Leveraging complexity frameworks to refine theories of engagement: Advancing self-regulated learning in the age of artificial intelligence

Capturing evidence for dynamic changes in self-regulated learning (SRL) behaviours resulting from interventions is challenging for researchers. In the current study, we identified students who were likely to do poorly in a biology course and those who were likely to do well. Then, we randomly assigned a portion of the students predicted to perform poorly to a science of learning to learn intervention where they were taught SRL study strategies. Learning outcome and log data (257 K events) were collected from n = 226 students. We used a complex systems framework to model the differences in SRL including the amount, interrelatedness, density and regularity of engagement captured in digital trace data (ie, logs). Differences were compared between students who were predicted to (1) perform poorly (control, n = 48), (2) perform poorly and received intervention (treatment, n = 95) and (3) perform well (not flagged, n = 83). Results indicated that the regularity of students' engagement was predictive of course grade, and that the intervention group exhibited increased regularity in engagement over the control group immediately after the intervention and maintained that increase over the course of the semester. We discuss the implications of these findings in relation to the future of artificial intelligence and potential uses for monitoring student learning in online environments.

Practitioner notes

What is already known about this topic

• Self-regulated learning (SRL) knowledge and skills are strong predictors of postsecondary STEM student success.
• SRL is a dynamic, temporal process that leads to purposeful student engagement.
• Methods and metrics for measuring dynamic SRL behaviours in learning contexts are needed.

What this paper adds

• A Markov process for measuring dynamic SRL processes using log data.
• Evidence that dynamic, interaction-dominant aspects of SRL predict student achievement.
• Evidence that SRL processes can be meaningfully impacted through educational intervention.

Implications for theory and practice

• Complexity approaches inform theory and measurement of dynamic SRL processes.
• Static representations of dynamic SRL processes are promising learning analytics metrics.
• Engineered features of LMS usage are valuable contributions to AI models.

     

Enhance low-achieving students' learning involvement in Taiwan's higher education: an approach via e-learning with problem-based learning and self-regulated learning

This study explored the effects of web-enabled pedagogies on students' involvement in learning. A series of quasi-experiments were conducted to investigate whether students' involvement increases over time if intervened, respectively, by problem-based learning (PBL), self-regulated learning (SRL), and their combinations. Two classes of 102 first-year students at a vocational school in a one-semester course were chosen for this empirical study. The results were generally supportive. The authors further discuss the implications for schools, scholars, and teachers engaged in e-learning.     

Transcultural analysis of the effectiveness of a program to promote self-regulated learning in Mozambique,Chile, Portugal,and Spain

The current investigation aims at assessing the effectiveness of an intervention program designed to enhance self-regulated learning (SRL) strategies at the university level, with students from different cultural, linguistic, and educational backgrounds. The central tool of the program is a set of letters in which a fictional first-year student describes his experiences as an SRL student. The program was implemented in four universities in different countries and continents (Portugal, Spain, Chile, and Mozambique), with an experimental group and a comparison group at each university (263 students from experimental groups and 247 from comparison groups). Findings display the effectiveness of the program in enhancing a set of motivational variables related to the study process and the use of SRL strategies. Data were consistent across the different cultural and academic contexts in which the program was implemented. The implications of these findings for university administrators and faculty are discussed.     

Changes in self-regulated learning profiles during an undergraduate peer-based intervention: A latent profile transition analysis

University students often have insufficient strategies to regulate their own learning independently, suggesting the need for adequate support. This study examined developmental changes in students’ self-regulated learning (SRL) profiles during their participation in Supplemental Instruction, a peer-based intervention, over the course of a semester and predictive variables of these changes. Latent profile transition analysis of a sample of 352 undergraduates revealed three distinct SRL profiles which emerged identically across time points: competent regulators, self-confident regulators, and goal-oriented regulators. Students in the competent regulators profile were most stable over time, while those in the goal-oriented regulators profile were most malleable, but in a positive sense. Results also indicate that students who attributed SI attendance to mastery goals were more likely to transition beneficially between SRL profiles. The observed predictors of transitions between profiles also highlighted the relative importance of motivational variables as opposed to cognitive-metacognitive variables in accounting for SRL development.     

Hard to reach and hard to teach: supporting the self-regulation of learning in an alternative provision secondary school

Since 2010, new types of state-funded schools have opened in England with a focus on providing alternative education provision. Very little is known about these schools, partly due to their novelty, and how they are attempting to re-engage those students who for various, and often complex, reasons have become disconnected from education. We scrutinised the approach used at one such school to examine what instructional practices were used, how they were adapted to the needs of the students and what factors enabled and obstructed (re)engagement. Data were collected over a month-long fieldwork visit and included semi-structured interviews with staff and students, and semi-structured classroom observations. Instructional approaches were used that supported the learning of students who were not experienced in, or had difficulty with, regulating their learning. These included breaking down tasks, providing lots of on-task prompts, encouragement, using frequent feedback and scaffolding, and offering quick support to students. This approach allowed students to re-engage with their learning and make progress towards important qualifications required for entry to the labour market and post-compulsory education and training.     

Regulation of emotions in socially challenging learning situations: an instrument to measure the adaptive and social nature of the regulation process

Self-regulated learning (SRL) research has conventionally relied on measures, which treat SRL as an aptitude. To study self-regulation and motivation in learning contexts as an ongoing adaptive process, situation-specific methods are needed in addition to static measures. This article presents an ‘Adaptive Instrument for Regulation of Emotions’ aimed at accessing students’ experiences of individual and socially shared regulation of emotions in a socially challenging learning situation. The instrument, grounded in self-regulated and socially regulated learning theory, comprises four interrelated components: the socio-emotional challenges experienced in a collaborative learning situation; individual and group-level attempts to regulate the immediate emotions evoked by the challenges; the personal goals; and goal attainment pursued in that situation. The theoretical foundation of the instrument and its components are outlined and some reliability issues illustrated. The limitations but also educational potential of the instrument to understand regulation of emotions in socially challenging learning situations are discussed.