The purpose of this study is to conduct a systematic review to understand state-of-art research related to learning preferences from the aspects of impacts, influential factors and evaluation methods.
This paper uses the systematic synthesis method to provide state-of-the-art knowledge on learning preference research by summarizing published studies in major databases and attempting to aggregate and reconcile the scientific results from the individual studies. The findings summarize aggregated research efforts and improve the quality of future research.
After analyzing existing literature, this study proposed three possible research directions in the future. First, researchers might focus on how to use the real-time tracking mechanism to further understand other impacts of learning preferences within the learning environments. Second, existing studies mainly focused on the influence of singular factors on learning preferences. The joint effects of multiple factors should be an important topic for future research. Finally, integrated algorithms might become the most popular evaluation method of learning preference in the era of smart learning environments.
This review used the search results generated by Google Scholar and Web of Science databases. There might be published papers available in other databases that have not been taken into account.
The research summarizes the state-of-art research related to learning preferences. This paper is one of the first to discuss the development of learning preference research in smart learning environments.
This work was supported by National Natural Science Foundation of China under Grant 61807013, and self-determined research funds of CCNU from the colleges’ basic research and operation of MOE(CCNU19ZN003).
Zhang, L., Du, X., Hung, J.-L. and Li, H. (2021), "Learning preference: development in smart learning environments", Information Discovery and Delivery, Vol. 49 No. 2, pp. 174-187. https://doi.org/10.1108/IDD-07-2020-0080
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