An investigation of pre-service teachers’ perceptions of generative artificial intelligence using an instrument based on expectancy-value theory and an evaluation of their learning anxiety

Abeer Aidh Alshwiah; Lamees Abdulrahman  Alaulamie

doi:10.30935/cedtech/17982

Abeer Aidh Alshwiah ¹ ^* , Lamees Abdulrahman Alaulamie ¹

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CONT ED TECHNOLOGY, Volume 18, Issue 1, Article No: ep635

https://doi.org/10.30935/cedtech/17982

Submitted: 28 February 2025, Published Online: 26 February 2026

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Abstract

This study aimed to determine the extent and effects of pre-service teachers’ (PSTs) knowledge of generative artificial intelligence (GenAI) techniques, and to identify their perceptions of the benefits and potential challenges of GenAI. It also sought to determine PSTs’ anxiety over GenAI learning and the risk of job replacement. Students’ perceptions of artificial intelligence were therefore gathered to help ascertain the changes necessary for integrating GenAI into their courses. To achieve these aims, a mixed methods approach was adopted. Thus, a survey (quantitative method) was conducted to discover the relationship between PSTs’ knowledge of GenAI and the following variables: (1) willingness to use GenAI, (2) concerns regarding the use of GenAI, (3) anxiety about learning, and (4) anxiety about job replacement. A sample of 170 PSTs participated in this survey, with results indicating moderate knowledge of GenAI. Moreover, positive correlations were found between the participants’ knowledge of GenAI and their willingness to use it, concern over its uses, and anxiety about learning and job replacement. Interviews (a qualitative method) were subsequently carried out with 10 survey participants to explore the potential benefits and challenges associated with using GenAI in learning, and to validate the survey results. GenAI technologies can provide users with instantly accessible feedback and suggestions for assignments. However, the interviewees mentioned a number of challenges, like a lack of training courses, presence of bias and discrimination in the data, and ignorance of the University’s rules for GenAI use.

Keywords: generative artificial intelligence, expectancy-value theory, anxiety, pre-service teachers

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Citation

Alshwiah, A. A., & Alaulamie, L. A. (2026). An investigation of pre-service teachers’ perceptions of generative artificial intelligence using an instrument based on expectancy-value theory and an evaluation of their learning anxiety. Contemporary Educational Technology, 18(1), Article ep635. https://doi.org/10.30935/cedtech/17982

Alshwiah, A. A., and Alaulamie, L. A. (2026). An investigation of pre-service teachers’ perceptions of generative artificial intelligence using an instrument based on expectancy-value theory and an evaluation of their learning anxiety. Contemporary Educational Technology, 18(1), ep635. https://doi.org/10.30935/cedtech/17982

Alshwiah AA, Alaulamie LA. An investigation of pre-service teachers’ perceptions of generative artificial intelligence using an instrument based on expectancy-value theory and an evaluation of their learning anxiety. CONT ED TECHNOLOGY. 2026;18(1), ep635. https://doi.org/10.30935/cedtech/17982

Alshwiah, Abeer Aidh, and Lamees Abdulrahman Alaulamie. "An investigation of pre-service teachers’ perceptions of generative artificial intelligence using an instrument based on expectancy-value theory and an evaluation of their learning anxiety". Contemporary Educational Technology 2026 18 no. 1 (2026): ep635. https://doi.org/10.30935/cedtech/17982

Alshwiah, Abeer Aidh et al. "An investigation of pre-service teachers’ perceptions of generative artificial intelligence using an instrument based on expectancy-value theory and an evaluation of their learning anxiety". Contemporary Educational Technology, vol. 18, no. 1, 2026, ep635. https://doi.org/10.30935/cedtech/17982

Alshwiah AA, Alaulamie LA. An investigation of pre-service teachers’ perceptions of generative artificial intelligence using an instrument based on expectancy-value theory and an evaluation of their learning anxiety. CONT ED TECHNOLOGY. 2026;18(1):ep635. https://doi.org/10.30935/cedtech/17982