Relationship Between Children’s Enjoyment, User Experience Satisfaction, and Learning in a Serious Video Game for Nutrition Education: Empirical Pilot Study
Why this work is in the frame
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Bibliographic record
Abstract
Background The design and use of serious video games for children have increased in recent years. To maximize the effects of these games, it is essential to understand the children’s experiences through playing. Previous studies identified that enjoyment and user experience satisfaction of the players are principal factors that can influence the success of serious video games and the learning of their players. However, research about the relationship between enjoyment and user experience satisfaction with learning in children 8 to 10 years old is sparse. Objective We examined the relationship of enjoyment and user experience satisfaction with the learning of children aged 8 to 10 years while playing a serious video game for health, FoodRateMaster. This serious video game teaches children about the characteristics of healthy and unhealthy foods and how to identify them in their environment. Methods Children aged 8 to 10 years were recruited from a primary school in Mexico. Participants completed 12 individual gaming sessions with FoodRateMaster in 6 weeks. A food knowledge questionnaire was administered before and after game play to assess the players’ food knowledge. In addition, after the gaming sessions, the children’s enjoyment and user experience satisfaction were evaluated using the EGameFlow questionnaire and the Game User Experience Satisfaction Scale (GUESS) questionnaire. Results We found significant positive associations for children’s (n=60) posttest knowledge with enjoyment (r58=0.36, P=.005) and user experience satisfaction (r58=0.27, P=.04). The children’s posttest knowledge scores were also positively correlated with challenge (r58=0.38, P=.003), knowledge improvement (r58=0.38, P=.003), and goal clarity (r58=0.29, P=.02) EGameFlow subscales and with narrative (r58=0.35, P=.006), creative freedom (r58=0.26, P=.04), and visual esthetics (r58=0.32, P=.01) GUESS subscales. Regression analysis indicated that the EGameFlow (F7,52=2.74, P=.02, R2=0.27) and the GUESS (F8,51=2.20, P=.04, R2=0.26) ratings significantly predicted the children’s posttest knowledge scores. EGameFlow challenge (β=0.40, t52=2.17, P=.04) and knowledge improvement (β=0.29, t52=2.06, P=.04) subscales significantly contributed to predicting children’s learning. None of the GUESS subscales significantly contributed to predicting children’s learning. Conclusions The findings of this study suggest that both enjoyment and user experience satisfaction for children aged 8 to 10 years were positively correlated with their learning and that were significant predictors of it. Challenge, knowledge improvement, narrative, creative freedom, and visual esthetics subscales correlated positively with children’s learning. In addition, challenge and knowledge improvement contributed to predicting their learning. These results are relevant to consider during the design stages of serious games developed for young children’s learning purposes.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it