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Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective
Published on: July 1, 2015
A Survey and Protocol for Assessing Online Learning Experience, Basic Psychological Needs, and Learning Engagement in
Jiannan Zhang1, Norharyanti Mohsin2, Siti Hajar Halili1
1Department of Curriculum and Instructional Technology, Faculty of Education, Universiti Malaya.
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Online learning is embedded in higher education, but evaluations often rely on access, satisfaction, or completion indicators that do not identify where engagement problems arise. This article presents a reproducible English-language survey and partial least squares structural equation modeling protocol for assessing association pathways among online learning experience, basic psychological needs, and learning engagement in university students. Online learning experience is measured through platform usability, instructional support, interaction quality, and learning flexibility; basic psychological needs through autonomy, competence, and relatedness; and learning engagement through behavioral, cognitive, and emotional engagement. The workflow specifies item-source mapping, questionnaire adaptation, expert review, pilot testing, electronic consent, eligibility screening, response-quality checks, construct scoring, common method bias diagnostics, higher-order construct estimation, measurement-model assessment, structural pathway testing, indirect-association analysis, psychological-need sensitivity analysis, regression-based robustness checks, and reproducibility file locking. Representative results from 386 valid responses demonstrate acceptable reliability, moderate construct correlations, retained measurement quality, a supported indirect association through basic psychological needs, nonsignificant control paths, and uneven dimensional scores. The protocol supports transparent diagnosis of how online learning experience is associated with psychological need satisfaction and engagement while avoiding causal interpretation from cross-sectional survey data.
