A Pilot Study of the Attractive Features of Active Videogames Among Chinese Primary School Children
Bibliographic record
Abstract
OBJECTIVE: The present study (1) explored the attractive features that affect Chinese primary school children's preferences of active videogames (AVGs) and (2) contrasted these findings with those in the Western literature. PARTICIPANTS AND METHODS: ") were employed. Participants used four selected AVGs for 3 minutes each. After each play period, children (1) described the strengths and weaknesses of each game as well as rated the attractive features of each game based on a 16-item questionnaire and (2) rated up to 5 items that were most influential regarding their AVG preferences. RESULTS: Participants indicated that control was the most significant feature, followed by feedback, goal, and graphics. The top five rated features imply that the perception of competence was the most appealing aspect and expected outcome of Chinese children who play AVGs. CONCLUSIONS: Compared with the Western findings regarding attractive AVG features, the present study found certain similarities as well as significant differences among Chinese AVG players. Based on the present study, control, feedback, goal, and graphics are the most significant features that attract Chinese children to play AVGs. Physical exertion, social interaction, competition, and learning outcomes, which are valued according to Western studies, were not mentioned as significant features by Chinese children. These findings demonstrate a need to investigate the effect of cultural background in AVG study design.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".