Analyzing AI’s Role in Promoting Diversity and Inclusivity within Educational Systems, Addressing different Learning Styles and Needs
DOI:
https://doi.org/10.47067/ramss.v7i4.446Keywords:
Artificial Intelligence, Inclusivity, Diversity, Education, Academic Performance, Teacher Training, Data AnalysisAbstract
This comprehensive study critically examines the critical role that artificial intelligence plays in varying contexts of education towards increasing diversity and inclusion. There is a higher emphasis on how AI has highly significant impacts on the ability to include a wide variety of diverse needs to learn among the students, the facilitation of accessibility to resources for people with disabilities, and the reduction of language barriers, which often pose a challenge to effective communication and comprehension. Data was collected through a strong quantitative research method. A sample size of 300 university educators was used. They were selected with the help of stratified random sampling from the list of various institutions located in the Punjab and Khyber Pakhtunkhwa provinces of Pakistan, hence providing a well-represented view of the educational scenario prevalent in these two provinces. Data were collected using self-administered questionnaires designed to elicit and review attitudes and experiences with AI by education instructors working in the educational field. By applying correlation analysis, regression analysis, and PCA collectively, statistically relevant and significant results were brought out. Correlation analysis revealed a very strong positive correlation that exists between the adoption of artificial intelligence and the improvement of academic results. This is confirmed by the correlation coefficient, which measures 0.70 with a p-value of 0.002, which is particularly related to academic performance and an associated coefficient of 0.68 with a p-value of 0.003, which is particularly related to higher engagement in inclusive classroom environments. A regression study was also carried out that revealed AI-based technologies as the major predictors of higher engagement among students, whose beta coefficient stood at 0.65 with a highly significant p-value less than 0.01. Lastly, PCA was conducted and various critical factors found to influence the integration of AI technologies, issues such as access for students and training for educators. These significant findings highlight the incredible ability of AI technology to create and promote educational settings that are not only more inclusive but also fundamentally fairer for all participants involved.
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