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Title: AI and the Future of Learning: Personalization, Equity, and Ethical Challenges
Authors: Dr. Shahzad Rasool, Humera Anwar Lodhi, Dr. Ijaz Hussain
Journal: Journal of Social Signs Review
| Category | From | To |
|---|---|---|
| Y | 2024-10-01 | 2025-12-31 |
Publisher: Knowledge Key Research Institute
Country: Pakistan
Year: 2025
Volume: 3
Issue: 4
Language: en
Keywords: Artificial Intelligence in EducationPersonalized Learningeducational equityEthical AI in Learning
By encouraging individualized learning and the creation of moral challenges that need serious thought, artificial intelligence (AI) is revolutionizing education (Roll et al., 2021; Selwyn, 2019). Examining how AI may improve personalized learning, advance equity and accessibility, and tackle ethical dilemmas was the goal of the current study. This paper examines the important role of AI in education, focusing on how it affects individualized instruction, equitable access to learning materials, and the moral conundrums raised by algorithm-based decision-making. To fully comprehend AI's impact in educational settings, the study used a mixed-methods research approach that combines quantitative and qualitative techniques. The study was restricted to universities that used AI-powered learning resources. Faculty, students, and EdTech experts from Pakistani public and private colleges that have incorporated AI-based learning resources make up the study's population. To guarantee a varied representation from both public and private universities, a stratified random sample technique was used. Surveys and semi-structured interviews were used to collect data on how well AI might tailor learning and alleviate educational disparities. In order to discover ethical concerns and issues, a validated questionnaire was developed to gather perspectives regarding AI-driven learning, and thematic analysis was utilized to analyze qualitative data. In order to help policymakers, educators, and tech developers create appropriate AI-driven learning environments, the project's outcomes would provide empirical evidence about the benefits and drawbacks of AI in education.
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