Students experience different levels of autonomy based on the mediation of self-regulated learning (SRL), but little is known about the effects of different mediation technologies on students' ...perceived SRL strategies. This mixed explanatory study compared two technology mediation models, Icourse (a learning management system) and Icourse+Pigai (an automatic writing evaluation system), with a control group that did not use technology. A quasi-experimental design was used, which involved a pre and post-intervention academic writing test, an SRL questionnaire, and one-to-one semi-structured student interviews. The aim was to investigate 280 Chinese undergraduate English as a foreign language (EFL) students' academic writing performance, lexical complexity, and perceptions of self-regulated strategies in academic writing. One-way ANCOVA of writing performance, Kruskal-Wallis test of lexical complexity, ANOVA of the SRL questionnaire, and grounded thematic content analysis revealed that, first, both Icourse and Icourse+Pigai provided significant support for the development of SRL strategies vs. the control group, although there was no significant difference between the two groups. Second, Icourse+Pigai-supported SRL was more helpful for improving students' academic writing performance because it enabled increased writing practice and correction feedback. Third, Icourse+Pigai-supported SRL did not significantly improve students' lexical complexity. In conclusion, we argue that both learning management systems and automated writing evaluation (AWE) platforms may be used to assist students' SRL learning to enhance their writing performance. More effort should be directed toward developing technological tools that increase both lexical accuracy and lexical complexity. We conclude that the technical tools used in this study were positively connected to the use of SRL techniques. However, when creating technologically mediated SRL activities, students' psychological study preferences should be considered.
Interactive ambulatory assessment offers a new approach to facilitate self-regulated learning in daily routine. 78 students were randomly assigned to the intervention (IG) and control group (CG). ...While preparing for a written exam, all the participants answered questions related to their learning behavior presented daily via electronic diaries (Phase 1). While preparing for a second exam (Phase 2), the CG completed the same assessment as in Phase 1, whereas the smartphones of the IG were fitted with intervening features to facilitate metacognitive strategy use. The IG was provided with near real-time feedback concerning their learning strategy use and personalized learning questions. Moreover, the IG completed a technology-based tutorial involving cognitive strategies before the beginning of Phase 2. Multilevel analyses revealed that cognitive and metacognitive strategies, internal resources and effectively used study time were associated with subjective learning success. The interventions promoted metacognitive strategies, internal resource-management strategies and subjective learning success.
•Smartphones were used to investigate self-regulated learning in daily routine.•Successful learning was characterized by an intensive use of learning strategies.•Effectively used learning time was associated with learning success.•Interactive Ambulatory Assessment fostered self-regulated learning in daily routine.•Feedback and learning questions supported metacognition.
•Challenge preference (CP) is an under-studied aspect of intrinsic motivation.•We tested CP as a predictor of elementary school academic achievement.•Controlling for executive functions, CP predicted ...math and English language arts.•Controlling for executive functions, CP predicted change in math.
Intrinsic motivation and executive functions (EFs) have been independently studied as predictors of academic achievement in elementary school. The goal of this investigation was to understand how students’ challenge preference (CP), an aspect of intrinsic motivation, is related to academic achievement while accounting for EFs as a confounding variable. Using data from a longitudinal study of 569 third-, fourth-, and fifth-graders (50% female), we tested students’ self-reported CP as a predictor of mathematics and English language arts (ELA) achievement in multilevel models that controlled for school fixed effects and student demographic characteristics. CP was positively associated with mathematics and ELA over and above the set of covariates and EFs. While also controlling for prior achievement, CP continued to explain a small amount of unique variance in mathematics, but not in ELA. These results underscore the importance of including measures of students’ intrinsic motivation, in addition to EFs, to obtain a comprehensive understanding of academic success.
Self-regulation is critical for successful learning, and socially shared regulation contributes to productive collaborative learning. The problem is that the psychological processes at the foundation ...of regulation are invisible and, thus, very challenging to understand, support, and influence. The aim of this paper is to review the progress in socially shared regulation research data collection methods for trying to understand the complex process of regulation in the social learning context, for example, collaborative learning and computer-supported collaborative learning. We highlight the importance of tracing the sequential and temporal characteristics of regulation in learning by focusing on data for individual- and group-level shared regulatory activities that use technological research tools and by gathering in-situ data about students’ challenges that provoke regulation of learning. We explain how we understand regulation in a social context, argue why methodological progress is needed, and review the progress made in researching regulation of learning.
Aim
The main aim of this commentary was to connect the insights from the contributions of the special issue on the intersection between depth and the regulation of strategy use. The seven ...contributions in this special issue stem from three perspectives: self‐regulated learning (SRL), model of domain learning (MDL), or the student approaches to learning (SAL).
Procedure
Prior to combining insights from different studies, the definition and operationalization of cognitive and metacognitive processing in the seven contributions is described. Subsequently, the grain size and statistical methods used in these contributions are discussed. This information allows us to – albeit cautiously – combine the results from the different studies regarding the relation between cognitive and metacognitive processing.
Conclusion
Deep processing and self‐regulation/monitoring showed a strong correlation, regardless of the theoretical framework or data collection method chosen. The strength of the correlation between surface processing and metacognitive processing differed, however, between the studies. Pathways for future research on students’ cognitive and metacognitive processing are suggested, at the methodological level as well as regarding the conceptualization of unregulated learning and surface processing.
Previous studies have reported mixed results regarding the relationship between students’ use of self-regulated learning (SRL) strategies and their performance in introductory programming courses. ...These studies were constrained by their reliance on self-report questionnaires as a means of collecting and analysing data. To address this limitation, this study aimed to employ eye-tracking and retrospective think-aloud techniques to identify differences in SRL strategy use for program comprehension tasks between high-performing students (N = 31) and low-performing students (N = 31) in an undergraduate programming course. All participants attended individual eye-tracking sessions to comprehend two Python program codes with different constructs. Their eye-tracking data and video-recalled retrospective think-aloud data were captured and recorded for analysis. The findings reveal that higher-order cognitive skills, such as elaboration and critical thinking, were mostly adopted by high-performing students, while basic cognitive and resource management strategy, such as rehearsal and help-seeking, were mostly employed by low-performing students when comprehending the program codes. This study not only demonstrates the design of combining eye-tracking and retrospective think-aloud data to explore students’ use of SRL strategies but also provides evidence to support the notion that program comprehension is a complex process that cannot be effectively addressed by employing merely rudimentary strategies, such as repetitively reading the same code segment. In the future, researchers could explore the possibility of using a webcam to monitor and assess students’ online programming processes and provide feedback based on their eye movements. They could also examine the effects of SRL strategies training on students’ motivation, engagement, and performance in various types of programming activities.
•61 undergraduates were enrolled in an introductory programming course.•We compared SRL strategy use for code reading in low- and high-performing students.•Eye-tracking and retrospective think-aloud data were combined for analysis.•High-performing students used more diverse and advanced cognitive strategies.
Abstract
This paper presents a theoretical perspective on the relationship between personality and self-regulated learning, by trying to study deeper the understanding of the relationship between the ...two constructs, based on the results of previous studies. Given the fact that the literature on the relationship between personality traits and the use of self-regulated learning strategies in the school environment is quite limited, we want to enrich the literature on this topic by summarizing a few relevant research results in this field. This paper includes a theoretical approach of the personality and self-regulated learning, by presenting their specifics and an analysis of the relationships between them, by synthesizing the results of a series of studies that have studied this relationship. The analyzed studies present various results, but most of them claim that personality traits represent important predictors of self-regulated learning and academic results. The results of the analyzed studies support especially the importance of conscientiousness as a predictor of self-regulated learning, being considered by some authors the most important component of personality. However, some studies have also identified positive relationships between extraversion, openness, neuroticism and agreeableness, and the use of self-directed learning strategies.
The purpose of the current study was twofold: (a) to investigate the developmental trends of 4 academic emotions (anxiety, boredom, enjoyment, and pride) and (b) to examine whether changes in ...emotions are linked to the changes in students' self-regulatory strategies (shallow, deep, and meta-cognitive) and achievement in mathematics. Four hundred and ninety-five Grade 7 students completed measures assessing their emotions and self-regulatory strategies in mathematics 3 times across 3 terms in a school year. Students' achievement for each term was collected from school records. Growth curve analyses showed that students' enjoyment and pride in mathematics declined, whereas boredom increased over time. Anxiety remained relatively stable across the study period. The growth curve analyses also showed that changes in positive emotions were systematically associated with changes in self-regulated learning and achievement. Overall, the results suggest that in addition to the "will" and the "skill," students need the "thrill" to succeed in school.
•Reciprocal relations between cognitive reappraisal and self-regulated learning were explored.•An explanatory mixed methods approach was used.•Results revealed that cognitive reappraisal predicted ...better self-regulated learning.•Effective self-regulated learning predicted better math problem-solving outcomes.•Cognitive reappraisal supports self-regulated learning and problem-solving outcomes.
Emotion regulation (ER) and self-regulated learning (SRL) are crucial to learners’ academic achievements. To date, little research has considered the dynamic relations between cognitive reappraisal (as a form of ER) and SRL in middle-to-upper-elementary-aged children. To address this gap, we conducted an explanatory mixed-methods study to examine relations between cognitive reappraisal, the four macro phases of SRL (task definition, planning/goal setting, enactment of learning strategies, monitoring/evaluation), and mathematics problem-solving outcomes in a sample of 134 elementary students from grades 3 through 6. Path analysis revealed that cognitive reappraisal positively predicted all four phases of SRL, but that the four phases of SRL did not predict cognitive reappraisal. Moreover, both task definition and planning/goal setting positively predicted enactment and monitoring/evaluation. Results from path analyses further revealed that task definition mediated relations between cognitive reappraisal and enactment, and reappraisal and monitoring. Enactment mediated relations between reappraisal and mathematics problem-solving outcomes. Finally, enactment predicted mathematics problem-solving outcomes. Further, quantitative results were cross-validated by results from trend analyses; results converged regarding the weakly sequenced nature of SRL and with regard to cognitive reappraisal serving as an important antecedent for effective SRL.
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