Trends on technologies and artificial intelligence in education for personalized learning: systematic literature review

The continuous development of new technology and rapid advancement of Artificial Intelligence (AI) contribute to the improvement and enrichment of the teaching and learning process. AI technology promotes a flexible, customized, and effective learning environment, as well as improves other educational competencies via personalized learning. To create a personalized learning environment, AI collects, compiles, and interprets data from a variety of sources to create student learning profiles. However, a lack of information exists on incorporating AI technology into educational settings to promote teaching efficiency in Malaysia. AI technology helps to predict how well students will learn, so we can make content that is tailored to each person’s goal and past success. To gain a better understanding of the concept and implementation of a personalized learning environment employing AI technology, a systematic literature review (SLR) was conducted to identify the trends of technologies and Artificial Intelligence in Education (AIEd) in promoting personalized learning. SLR has become the standard methodology for identifying answers by tracing the outcomes of past research by identifying and synthesising significant findings using systematic, transparent and repeatable techniques at each stage of the process. The literature search was performed in SCOPUS and Web of Sciences WoS) database and thirty-two articles from the years 2016 to 2022 were initially reviewed. From this number, 14 articles were included for analysis. Based on the findings, most learning elements, such as technology, teaching approach, teaching content can be adapted to each student's needs and learning intent in personalized learning. Personalised learning using AI is an approach that focuses on generating training to match the specific needs of each student such as in adaptive learning, online learning, MOOCs, and many other technologies. A few approaches on the other hand, appear to witness technological advancement as providing opportunities for individualised learning by applying analytical tools and algorithms to create automated adaptive learning activities and materials. The study of technologies for personalized learning in education in other nations has primarily concentrated on higher education, and it is advised that the scope of the research be expanded. In Malaysia. the implementation of these technologies in education should be bolstered. The research and practices reported in the study also show how personalized learning was used and factors that made it work, thus the finding of this paper will guide other researchers to recognize various personal traits and the identification of appropriate technology trends and activities for further studies, as well as assist developers in the development of the personalized learning system and closely related to the adaptive learning systems.

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