The Use of Artificial Intelligence Tools in Assessing Content Validity: A Comparative Study with Human Experts
This addresses the problem of automating educational assessment for test developers, but it is incremental as it builds on existing AI evaluation methods.
The study compared AI and human evaluators on assessing content validity of B1-level English reading comprehension test items, finding no statistically significant differences in scores, with AI potentially replacing humans in some cases.
In this study, it was investigated whether AI evaluators assess the content validity of B1-level English reading comprehension test items in a manner similar to human evaluators. A 25-item multiple-choice test was developed, and these test items were evaluated by four human and four AI evaluators. No statistically significant difference was found between the scores given by human and AI evaluators, with similar evaluation trends observed. The Content Validity Ratio (CVR) and the Item Content Validity Index (I-CVI) were calculated and analyzed using the Wilcoxon Signed-Rank Test, with no statistically significant difference. The findings revealed that in some cases, AI evaluators could replace human evaluators. However, differences in specific items were thought to arise from varying interpretations of the evaluation criteria. Ensuring linguistic clarity and clearly defining criteria could contribute to more consistent evaluations. In this regard, the development of hybrid evaluation systems, in which AI technologies are used alongside human experts, is recommended.