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Category: Project

Description: Research has shown that serious games, digital game based learning, or educational videogames can be a powerful learning instrument. However, experimental and meta-research revealed several moderators and variables influencing the resulting learning outcomes. Advances in the areas of learning and game analytics potentially allow for controlling and improving the underlying learning processes by adapting the game and its mechanics to individual needs of the learner, properties of the learning material, and/or environmental factors. This might be one of the major advantages of highly dynamic learning environments such as video games, compared to more static learning material. However, the field is still in its infancy and no clear cut guidelines are available yet. To shed more light on this topic and to identify common grounds for further research, we conducted a systematic analysis of the literature. For this review, we followed and documented the PRISMA guidelines and theoretical recommendations for systematic reviews. Particular interest was paid to different modes of adaptivity (e.g., real-time, between learning sequences), adaptive mechanic (e.g., difficulty, pace, presentation), differences in learning domains and populations, theoretical frameworks (e.g., cognitive or motivational models), research methods (e.g., experimental, explorative, laboratory setting, real-world application), theoretical frameworks (e.g., flow, Yerkes-Dodson law), measured concept (e.g., heart rate, performance), as well as on the underlying measures and analytics (e.g., behavioural or physiological data, raw or processed data). This review provides a clear picture of the state-of-the art and the entangled potentials and challenges. Additionally, research gaps and structural weaknesses of the current approaches within the field will be discussed.