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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

  • Imam Abdulrahman Bin Faisal University

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article numberep635
JournalContemporary Educational Technology
Volume18
Issue number1
DOIs
StatePublished - Jan 2026

Keywords

  • anxiety
  • expectancy-value theory
  • generative artificial intelligence
  • pre-service teachers

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