
The increasing popularity of mobile devices and advancements in digital gaming have stimulated the development of educational solutions that combine entertainment and learning. As part of Mobile Learning (m-learning) and Game-Based Learning (GBL) approaches, mobile educational games have been shown to promote motivation, engagement, and autonomy in the teaching process. This article presents a Systematic Literature Mapping (SLM) analysis of 176 studies published between 2019 and 2024 in the Scopus, Web of Science and IEEE Xplore databases. The objective was to identify trends, technologies, methodologies, and evaluation strategies relating to the development and use of educational games in mobile applications. The SLM protocol comprised three stages: planning, execution, and reporting. The results reveal the diversity of approaches and technologies adopted, including game engines, augmented reality, and native languages, as well as the application of various methodologies and gamification elements. There was also a growing emphasis on personalization and user-centered design. However, challenges such as a lack of standardization, limited empirical validation, and accessibility and infrastructure barriers persist. The SLM highlights the potential of mobile games in developing cognitive and socio-emotional skills and emphasizes the need for future studies to improve evaluation models and the personalization and application of these resources in different educational contexts.
TK7885-7895, QA76.75-76.765, Computer engineering. Computer hardware, Computer software, Systematic Literature Mapping, Mobile Applications, Educational Games
TK7885-7895, QA76.75-76.765, Computer engineering. Computer hardware, Computer software, Systematic Literature Mapping, Mobile Applications, Educational Games
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
