GenAI Learning for Game Design: Both Prior Self-Transcendent Pursuit and Material Desire Contribute to a Positive Experience

This study explores factors influencing positive experiences with generative AI (GenAI) in a learning game design context. Using a sample of 26 master’s-level students in a course on AI’s societal aspects, this study examines the impact of (1) prior knowledge and attitudes toward technology and learning, and (2) personal value orientations. Results indicated that both students’ self-transcendent goals and desire for material benefits have positive correlations with collaborative, cognitive, and affective outcomes. However, self-transcendent goals are a stronger predictor, as determined by stepwise regression analysis. Attitudes toward technology were positively associated with cognitive and affective outcomes during the first week, though this association did not persist into the second week. Most other attitudinal variables were not associated with collaborative or cognitive outcomes but were linked to negative affect. These findings suggest that students’ personal values correlate more strongly with the collaborative, cognitive, and affective aspects of using GenAI for educational game design than their attitudinal attributes. This result may indicate that the design experience neutralizes the effect of earlier attitudes towards technology, with major influences deriving from personal value orientations. If these findings are borne out, this study has implications for the utility of current educational efforts to change students’ attitudes towards technology, especially those that encourage more women to study STEM topics. Thus, it may be that, rather than pro-technology instruction, a focus on value orientations would be a more effective way to encourage diverse students to participate in STEM programs.

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Publication Details

Journal
Big Data and Cognitive Computing
Published
2025-03-27
DOI
https://doi.org/10.3390/bdcc9040078
Citations
2
Primary Topic
Innovative Human-Technology Interaction
Type
article
Field-Weighted Citation Impact
3.87
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article

GenAI Learning for Game Design: Both Prior Self-Transcendent Pursuit and Material Desire Contribute to a Positive Experience

James E. Katz, Dongpeng Huang
2 citations
Big Data and Cognitive Computing
Innovative Human-Technology Interaction
3.87
article

GenAI Learning for Game Design: Both Prior Self-Transcendent Pursuit and Material Desire Contribute to a Positive Experience

James E. Katz, Dongpeng Huang
article en
2 citations

Abstract

This study explores factors influencing positive experiences with generative AI (GenAI) in a learning game design context. Using a sample of 26 master’s-level students in a course on AI’s societal aspects, this study examines the impact of (1) prior knowledge and attitudes toward technology and learning, and (2) personal value orientations. Results indicated that both students’ self-transcendent goals and desire for material benefits have positive correlations with collaborative, cognitive, and affective outcomes. However, self-transcendent goals are a stronger predictor, as determined by stepwise regression analysis. Attitudes toward technology were positively associated with cognitive and affective outcomes during the first week, though this association did not persist into the second week. Most other attitudinal variables were not associated with collaborative or cognitive outcomes but were linked to negative affect. These findings suggest that students’ personal values correlate more strongly with the collaborative, cognitive, and affective aspects of using GenAI for educational game design than their attitudinal attributes. This result may indicate that the design experience neutralizes the effect of earlier attitudes towards technology, with major influences deriving from personal value orientations. If these findings are borne out, this study has implications for the utility of current educational efforts to change students’ attitudes towards technology, especially those that encourage more women to study STEM topics. Thus, it may be that, rather than pro-technology instruction, a focus on value orientations would be a more effective way to encourage diverse students to participate in STEM programs.

Big Data and Cognitive ComputingVol. 9(4)
Boston University (US)
Openalex Percentile: Top 9%
Innovative Human-Technology Interaction
3.87
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GenAI Learning for Game Design: Both Prior Self-Transcendent Pursuit and Material Desire Contribute to a Positive Experience — James E. Katz, Dongpeng Huang · Big Data and Cognitive Computing (2025) | TGRS Research Map | TGRS