Assessing EFL Undergraduates’ Attitudes, Engagement, and Satisfaction Toward the Use of Artificial Intelligence in Enhancing Reading Comprehension

This study aims to assess undergraduates’ attitudes, engagement, and satisfaction toward using Artificial Intelligence (AI) tools to enhance reading comprehension within the context of English as a Foreign Language (EFL) in Saudi Arabia. It measures their sub-dimensions; cognate, cognitive, and effectiveness attitude and behavioral, emotional, and cognitive engagement. A quantitative research design was employed using a five-point Likert scale-based questionnaire to address key questions on attitudes, engagement, satisfaction, and their correlations. A total of 170 English Language and Literature undergraduates from a Saudi university participated. Findings showed satisfaction ranked highest (M = 4.04), followed by attitude (M = 3.95), and engagement lowest (M = 3.90). Cognitive engagement (M = 4.14) was the strongest sub-dimension, closely linked to satisfaction, whereas emotional and behavioral engagement were weaker, indicating a need for more interactive AI tools. Students expressed willingness to recommend AI tools, though the impact of attitudes on academic success suggested room for enhancement. This study contributes to EFL research by holistically analyzing all the three dimensions and their sub-dimensions toward using AI-assisted reading comprehension. Unlike previous studies that examined these dimensions separately, it explores their interconnections. The main aim is to present the findings as recommendations for educators, AI developers, and EFL program administrators to better integrate AI tools in language education, as well as to contribute to a successful Al-assisted reading comprehension development, pedagogical insights, and practical implications for EFL teaching practices.