Empirical validation of the DEGREE model for mobile educational games in secondary education with the technology acceptance model
Abstract
This research explores the usability and user acceptance of a systematic assessment model for mobile digital educational games. While much of the current research focuses on how students adopt learning technologies, it rarely considers how they perceive the actual tools used to evaluate them. To fill this gap, our study combines the Technology Acceptance Model (TAM) with the DEGREE model to better understand user attitudes toward these assessment frameworks. A quantitative methodology was implemented, employing a structured instrument based on DEGREE dimensions and TAM constructs. After refining the instrument through expert feedback and preliminary pilot studies, we distributed the questionnaire to a large cohort of 4,800 high school students across 207 schools in Indonesia. This extensive participant pool was specifically tasked with assessing two learning platforms: Duolingo and Minecraft Education Edition. To analyze the empirical data, we utilized the AMOS software to execute covariance-based Structural Equation Modelling (CB-SEM). While the primary model incorporating a hedonic 'Fun' variable failed to meet fit requirements, a subsequent refined model excluding this factor displayed superior goodness-of-fit. Our results indicate that Attitude Toward Using is predominantly shaped by Perceived Usefulness, while Perceived Ease of Use exerts only a negligible influence. Furthermore, functional usability elements, specifically accessibility and operability, proved more significant than hedonic components in the evaluation process. This work expands the utility of TAM for assessing meta-level analytical instruments and emphasizes the necessity of usability-centric strategies in evaluating mobile game-based learning environments.
Fields of Study & Subjects
Technology Adoption and User Behaviour
Educational Games and Gamification
Usability and User Interface Design
Publication details
- Journal / source
- Decision Science Letters
- Publisher
- Growing Science
- Volume
- 15
- Issue
- 3
- Pages
- 867–880
- Publication date
- 1 January 2026
- Language
- EN