Background
Even though monitoring and control enactment are key aspects of self‐regulated learning (SRL), Adaptive learning technologies (ALTs) may reduce the need for learners to monitor and control ...their learning. Personalized dashboards are effective in supporting learners' monitoring and can potentially support control behaviour. Allowing learners to enact control over their learning process, seems to hold potential for increasing their motivation.
Objectives
Therefore, this study's aim was to investigate the relation between control enactment and motivation. We examined how learners enacted control while learning with an ALT with personalized dashboards and examined the relation between learners' enactment of control and their motivation.
Methods
Seventy‐eight primary school learners (Grade 5) participated. During the lesson, learners worked on mathematics in the ALT and concurrently were shown personalized visualizations that supported monitoring and enacting control over their learning process. Learners could enact control to change problems' difficulty to easy, medium, or hard. Motivation was measured before and after learning.
Results
The SEM analyses showed that how learners enacted control was related to their motivation. Choosing difficult problems was related to more enjoyment and competence while choosing easy problems related to more pressure and tension. Learners who complied with the suggested difficulty level experienced less choice, but also less pressure/tension and more enjoyment and competence.
Conclusions
These results provide avenues to account for broader learner characteristics like SRL and motivation to optimize learning. This way, hybrid systems in which control enactment is a shared responsibility of the system and learner, can be improved to support SRL development.
Lay Description
What is currently known
Monitor and control enactment are key aspects of self‐regulated learning (SRL).
Adaptive learning technologies may reduce the need for learners to monitor and control their learning.
Personalized dashboards support learners' monitoring behaviour and can potentially also support control enactment.
Enactment of control could positively affect learners' motivation.
What does this paper add
There is a large variation in how learners enact control and whether they comply with the scaffold.
Learners who chose more difficult problems experienced more enjoyment, while learners choosing easy problems, experienced more pressure.
Learners complied with the scaffold, experienced less choice, but also less pressure and more enjoyment.
This study provides avenues to account for broader learner characteristics like SRL and motivation to optimize learning.
Practical implications
Support control enactment by actively involve learners in choice during the learning process.
Offer monitor and enactment in conjunction, as learners can only make well‐founded choices if they can monitor their learning process.
Intrinsically and extrinsically motivated learners showed different choice patterns and learning experience.
It is important to have an understanding and monitoring of learners' motivation.
Penelitian ini Untuk mengetahui kebugaran Jasmani dan Self-Regulated Learning kondisi siswa sekolah dasar pada masa adaptasi kebiasaan baru. Penelitian ini menggunakan penelitian deskritif ...kuantitatif dengan metode survei cross sectional, dengan instrumen tes TKJI (Tes Kebugaran Jasmani Indonesia) dan angket kuesioner Self-Regulated Learning untuk teknik pengambilan data. Populasi dalam penelitian ini adalah Sekolah Dasar Negeri Ter-Akreditasi A di Se-Kecamatan Sukaraja Kabupaten Sukabumi. Anggota sampel yang dignakan dalam penelitian ini adalah 10 Sekolah Dasar Negeri Ter-Akreditasi A di Kecamata Penelitian ini Untuk mengetahui kebugaran Jasmani dan Self-Regulated Learning kondisi siswa sekolah dasar pada masa adaptasi kebiasaan baru. Penelitian ini menggunakan penelitian deskritif kuantitatif dengan metode survei cross sectional, dengan instrumen tes TKJI (Tes Kebugaran Jasmani Indonesia) dan angket kuesioner Self-Regulated Learning untuk teknik pengambilan data. Populasi dalam penelitian ini adalah Sekolah Dasar Negeri Ter-Akreditasi A di Se-Kecamatan Sukaraja Kabupaten Sukabumi. Anggota sampel yang dignakan dalam penelitian ini adalah 10 Sekolah Dasar Negeri Ter-Akreditasi A di Kecamatan Sukaraja Kabupaten Sukabumi dan 10 siswa yang dijadikan sampel disetiap sekolahnya dengan usia 10-12 tahun yang dilakukan secara acak menggunakan metode simple random sampling. Teknik analisis penelitian ini menggunakan persentase. Hasil dari penelitian ini menunjukan bahwa tingkat kebugaran jasmani siswa putra ada pada klasifikasi baik sebesar 14%, klasifikasi sedang sebesar 72%, sedangkan yang mempunyai kriteria kurang 10% dan kurang sekali sebesar 3% serta klasifikasi siswa putri menunjukan klasifikasi baik sebesar 2%, klasifikasi sedang sebesar 76%, sedangkan yang mempunyai kriteria kurang 21%. dan hasil dari penelitian survei Self-Regulated Learning siswa di SDN ter-akreditasi A Kec. Sukaraja Kab. Sukabumi berada dikategori “tinggi” sebesar 52% dengan jumlah 52 siswa, berikutnya pada kategori sedang sebesar 34% dengan jumlah 34 siswa dan kategori “rendah” sebesar 14% dengan jumlah 14 siswa. Maka dapat disimpulkan bahwa tingkat kebugaran jasmani siswa Sekolah Dasar Negeri Ter-Akreditasi A di Se-Kecamatan Sukaraja Kabupaten Sukabumi berada pada klasifikasi “sedang” dan Self-Regulated Learning siswa di SDN ter-akreditasi A Kec. Sukaraja Kab. Sukabumi berada dikategori “tinggi”. n Sukaraja Kabupaten Sukabumi dan 10 siswa yang dijadikan sampel disetiap sekolahnya dengan usia 10-12 tahun yang dilakukan secara acak menggunakan metode simple random sampling. Teknik analisis penelitian ini menggunakan persentase. Hasil dari penelitian ini menunjukan bahwa tingkat kebugaran jasmani siswa putra ada pada klasifikasi baik sebesar 14%, klasifikasi sedang sebesar 72%, sedangkan yang mempunyai kriteria kurang 10% dan kurang sekali sebesar 3% serta klasifikasi siswa putri menunjukan klasifikasi baik sebesar 2%, klasifikasi sedang sebesar 76%, sedangkan yang mempunyai kriteria kurang 21%. dan hasil dari penelitian survei Self-Regulated Learning siswa di SDN ter-akreditasi A Kec. Sukaraja Kab. Sukabumi berada dikategori “tinggi” sebesar 52% dengan jumlah 52 siswa, berikutnya pada kategori sedang sebesar 34% dengan jumlah 34 siswa dan kategori “rendah” sebesar 14% dengan jumlah 14 siswa. Maka dapat disimpulkan bahwa tingkat kebugaran jasmani siswa Sekolah Dasar Negeri Ter-Akreditasi A di Se-Kecamatan Sukaraja Kabupaten Sukabumi berada pada klasifikasi “sedang” dan Self-Regulated Learning siswa di SDN ter-akreditasi A Kec. Sukaraja Kab. Sukabumi berada dikategori “tinggi”. Kata Kunci : Kebugaran Jasmani, Self-Regulated Learning
The purpose of this study was to examine the effects of students' self-regulated learning (SRL) levels on their perceptions of community of inquiry (CoI) and their affective outcomes (task-specific ...attitudes and self-efficacy). Participants were 180 college students enrolled in a required online course. Using the cluster analysis method, SRL levels were grouped into four levels (High regulators, Mid regulators lacking efforts, Mid regulators lacking values, and Low regulators). ANOVA revealed that highly self-regulated students demonstrated a stronger sense of CoI and achieved higher affective outcomes, compared to low self-regulated students. The finding confirms that SRL could play an important role in the framework of community of inquiry.
•By using cluster analysis, students’ self-regulated learning were grouped into four levels.•Self-regulated learning determined students’ perceived community of inquiry, attitudes, and self-efficacy.•Self-regulated learning or learning presence is important in cultivating positive community of inquiry.
Learning sciences are embracing the significant role technologies can play to better detect, diagnose, and act upon self-regulated learning (SRL). The field of SRL is challenged with the measurement ...of SRL processes to advance our understanding of how multimodal data can unobtrusively capture learners' cognitive, metacognitive, affective, and motivational states over time, tasks, domains, and contexts. This paper introduces a self-regulated learning processes, multimodal data, and analysis (SMA) grid and maps joint and individual research of the authors (63 papers) over the last five years onto the grid. This shows how multimodal data streams were used to investigate SRL processes. The two-dimensional space on the SMA grid is helpful for visualizing the relations and possible combinations between the data streams and how the measurement of SRL processes. This overview serves as an analytical introduction to the current special issue “Advancing SRL Research with Artificial Intelligence (AI)” and we encourage to position new research and unexplored frontiers. We emphasize the need for intensive and strategic collaboration to accelerate progress using new interdisciplinary methods to develop accurate measurement of SRL in educational technologies.
•Self-regulated learning (SRL) field started using one data stream to analyse a certain SRL process with simple statistics.•We diversified our research towards the horizontal approach analysing multiple SRL processes with one data stream using more advanced statistical techniques.•As well as to the vertical approach, investigating one SRL process using multiple data streams.•Novel is an integrated approach aligning multimodal data investigating multiple SRL processes with advanced AI techniques.
The anthropomorphic characteristics of artificial intelligence (AI) can provide a positive environment for self‐regulated learning (SRL). The factors affecting adolescents' SRL through AI ...technologies remain unclear. Limited AI and disciplinary knowledge may affect the students' motivations, as explained by self‐determination theory (SDT). In this study, we examine the mediating effects of needs satisfaction in SDT on the relationship between students' previous technical (AI) and disciplinary (English) knowledge and SRL, using an AI conversational chatbot. Data were collected from 323 9th Grade students through a questionnaire and a test. The students completed an AI basic unit and then learned English with a conversational chatbot for 5 days. Confidence intervals were calculated to investigate the mediating effects. We found that students' previous knowledge of English but not their AI knowledge directly affected their SRL with the chatbot, and that satisfying the need for autonomy and competence mediated the relationships between both knowledge (AI and English) and SRL, but relatedness did not. The self‐directed nature of SRL requires heavy cognitive learning and satisfying the need for autonomy and competence may more effectively engage young children in this type of learning. The findings also revealed that current chatbot technologies may not benefit students with relatively lower levels of English proficiency. We suggest that teachers can use conversational chatbots for knowledge consolidation purposes, but not in SRL explorations.
Practitioner notes
What is already known about this topic
Artificial intelligence (AI) technologies can potentially support students' self‐regulated learning (SRL) of disciplinary knowledge through chatbots.
Needs satisfaction in Self‐determination theory (SDT) can explain the directive process required for SRL.
Technical and disciplinary knowledge would affect SRL with technologies.
What this paper adds
This study examines the mediating effects of needs satisfaction in SDT on the relationship between students' previous AI (technical) and English (disciplinary) knowledge and SRL, using an AI conversational chatbot.
Students' previous knowledge of English but not their AI knowledge directly affected their SRL with the chatbot.
Autonomy and competence were mediators, but relatedness was not.
Implications for practice and/or policy
Teachers should use chatbots for knowledge consolidation rather than exploration.
Teachers should support students' competence and autonomy, as these were found to be the factors that directly predicted SRL.
School leaders and teacher educators should include the mediating effects of needs satisfaction in professional development programmes for digital education.
Massive Open Online Courses (MOOCs) provide a great platform to study individual and group differences of learners in perceptions, motivations, and behaviors under self-directed learning context. ...This study examined the relationships, in particular, influential relationships, among MOOC learners' demographics, their self-regulated learning (SRL) strategy usage, perceived learning, and satisfaction. Participants were 4503 learners from 17 Coursera courses who responded to an online survey in 2018. Structural equation modeling showed that participants' age, gender, highest degree, and the number of online courses previously taken significantly predicted both goal setting and environment structuring usage. Previous experience with the course topics only predicted goal setting, not environment structuring. Gender, goal setting and environment structuring strategy usage predicted participants' perceived affective learning. Highest degree, the number of online courses previously took, goal setting, environment structuring strategy usage and perceived affective learning predicted participants' satisfaction with the course. Participants identified themselves with a Latin America culture had better environment structuring strategy usage than any other cultural group and higher perceived affective learning than the other cultural groups except for Other. The results provided implications for researchers studying self-directed learning environments, differences in learning of learners with diverse backgrounds, and SRL behaviors, as well as for educators dealing with increasing SRL strategy usage, improving online learners’ satisfaction and teaching cross-culturally.
•MOOC learners' demographics predicted their self-regulated learning strategy.•SRL strategy, some demographics predicted MOOC learners' perceived learning.•SRL strategy, some demographics and perceived learning predicted satisfaction.•Latin America cultural group used more SRL and perceived higher learning.
This work aims to examine the relationship between general self-regulated learning abilities and students' general intellectual abilities, mathematical learning abilities, and academic achievement. A ...study was conducted with a sample of eighth-grade students (N=325). The research employed a survey and descriptive method, and the instruments used included a test of general intellectual abilities, a test of self-regulated learning abilities, a test to measure mathematical learning abilities, and a standardized math knowledge test. Based on the obtained results, we indicate those factors with high or moderately high correlations. Among the results obtained, there is a high correlation between general intellectual abilities and general self-regulated learning abilities (subtests for interpreting graphs and interpreting geographic maps). The results show a high correlation between the total score on the self-regulated learning abilities test and math achievement. A moderately high correlation was achieved between the test of general intellectual abilities and self-regulated learning abilities (subtests for finding necessary information, exploring new material, and the index of developed abilities and techniques for self-regulated learning). On the math learning ability test, various abilities are differentiated, including formalization of mathematical content, spatial abilities, imagination, flexibility, and critical thinking. Based on the research results, it is considered significant to investigate the effects of different innovative teaching systems and teaching methods on students' self-regulated learning abilities and mathematical learning abilities.
Self-regulated learning (SRL) can be defined as the ability of learners to act independently and actively manage their own learning process. This skill becomes especially important in online ...environments, which allow learners to decide where and how to study. Most research on SRL has focused on students; few studies have addressed teachers' SRL as learners, and only a handful has done so in the context of online learning. A better understanding of teachers' SRL is essential since teachers are expected to support the development of their students' SRL abilities. This study contributes to bridging this gap by examining how online learning patterns reflect the self-regulated learning of teachers as learners in an online professional development (PD) course on nanotechnology. The study applies a mixed methods approach that combines the qualitative analysis of interviews with teacher learners and a personal summary of their learning process represented in four vignettes as well as quantitative log-file analysis to identify teachers' learning patterns. The patterns identified are interval learning, on-track learning, skipping difficult parts, concentrated learning toward the end of the course (i.e., “bingeing”), and watching together. These patterns indirectly shed light on teachers' SRL skills, especially their time management and task strategies, demonstrating that there is no one-size-fits-all approach to learning. The study highlights the need for a holistic approach, provides deeper insights into teachers’ learning experiences, and helps design future online PD courses.
•We identified teachers’ learning patterns in an online professional development course.•Four vignettes represent teachers' learning strategies and their time management skills.•We show that most teachers studied weekly, whereas others ‘binged’ or engaged in ‘interval learning’.•The learning patterns taught us about teachers’ self-regulated learning (SRL) skills.•Digital footprints show how teachers adapted and combined learning patterns during the course.
•The meta-analysis tested the effects of self-regulated learning (SRL) trainings.•SRL trainings improved university students’ academic performance.•SRL trainings improved various (meta-) cognitive ...and resource management strategies.•SRL trainings enhanced students’ motivation – especially self-efficacy.•Training design and student characteristics moderated training effects.
The present meta-analysis tested the effects of extended self-regulated learning training programs on academic performance, self-regulated learning strategies, and motivation of university students. The literature search revealed 49 studies (5,786 participants) that met the inclusion criteria. A three-level meta-analysis based on 251 effect sizes revealed an overall effect size of g = 0.38. The largest effect sizes were obtained for metacognitive strategies (g = 0.40) and resource management strategies (g = 0.39) followed by academic performance (g = 0.37), motivational outcomes (g = 0.35), and cognitive strategies (g = 0.32). Training effects varied for specific self-regulated learning strategies and ranged between 0.23 (rehearsal) and 0.61 (attention and concentration). Moderator analyses revealed differential training effects depending on course design characteristics: Feedback predicted larger training effects for metacognitive and resource management strategies as well as motivation. Cooperative learning arrangements predicted larger training effects for cognitive and metacognitive strategies. The provision of learning protocols predicted larger training effects for resource management strategies. Moreover, training programs based on a metacognitive theoretical background reported higher effects sizes for academic achievement compared to training programs based on cognitive theories. Further, training programs that targeted older students and students with lower prior academic achievement showed larger effect sizes for resource management strategies. To conclude, self-regulated learning training programs enhanced academic performance, self-regulated learning strategies, and motivation of university students.
Background
Lecturers give feedback on assessed work in the hope that students will take it on board and use it to help regulate their learning for the next assessment. However, little is known about ...how students’ conceptions of feedback relate to students’ self‐regulated learning and self‐efficacy beliefs and academic performance.
Aims
This study explores student beliefs about the role and purpose of feedback and the relationship of those beliefs to self‐reported self‐regulation and self‐efficacy, and achievement.
Sample
A total of 278 university students in a general education course on learning theory and approaches in a research‐intensive university.
Methods
Self‐reported survey responses for students’ conceptions of feedback (SCoF), self‐regulation (SRL), academic self‐efficacy (ASE), and Grade Point Average (GPA) were evaluated first with confirmatory factor analysis and then interlinked in a structural equation model.
Results and conclusions
Three SCoF factors predicted SRL and/or GPA. The SCoF factor ‘I use feedback’ had positive associations with SRL (β = .44), GPA (β = .45), and ASE (β = .15). The SCoF factors ‘tutor/marker comments’ and ‘peers help’ both had negative relations to GPA (β = −.41 and −.16, respectively). ‘Peers help’ had a positive connection to SRL (β = .21). ASE itself made a small contribution to overall GPA (β = .16), while SRL had no statistically significant relation to GPA. The model indicates the centrality of believing that feedback exists to guide next steps in learning and thus contributes to SRL, ASE, and increased GPA.
