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Title: | Investigating the predictors of adolescent learners’ continuance intention to engage with a gamified e-learning platform about traffic safety in Vietnam | Authors: | LE, Hoang Nam CUENEN, Ariane TRINH, Tu Anh JANSSENS, Davy WETS, Geert KHATTAK, Wisal BRIJS, Kris |
Issue Date: | 2025 | Publisher: | Elsevier | Source: | Transportation Research Part F: Traffic Psychology and Behaviour, 109 (February) , p. 1229 -1245 | Abstract: | Introduction: Although e-learning systems are seen as a key part of learning and training activities, many learners stop using them after a period of initial engagement. Prior studies provided insights into e-learning participation, but in the context of traffic safety, little research has been done on learners’ intention to continue using (gamified) e-learning. Objectives: This study aims to investigate whether the following predictors of learners’ continuance intention towards a gamified e-learning platform: satisfaction, attitude, interface design, learning content, learning management and gamification. In addition, the study investigates whether satisfaction mediates the effects of these predictors. Method: A sample of 322 Vietnamese adolescents participated in a study where a gamified e-learning platform was implemented in a sample of high school students. Results: Satisfaction, gamification, interface design and learning content were found to be important predictors of continuance intention. Moreover, satisfaction was a significant mediator of the effects generated by gamification, interface design and learning content on continuance intention. Practical implications: The findings of this study offer useful insights on the successful implementation of a gamified e-learning platform about traffic safety. | Keywords: | Continuance intention;E-learning;Gamification;Traffic safety education;Vietnam | Document URI: | http://hdl.handle.net/1942/45476 | ISSN: | 1369-8478 | e-ISSN: | 1873-5517 | DOI: | https://doi.org/10.1016/j.trf.2025.01.032 | Rights: | © 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. | Category: | A1 | Type: | Journal Contribution |
Appears in Collections: | Research publications |
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