Effectiveness of AI-Based Personalised Reading Platforms in Enhancing Reading Comprehension

Authors

DOI:

https://doi.org/10.56059/jl4d.v11i1.955

Keywords:

microlearning, instructional design, instructional methods, cognitive load theory, learning effectiveness

Abstract

This study aimed at evaluating the effectiveness of microlearning in higher education. The sample consisted of first-year MBA students, and a post-test control group design was used to assess the effectiveness of a microlearning module. The results indicated that the use of microlearning was significantly related to learning performance and participants' reactions to the module. Moreover, the microlearning group scored significantly higher than the control group. The findings suggest that microlearning has the potential to improve learning outcomes and enhance participant engagement. However, the study has certain limitations, and future research is needed to gain a comprehensive understanding of the optimal design and delivery of microlearning modules. The study supports the use of microlearning in higher education as an effective instructional strategy.

Author Biography

Muhamad Taufik Hidayat, Institut Pendidikan Indonesia Garut

Muhamad Taufik Hidayat is an Assistant Professor currently teaching at Institut Pendidikan Indonesia Garut. He received his Master's Degree in English Education from Universitas Pendidikan Indonesia, where he developed a keen interest in language, education, language learning, language acquisition and translation studies. Email: mtaufikhidayat637@gmail.com, muhamadtaufik@institutpendidikan.ac.id

Downloads

Published

2024-03-23

How to Cite

Hidayat, M. T. (2024). Effectiveness of AI-Based Personalised Reading Platforms in Enhancing Reading Comprehension. Journal of Learning for Development, 11(1), 115–125. https://doi.org/10.56059/jl4d.v11i1.955

Issue

Vol. 11 No. 1 (2024): ISSUE 1

Section

Research Articles

License

Copyright (c) 2024 Muhamad Taufik Hidayat

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Authors who publish with this journal agree to the following terms:

    1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.

 

    1. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.

 

  1. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Received 2023-03-25
Accepted 2024-02-27
Published 2024-03-23