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Personalised Learning in STE(A)M Education: A Literature Review

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Blended Learning: Re-thinking and Re-defining the Learning Process. (ICBL 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12830))

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Abstract

This paper presents a review study on the characteristics and patterns of personalised learning in the context of STEM and STEAM (or STE(A)M) education, which involves the disciplinary integration of Science, Technology, Engineering, Mathematics, as well as Arts. It covered a total of 63 papers published in 2011–2020 collected from Scopus and Google Scholar. The results show the widespread practice of personalised learning, and the United States was the country with most studies carried out. In terms of the level of education, secondary education was a major focus. Mathematics accounted for the largest proportion of subject discipline in the studies, followed by Science and Engineering. Blended environment was the most popular mode of education, followed by the face-to-face classroom. The most frequent objective of personalised learning was to cater for students’ learning styles. The popular means to achieve personalised learning included the use of blended learning, learning analytics, and adaptive e-learning systems. Regarding the research issue, above half of the studies evaluated the impact or effectiveness of a technology, system or device for personalised learning. Based on the results, potential areas of future work are suggested, such as the contextualised practice of STE(A)M education in various countries, and the personalisation in interdisciplinary STE(A)M education.

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Acknowledgments

The work described in this paper was partially supported by a grant from the Open University of Hong Kong (2021/011).

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Authors and Affiliations

  1. The Open University of Hong Kong, Hong Kong, China

    Kam Cheong Li & Billy Tak-Ming Wong

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  1. Kam Cheong Li
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  2. Billy Tak-Ming Wong
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Correspondence to Billy Tak-Ming Wong .

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Editors and Affiliations

  1. Hong Kong Polytechnic University, Hong Kong, China

    Richard Li

  2. Open University of Hong Kong, Hong Kong, China

    Simon K. S. Cheung

  3. Kansai University, Osaka, Japan

    Chiaki Iwasaki

  4. City University of Hong Kong, Hong Kong, China

    Lam-For Kwok

  5. Nihon Fukushi University, Nagoya, Japan

    Makoto Kageto

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Li, K.C., Wong, B.TM. (2021). Personalised Learning in STE(A)M Education: A Literature Review. In: Li, R., Cheung, S.K.S., Iwasaki, C., Kwok, LF., Kageto, M. (eds) Blended Learning: Re-thinking and Re-defining the Learning Process.. ICBL 2021. Lecture Notes in Computer Science(), vol 12830. Springer, Cham. https://doi.org/10.1007/978-3-030-80504-3_12

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  • DOI: https://doi.org/10.1007/978-3-030-80504-3_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-80503-6

  • Online ISBN: 978-3-030-80504-3

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