Characteristics Of Self-regulated Learning Research Articles

Self-Regulated Learning in Science Classes with a Discovery Learning Environment and Collaborative Discovery Learning Environment

The study aims to compare how discovery learning and collaborative discovery learning affect knowledge acquisition, the development of understanding through phases of self-regulated learning (SRL), and the use of SRL strategies at the individual level. The sample consists of 981 eleven-year-old students. The results show that both methods have a positive effect on knowledge acquisition. Collaborative discovery learning has more positive effects on the development of students’ understanding by developing collaborative skills. Motivational strategies (especially in girls) are more developed in collaborative discovery learning than in discovery learning. Students who show more pronounced negative characteristics of self-regulation also achieve poorer results in the knowledge test, and this is more pronounced in students who have participated in discovery learning. The tendency of an affirmative attitude towards the characteristics of SRL in the entire population of students indicates a proportional growth in accordance with success in learning, but in more successful students, it indicates a uniform retention of an affirmative attitude. The tendency toward an affirmative attitude regarding the characteristics of collaborative learning is inversely proportional to students’ success, with a more pronounced attitude decrease in more successful students.

The Investigation of Self-Regulated Learning among Low Proficiency EFL Students

This study aimed at investigating (1) the characteristics of self-regulated learning (SRL) among low proficiency EFL students and (2) the variation for SRL among students with different English proficiency. Participants were 85 Thai university students who were categorized as low proficiency EFL students based on their Test of English for International Communication (TOEIC) score. These students were divided into two groups: G1 and G2. The results revealed that students in the G1 group had a significantly lower TOEIC score than the students in the G2 group. For the investigation of SRL, the exploratory factor analyses (EFA) demonstrated ten subscales: Five for motivational and five for learning strategy factors. Multiple regressions that determined the influences of SRL on proficiency revealed that the students who possessed higher task value and intrinsic goal orientation were more proficient. On the contrary, if the students had higher test anxiety, they were less proficient. Students in the G1 and G2 groups differed significantly for extrinsic goal orientation. The students in the G2 group (with higher TOEIC score) had more extrinsic goal orientation than did the G1 group students. For Learning strategy in SRL, a multiple regression for learning strategy factors revealed that there were correlations between elaboration and critical thinking and proficiency of Thai EFL students. This factor was a significant predictor of the variation of proficiency. Significant differences were also found between the G1 and G2 groups in peer learning. The lower proficient group tended to rely more on their peers and seek for help. For pedagogical implications, teachers need to provide motivational environments in order to improve the mental state of low proficiency students. Attention should be paid to students who cannot perform well in class in order to raise their confidence and lessen anxiety in learning English.

An Empirical Study on the Relationship between Cognition and Metacognition in Technology-Enhanced Self-Regulated Learning

Self-regulated learning (SRL) has become an indispensable ability for learners to succeed in self-study. A fast-growing number of learners worldwide opt for studying via technology-enhanced learning environments (TELEs) to enrich their education. Since the outbreak of the global COVID-19 pandemic, learners have relied more and more on online and distance learning for their own education purposes; this circumstance urges learners to self-regulate their learning processes. Striving for understanding learners’ SRL ability in TELEs to provide them with sufficient support, this research analyzed the relationship between the two key factors of SRL, cognition and metacognition, from the context of self-study in TELEs. Applying our proposed hypothetical model on the relationship between cognition and metacognition, we conducted a pilot study in which 20 postgraduate students solved a complex academic task delivered via a TELE—the learning management system Moodle. In this experiment, the correlation between the students’ cognitive and metacognitive scores was analyzed. The experimental results showed that there is a positive linear correlation between cognition and metacognition of a learner when he or she performs a complex task in TELEs, and such a correlation can be classified into different profiles. Implications include opportunities to help learners understand their SRL profiles and provide recommendations for further research on the granularity of SRL characteristics.

The Japanese EFL Learners' Self-Regulated Language Learning and Proficiency

The purpose of this study was to explore the relationship between learners’ self-regulated language learning and proficiency and to examine the differences in characteristics of self-regulated learning (SRL) between low- and high-proficiency learners. SRL is a learning process throughout setting goals, monitoring tasks, and reflecting on performance, which includes both cognitive and affective aspects. Participants were 97 Japanese university students of English. Based on their proficiency, 67 out of them were assigned to the L group and 30 to the H group in order to compare the difference of their SRL skills. They all took the Motivated Strategies for Learning Questionnaire (MSLQ) online to measure their SRL skills and reported their latest TOEIC scores to determine their English proficiency. The MSLQ includes 81 items that were administered on the website for ease of access. Exploratory factor analyses determined five motivational and six learning strategy factors. Based on these factors, multiple regressions and t-tests were performed. Multiple regressions examining the influences of SRLs on proficiency subsequently showed that three learning strategy factors in SRL―metacognitive strategies, effort regulation, and coping with problems―significantly predicted the variance in learners’ proficiency; no motivational factors predicted it, even though correlations between three out of five factors and proficiency were found, namely, self-efficacy, intrinsic goal orientation, and test anxiety. Later t-tests, however, showed significant differences in SRL between low- and high-proficiency learners in the following motivational and learning strategy factors: self-efficacy, intrinsic goal orientation, test anxiety, metacognitive strategies, effort regulation, and coping with problems. The findings suggest that although they did not directly account for learner proficiency, yet motivational factors were evidently related to English proficiency level. Based on these results, the characteristics of less proficient learners compared to those of more proficient learners are discussed.

The Role of Self-Regulation and Structuration in Mobile Learning

The roles of self-regulation and structuration in mobile learning are poorly understood. This study therefore examines these aspects in relation to the design and use of mobile technology in an online language learning setting. The online self-regulated learning (SRL) instrument was adopted to measure students' perceived level of self-regulation. Structuration Theory was applied as the theoretical lens for understanding students' technology-mediated learning practices. The results show that several factors defining learners' level of self-regulation were correlated with their mode of structuration. The analysis indicates that students' SRL characteristics are correlated with their structures regarding their technologies-in-practice and their practical assumptions about effectiveness in learning. An implication for practice is that students' SRL dimensions need to be taken into account when designing educational software for mobile technology. For research, this study has demonstrated the explanatory power of ST and how students' structures are related to their SRL characteristics.

Personal and behavioural variables and the self-regulated learning abilities of African learners

Accepting responsibility for one's learning is not only an important variable that influences effective learning, but is also one of the main characteristics of selfregulated learning. Self-regulated learners know how to use their knowledge of the personal (e.g. goal setting) and behavioural variables (e.g. learning strategies) that affect learning to their advantage. Within the context of self-regulated learning, much emphasis is placed on the role of the self and self-knowledge. In this article self-regulated learning and the role of the self are evaluated from a Christian perspective. In the research underlying this article it was established that, although there were some statistically significant relationships between some personal and behavioural variables and the self-regulated learning abilities of African students, these relationships were not of practical significance. The results of the research led to the conclusion that the subjects lacked knowledge of themselves as learners.