Abstract

The present decade has seen a rise in the use of Artificial Intelligence (AI). The utilization of AI has become popular in different sectors including education. These AI tools have several advantages such as personalized learning, instant feedback and automated learning which could enhance learning outcomes. However, concerns have been raised over the effectiveness of these AI tools on student learning outcomes. The purpose of this study is to assess the effectiveness of AI-powered homework tools on student learning outcomes. The objective of the study was to investigate how AI- powered homework tools affect a learner’s academic performance. To guide this research, Cognitive Load Theory (CLT) by John Sweller was applied.  The theory explains how the brain processes and stores information. Sweller suggests that the brain’s long-term memory is unlimited but the working memory is limited. Thus, it is important that learning is structured effectively by breaking down complex concepts or removing unnecessary information. This study is done on existing research papers and scholarly articles using descriptive research design. 50 articles were found on the topic and from these a sample of 30% was used. Sources suggest that while AI tools can positively affect students’ academic performance, care should be taken to avoid overreliance. These findings will contribute to the ongoing discourse on the use of AI in learning, thus, giving insights to policymakers, teachers and educators on how best to enforce the use of AI in a school environment.