Navigating beyond the “AI-generated view”: an educational intervention for source verification in higher education
DOI:
https://doi.org/10.31637/epsir-2027-2946Keywords:
generative artificial intelligence, AI-powered search engines, information literacy, source verification, higher education, critical information evaluation, digital navigation, task designAbstract
Introduction: The integration of generative artificial intelligence into search engines is transforming information access practices in higher education. Features such as the so-called “AI-generated view” provide synthesized answers that may reduce students’ navigation and verification of sources. Methodology: This study analyzes an educational intervention designed to promote active search and verification practices beyond AI-generated responses. The intervention was implemented over one academic semester in a university course involving 146 students. The activity required documentary evidence of the search process, including URLs, screenshots, verification of academic references through DOIs, and cross-checking information across multiple digital sources. Results: The findings show that students initially tended to accept AI-generated information without accessing external links or verifying references. The introduction of explicit requirements for navigation and validation encouraged more active exploration of sources. Discussion: The results suggest that task design can influence how students use AI-powered search engines. Conclusions: The study highlights the role of pedagogical task design in strengthening media and information literacy in higher education contexts increasingly mediated by artificial intelligence.
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