ERIC Number: EJ1144630
Record Type: Journal
Publication Date: 2017-Jul
Pages: 46
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0735-6331
EISSN: N/A
Person-Oriented Approaches to Profiling Learners in Technology-Rich Learning Environments for Ecological Learner Modeling
Jang, Eunice Eunhee; Lajoie, Susanne P.; Wagner, Maryam; Xu, Zhenhua; Poitras, Eric; Naismith, Laura
Journal of Educational Computing Research, v55 n4 p552-597 Jul 2017
Technology-rich learning environments (TREs) provide opportunities for learners to engage in complex interactions involving a multitude of cognitive, metacognitive, and affective states. Understanding learners' distinct learning progressions in TREs demand inquiry approaches that employ well-conceived theoretical accounts of these multiple facets. The present study investigated learners' interactions with BioWorld, a TRE developed to guide students' clinical reasoning through diagnoses of simulated patients. We applied person-oriented analytic methods to multimodal data including verbal protocols, questionnaires, and computer logs from 78 task solutions. Latent class analysis, clustering methods, and latent profile analysis followed by logistic regression analyses revealed that students' clinical diagnosis ability was positively correlated with advanced self-regulated learning behaviors, high confidence and cognitive strategy use, critical attention to experts' feedback, and their positive emotional responses to feedback. The study results have the potential to contribute to a theory-guided approach to designing TREs with a data-driven assessment of multidimensional growth. Building on the study results, we introduce and discuss an ecological learner model for assessing multidimensional learner traits which can be used to design a TRE for adaptive scaffolding.
Descriptors: Educational Technology, Technology Uses in Education, Simulation, Patients, Teaching Methods, Questionnaires, Diaries, Problem Based Learning, Self Management, Goal Orientation, Achievement, Feedback (Response), Medical Students, Medical Education, Emotional Response, Student Characteristics, Surveys, Protocol Analysis, Cognitive Processes, Performance, Student Attitudes, Difficulty Level, Self Efficacy, Problem Solving, Student Reaction, Undergraduate Students, Regression (Statistics), Statistical Analysis
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Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Assessments and Surveys: Patterns of Adaptive Learning Survey
Grant or Contract Numbers: N/A