https://revistas.ponteditora.org/index.php/e3/issue/feed 2026-07-19T01:56:24-05:00 Áurea Sousa | Maria José Gonçalves | Luís Filipe Sardinha | António Abreu | Jão Vidal Carvalho | Manuel Silva luis.sardinha@staff.uma.pt Open Journal Systems <p data-start="361" data-end="688">Under the motto of Fernando Pessoa, “<em>My homeland is the Portuguese language,</em>” <strong>e³</strong> – Journal of Economics, Business and Entrepreneurship in the community of Portuguese-speaking countries is an international peer-reviewed scientific journal dedicated to the dissemination of research in economics, management and entrepreneurship.</p> <p data-start="690" data-end="970">Initially focused on promoting scientific knowledge within the Lusophone community, the journal now aims to foster dialogue between Portuguese-speaking and international researchers, contributing to the advancement of interdisciplinary research and knowledge transfer to society.</p> <p data-start="972" data-end="1156">The journal is published biannually in digital format and provides immediate open access to all content, supporting the principle that scientific knowledge should be freely accessible.</p> https://revistas.ponteditora.org/index.php/e3/article/view/1218 2026-06-10T05:31:28-05:00 Paola Palomino-Flores paola.palomino@upc.edu.pe Olenka Palomino-Flores palomino.ole@gmail.com Orly Carvache-Franco ocarvach@hotmail.com Klaus Berckholtz-Benavides k.berckh@gmail.com

<p>This study examines the transformation of learning processes in higher education within contexts mediated by artificial intelligence (AI), focusing on how students evaluate the quality and reliability of knowledge in algorithmic environments. Using a qualitative approach, 20 semi-structured interviews were conducted with undergraduate students in the final two semesters of their program who use AI tools in their academic activities. The analysis identified differentiated patterns in verification practices, levels of cognitive autonomy, and criteria for evaluating information. The findings suggest that students combine active validation strategies with judgments based on the coherence and immediacy of responses. Uneven bias detection was also observed, revealing limitations in the critical evaluation of AI-generated content. The study concludes that the quality of learning in AI-mediated environments depends in part on situated practices of verification, evaluation, and trust regulation. In this regard, the study proposes the incorporation of “epistemic hygiene,” understood as the systematic development of competencies in critical judgment, comparison, and validation of knowledge generated by algorithmic systems.</p>

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