Exploring the combined effects of group awareness support and students’ self-regulated learning levels on socially shared regulation of learning and learning outcomes in CSCL

Self-regulated learning is one of the growing aspects in the field of educational psychology. It plays a very important role in the academic success of the students. In addition, the failure of self-regulation resulted in academic procrastination. Academic procrastination is recurring behavior of students. The objective of the present study is to find out the levels of self-regulated learning, levels of academic procrastination, and the influence of self-regulated learning on the academic procrastination of the students. The present study was a Descriptive survey and questionnaire-based. The study was performed in the Kamrup (M) colleges of Assam affiliated with Gauhati University. The sample of the present study was 142 college students both boys and girls. The data were collected both offline and online. To run the statistical test, SPSS was used. Z score, percentage, Chi-square, correlation, and regression analyses were performed to test the null hypotheses and find out the objectives. The result indicates that college students are self-regulated learners as all the students fall under the extremely high level of self-regulated learning to average level of self-regulated learning. Again they are also an academic procrastinator. It was also indicated that there is a significant negative correlation between self-regulated learning and academic procrastination. Also, regression analysis indicated that self-regulated learning is a strong predictor of academic procrastination of college students. The level of students' self-regulated learning and academic procrastination must be pointed out in order to ensure the student's academic success.

Learning to learn and learning to cooperate are two important goals for individuals. Moreover, self regulation has been identified as fundamental to prevent school failure. The goal of the present study was to assess the interactions between self-regulated learning, cooperative learning and academic self-efficacy in secondary education students experiencing cooperative learning as the main pedagogical approach for at least one school year. 2.513 secondary education students (1.308 males, 1.205 females), 12–17 years old (M = 13.85, SD = 1.29), enrolled in 17 different schools belonging to the National Network of Schools on Cooperative Learning in Spain agreed to participate. They all had experienced this pedagogical approach a minimum of one school year. Participants were asked to complete the cooperative learning questionnaire, the strategies to control the study questionnaire and the global academic self-efficacy questionnaire. Participants were grouped based on their perceptions on cooperative learning and self-regulated learning in their classes. A combination of hierarchical and κ-means cluster analyses was used. Results revealed a four-cluster solution: cluster one included students with low levels of cooperative learning, self-regulated learning and academic self-efficacy, cluster two included students with high levels of cooperative learning, self-regulated learning and academic self-efficacy, cluster three included students with high levels of cooperative learning, low levels of self-regulated learning and intermediate-low levels of academic self-efficacy, and, finally, cluster four included students with high levels of self-regulated learning, low levels of cooperative learning, and intermediate-high levels of academic self-efficacy. Self-regulated learning was found more influential than cooperative learning on students’ academic self-efficacy. In cooperative learning contexts students interact through different types of regulations: self, co, and shared. Educators should be aware of these interactions, symmetrical or asymmetrical, because they determine the quality and quantity of the students’ participation and achievements, and they are key elements to prevent school failure.

In the literature, studies on technology-supported learning, especially using LMS, have been widely carried out during a pandemic. However, little is known about LMS, which is interesting and helps to develop students' statistical reasoning abilities for online learning by considering the students' Self-Regulated Learning (SRL) levels (High, medium and low). This study aims to examine and analyze the differences in statistical reasoning abilities of students who study using LMS in terms of SRL levels (high, medium and low). This study uses a quantitative method with the type of One-group pre-test post-test design. What took sampled randomly at the University of Pasundan Bandung, totalling 54 third-level students of Pasundan University Bandung, Indonesia. Research data related to statistical reasoning abilities were collected through a test consisting of six questions. In contrast, SRL level data were collected using a questionnaire consisting of 46 question items. Paired t-test and One-way ANOVA analysis were applied to answer the research hypothesis. The results of the study concluded that students studying with LMS with High SRL obtained a higher increase in statistical reasoning ability than students studying with LMS with Medium and low SRL categories, with the criteria for improvement in the three categories being in the high and medium improvement categories. Research findings related to learning using LMS can be used as an alternative learning model in online learning situations.

Despite their potential to deliver a high-quality learning experience, massive open online courses (MOOCs) pose several issues, such as high dropout rates, difficulties in collaboration between students, low teaching involvement, and limited teacher–student interaction. Most of these issues can be attributed to the large number, diversity, and variation in self-regulated learning (SRL) skills of participants in MOOCs. Many instructional designers try to overcome these issues by incorporating collaborative activities. Others try to scaffold students’ SRL levels by making SRL-focused interventions. However, limited research combines the study of SRL-focused interventions with students’ engagement in collaborative activities, course retention, and learning outcomes of MOOC environments. We deployed a programming-oriented MOOC in which we incorporated chat-based collaborative activities, supported by a learning analytics dashboard. Students were asked to complete SRL-focused questionnaires at the beginning and the end of the course. Based on their score, we calculated an average score that forms their SRL level, creating three groups: (a) control, (b) general intervention, and (c) personalized intervention in which we provided personalized interventions. We compared the students’ learning outcomes, participation in collaborative activities, and retention in the MOOC. These comparisons provided evidence regarding the positive impact of different intervention modes on students’ engagement in collaborative activities and their learning outcomes, with respect to their various SRL profiles. Students allocated to the general and personalized intervention groups displayed increased participation in the collaborative activities and learning outcomes, as compared to students assigned to the control group. We also documented that the SRL interventions positively affected students’ course retention.

The effect of self-regulated learning on college students' perceptions of community of inquiry and affective outcomes in online learning

This study aims to analyze the relationship between the use of ChatGPT and the self-regulated learning of students in the Islamic Education Department (PAI) at UIN Raden Intan Lampung. In line with technological advancements, ChatGPT, an artificial intelligence-based tool, has increasingly been utilized in various academic activities, including supporting independent learning processes. This research employs a quantitative approach using a correlational method, where data is collected through a questionnaire measuring both the frequency of ChatGPT use and the level of students' self-regulated learning. The sample consists of 33 randomly selected PAI students. Data analysis was conducted using Pearson correlation analysis to determine the relationship between the two variables. The results indicate a significant and positive relationship between the use of ChatGPT and students' self-regulated learning, meaning that the more frequently students use ChatGPT, the higher their level of self-regulated learning. These findings highlight the potential of ChatGPT as an effective tool for enhancing students' self-regulated learning in the digital age and provide recommendations for developing technology-based learning strategies in higher education.

ObjectivesTo explore the influence of critical thinking,self-regulated learning and system usability on the acceptance of e-learning onpatient safety.MethodsA cross-sectional study was conducted, using a 32-questiononline survey. One hundred ninety-three (n=193 medical students participated inthe study and were asked to rate levels of reflective thinking, self-regulatedlearning and attitudes towards patient safety using scales from theQuestionnaire for Reflective Thinking, the Attitudes to Patient SafetyQuestionnaire and the System Usability Scale. Differences between reflectionlevels were calculated using paired t-tests, associations between criticalthinking and self-regulated learning were calculated using linear correlations.We performed linear multiple regression analysis to identify predictors forstudent acceptance of the e-learning.ResultsStudents (n=193) engaged in intermediate levels ofreflection (5-point Likert, M=3.62, SD=0.73) and significantly (t(143)=15.15,p<0.001, d=1.57) lower levels (M=2.35, SD=0.87) of critical reflection. Moststudents showed high (≥ 4; 44.1%) or intermediate (<4 level > 2; 29.4 %)levels of self-regulated learning. A regression model indicated that 5predictors (Reflection, critical reflection, self-regulated learning,relevance, usability) explained 65.3% of the variance (R²=0.653, F(5, 96)=39.02,p<0.01) of perceived total quality.ConclusionsThis study shows that reflection and learning skillsare important factors for e-learning acceptance, but perceived relevance andsystem usability play a more important role. From a didactic perspective, it is indispensable to provide the studentswith sufficient examples and links to professional practice to enhance theperception of relevance and to improve system usability permanently.

Team-Based Learning (TBL) has been widely applied in different fields (courses) and has been indicated to be efficient. Meanwhile, many studies have asserted that Group awareness (GA) information, which visually displays peers’ learning context and activities, can increase peer participation within an online collaborative learning environment. As the level of preparation by students before class affects their subsequent learning performance in the TBL process, this study incorporates GA information into the preparation stage of TBL process and further develops the online TBL + GA system in order to raise peer preparation level. Furthermore, self-regulated learning (SRL) levels of a student and online learning environment interactively influence learning effectiveness. Accordingly, this study further investigates how the TBL + GA environment influences students with different SRL levels. Two freshman classes were randomly chosen, with one as the control class (using the traditional TBL) and the other as the experimental class using the TBL + GA. Analytical results indicate that although the two classes do not reach significance overall on preparation level, TBL + GA can significantly enhance preparation levels for high-SRL students, but not low-SRL students.

he system employing semester credit units requires students' good self-regulated learning in order that they attain learning goals successfully. The present article concerns a research aimed at knowing (l) of what level mechanical engineering students' self­ dependence in learning was as seen from both their self-stated views about their self-regulated learning and their self-regulated learning in practice; (2) whether there was any difference in level of self­ regulated learning among those having different types of high school educational background; (3) whether there was any difference in level of self-regulated learning among those having studied for different numbers of semesters; and (4) whether the environment where they live influences their self-dependence in learning, or, in other words, their self-regulated learning. The research employed a positivistic approach which was exploratory in nature. The population consisted of 254 students of the Mechanical Engineering Education Study Program, Faculty of Engineering, State University of Yogyakarta, who were taking courses in one even-numbered semester or another in the academic year of 2005/2006. The sample size was 228 and the research subjects were randomly selected. The data were compiled by using a closed self-report type of questionnaire using a Linkert-type scale model. The data were analyzed by means of non-parametric statistics using the Kruskal-Wallis Test and the Mann-Whitney U Test since the data distribution did not fulfill the inferential parametric analysis assumption The research findings indicate that (1) the level of the students' self-regulated learning was very good though the mean score for their self-regulated learning in practice is lower than that for their self-stated views about their self-regulated learning; (2) there is no difference in level of self-regulated learning between those with a general high school educational background and those with a vocational high school educational background, according to both their self-stated views on it and their self-regulated learning in practice; (3) there is no difference in level of self-regulated learning between those who live with their family and those who live at some off-campus housing, according to both their self-stated views on it and their self-regulated learning in practice; and (4) there is no difference in level of self-regulated learning among those having studied for different numbers of semesters, according to both their self-stated views on it and their self-regulated learning in practice, excluding the views of those in their second semester on their self­ regulated learning

The purpose of this study is to determine students’ levels of self-regulated learning by adjusting MotivatedStrategies for Learning Questionnaire (MSLQ) developed by (Pintrich et al., 1993). This study involved 436undergraduate students. The validity of instrument used was checked by convergent validity and discriminatevalidity in Structural Equation Modeling. The reliability of scale was measured by internal consistency analyseswhilst students’ levels of self-regulated learning detected by descriptive analyses involving percentage,frequency, means, t-tests and standard deviation . As a result it can be concluded that MSLQ is recognized as avalid and reliable scale in order to examine levels of self-regulated learning among university students inMalaysia. Besides, the students’ self-regulated learning strategies are found to be generally in the middle range;their highest level of skills being Effort regulation, whereas the lowest skill is Metacognitive strategies. Thestudents’ level of self-regulated learning in social sciences faculties was significantly lower than students inscience faculties.

Bebras task is a problem solving problem that integrates computational thinking in it, which the stages in computational thinking consist of: decomposition, abstraction, algorithm, and pattern recognition. This study aims to describe the profile of student’s computational thinking based on the level of self-regulated learning in completing bebras task. This study is a qualitative-descriptive study with three research subjects based on the level of students’ self-regulated learning, namely high self-regulated learning, medium self-regulated learning, and low self-regulated learning. The results of this study indicate that students with different levels of self-regulated learning have different computational thinking ability in completing bebras task. Student with high level of self-regulated learning can reach the stages of decomposition, abstraction, algorithm, and pattern recognition. Student with medium level of self-regulated learning can reach the stages of decomposition, absraction, and algorithm. Student with low level of self-regulated learning can reach the stage of decomposition only. Student with low level of self-regulated learning do not yet reflect independence in learning.

This study examines how 2×2 Achievement Goal Orientations (AGO) relate to Self-Regulated Learning (SRL) levels in pre-service music teachers, considering variables that influence these orientations. The research found that female pre-service music teachers showed higher achievement orientations than males, especially in Learning-Approach and Learning-Avoidance Orientations. Different grade levels and study habits also impacted these orientations. Students who studied more displayed greater Learning-Approach Orientation and SRL. Females had higher SRL scores, particularly in Planning, Goal Setting, and Strategy Use. Academic achievers showed more positive orientations and lower Learning Dependency. These insights can guide interventions and support systems for pre-service music teachers, enhancing learning outcomes and teacher education programs.

Recent advances in technology-enhanced language learning (TELL) emphasize innovative methods to improve speaking skills in English for specific purposes (ESP) classes, particularly for Law students. However, research comparing the effectiveness of digital storytelling (DST) and video-assisted instruction (VAI) in developing speaking performance remains limited, particularly in relation to students' self-regulated learning (SRL) levels. This study explores the impact of DST and VAI on speaking performance across SRL levels through a quasi-experimental research design. A total of 48 undergraduate ESP students majoring in Law at a private university in Indonesia were categorized into higher and lower self-regulation groups. The data were collected through an SRL questionnaire and speaking tests and analyzed using two-way ANOVA and independent samples t-tests. The results revealed that students in the DST group significantly outperformed those in the VAI group (Sig. = 0.009). However, no significant interaction effect was found between SRL, instructional approach, and speaking proficiency. The finding implies that DST enhances speaking proficiency by combining structured oral production with creative narrative development, requiring students to rehearse, refine, and integrate linguistic elements in an authentic context. EFL teachers should integrate DST in their classes to improve communication skills in professional and academic settings.

This study aims to identify student learner profiles based on a combination of prior knowledge and Self-Regulated Learning (SRL) levels and to analyze the differential impact of an adaptive learning module on knowledge and SRL improvement in each profile. Using a mixed-methods explanatory sequential design, 92 undergraduate physics education students were selected through purposive sampling. K-Means cluster analysis was applied to form learner profiles, followed by a six-week pre–post intervention and qualitative interviews. The results identified three learner profiles (Proficient-Autonomous Learner, Resilient-Developing Learner, and Proficient-Fragile Achiever). The result showed that the adaptive module significantly improved Results showed significant knowledge gains across profiles, while SRL improvements differed significantly. The Proficient–Fragile Achiever group demonstrated the largest SRL gain (p &lt; .001; large effect size, d &gt; 0.80), associated with more frequent scaffolding support. In conclusion, the effectiveness of adaptive modules is highly dependent on learner profiles, with the most significant benefits in their ability to provide external support for building self-regulation skills. These findings imply that learning technology design should incorporate SRL as a key variable for personalization, and institutions can utilize these platforms as intervention tools for students with weak learning independence.

PurposeThe purpose of this study was to construct a multi-center cross-sectional study to predict self-regulated learning (SRL) levels of Chinese medical undergraduates.MethodsWe selected medical undergraduates by random sampling from five universities in mainland China. The classical regression methods (logistic regression and Lasso regression) and machine learning model were combined to identify the most significant predictors of SRL levels. Nomograms were built based on multivariable models. The accuracy, discrimination, and generalization of our nomograms were evaluated by the receiver operating characteristic curves (ROC) and the calibration curves and a high quality external validation.ResultsThere were 2052 medical undergraduates from five universities in mainland China initially. The nomograms constructed based on the non-overfitting multivariable models were verified by internal validation (C-index: learning motivation: 0.736; learning strategy: 0.744) and external validation (C-index: learning motivation: 0.986; learning strategy: 1.000), showing decent prediction accuracy, discrimination, and generalization.ConclusionComprehensive nomograms constructed in this study were useful and convenient tools to evaluate the SRL levels of undergraduate medical students in China.