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Arab World English Journal (AWEJ) Special Issue on Artificial Intelligence 2025 Pp.112-138
Department of English Language and Literature, College of Languages and Translation, Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia
Department of English Language and Literature, College of Languages and Translation, Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia
Department of English Language and Literature, College of Languages and Translation, Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia
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.
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Shaden Khalid Alarifi
A student pursuing a Master’s in Applied Linguistics at the Department of English Language and Literature, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia. She earned her BA in English Language and Literature from IMSIU.
ORCiD: https://orcid.org/0009-0004-9055-6260
Manal Mohammad Alsahli
A student pursuing a Master’s in Applied Linguistics at the Department of English Language and Literature, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia. She earned her BA in English Language and Literature from IMSIU.
ORCiD: https://orcid.org/0009-0002-6175-5717
Dr. Talal Musaed Alghizzi
An Associate Professor in Applied Linguistics at the Department of English Language and Literature, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia.
He earned his BA in English Language and Literature and an MA in Translation from IMSIU, followed by a second MA and a PhD in Applied Linguistics from University College Cork, Ireland. Dr. Alghizzi’s research interests include translation, language skills, and technology integration. He has published numerous articles in reputable journals such as Frontiers in Psychology, Electronics, and Heliyon. ORCiD: https://orcid.org/0000-0002-1088-9216