Gamification and e-learning for young learners: A systematic literature review, bibliometric analysis, and future research agenda
Article
Behl, A., Jayawardena, N., Pereira, V., Islam, N., Del Giudece, M. and Choudrie, J. 2022. Gamification and e-learning for young learners: A systematic literature review, bibliometric analysis, and future research agenda. Technological Forecasting and Social Change. 176 (Art. 121445). https://doi.org/10.1016/j.techfore.2021.121445
Authors | Behl, A., Jayawardena, N., Pereira, V., Islam, N., Del Giudece, M. and Choudrie, J. |
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Abstract | Over the last few years, gamification has sparked significant interest in both industry and academia. However, the focus of the debate has been mostly on game studies and human-computer interaction (HCI). Even though games are increasingly being supplied as services to customers, few academic works have linked game studies to the service or marketing literature (Dikcius and Urbonavicius, 2020; Dukembay and Zhaksylyk, 2019). This paper presents an examination of the emerging trends of gamification and e-learning for young learners. The first section presents a text-based cluster bibliometric analysis based on 222 qualified articles published between 2015 and 2020. We conducted this analysis to identify the most prominent themes in the literature through cluster identification via the VOS viewer software. As the themes were found to be interlinked, the second section presents a systematic literature review based on a bibliometric analysis performed using the PRISMA method on 32 qualified articles. The findings highlighted the four major future research themes of personalization, game elements, learner styles, and learner engagement. Finally, we provide a future research agenda based on the theory, characteristics, context, and methodology (TCCM) framework. Our findings offer key insights aimed at enabling actors in education policy making and gamification-based software companies and agencies to identify the gamification techniques best suited for e-learning. |
Journal | Technological Forecasting and Social Change |
Journal citation | 176 (Art. 121445) |
ISSN | 0040-1625 |
Year | 2022 |
Publisher | Elsevier |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.techfore.2021.121445 |
Publication dates | |
Online | 31 Dec 2021 |
Mar 2022 | |
Publication process dates | |
Deposited | 25 Mar 2024 |
https://repository.uel.ac.uk/item/8x789
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