Short-Term Gains, Long-Term Gaps: the Impact of Gen-AI and Search Technologies on Retention

dc.contributor.author Akgün, Mahir
dc.contributor.author Toker, Sacip
dc.contributor.other Information Systems Engineering
dc.date.accessioned 2025-09-05T15:34:24Z
dc.date.available 2025-09-05T15:34:24Z
dc.date.issued 2025
dc.description Google; Gates Foundation; Hewlett Packard Enterprise; Eedi; VitalSource; Duolingo English Test; Springer en_US
dc.description.abstract The rise of Generative AI (GenAI) tools, such as ChatGPT, has transformed how students access and engage with information, raising questions about their impact on learning outcomes and retention. This study investigates how GenAI (ChatGPT), search engines (Google), and e-textbooks influence student performance across tasks of varying cognitive complexity, based on Bloom’s Taxonomy. Using a sample of 123 students, we examined performance in three tasks: [1] knowing and understanding, [2] applying, and [3] synthesizing, evaluating, and creating. Results indicate that ChatGPT and Google groups outperformed the control group in immediate assessments for lower-order cognitive tasks, benefiting from quick access to structured information. However, their advantage diminished over time, with retention test scores aligning with those of the e-textbook group. For higher-order cognitive tasks, no significant differences were observed among groups, with the control group demonstrating the highest retention. These findings suggest that while AI-driven tools facilitate immediate performance, they do not inherently reinforce long-term retention unless supported by structured learning strategies. The study highlights the need for balanced technology integration in education, ensuring that AI tools are paired with pedagogical approaches that promote deep cognitive engagement and knowledge retention. © 2025 Elsevier B.V., All rights reserved. en_US
dc.identifier.doi 10.1007/978-3-031-99264-3_6
dc.identifier.isbn 9789819671748
dc.identifier.isbn 9789819664610
dc.identifier.isbn 9783032008831
dc.identifier.isbn 9789819671779
dc.identifier.isbn 9783031949425
dc.identifier.isbn 9789819666874
dc.identifier.isbn 9783031936968
dc.identifier.isbn 9783031941207
dc.identifier.isbn 9789819669653
dc.identifier.isbn 9783031961953
dc.identifier.issn 1865-0937
dc.identifier.issn 1865-0929
dc.identifier.scopus 2-s2.0-105013019597
dc.identifier.uri https://doi.org/10.1007/978-3-031-99264-3_6
dc.identifier.uri https://hdl.handle.net/20.500.14411/10798
dc.language.iso en en_US
dc.publisher Springer Science and Business Media Deutschland GmbH en_US
dc.relation.ispartof Communications in Computer and Information Science – Poster papers and late breaking results, workshops and tutorials, practitioners, industry and policy track, doctoral consortium, blue sky and wide AIED papers presented at the 26th International Conference on Artificial Intelligence in Education, AIED 2025 – Palermo – 335989 en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject AI in Education en_US
dc.subject Bloom’s Taxonomy en_US
dc.subject Generative AI en_US
dc.subject Retention en_US
dc.subject Search Tools en_US
dc.subject Artificial Intelligence en_US
dc.subject Education Computing en_US
dc.subject Engineering Education en_US
dc.subject Learning Systems en_US
dc.subject Search Engines en_US
dc.subject Students en_US
dc.subject Teaching en_US
dc.subject AI in Education en_US
dc.subject Bloom’s Taxonomy en_US
dc.subject Cognitive Task en_US
dc.subject Control Groups en_US
dc.subject E-Textbooks en_US
dc.subject Performance en_US
dc.subject Retention en_US
dc.subject Search Tools en_US
dc.subject Short-Term Gains en_US
dc.subject Textbooks en_US
dc.title Short-Term Gains, Long-Term Gaps: the Impact of Gen-AI and Search Technologies on Retention en_US
dc.type Conference Object en_US
dspace.entity.type Publication
gdc.author.institutional Toker, Sacip
gdc.author.scopusid 57528167000
gdc.author.scopusid 56608927500
gdc.coar.access metadata only access
gdc.coar.type text::conference output
gdc.description.department Atılım University en_US
gdc.description.departmenttemp [Akgün] Mahir, Pennsylvania State University, University Park, United States; [Toker] Sacip, Department of Information Systems Engineering, Atilim University, Ankara, Turkey en_US
gdc.description.endpage 52 en_US
gdc.description.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality N/A
gdc.description.startpage 44 en_US
gdc.description.wosquality N/A
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