Trends and development in technology-enhanced adaptive/personalized learning : a systematic review of journal publications from 2007 to 2017

Haoran XIE*, Hui-Chun CHU, Gwo-Jen HWANG, Chun Chieh WANG

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

290 Citations (Scopus)


In this study, the trends and developments of technology-enhanced adaptive/personalized learning have been studied by reviewing the related journal articles in the recent decade (i.e., from 2007 to 2017). To be specific, we investigated many research issues such as the parameters of adaptive/personalized learning, learning supports, learning outcomes, subjects, participants, hardware, and so on. Furthermore, this study reveals that personalized/adaptive learning has always been an attractive topic in this field, and personalized data sources, for example, students’ preferences, learning achievements, profiles, and learning logs have become the main parameters for supporting personalized/adaptive learning. In addition, we found that the majority of the studies on personalized/adaptive learning still only supported traditional computers or devices, while only a few studies have been conducted on wearable devices, smartphones and tablet computers. In other words, personalized/adaptive learning has a significant number of potential applications on the above smart devices with the rapid development of artificial intelligence, virtual reality, cloud computing and wearable computing. Through the in-depth analysis of the trends and developments in the various dimensions of personalized/adaptive learning, the future research directions, issues and challenges are discussed in our paper.

Original languageEnglish
Article number103599
JournalComputers and Education
Early online date6 Jun 2019
Publication statusPublished - Oct 2019
Externally publishedYes

Bibliographical note

The research described in this paper has been partially supported by the Ministry of Science and Technology of the Republic of China under contract number MOST 106-2511-S-011 -005 -MY3 and MOST 104-2511-S-031 -003 -MY4, the Innovation and Technology Fund (Project No. GHP/022/17GD) from the Innovation and Technology Commission of the Government of the Hong Kong Special Administrative Region, and the Interdisciplinary Research Scheme of the Dean's Research Fund 2018-19 (FLASS/DRF/IDS-3) of The Education University of Hong Kong.


  • Adaptive/personalized learning
  • Application in subject areas
  • Pedagogical issues
  • Teaching and learning strategies


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  • The Most Cited Article in Computers & Education

    XIE, Haoran (Recipient), CHU, Hui-Chun (Recipient), HWANG, Gwo-Jen (Recipient) & WANG, Chun Chieh (Recipient), Sept 2021

    Prize: Prize (CDCF)

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