Qi, F; Jiang, L; Chen, Y; Zhu, L and Jiang, Y (2024) Identifying Chinese students' perceptions of smart classrooms and their relationships with design features. Building Research & Information, 52(7), pp. 781-798. ISSN 0961-3218
Abstract
Taking classes in a smart classroom is a novel experience for most college students in China, and comprehensive research on how Chinese students perceive smart classroom environments is limited. This study explored students' perceptions of smart classroom environments in plain language through a survey involving 358 students. The semantic difference and Kansei Engineering methods were employed to investigate students' perceptions of learning and physical environments and their relationships with the design features of smart classrooms. Statistical analysis revealed six factors of subjective assessments with a total interpretation rate of 66.29% and five design features of smart classrooms with a total interpretation rate of 59.40%. No significant differences were found across all the factors based on gender, but there were significant differences in students' technology self-efficacy according to each factor of subjective evaluation and design feature. All factors of the subjective assessments and design features exhibited significant correlations. Furthermore, regression models revealed a significant relationship between affective perception and other dimensions of subjective assessments and an important connection between the active learning environment and all design features. Thus, this study provides an empirical foundation for understanding students' perceptions of smart classrooms and offers a user-based perspective for designing smart classrooms.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | design features; kansei engineering; semantic differential; smart classroom; subjective assessments; questionaire survey |
| Index terms: | self-efficacy, dimension, regression model, college student, active learning, statistical analysis, classroom, China, survey |
| Subjects: | data collection methods, construction type, human factors and perception, learning methods, health monitoring assessment and metrics, data science, Geography, sociology, statistical analysis |
| Topics: | Education, Health and Safety, Research Practice, Geographical Context, Stakeholder Management, Construction Technology |
| Descriptive scope: | 4 PCEA |
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