Measuring self-regulated learning and the role of AI: Five years of research using multimodal multichannel data

I Molenaar, S de Mooij, R Azevedo, M Bannert… - Computers in Human …, 2023 - Elsevier
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 …

Learning mechanisms explaining learning with digital tools in educational settings: A cognitive process framework

F Reinhold, T Leuders, K Loibl, M Nückles… - Educational Psychology …, 2024 - Springer
To explain successful subject matter learning with digital tools, the specification of mediating
cognitive processes is crucial for any empirical investigation. We introduce a cognitive …

A complex systems approach to analyzing pedagogical agents' scaffolding of self-regulated learning within an intelligent tutoring system

DA Dever, NA Sonnenfeld, MD Wiedbusch… - Metacognition and …, 2023 - Springer
Abstract Self-regulated learning (SRL), learners' monitoring and control of cognitive,
affective, metacognitive, and motivational processes, is essential for learning. However …

Using eye tracking to examine expert-novice differences during simulated surgical training: A case study

S Li, MC Duffy, SP Lajoie, J Zheng… - Computers in Human …, 2023 - Elsevier
Eye tracking data can serve as a unique metric for comparing expert-novice differences by
providing insights into attentional processes, which can lead to timely intervention and better …

Capturing sequences of learners' self-regulatory interactions with instructional material during game-based learning using auto-recurrence quantification analysis

DA Dever, MJ Amon, H Vrzakova… - Frontiers in …, 2022 - frontiersin.org
Undergraduate students (N= 82) learned about microbiology with Crystal Island, a game-
based learning environment (GBLE), which required participants to interact with instructional …

Unpacking perceived risks and AI trust influences pre-service teachers' AI acceptance: A structural equation modeling-based multi-group analysis

C Zhang, M Hu, W Wu, F Kamran, X Wang - Education and Information …, 2024 - Springer
Artificial intelligence (AI) integration in education has grown significantly recently. However,
the potential risks of AI have led to educators being wary of implementing AI systems. To …

Student profiles of change in a university course: A complex dynamical systems perspective

O Poquet, J Jovanovic, A Pardo - LAK23: 13th international learning …, 2023 - dl.acm.org
Learning analytics approaches to profiling students based on their study behaviour remain
limited in how they integrate temporality and change. To advance this area of work, the …

Supporting self-regulated learning in clinical problem-solving with a computer-based learning environment: the effectiveness of scaffolds

J Zheng, SP Lajoie, T Wang, S Li - Metacognition and Learning, 2023 - Springer
Computer-supported scaffolding plays a pivotal role in advancing problem-solving skills and
improving cognitive learning outcomes in self-regulated learning. However, there is limited …

Using multilayer network analysis to detect the collaborative knowledge construction characteristics among learner groups with low, medium, and high levels of …

F Ouyang, M Wu, J Gu - Computers & Education, 2024 - Elsevier
Collaborative knowledge construction (CKC) is advanced by group members' cognitive
engagement across three levels: individual-level knowledge processing and proposing, the …

Examining the Interplay between Self-Regulated Learning Activities and Types of Knowledge within a Computer-Simulated Environment.

S Li, X Huang, T Wang, Z Pan, SP Lajoie - Journal of Learning Analytics, 2022 - ERIC
This study examines the temporal co-occurrences of self-regulated learning (SRL) activities
and three types of knowledge (ie, task information, domain knowledge, and metacognitive …