Buddha, Hareesh and Shuib, Liyana and Idris, Norisma and Eke, Christopher Ifeanyi (2024) Technology-Assisted Language Learning Systems: A Systematic Literature Review. IEEE Access, 12. pp. 33449-33472. ISSN 2169-3536, DOI https://doi.org/10.1109/ACCESS.2024.3366663.
Full text not available from this repository.Abstract
This study provides a systematic review of technology-assisted language learning. This study provides a summary content of the reviewed articles in the aspects of technology usage, language, and learning skills, and the benefits offered by technology in language learning. The study focused on the published articles between 2012 and 2022. Out of 5719 articles initially retrieved from five academic databases and reviewed, twenty-seven (27) research articles were selected. Based on the review findings, the most used technology is the intelligent system (n=7). The study also revealed that the most common target language is English (n=22), whereas skills such as vocabulary, writing, and grammar gained the most attention in the selected studies. The review also identified and analyzed the empirical evidence on the benefits of technology in language learning, such as language performance development, motivation, metacognitive skills, positive attitudes towards learning, enhancement of students' learning retention, collaborative learning model, and extensive learning opportunity. Barriers to the implementation of the technology, such as learning anxiety, insufficient technology literacy, and technical limitations, were also recognized, and some suggestions were provided to overcome those barriers. Thus, this review can be used as a guide for educators and researchers who intend to design technology-assisted language learning and teaching in the future.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Natural language processing; Language learning; learning skills; systematic literature review; technology-assisted language learning |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Computer Science & Information Technology > Department of Artificial Intelligence Faculty of Computer Science & Information Technology > Department of Information System |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 13 Nov 2024 02:53 |
| Last Modified: | 13 Nov 2024 02:53 |
| URI: | http://eprints.um.edu.my/id/eprint/45843 |
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