"AI Framework for Predicting Student Comprehension in Online Learning: Lecturer Perspectives"

"Artificial Intelligence (AI) has become a transformative force in higher education, particularly in addressing the challenge of assessing and supporting student comprehension within online learning environments. This study examines university lecturers\u2019 perspectives on the pedagogical potential and ethical implications of AI-driven frameworks designed for real-time comprehension prediction. Drawing on data collected through a structured questionnaire distributed to Sri Lankan lecturers with varied online teaching experience, the research integrates qualitative insights. Findings indicate that lecturers demonstrate a strong appreciation for the pedagogical value of AI-based systems, especially those that facilitate adaptive and data-informed teaching. Most respondents viewed real-time feedback and behavioral analysis tools as effective mechanisms to enhance engagement and instructional responsiveness. This optimism reflects a growing readiness among educators to integrate AI into their online pedagogical practice, provided such systems align with educational objectives and institutional capacity. Simultaneously, ethical considerations emerged as a defining concern. The study recognises that while lecturers recognize AI\u2019s potential to strengthen online teaching through real-time comprehension prediction, their support is contingent upon clear ethical safeguards and institutional accountability. It recommends that universities develop policy frameworks that prioritize informed consent, privacy protection, and equitable access, alongside targeted capacity-building initiatives. Balancing technological innovation with ethical responsibility will be essential for AI to serve as a genuine pedagogical ally in higher education."