Assessment in the Age of AI A writing-based approach in a Psychology Research Methods course

Abstract

This personal narratives reflects on how the availability of generative AI has prompted a reevaluation of assessment strategies in my undergraduate research methods course. Traditionally, the course focused on developing students’ ability to read and synthesize primary-source research using a series of article summaries. I suspected, though, that some students were submitting articulate, but AI-generated summaries without engaging with the source material. To address this, I piloted a new strategy: integrating open-ended, application-based questions that asked students to connect course concepts to the specific journal articles they had chosen. Given that I was piloting this approach during the Spring 2025 semester, I introduced these questions as extra-credit prompts rather than prompts scored for test credit.
 
The responses fell into three clear patterns: students who left the questions blank, those who provided surface-level answers, and those who demonstrated deep, thoughtful application of course content. This approach highlighted for me the limitation of traditional article summary assignments in the AI era; however, it also highlighted the potential of applied assessments to encourage students to encourage with research literature. Encouraged by the insights this approach provided, I now plan to integrate similar prompts into standard assessments and class activities, using both shared and student-selected articles to scaffold research literacy. This narrative emphasizes the emotional and pedagogical impact of this small assessment change in my course. It argues that the goal is not to “detect” AI use, but to design learning experiences that motivate students to engage with research literature.