To understand the development of students’ higher-order thinking skills (HOTS) in the smart classroom environment, a structural equation modeling analysis was used to examine the relationships between key factors that influence students’ learning and their HOTS within a smart classroom environment. A sample of 217 first-year Chinese college students, who studied in a smart classroom environment for one semester, completed a survey that measures their smart classroom preferences, learning motivation, learning strategy, peer interaction, and HOTS. The results indicated that peer interaction and learning motivation had a direct impact on students’ HOTS. Furthermore, indirect effects were found between students’ learning strategy and HOTS through the mediator peer interaction, and between smart classroom preferences and HOTS through the following: learning motivation, the combination of learning strategy and peer interaction, and the combination of learning motivation, learning strategy and peer interaction. Based on these findings, this study recommends that instructors teaching in a smart learning environment should focus on improving peer interaction and learning motivation, as well as smart classroom preferences and learning strategy, to hone students’ HOTS.
Background
Inquiry‐based learning is a salient instructional approach to cultivate students' higher order thinking skills (HOTS). With the presence and advancement of new technologies, their usage for inquiry learning in university context is increasingly ubiquitous. However, in most circumstances, college students cannot integrate technologies to their inquiry learning in efficient ways or their abilities to use technologies are not good enough. Previous studies found that intrinsic motivation (IM), peer interaction (PI) and classroom connectedness (CC) were key factors to influence students' approaches to using technologies from the personal, behavioural and environmental perspectives.
Objectives
This study investigated the influence of these three essential learning factors (IM, PI and CC) on students' HOTS and the mediate influence of deep approach to using technologies (DAUT) between these learning factors and HOTS in the technology‐enhanced open inquiry‐based learning context.
Methods
A questionnaire was administered to 80 university students who had studied with the technology‐enhanced open inquiry‐based learning approach. The partial least squares method was employed to investigate the relationships among learning factors, DAUT and HOTS.
Results and Conclusions
Results showed that CC and PI were positively directly related to HOTS. DAUT was a significant mediator between two (i.e., IM and PI) of the three learning factors and HOTS. The findings of the study have practical implications for instructors, indicating that they should pay attention to students' IM and PI in deepening their approach to using technologies as well as to improve students' HOTS in technology‐enhanced open inquiry‐based learning.
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