Work

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

Year: 2024

Type: article

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.

Source: International Journal of ADVANCED AND APPLIED SCIENCES

DOI: 10.21833/ijaas.2024.12.004

Authors: Yusra Jadallah Abed Khasawneh, Mohamad Ahmad Saleem Khasawneh

Institutions: Ajloun National University, King Khalid University

Language: English

Topic: Educational Technology in Learning

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $469