences in self-regulated learning among elementary school teachers in terms of external factors such as teacher income, job position, and school status. The participants were 72 primary and junior high school teachers from North Sumatra recruited using an incidental sampling method. The measuring instrument employed is a self-regulating learning scale set up by the characteristics indicated by Pintrich, Smith, Garcia, and McKeachie (1991). The results show that self-regulated learning instructors are in the top group, and there is no difference in self-regulated learning teachers in terms of salary, work position, or school status.

Efektivitas layanan informasi menggunakan teknik problem-based learning untuk meningkatkan self regulated learning siswa

This research is motivated by the problems of students' self-regulated learning . This can be seen in the students when studying, there is no preparation for learning by students, students do not pay attention to the teacher during learning activities, lack of student responsibility for the assignments given by the teacher. Efforts made to improve student self-regulated learning are information services using a problem-based learning approach. The aims of this study were (1) to analyze the differences in the self-regulated learning of students in the experimental group before and after being given information services using a problem-based learning approach, (2) to analyze the differences in self-regulated learning of students in the control group before and after being given information services without using a problem-based approach learning, (3) testing the effectiveness of information services using a problem-based learning approach to improve student self-regulated learning . This study used an experimental design with a pretest and posttest control group design. The subjects in this study were 70 students at MTsN 1 City of SungaiFull, with a low self-regulated learning category . The instrument used in this study is a self-regulated learning instrument with a Likert scale. The technique used by purposive sampling. Data were analyzed using the Wilcoxon Signed Ranks Test and the Kolmogrof Smirnov 2 Independent Sample test with the help of SPSS version 20.00. The results of this study indicate that information services using a problem- based learning approach are effective in increasing student self-regulated learning . The results of this study can be used as a reference in assisting counseling guidance service programs, especially using a problem-based learning approach to overcome students' low self-regulated learning.

What Can Off- and Online Measures Tell about Students’ Self-Regulation and Their Achievement While Learning Science Expository Hypertext

Self-regulated learning (SRL) plays an important role in successful learning with hypertexts. The use of appropriate SRL strategies helps students acquire new knowledge more efficiently. We investigated the use of SRL strategies in individual learning from expository science hypertext, the correlations between different measures of self-regulation, and the differences in SRL between more and less successful students. A sample of 443 ninth graders from 15 different schools participated in the study. A variety of off- and online measures were used to measure SRL. Data were collected from student traces, questionnaires, tests scores, and notes. Low correlations between the off- and online measures of SRL suggest that they measure different aspects of SRL use in learning digital science texts. Student achievement in science positively correlated with their use of SRL strategies. Students with higher knowledge gains reported the higher use of deep cognitive strategies, higher motivation for learning, and used a higher number of strategies in note-taking while learning. The results of this study may have practical implications for teachers to support student SRL and for developers of digital learning materials to incorporate SRL scaffolding into learning topics.

Exploring the link between self‐regulated learning and learner behaviour in a massive open online course

AbstractBackgroundLearners in Massive Open Online Courses (MOOCs) are presented with great autonomy over their learning process. Learners must engage in self‐regulated learning (SRL) to handle this autonomy. It is assumed that learners' SRL, through monitoring and control, influences learners' behaviour within the MOOC environment (e.g., watching videos). The exact relationship between SRL and learner behaviour has however not been investigated.ObjectivesWe explored whether differences in SRL are related to differences in learner behaviour in a MOOC. As insight in this relationship could improve our understanding of the influence of SRL on behaviour, could help explain the variety in online learner behaviour, and could be useful for the development of successful SRL support for learners.MethodsMOOC learners were grouped based on their self‐reported SRL. Next, we used process mining to create process models of learners' activities. These process models were compared between groups of learners.Results and conclusionsFour clusters emerged: average regulators, help seekers, self‐regulators, and weak regulators. Learners in all clusters closely followed the designed course structure. However, the process models also showed differences which could be linked to differences in the SRL scores between clusters.TakeawaysThe study shows that SRL may explain part of the variability in online learner behaviour. Implications for the design of SRL interventions include the necessity to integrate support for weak regulators in the course structure.

Gender Differences in Self-Regulated Online Learning During the COVID-19 Lockdown.

Due to the spread of the epidemic around the world, online learning has received greater attention. Self-regulated learning (SRL) is an important factor for students to achieve academic success. This study investigated the gender differences in SRL and three sub-constructs of SRL in the context of online learning, that is the preparatory, performance, and appraisal phases. A total of 400 high school students (males = 125, females = 275) from China participated in this study. In order to identify whether there were gender differences in their self-regulated online learning (SROL), independent sample t-test was performed. The results showed that there were significant gender differences in the SROL (t = –3.334, p = 0.001 < 0.01, d = –0.410) and the three sub-constructs of SROL (preparatory: t = –0.702, p = 0.008 < 0.01, d = 0.018; performance: t = –3.801, p = 0.000 < 0.01, d = 0.456; appraisal: t = –3.120, p = 0.002 < 0.01, d = 0.361). The findings indicated that females performed better than males in all three dimensions of learners’ online self-regulated learning.

Perbedaan Self-Regulated Learning Pada Siswa Kelas Internasional dengan Siswa Kelas Reguler di SMA Shafiyyatul Amaliyah Medan

Method used in this research is the comparative method. The population in this study were all students of class X and XI SMA Shafiyyatul Amaliyah, namely 210 students. International class with a total of 30 in the regular class with a total of 180 students. The number of samples is 60 samples, 30 from the international class and 30 from the regular class. The technique used in sampling the two sample groups is the random sampling technique, meaning that all members in the population have the same opportunity to be selected as samples. Based on the calculation results of theanalysis t-test, it is known that there are differences in self-regulated learning between international class students and students in regular classes. This result is known by looking at the value or coefficient of difference in the ttest of 5.652 with a significance of 0.000 (p

MOTIVASI DAN KEMANDIRIAN BELAJAR PADA MAHASISWA BARU

This study aims to determine learning independence which is influenced by the learning motivation of new students. A total of 460 new students of class 2019 were involved in this research. The instrument used was a scale of self-regulated learning and a scale of learning motivation. The data analysis used is the assumption test, hypothesis test, and difference test. The results show 1) based on the assumption test that the research data is proven normality and linearity; 2) based on the hypothesis test that there is a positive relationship between learning motivation and self-regulated learning (r = 0.770; p &lt;0.01), and there is an effect of learning motivation on self-regulated learning (R² = 0.592; p &lt;0.01); 3) based on different tests that there are differences in self-regulated learning based on student demographic factors [F = 1.321, p &lt;0.05].Learning Motivation

Individual differences in self-regulated learning: Exploring the nexus of motivational beliefs, self-efficacy, and SRL strategies in EFL writing

This study examines the predictive effects of motivational beliefs and self-efficacy on multiple dimensions of self-regulated learning (SRL) strategies in English as a foreign language (EFL) writing. Undergraduate students ( n = 389) were recruited voluntarily from four universities in mainland China. They were invited to complete a set of questionnaires to measure their motivational beliefs (extrinsic and intrinsic goal orientation, task value, and control of learning belief), self-efficacy (linguistic self-efficacy, performance self-efficacy, and self-regulatory efficacy) and SRL strategies (cognition, metacognition, social behavior, and motivational regulation). Multiple regression analyses revealed that motivational beliefs had significant predictive effects on SRL strategies; among which task value and intrinsic goal orientation were significant predictors of nine sub-factors of SRL strategies. Self-efficacy was a strong predictor of metacognitive, cognitive, and motivational regulation strategies. While linguistic self-efficacy had a significant predictive power on text processing alone, self-regulatory efficacy generated a significant effect on a collection of SRL strategies including knowledge rehearsal, goal-oriented monitoring, idea planning, peer learning, and interest enhancement. Pedagogical implications are also discussed.

Secondary students’ online self-regulated learning during flipped learning: A latent profile analysis

Flipped learning (FL) makes greater use of students' self-regulated learning (SRL) skills when they regulate their online learning behavior. Previous research has shown the value of SRL support during FL to enhance students' SRL and learning outcomes. However, as previous studies have indicated that SRL behavior varies, should SRL support be tailored to these differences in SRL? We applied latent profile analysis to identify subgroups in 150 eighth-graders during FL. We used practically relevant online behavioral data to represent students’ online SRL activities, which we gathered unobtrusively in an ecologically valid secondary educational classroom setting. We found five distinct SRL profiles from low completion and no activity to full completion and very high activity. In addition, students in the profile who showed low SRL activity achieved significantly worse learning outcomes than students in the three profiles with higher SRL activity. Finally, we explored whether SRL activity profile membership can be explained by student characteristics (i.e., self-reported SRL, motivation, and prior knowledge). None of the student-level variables predicted profile membership, but our approach offers leads for future research to further investigate the potential of tailored SRL support.

Individual Differences in Self-regulated Learning of College Students Enrolled in Online College Courses

ABSTRACT With online course delivery on the rise, it is essential to understand the preparedness of students attending traditional universities. Prior research has found that some students struggle in online courses, which leads to a quest to better understand the reason why. Studies of self-regulated learning (SRL) in online and blended courses have added to our understanding. However, few studies have used a person-centered approach to study profiles of SRL in fully online courses, and none with a population of students attending a traditional university. This is of importance, especially at a time when traditional universities are increasingly providing online courses. To address the gaps in previous SRL profile research, the current study examined individual differences in SRL profiles of 477 students attending online courses at a traditional university setting, using the Online Self-regulated Learning Questionnaire (OSLQ). Using latent profile analysis, we found four different profiles, with a majority of the students falling in groups representing lower levels of SRL skills. We also explored the possible relationship of experience in online learning, online comfort, age, and gender with the identified self-regulated learning profiles. Relationships were found between the profiles and comfort level as well as with gender.

STUDI KOMPARATIF SELF REGULATED LEARNING SISWA ASRAMA DAN NON-ASRAMA DI SMA IT IZZUDDIN PALEMBANG

In IT Izzuddin High School Palembang, after the learning activities are finished students/students have a different environment. Consists of boarding students and non-boarding students. The existence of environmental differences will certainly provide different support and obstacles. Starting from this the researcher wants to compare the self-regulated learning of boarding and non-boarding students with the title “Comparative Study of Self Regulated Learning of Dormitory and Non-Boarding Students at IT Izzuddin Palembang High School”. This study aims to determine whether there are differences in self-regulated learning between boarding students and non-boarding students at IT Izzuddin Palembang High School.This research method uses a quantitative approach. This type of research is comparative research. The population in this study were all students of IT Izzuddin Palembang High School it the 2019/2020 school years, totaling 140 students, consisting of 69 boarding students and 71 non-boarding students. From this population, a sample of 60 boarding students and 63 non-boarding students was taken. The sampling technique is proportionate stratified random sampling. After the content validity test, Cronbach's alpha coefficient of 0.730 was obtained. The result is &gt; 0.6 then the instrument is reliable. Methods of data analysis using t-test and then given an interpretation of the results.Based on the results og the hypothesis test, t = 2.777 with p = 0.006. Because the value of p &lt; 5% (0.006 &lt; 0.05) then H0 is rejected and H1 is accepted, there is a significant difference in self-regulated learning between boarding and non-boarding students at IT Izzuddin Palembang High School where the level of self-regulated learning of boarding students is higher compared to no

Gender differences on students’ self-regulated learning in mathematics

Self-regulated learning (SRL) is a process carried out by students on their awareness in formulating goals, determining strategies, motivating and monitoring themselves in learning and evaluating the results of their learning. This study aims to describe the SRL of junior high school students in learning mathematics from gender differences. The method used in this research is quantitative descriptive. The study was conducted at SMPN 1 Pecangaan. The sample used was 73 8th-grade students, consisting of 35 male students and 38 female students. The data were retrieved by using a questionnaire with Likert scale. The results of this study indicated that there were differences in SRL between male and female students in learning mathematics based on independent t-test (0.001< 0.05). Female students were superior in each indicator of all aspects of SRL, namely metacognition, motivation, and active involvement in learning activities. It can be concluded that female students have better SRL in learning mathematics compared to male students.

Differences in Self-Regulated Learning (SRL) and Online Learning Satisfaction Across Academic Disciplines: A Study of a Private University in Malaysia

Students’ online learning satisfaction is an important variable used to measure attainment of learning outcomes in blended learning courses. Previous studies found that learners who portray a high level of SRL contributed positively to online learning satisfaction. To date, research has also shown that students display different level of online learning satisfaction under different academic disciplines. Therefore, this quantitative research aims to investigate if students’ SRL abilities significantly influence their online learning satisfaction in blended learning courses and if differences exist in online learning satisfaction across multiple academic disciplines. A set of online self-reported questionnaire was posted through the official LMS of the university to collect data from 497 undergraduate students in a private university in Malaysia. The results from the multiple regression analysis revealed that SRL explained 40.2% of the variability in online learning satisfaction (OLS). In addition, the results from one-way ANOVA with Tukey Post Hoc analysis revealed that OLS level was significantly different statistically between students in Health &amp; Medical science discipline and Innovation &amp; Technology discipline. The outcomes of this research provide insights as to where future efforts need to be directed, especially in the areas related to the development of students’ self-regulated learning (SRL) abilities.