Authors :
Niteegya Bhushan
Volume/Issue :
Volume 11 - 2026, Issue 4 - April
Google Scholar :
https://tinyurl.com/mej47vba
Scribd :
https://tinyurl.com/2hyrwfbz
DOI :
https://doi.org/10.38124/ijisrt/26apr209
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
The expeditious evolution of generative artificial intelligence (GenAI) is fundamentally reshaping pedagogy,
learning settings, and academic practices within higher education. Despite a proliferation of literature on GenAI in
education, the field remains fragmented across technological, pedagogical, and psychological domains. This review
synthesizes recent literature (2020–2025), focusing on GenAI's role in supporting academic achievement via AI-mediated
digital practices. The analysis specifically examines how key psychological mediators including motivation, cognitive
engagement, self-regulated learning, and emotional engagement interact with GenAI use. Furthermore, the paper addresses
critical ethical and governance challenges related to GenAI adoption, such as algorithmic bias, academic integrity, data
governance, and student privacy. Based on this synthesis, a conceptual framework is proposed to explain how GenAI can
effectively promote academic achievement when integrated within ethically responsible and pedagogically sound educational
environments.
Keywords :
Generative Artificial Intelligence; Academic Achievement; Higher Education; Educational Technology; Student Engagement.
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The expeditious evolution of generative artificial intelligence (GenAI) is fundamentally reshaping pedagogy,
learning settings, and academic practices within higher education. Despite a proliferation of literature on GenAI in
education, the field remains fragmented across technological, pedagogical, and psychological domains. This review
synthesizes recent literature (2020–2025), focusing on GenAI's role in supporting academic achievement via AI-mediated
digital practices. The analysis specifically examines how key psychological mediators including motivation, cognitive
engagement, self-regulated learning, and emotional engagement interact with GenAI use. Furthermore, the paper addresses
critical ethical and governance challenges related to GenAI adoption, such as algorithmic bias, academic integrity, data
governance, and student privacy. Based on this synthesis, a conceptual framework is proposed to explain how GenAI can
effectively promote academic achievement when integrated within ethically responsible and pedagogically sound educational
environments.
Keywords :
Generative Artificial Intelligence; Academic Achievement; Higher Education; Educational Technology; Student Engagement.