Training Epistemic Skepticism: The Effectiveness of AI Output Validation Exercises in Enhancing Students' Critical Thinking Skills in Pet Morphology Analysis - Risya Pramana Situmorang; Gamaliel Septian Airlanda; Sefni Oemolos (JIPI (Jurnal IPA & Pembelajaran IPA), 2026)
In a context of widespread use of artificial intelligence (AI) for visual analysis, an important pedagogical challenge is to encourage the development of a critical approach that goes beyond simply using tools to analyze in depth the results produced by AI. The purpose of this study is to develop pre-service teachers’ critical thinking about information produced by AI by using a case study on the morphology of cat whiskers and evidence from GPT-4.0. Using mixed-methods, the study examined narrative project reports in which students captured whisker images and requested AI analysis, while independently cross-checking results with veterinary literature. Qualitative analysis found improved critical thinking, concluding that validating AI accuracy promotes crucial scientific skepticism and empowers students to be informed consumers of technology. While the findings validate the usefulness of these types of verification activities, the study indicates that higher-level skills (e.g., forming competing hypotheses) need to be developed in instruction. In the end, this approach will help students analyze critically claims about AI and ways to trust and suspect AI that are appropriate for an AI-laden knowledge environment. The findings also emphasise the need to intentionally incorporate verification tasks into prospective teachers' programmes so they are prepared to facilitate digital literacy in the classrooms of tomorrow. In this study, a qualitative content analysis method, transcribing and coding of action research project reports, was employed as a means to identify key critical thinking constructs. Results were further grouped according to our research questions, and rigor was achieved through triangulation, peer debriefing, and member checks