The Role of Personalized AI-Based Learning Tools in Reducing Cognitive Overload and Enhancing Academic Motivation
DOI:
https://doi.org/10.47067/ramss.v8i3.544Keywords:
Personalized AI, Cognitive Overload, Academic Motivation, University Students, Adaptive Learning, Higher Education, Student Engagement, Learning Efficiency, Quantitative Research, SPSSAbstract
This study observed into the impact of AI-based personalized learning systems on the management of cognitive overload and motivation in learning among university students. The focus of the study is on the AI use and student's motivational levels during the learning process as well as information retention. The study employed a quantitative methodology which was based on a sample of250 university students from the Punjab region of Pakistan and structured questionnaires. Participants from the sample were selected using simple random sampling, and the information was analyzed using version 26 of the SPSS software package. The relationships among the variables were tested using regression, correlation, descriptive, and ANOVA statistics. The results have established an opposite and significant relation between the use AI-based learning tools and the extent of cognitive overload; which suggests that the personalized AI help had lowered mental strain amongst students. Furthermore, the regression showed that AI tools have strong positive impacts on academic motivation, while cognitive overload was associated with lower motivation. These results clearly demonstrate that AI-based, and personalized learning tools can help foster a positive, productive and stimulating learning atmosphere. This research further recognizes the use of AI in the post-secondary learning environment with the aim of learning optimization, stress alleviation, and motivation enhancement. Clearly, the incorporation of personalized AI tools in education is beneficial for improving academic performance and student engagement.
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