Gamify: Towards Tailored Gamification Informed by Users' Personality, Emotional State, and Demographics

Third Author's Department

Computer Science & Engineering Department

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https://doi.org/10.5220/0013290300003932

All Authors

Amal Yassien Youssef Elsharkawy Alia Elbolock Slim Abdennadher

Document Type

Research Article

Publication Title

International Conference on Computer Supported Education Csedu Proceedings

Publication Date

1-1-2025

doi

10.5220/0013290300003932

Abstract

Recently, gamification has gained world-wide interest in several domains, especially educational ones, to increase user engagement and learning effectiveness. Using gamification, there are several mechanics that designers leverage to motivate users to engage with the game (e.g. streaks, progress, time limit, .. etc). However, it remains unclear which gamification mechanic would be most effective for individuals with different personality traits and emotional states, age, gender, and field-of-study. To this end, we introduce “Gamify”, a user-profile empirical study (N = 65) that sheds light on how gamification mechanics, namely rewarding and penalizing, along with user profile (made up of (1) personality (represented by Big-Five Model), (2) emotional state, (3) age group, (4) field-of-study, and (5) gender) affect users' experience. To achieve this, we have designed a trivia-based game, where users have riddles that they should answer using 4 provided choices. Within our user-study, we had 4 different levels (reward only, penalty only, reward and penalty, no gamification mechanic). Our results show that the preference of specific gamification mechanic differed according to user profiles. For instance, users below 18 preferred being exposed to both the rewarding and penalizing mechanic. Using Gamify, game developers can create a tailored gaming experience that engages users having different user profiles.

First Page

737

Last Page

744

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