Pre-service teachers’ perceptions and readiness to embrace AI-based assessment and grading systems: Implications for future educational practices
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2025
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Abstract
This study investigated pre-service educators’ perceptions and willingness to adopt AI-powered assessment and grading tools as innovative alternatives to traditional evaluation methods. The research addressed six research questions and one hypothesis. A descriptive correlational research design was employed to explore pre-service educators’ perceptions and readiness toward adopting AI-driven assessment tools, guided by the constructs of the Technology Acceptance Model (TAM), specifically perceived ease of use and perceived usefulness. The study sample comprised 220 pre-service educators randomly selected from the Federal College of Education (Technical), Akoka, Lagos, Nigeria. Out of the 220 questionnaires distributed, 198 were duly completed and returned. Data were collected using a researcher-developed instrument titled Perceptions and Willingness of Pre-Service Teachers toward the Adoption of AI-Powered Assessment Tools. The reliability of the instrument was confirmed through Cronbach’s Alpha, which yielded a coefficient of 0.73, indicating good internal consistency. Descriptive statistics, including mean and standard deviation, were used to answer the research questions, while multiple regression analysis was applied to test the hypothesis at a 0.05 level of significance. The findings revealed that pre-service educators viewed AI-powered assessment tools as useful, efficient, and user-friendly, with a generally high level of willingness to adopt them. However, some concerns were noted regarding trust, transparency, and the accuracy of AI grading systems. The study concludes that integrating AI-based assessment and grading tools into teacher education curricula could enhance instructional efficiency, improve feedback quality, and better prepare future teachers for technologically advanced educational environments.
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| Authors | Ejiro Ufuoma Oduntan, Rashidat Kehinde Ademosu, Oluwatomi Modupeola Alade |
| Journal | Aminu Kano Academic Scholars Association Multidisciplinary Journal |
| Year | 2025 |
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| Keywords | Keywords not found |
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