Susanne P. Lajoie
McGill University
Human–computer interactionMetacognitionCollaborative learningMathematics educationArtificial intelligencePsychologyEducational technologyCognitionCognitive psychologySelf-regulated learningLearning environmentIntelligent tutoring systemContext (language use)Problem-based learningClinical reasoningAffect (psychology)Computer scienceMultimediaMedical educationKnowledge managementSocial psychology
208Publications
29H-index
3,191Citations
Publications 208
Newest
#1Maedeh Kazemitabar (McGill University)H-Index: 5
#2Susanne P. Lajoie (McGill University)H-Index: 29
Last. Tenzin Doleck (SFU: Simon Fraser University)H-Index: 13
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Abstract The ability to detect and regulate emotions is an important aspect of emotional intelligence that can benefit individuals in their personal well-being and social interactions (Mayer, Caruso, Salovey, 2016). This study examined emotion regulation (ER) in medical students as they practiced learning how best to communicate undesired news to patients in an international technology-rich learning environment (TRLE; Lajoie et al., 2012). Gross’ (2015) process model of ER served as the theoreti...
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#1Tianshu Li (McGill University)H-Index: 1
#2Susanne P. Lajoie (McGill University)H-Index: 29
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#1Shan Li (McGill University)H-Index: 8
#2Susanne P. Lajoie (McGill University)H-Index: 29
Integrating the two dominant theories of self-regulated learning (SRL) and cognitive engagement could advance our understanding of what makes students more efficient, effective learners. An integration of these theories has yet to be explored, and this paper addresses this gap by proposing a novel integrative model of SRL engagement. Specifically, we identified the nature of cognitive engagement (i.e., changing consecutively, context-dependent, comprising quantitative and qualitative dimensions,...
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#2Susanne P. Lajoie (McGill University)H-Index: 29
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#1Lingyun Huang (McGill University)H-Index: 2
#2Susanne P. Lajoie (McGill University)H-Index: 29
Abstract Self-regulated learning (SRL) has a predictable and instrumental effect on learning complicated knowledge. This study investigates the role of SRL in acquiring technological pedagogical content knowledge (TPACK), an important aspect of teachers' effective technology use. The present study identified several regulatory procedural patterns used by teachers in the context of their TPACK achievements. A computer-based context, nBrowser, was used to facilitate teachers lesson planning around...
1 CitationsSource
#1Susanne P. Lajoie (McGill University)H-Index: 29
#2Shan Li (McGill University)H-Index: 8
Last. Juan Zheng (McGill University)H-Index: 9
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Monitoring one’s learning activities is a key component of self-regulated learning (SRL) leading to successful learning and performance outcomes across settings. Achievement emotions also play an i...
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#1Osamu Nomura (Hirosaki University)H-Index: 5
#2Jeffrey Wiseman (McGill University)H-Index: 13
Last. Susanne P. Lajoie (McGill University)H-Index: 29
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Medical learners' achievement emotions during educational activities have remained unexamined in Asian cultural contexts. The Medical Emotion Scale (MES) was previously developed to assess achievement emotions experienced by North American medical learners during learning activities. The goal of this study was to create and validate a Japanese version of the Medical Emotion Scale (J-MES). We translated the MES into Japanese and conducted two initial validation studies of the J-MES. In the first ...
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#1Shan Li (McGill University)H-Index: 8
#2Susanne P. Lajoie (McGill University)H-Index: 29
Last. Huaqin Cheng (PKU: Peking University)H-Index: 1
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Abstract In the present paper, we used supervised machine learning algorithms to predict students’ cognitive engagement states from their facial behaviors as 61 students solved a clinical reasoning problem in an intelligent tutoring system. We also examined how high and low performers differed in cognitive engagement levels when performing surface and deep learning behaviors. We found that students’ facial behaviors were powerful predictors of their cognitive engagement states. In particular, we...
2 CitationsSource
#1Susanne P. Lajoie (McGill University)H-Index: 29
#2Juan Zheng (McGill University)H-Index: 9
Last. Maren Gube (McGill University)H-Index: 3
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Abstract There is an active strand of research on how affect and self-regulatory activities influence performance and learning outcomes, but the mechanisms through which they interact during learning remain poorly understood. Additionally, these constructs have been under-researched in medical education. Using multimodal data in the context of a clinical reasoning task for medical students learning case diagnosis, we explored the temporal nature of cognition, affect, motivation, and self-regulat...
8 CitationsSource
#1Shan Li (McGill University)H-Index: 8
#2Juan Zheng (McGill University)H-Index: 9
Last. Jeffrey Wiseman (McGill University)H-Index: 13
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Prior research has focused extensively on how emotion tendencies (e.g., duration, frequency, intensity, and valence) affect students’ performance, but little is known about emotion variability (i.e., the fluctuations in emotion states) and how emotion variability affects performance. In this paper, emotion variability was examined among 21 medical students in the context of solving two patient cases of different complexity with BioWorld, a computer-based intelligent tutoring system. Specifically...
1 CitationsSource