A structural equation model analysis of English for specific purposes students' attitudes regarding computer-assisted language learning: UTAUT2 model - Bessadok, Adel; Hersi, Mustafa (Library hi tech, 2025)
PurposeThe objective of this study is to investigate the key determinants affecting the acceptance and utilization of Blackboard as a Computer-Assisted Language Learning (CALL) platform among Saudi university students pursuing English as a foreign language (EFL) courses.Design/methodology/approachUnderstanding how to engage EFL students in their learning requires identifying the factors that influence their acceptance and use of CALL tools, particularly on Blackboard's LMS platform. This study proposes and validates a research framework that predicts students' behavioral intentions and usage of CALL by utilizing the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) by Venkatesh et al. (2012). This research model provides insight into the various drivers that impact CALL acceptance via Blackboard LMS. The study's findings demonstrate UTAUT2's superior ability to address the fear of technology adoption and provide valuable insights into the factors that influence technology intention and usage.FindingsThe study's findings indicate that performance expectancy, social influence, effort expectancy and price value significantly affect the attitudes of EFL students toward using CALL. The habit factor was the most robust predictor of behavioral intention and technology use, indicating that CALL usage can become automatic for students and improve their engagement in EFL learning. The study highlights the importance of providing better technical and organizational support to EFL students who want to use CALL more effectively. The theoretical and practical implications of the study's findings are thoroughly discussed.Originality/valueUnderstanding how to engage EFL students in their learning requires identifying the factors that influence their acceptance and use of CALL tools, particularly on Blackboard's LMS platform. This study proposes and validates a research framework that predicts students' behavioral intentions and usage of CALL by utilizing the UTAUT2 by Venkatesh et al. (2012). This research model provides insight into the various drivers that impact CALL acceptance via Blackboard LMS. The study's findings demonstrate UTAUT2's superior ability to address the fear of technology adoption and provide valuable insights into the factors that influence technology intention and usage.