Evaluating the Impact of AI Dependency on Cognitive Ability among Generation Z in Higher Educational Institutions: A Conceptual Framework

Suraya Ika Tamrin, Nor Farehan Omar, Khairul Nazlin Kamaruzaman, Azlul Kalilah Zaghlol and Muhammad Ridzuan Abdul Aziz

Information Management and Business Review, 2024, vol. 16, issue 3, 1027-1033

Abstract: This research aims to examine the factors of AI dependency (AID) and to investigate the relationship between AI dependency on cognitive ability (CA) among Generation Z (Gen Z) in higher educational institutions. The factors involved are academic self-efficacy (ASE), academic stress (AS), and performance expectation (PE). In this research, the proposed research design is a quantitative method. A self?administered questionnaire will be distributed to respondents, a group of students who were born between 1997 to 2012, and the AI user. The questionnaire will be utilizing the Google Form platform for easier data collection. A snowball sampling method will be applied. Then, the data collected will be analyzed through the partial least square (PLS-SEM) technique. The research findings are expected to highlight the significant emphasis on the contributing factors of AI dependency among Gen Z students. Then, the findings will also provide a model to understand better the impact of AI dependency on cognitive ability. Additionally, it is foreseen that the findings will help various parties, including the government, to create better models for helping Gen Z students apply AI in decent ways to help them increase their cognitive ability. It is also considered a long-term strategy to become a nation with numbers of high cognitive ability citizens. Further, a practical framework based on AI dependency on cognitive ability will be developed as a guideline to support the effort of the government or industry practitioners to increase awareness among Gen Z students on how crucial to possess high cognitive ability.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:rnd:arimbr:v:16:y:2024:i:3:p:1027-1033

DOI: 10.22610/imbr.v16i3S(I)a.4191

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