AI-Supported Formative Assessments: Enhancing Student-Centered Learning and Teacher Perceptions - Mousa, Mojahed (Journal of Pedagogy and Education Science, 2025)
This study evaluates the effectiveness of AI-supported formative assessments in student-centered learning. Using a reliable questionnaire with a Cronbach's alpha of .854, the research explores teachers' views on AI tools and their impact on formative assessment practices. The findings reveal a generally positive attitude among educators, with an average score of 92.79 and a moderate standard deviation of 9.03, indicating a strong appreciation for AI's role in data collection, analysis, and the creation of innovative assessment tasks. However, the variability in responses points to differing levels of familiarity and perception regarding AI. Interestingly, there were no significant differences in opinions among teachers from public, private, or UNRWA schools, suggesting that factors beyond the type of school play a role in shaping perceptions of AI in formative assessment. Ethical concerns also emerged, including issues related to data privacy, intellectual property, and the potential effects on critical thinking skills. These concerns underscore the necessity for robust data protection policies, ethical guidelines, and comprehensive educational training to mitigate risks and foster responsible AI use. The study concludes that while AI has the potential to greatly enhance formative assessments by boosting efficiency and offering valuable insights, its integration must be approached with careful attention to ethical considerations and academic integrity. Establishing clear guidelines and training programs is crucial for effectively utilizing AI in a student-centered learning environment.