How do students' self‐regulation skills affect learning satisfaction and continuous intention within desktop‐based virtual reality? A structural equation modelling approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Virtual reality, as an excellent supportive instructional technology, has gained increasing attention from educators and professionals, where desktop‐based virtual reality (DVR) is broadly adopted due to its affordability and accessibility. However, when evaluating students' learning experiences such as flow experiences in DVR environments, most studies adopt a single construct (the total score of flow experience) rather than multiple constructs (enjoyment, engagement, concentration, presence and time distortion). This study implemented desktop‐based virtual reality for a STEM bridge designing program with a total of 254 undergraduates to investigate the relationship between self‐regulation skills, five dimensions of flow experience, learning satisfaction and continuous intention when engaging in a DVR learning environment. The results revealed that self‐regulated learning exerted a dominant impact on students' learning attitudes in DVR learning, in which students' flow experience had a significant mediating effect. Notably, although DVR exhibited poor time distortion, higher satisfaction and continuous intention were still predicted by the mentality of flow experience (ie, enjoyment, engagement, concentration and presence). The findings of this study contribute to the consideration of learning experiences and attitudes, which has insights for the future design of desktop‐based virtual reality environments and related instructional activities. Practitioner notes What is already known about this topic Students are different in self‐regulation skills, which influences their satisfaction and continuous intention in learning. Students' self‐regulation skills are one of the important variables in predicting their flow experience. A high level of flow experience contributes to a coherent and efficient learning experience within desktop‐based virtual reality (DVR) environments. What this paper adds Students' self‐regulation skills positively predicted their flow experience and satisfaction in DVR environments. The components of flow experience (enjoyment, concentration and presence) partially mediated the relationship between self‐regulation skills and satisfaction. Students' self‐regulation skills indirectly affect continuous intention by the enjoyment and engagement of flow experiences. Implications for practice and/or policy When delivering DVR‐based learning activities educators should be supportive of students with low levels of self‐regulation skills. Emphasis on promoting flow experiences such as enjoyment, engagement, concentration and presence in designing a DVR‐based classroom could enhance student satisfaction and continuous intention. Embedding scaffolding or feedback in DVR settings would support self‐regulated learning and subsequently improve student satisfaction and persistence through enhanced flow experience.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it