Teachers’ Perceptions of AI-Based Evaluation and a Suggested Questionnaire
DOI:
https://doi.org/10.3991/ijim.v20i13.61147Keywords:
teachers’ perceptions, artificial intelligence, evaluation, assessment, exams, questionnaireAbstract
Artificial intelligence tools are being utilized by teachers for various purposes, among which is their use for evaluation. The present research examines teachers’ perceptions of this use. It does that by suggesting a relevant questionnaire. Moreover, the research examines the level of teachers’ perceptions of this use, and whether there are significant differences in these perceptions due to background variables, specifically gender, qualification, specialization and experience with AI. Two hundred and sixty-four teachers participated in the research. We used R and SPSS 27.00 to analyse the data. The research results indicated that the suggested questionnaire had two components, with good model fit and indices. The Gender variables resulted in significant differences in the component ‘assessment with AI’ with small effect size. The Qualification variable resulted in significant difference in the ‘Exams prepared with AI’ component, with negligible effect size. AI experience variable made a significant difference only for the "Exams prepared with AI" component, consistently benefiting those with more experience. This effect, however, was negligible. It is recommended that the suggested questionnaire be used by educational researchers in different populations to verify the level of teachers’ perceptions of AI-based evaluation, across different cultures, in addition to the effect of different background variables on this level.Artificial intelligence (AI) tools are being utilized by teachers for various purposes, among which is their use for evaluation. The present study examines teachers’ perceptions of this use. It does that by suggesting a relevant questionnaire. Moreover, the research examines the level of teachers’ perceptions of this use and whether there are significant differences in these perceptions due to background variables, specifically gender, qualification, specialization, and experience with AI. Two hundred and sixty-four teachers participated in the research. We used R and SPSS 27.00 to analyze the data. The study results indicated that the suggested questionnaire had two components, with good model fit and indices. The gender variables resulted in a significant difference in the component ‘assessment with AI’ with a small effect size. The qualification variable resulted in a significant difference in the ‘Exams prepared with AI’ component, with negligible effect size. The AI experience variable made a significant difference only for the “Exams prepared with AI” component, consistently benefiting those with more experience. This effect, however, was negligible. It is recommended that the suggested questionnaire be used by educational researchers in different populations to verify the level of teachers’ perceptions of AI-based evaluation across different cultures, in addition to the effect of different background variables on this level.
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