<![CDATA[The rapid adoption of generative artificial intelligence (AI) in higher education has raised concern about cognitive laziness, a tendency of students to offload thinking processes to AI tools without critical engagement (Risko & Gilbert, 2016; Gerlich, 2025). This quasi-experimental study examined the effect of a Transformative Learning-based instructional design on mitigating AI-induced cognitive laziness among pre-service biology teachers studying the Bioethics topic within the Biotechnology course. A one-group pretest-posttest design was applied to 30 students of the Biology Education Study Program, FKIP Universitas Pasundan, selected through purposive sampling. The intervention was implemented in four stages adapted from Mezirow's framework: disorienting dilemma, critical reflection, reflective discourse, and action planning, applied to bioethical case analysis so that students had to justify positions instead of relying uncritically on AI-generated answers. Data were collected using a Cognitive Laziness Scale and analyzed using a paired-sample t-test and N-gain calculation. Results showed a statistically significant decrease in cognitive laziness scores from pretest to posttest (p < 0.05), with an average N-gain in the moderate category. Students demonstrated improved habits of verifying AI output and constructing independent ethical arguments. These findings suggest that Transformative Learning is a viable pedagogical strategy to preserve critical thinking amid increasing AI use in biotechnology and bioethics instruction]]>
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