International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12
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 Volume 11, Issue 12 (December 2024), Pages: 34-41

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 Original Research Paper

Cognitive load analysis of adaptive learning technologies in special education classrooms: A quantitative approach

 Author(s): 

 Yusra Jadallah Abed Khasawneh 1, Mohamad Ahmad Saleem Khasawneh 2, *

 Affiliation(s):

 1Department of Educational Administration, Faculty of Educational Sciences, Ajloun National University, Ajloun, Jordan
 2Special Education Department, King Khalid University, Abha, Saudi Arabia

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 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0002-1390-3765

 Digital Object Identifier (DOI)

 https://doi.org/10.21833/ijaas.2024.12.004

 Abstract

This study examines the effects of adaptive learning technology on cognitive load in special education classrooms using a quantitative approach. The research included students with various disabilities who interacted with adaptive learning tools such as Virtual Reality (VR), Gamification, and Artificial Intelligence (AI). Data analysis involved statistical methods like descriptive statistics, t-tests, ANOVA, correlation, and regression analyses. The findings indicate notable differences in the cognitive load associated with different technologies, with AI technology resulting in a higher cognitive burden compared to VR and Gamification. Additionally, factors such as academic performance, age, and gender were found to influence the level of cognitive load experienced by students. The results emphasize the importance of considering the cognitive demands of adaptive learning technologies and tailoring instructional design and technology integration based on individual needs. Recommendations are offered to educators, curriculum developers, and policymakers to enhance learning opportunities for students with disabilities.

 © 2024 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

 Adaptive learning, Cognitive load, Special education, Virtual reality, Artificial intelligence

 Article history

 Received 3 April 2024, Received in revised form 15 October 2024, Accepted 16 November 2024

 Acknowledgment

The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Large Research Groups under grant number (RGP.2 / 311 /45).

 Compliance with ethical standards

 Ethical considerations

Informed consent was obtained from all participants or their legal guardians. Participant anonymity and data confidentiality were strictly maintained.

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Khasawneh YJA and Khasawneh MAS (2024). Cognitive load analysis of adaptive learning technologies in special education classrooms: A quantitative approach. International Journal of Advanced and Applied Sciences, 11(12): 34-41

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 Tables

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