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Advancing Higher Education: Longitudinal Study on AI Integration and Its Impact on Learning

International Journal of Cyber and IT Service Management · Vol. 5 No. 1 (2025) · pp. 23–30

DOI
10.34306/ijcitsm.v5i1.185
ISSN
2808-554X, 2797-1325
Published
2025-03-10
Publisher
Pandawan Sejahtera Indonesia
Language
en
License
creativecommons.org/licenses/by/4.0/

Abstract

The integration of Artificial Intelligence (AI) into higher education is reshaping the learning landscape. This longitudinal study explores AI impact on learning outcomes, student engagement, and the overall educational experience, focusing on five key variables: AI-enabled Personalized Learning (AIPL), Student Engagement Metrics, Cognitive Skill Development (CSD), Digital Literacy Advancement (DLA), and Educational Resource Optimization (ERO). Using Structural Equation Modeling (SEM) with SmartPLS, the study analyzes these variables to assess AI effectiveness as a pedagogical tool. By evaluating how AI influences student engagement and academic performance, this research highlights the potential of AI to enhance cognitive skills and digital literacy, optimize educational resources, and improve learning efficiency. The study spans multiple academic terms to track the evolving impact of AI, ensuring its long-term sustainability in modern education. The findings aim to inform future strategies for AI integration in higher education, contributing to the broader discourse on AI transformative role in education and providing actionable insights for educators and policymakers. By focusing on the core principles of AI-driven innovation and learning optimization, this research seeks to offer evidence-based recommendations to improve the quality and accessibility of education.

Keywords

Collaboration network of the authors

40 authors · 118 co-authorship links · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Catur Insan Cendekia Cirebon
  • Universitas Raharja
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Untung RahardjaAffiliation unknown3
Tuti NurhaeniAffiliation unknown2
Alfri AdiwijayaAffiliation unknown2
Dwi JulianingsihAffiliation unknown2
Mochamad Heru Riza ChakimAffiliation unknown2
Chandra LukitaUniversitas Catur Insan Cendekia Cirebon2
Ninda LutfianiUniversitas Raharja1
Ankur SinghAffiliation unknown1
Widya FebrianiAffiliation unknown1
Nuke Puji Lestari SantosoAffiliation unknown1
Amitkumar DudhatAffiliation unknown1
Husni Teja SukmanaAffiliation unknown1
Aditya MardiansyahAffiliation unknown1
Dewi ImmaniarAffiliation unknown1
Dedeh SupriyantiAffiliation unknown1
Nanda SeptianiAffiliation unknown1
Nur AzizahAffiliation unknown1
Hilda HildaAffiliation unknown1
Aan KaniviaAffiliation unknown1
Muhammad Faizal FazriAffiliation unknown1
Sabda MaulanaAffiliation unknown1
Suhandi SuhandiAffiliation unknown1
Suryari PurnamaAffiliation unknown1
Bayu Laksma PradanaAffiliation unknown1
Gautam KhannaAffiliation unknown1
Agung RizkyAffiliation unknown1
Muhammad Farhan KamilAffiliation unknown1
Brigitta CallulaAffiliation unknown1
Nur AzizahAffiliation unknown1
Kawl W KartsAffiliation unknown1
Ankur Singh BistAffiliation unknown1
Megha UpretiAffiliation unknown1
Chitra PandeyAffiliation unknown1
Buphest RawatAffiliation unknown1
Goh YaoAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://iiast.iaic-publisher.org/ijcitsm/index.php/IJCITSM/oai, first harvested 6 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Advancing Higher Education: Longitudinal Study on AI Integration and Its Impact on Learning</dc:title>
	<dc:creator xml:lang="en">Hardini, Marviola</dc:creator>
	<dc:creator xml:lang="en">Hetilaniar, Hetilaniar</dc:creator>
	<dc:creator xml:lang="en">Girsang, Semaria Eva Elita</dc:creator>
	<dc:creator xml:lang="en">Windiartono Putra, Souza Nurafrianto</dc:creator>
	<dc:creator xml:lang="en">Hikam, Ihsan Nuril</dc:creator>
	<dc:subject xml:lang="en">Artificial Intelligence</dc:subject>
	<dc:subject xml:lang="en">Higher Education</dc:subject>
	<dc:subject xml:lang="en">Personalized Learning</dc:subject>
	<dc:subject xml:lang="en">Student Engagement</dc:subject>
	<dc:description xml:lang="en">The integration of Artificial Intelligence (AI) into higher education is reshaping the learning landscape. This longitudinal study explores AI impact on learning outcomes, student engagement, and the overall educational experience, focusing on five key variables: AI-enabled Personalized Learning (AIPL), Student Engagement Metrics, Cognitive Skill Development (CSD), Digital Literacy Advancement (DLA), and Educational Resource Optimization (ERO). Using Structural Equation Modeling (SEM) with SmartPLS, the study analyzes these variables to assess AI effectiveness as a pedagogical tool. By evaluating how AI influences student engagement and academic performance, this research highlights the potential of AI to enhance cognitive skills and digital literacy, optimize educational resources, and improve learning efficiency. The study spans multiple academic terms to track the evolving impact of AI, ensuring its long-term sustainability in modern education. The findings aim to inform future strategies for AI integration in higher education, contributing to the broader discourse on AI transformative role in education and providing actionable insights for educators and policymakers. By focusing on the core principles of AI-driven innovation and learning optimization, this research seeks to offer evidence-based recommendations to improve the quality and accessibility of education.</dc:description>
	<dc:publisher xml:lang="en">Pandawan Sejahtera Indonesia</dc:publisher>
	<dc:date>2025-03-10</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://iiast.iaic-publisher.org/ijcitsm/IJCITSM/article/view/185</dc:identifier>
	<dc:identifier>10.34306/ijcitsm.v5i1.185</dc:identifier>
	<dc:source xml:lang="en">International Journal of Cyber and IT Service Management; Vol. 5 No. 1 (2025): April; 23-30</dc:source>
	<dc:source>2808-554X</dc:source>
	<dc:source>2797-1325</dc:source>
	<dc:source>10.34306/ijcitsm.v5i1</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://iiast.iaic-publisher.org/ijcitsm/IJCITSM/article/view/185/110</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2025 Marviola Hardini, Hetilaniar Hetilaniar, Semaria Eva Elita Girsang, Souza Nurafrianto Windiartono, Ihsan Nuril Hikam</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0/</dc:rights>
</oai_dc:dc>