This meta-analytic review explores the effects of self-assessment on students' self-regulated learning (SRL) and self-efficacy. A total of 19 studies were included in the four different meta-analyses ...conducted with a total sample of 2305 students. The effects sizes from the three meta-analyses addressing effects on different measures of SRL were 0.23, 0.65, and 0.43. The effect size from the meta-analysis on self-efficacy was 0.73. In addition, it was found that gender (with girls benefiting more) and certain self-assessment components (such as self-monitoring) were significant moderators of the effects on self-efficacy. These results point to the importance of self-assessment interventions to promote students’ use of learning strategies and its effects on motivational variables such as self-efficacy.
•Self-assessment effects on self-regulated learning (SRL) and self-efficacy were explored.•19 studies (2305 students) were included in four different meta-analyses.•Effects sizes from the three meta-analyses on SRL were 0.23, 0.65 and 0.43.•The effect size from the meta-analysis on self-efficacy was 0.73.
The authors propose a theoretical model linking emotions, self-regulated learning, and motivation to academic achievement. This model was tested with 5,805 undergraduate students. They completed the ...Self-Regulated Learning, Emotions, and Motivation Computerized Battery (LEM-B) composed of 3 self-report questionnaires: the Self-Regulated Learning Questionnaire (LQ), the Emotions Questionnaire (EQ), and the Motivation Questionnaire (MQ). The findings were consistent with the authors' hypotheses and appeared to support all aspects of the proposed model. The structural equation model showed that students' emotions influence their self-regulated learning and their motivation, and these, in turn, affect academic achievement. Thus, self-regulated learning and motivation mediate the effects of emotions on academic achievement. Moreover, positive emotions foster academic achievement only when they are mediated by self-regulated learning and motivation. The results are discussed with regard to the key role of emotions in academic settings and in terms of theoretical implications for researchers.
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CEKLJ, FFLJ, NUK, ODKLJ, PEFLJ
The purpose of this study is to determine the effect of self-regulated learning on student academic integrity with religiosity as the moderator variable. The approach used in this research is ...correlational causality. By using three measurement scales (self-regulated learning scale , academic integrity scale and religiosity) for 380 respondents , the results show that self-regulation learning affects academic integrity with religiosity as a moderator variable of 54.2 % . Based on the results obtained, it shows that the effect of self-regulated learning on academic integrity in students is in the form of a positive relationship, meaning that the higher the level of self-regulated learning in students, the higher the level of academic integrity . Religiosity as a moderator variable in this study illustrates that it can strengthen the influence of self- regulated learning variables on student academic integrity.
Tujuan penelitian ini adalah untuk mengetahui pengaruh self regulated learning terhadap academic integrity mahasiswa dengan religiosity sebagai variabel moderator. Pendekatan yang digunakan dalam penelitian ini adalah kausalitas korelasional. Dengan menggunakan tiga skala pengukuran (skala self regulated learning, skala academic integrity dan skala religiosity) terhadap 380 responden, diperoleh hasil bahwa self regulation learning berpengaruh terhadap academic integrity dengan religiosity sebagai variabel moderator sebesar 54,2%. Berdasarkan hasil yang diperoleh menunjukkan bahwa pengaruh self regulated learning terhadap academic integrity pada mahasiswa berupa hubungan yang positif, artinya semakin tinggi tingkat self regulated learning pada mahasiswa maka semakin tinggi pula tingkat academic integrity. Religiosity sebagai variabel moderator dalam penelitian ini menggambarkan dapat memperkuat pengaruh variabel self regulated learning terhadap academic integrity mahasiswa.
As enrolments in online courses continue to increase, there is a need to understand how students can best apply self-regulated learning strategies to achieve academic success within the online ...environment. A search of relevant databases was conducted in December 2014 for studies published from 2004 to Dec 2014 examining SRL strategies as correlates of academic achievement in online higher education settings. From 12 studies, the strategies of time management, metacognition, effort regulation, and critical thinking were positively correlated with academic outcomes, whereas rehearsal, elaboration, and organisation had the least empirical support. Peer learning had a moderate positive effect, however its confidence intervals crossed zero. Although the contributors to achievement in traditional face-to-face settings appear to generalise to on-line context, these effects appear weaker and suggest that (1) they may be less effective, and (2) that other, currently unexplored factors may be more important in on-line contexts.
•Time management, metacognition, effort regulation & critical thinking predicted grade.•Rehearsal, elaboration and organisation were not related to online grade.•Peer learning should be prioritised in the context of online learning.•SRL strategy effects are weaker in the online context than in the traditional classroom.
Self-regulated learning (SRL) includes the cognitive, metacognitive, behavioral, motivational, and emotional/affective aspects of learning. It is, therefore, an extraordinary umbrella under which a ...considerable number of variables that influence learning (e.g., self-efficacy, volition, cognitive strategies) are studied within a comprehensive and holistic approach. For that reason, SRL has become one of the most important areas of research within educational psychology. In this paper, six models of SRL are analyzed and compared; that is, Zimmerman; Boekaerts; Winne and Hadwin; Pintrich; Efklides; and Hadwin, Järvelä and Miller. First, each model is explored in detail in the following aspects: (a) history and development, (b) description of the model (including the model figures), (c) empirical support, and (d) instruments constructed based on the model. Then, the models are compared in a number of aspects: (a) citations, (b) phases and subprocesses, (c) how they conceptualize (meta)cognition, motivation and emotion, (d) top-down/bottom-up, (e) automaticity, and (f) context. In the discussion, the empirical evidence from the existing SRL meta-analyses is examined and implications for education are extracted. Further, four future lines of research are proposed. The review reaches two main conclusions. First, the SRL models form an integrative and coherent framework from which to conduct research and on which students can be taught to be more strategic and successful. Second, based on the available meta-analytic evidence, there are differential effects of SRL models in light of differences in students' developmental stages or educational levels. Thus, scholars and teachers need to start applying these differential effects of the SRL models and theories to enhance students' learning and SRL skills.
PurposeThis study explores a conceptual framework that addresses a school principal's self-regulated learning (SPSRL) as well as possible avenues for future conceptualization of, and research into ...this issue.Design/methodology/approachThe conceptual framework of SPSRL is based on an extensive literature review of the research on student’s and teacher’s self-regulated learning models.FindingsA novel conceptual and practical SPSRL framework for planning, performing, monitoring and self-reflection is elaborated.Research limitations/implicationsThis novel SPSRL conceptual framework provides school principals with a means to shape and develop processes, strategies and structures to monitor and evaluate their learning, enabling them to react effectively in uncertain and dynamic environments. This framework may open the way to future research into possible contributions of the SPSRL construct with other variables related to principal effectiveness. The suggested framework should be examined empirically in various sociocultural contexts, possibly substantiating its conceptual validity.Originality/valueThe SPSRL conceptual framework can improve school learning, which might connect the individual (the school principal) and organizational (teachers) learning levels.
The existing literature suggests that self-regulated learning (SRL) strategies are relevant to student grade performance in both online and blended contexts, although few, if any, studies have ...compared them. However, due to challenges unique to each group, the variety of SRL strategies that are implicated, and their effect size for predicting performance may differ across contexts. One hundred and forty online students and 466 blended learning students completed the Motivated Strategies for Learning Questionnaire. The results show that online students utilised SRL strategies more often than blended learning students, with the exception of peer learning and help seeking. Despite some differences in individual predictive value across enrolment status, the key SRL predictors of academic performance were largely equivalent between online and blended learning students. Findings highlight the relative importance of using time management and elaboration strategies, while avoiding rehearsal strategies, in relation to academic subject grade for both study modes.
•Few studies have online learner's and blended learners SRL strategy use & grade.•Online and blended learners differed in their SRL strategies use.•Individual predictive value of SRL strategies differed for online/blended learners.•Overall predictors of grade were equivalent for online and blended learners.•Time management/elaboration/rehearsal strategies key for predicting grade.
This study examined the extent to which instructional conditions influence the prediction of academic success in nine undergraduate courses offered in a blended learning model (n=4134). The study ...illustrates the differences in predictive power and significant predictors between course-specific models and generalized predictive models. The results suggest that it is imperative for learning analytics research to account for the diverse ways technology is adopted and applied in course-specific contexts. The differences in technology use, especially those related to whether and how learners use the learning management system, require consideration before the log-data can be merged to create a generalized model for predicting academic success. A lack of attention to instructional conditions can lead to an over or under estimation of the effects of LMS features on students' academic success. These findings have broader implications for institutions seeking generalized and portable models for identifying students at risk of academic failure.
•Predictive models in learning analytics need to account for instructional conditions.•Instructional conditions are based in the theory of self-regulated learning.•The study was conducted with a nine undergraduate blended learning (n=4139) courses.•Generalized predictive models were not suitable to inform practice and research.•Course specific models better detected variables of relevance for teaching practice.•Further implications for educational research and practice are discussed.
•We investigated how learners choose self-regulated learning strategies.•Subjects tried two strategies, evaluated each, then chose one to use in the future.•Normatively effective strategies rated as ...more effortful and worse for learning.•Mental effort indirectly affected strategy choice via perceived learning.•Learners may interpret the mental effort of effective strategies as poor learning.
How do learners make decisions about how, what, and when to study, and why are their decisions sometimes ineffective for learning? In three studies, learners experienced a pair of contrasting study strategies (Study 1: interleaved vs. blocked schedule; Studies 2 & 3: retrieval practice vs. restudy) and rated their perceptions of each strategy before choosing one for future use. In all three studies, mediation analysis revealed that participants who perceived a strategy as more effortful rated it as less effective for learning and, in turn, were less likely to choose it for future study. Further, choosing the more effortful strategy was associated with better long-term retention (Study 3), contrary to participants’ judgments. A final fourth study suggested that these relationships were not driven by the mere act of providing ratings. Our results thus support a misinterpreted-effort hypothesis in which the mental effort associated with many normatively effective learning strategies (desirable difficulties; Bjork & Bjork, 1992) leads learners to misinterpret them as ineffective for learning and consequently not to employ them in self- regulated learning.
Self-Regulated Learning (SRL) is related to increased learning performance. Scaffolding learners in their SRL activities in a computer-based learning environment can help to improve learning ...outcomes, because students do not always regulate their learning spontaneously. Based on theoretical assumptions, scaffolds should be continuously adaptive and personalized to students' ongoing learning progress in order to promote SRL. The present study aimed to investigate the effects of analytics-based personalized scaffolds, facilitated by a rule-based artificial intelligence (AI) system, on students' learning process and outcomes by real-time measurement and support of SRL using trace data. Using a pre-post experimental design, students received personalized scaffolds (n = 36), generalized scaffolds (n = 32), or no scaffolds (n = 30) during learning. Findings indicated that personalized scaffolds induced more SRL activities, but no effects were found on learning outcomes. Process models indicated large similarities in the temporal structure of learning activities between groups which may explain why no group differences in learning performance were observed. In conclusion, analytics-based personalized scaffolds informed by students’ real-time SRL measured and supported with AI are a first step towards adaptive SRL supports incorporating artificial intelligence that has to be further developed in future research.
•Analytics-based scaffolds using trace data can support learning in real-time.•Personalized scaffolds induce metacognitive activities.•Personalized scaffolds most effective in promoting monitoring activities.•Students seldom plan and evaluate their learning and need more focused support.•Process models reveal possible explanation of missing effects on learning outcome.
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