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| Natura: | Preprint |
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2026
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| Accesso online: | https://arxiv.org/abs/2603.13267 |
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| _version_ | 1866910052440342528 |
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| author | Ricker, Anna Katharina Marquardt, Kai Happe, Lucia |
| author_facet | Ricker, Anna Katharina Marquardt, Kai Happe, Lucia |
| contents | Although personalization is widely advocated in gamified learning, empirical evidence on how learner characteristics and task context shape motivational preferences remains limited. This study examines how user characteristics and learning activity types relate to preferences for gamification elements in digital education. A large-scale quantitative survey (N = 530), including 34% underage participants, assessed preferences for 13 gamification elements in relation to Age, Gender, HEXAD Player Type, Big Five Personality Traits, Felder-Silverman Learning Styles, and Bloom-based Learning Activity Types. Inferential statistical analyses and exploratory machine learning techniques revealed systematic but generally small-to-moderate effects across parameters. Age emerged as the most consistent predictor of preference, followed by player type and personality traits, whereas gender and learning styles showed comparatively weaker associations. In addition, learning activity type significantly influenced the perceived suitability of gamification elements, indicating that motivational design is task-dependent. The findings suggest that gamification effectiveness cannot be reduced to universally motivating elements. Instead, preferences are shaped by the interaction of learner characteristics and instructional context. These results provide empirical grounding for adaptive and modular gamification strategies in digital learning environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_13267 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Gamification Preferences in Digital Education: The Role of Individual Differences Ricker, Anna Katharina Marquardt, Kai Happe, Lucia Computers and Society Human-Computer Interaction Software Engineering Although personalization is widely advocated in gamified learning, empirical evidence on how learner characteristics and task context shape motivational preferences remains limited. This study examines how user characteristics and learning activity types relate to preferences for gamification elements in digital education. A large-scale quantitative survey (N = 530), including 34% underage participants, assessed preferences for 13 gamification elements in relation to Age, Gender, HEXAD Player Type, Big Five Personality Traits, Felder-Silverman Learning Styles, and Bloom-based Learning Activity Types. Inferential statistical analyses and exploratory machine learning techniques revealed systematic but generally small-to-moderate effects across parameters. Age emerged as the most consistent predictor of preference, followed by player type and personality traits, whereas gender and learning styles showed comparatively weaker associations. In addition, learning activity type significantly influenced the perceived suitability of gamification elements, indicating that motivational design is task-dependent. The findings suggest that gamification effectiveness cannot be reduced to universally motivating elements. Instead, preferences are shaped by the interaction of learner characteristics and instructional context. These results provide empirical grounding for adaptive and modular gamification strategies in digital learning environments. |
| title | Gamification Preferences in Digital Education: The Role of Individual Differences |
| topic | Computers and Society Human-Computer Interaction Software Engineering |
| url | https://arxiv.org/abs/2603.13267 |