Advanced Learning Analytics with AI: Analyzing Stakeholder Perceptions of Feedback, Assessment, Engagement, and Faculty Development in MENA Higher Education Using NLP
摘要
This study explores the perceptions of students and faculty members across multiple MENA countries, including the UAE, Jordan, Egypt, Saudi Arabia, and Oman, focusing on the effects of internationalization and technological integration in higher education. Using a mixed-methods approach, the research incorporates Natural Language Processing (NLP) analysis, thematic coding, and participant feedback on key educational quality factors: feedback mechanisms, assessment practices, student engagement, diversity and inclusivity, faculty development, and graduate outcomes. Data was collected through an online questionnaire, with participants representing diverse demographics and academic fields. The findings provide valuable insights into the influence of English as the primary medium of instruction on Arabic proficiency, the role of technology in enhancing personalized learning, and the importance of faculty-student engagement. The study highlights the need for improved bilingual proficiency, transparent feedback processes, and support for experiential learning. It emphasizes areas for policy reform to better align academic strategies with evolving educational standards and cultural contexts.