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Transforming Prospective Elementary Teachers' Social Studies Learning through Generative AI in the Digital Era

Jurnal Geografi · Vol. 18 No. 2 (2026) · pp. 352–369

DOI
10.24114/jg.v18i2.74429
ISSN
2549-7057, 2085-8167
Published
2026-08-27
Publisher
Universitas Negeri Medan
Language
en
License
creativecommons.org/licenses/by/4.0

Abstract

The rapid integration of Artificial Intelligence (AI) into higher education is transforming how prospective elementary school teachers access, interpret, and construct knowledge in Social Studies education. This study examines changes in learning patterns among prospective elementary school teachers in AI-supported Social Studies education, identifies factors associated with these changes, and explores instructional strategies used to maintain critical and reflective learning. Using a qualitative exploratory design, the study was conducted at Universitas Iskandar Muda, Banda Aceh, Indonesia. Data were collected through classroom observations, in-depth interviews with two lecturers and two prospective teachers, and document analysis. Data were analyzed interactively through data reduction, data display, and conclusion drawing. The findings reveal a shift from predominantly literature-based and reflective learning toward faster, AI-assisted information seeking and knowledge production. Participants associated this transformation with technological development, digital learning culture, academic workload, limited academic literacy, generational characteristics, and lecturers’ pedagogical practices. Although AI was perceived to improve the efficiency of information retrieval and broaden access to learning resources, participants also expressed concerns about reduced critical reflection, weaker social argumentation, and less intensive academic interaction when AI was used uncritically. In response, lecturers employed problem-based, inquiry-based, reflective, and collaborative learning, supported by AI literacy development, to encourage verification, interpretation, and critical engagement with AI-generated information. These findings highlight the importance of pedagogically guided AI integration in developing adaptive, critical, reflective, and human-centered Social Studies 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 Halu Oleo
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Wa IbaUniversitas Halu Oleo3
Ma’ruf KasimUniversitas Halu Oleo3
Abdul Muis BalubiAffiliation unknown3
Agus KurniaAffiliation unknown3
ABDUL RAHMANUniversitas Halu Oleo2
Dwiky Pobri CesarianAffiliation unknown2
Kadir SabiluAffiliation unknown2
Abdul Muis BalubiUniversitas Halu Oleo1
Agus RianoAffiliation unknown1
Muhammad IdrisUniversitas Halu Oleo1
L O M AslanUniversitas Halu Oleo1
La Ode Baytul AbidinUniversitas Halu Oleo1
Nova IndrianaUniversitas Halu Oleo1
Dita Pramesti Chayani RUniversitas Halu Oleo1
Marsella Rifiana Vean HasanAffiliation unknown1
Wellem H. MuskitaAffiliation unknown1
Tiyana TiyanaAffiliation unknown1
Ode MursalimUniversitas Halu Oleo1
Faisal Idul DarhinAffiliation unknown1
La Ode Kadir HusainAffiliation unknown1
Muhaimin HamzahUniversitas Halu Oleo1
Oce AstutiAffiliation unknown1
Dania DaniaAffiliation unknown1
Wellem H. MuskitaAffiliation unknown1
Laode M. AslanAffiliation unknown1
Roslindah Daeng SiangUniversitas Halu Oleo1
Irdam RianiUniversitas Halu Oleo1
Wa Ode PilianaUniversitas Halu Oleo1
Budiyanto BudiyantoUniversitas Halu Oleo1
Syamsul KamriUniversitas Halu Oleo1
Ragil LarasatiUniversitas Halu Oleo1
Pini AriskaUniversitas Halu Oleo1
Arwin ArwinAffiliation unknown1
Nurrahman FajriAffiliation unknown1
Aljikri YantoAffiliation unknown1
Rahmawati RahmawatiAffiliation 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) http://jurnal.unimed.ac.id/2012/index.php/geo/oai, first harvested 9 Nov 2026, last seen 9 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Transforming Prospective Elementary Teachers' Social Studies Learning through Generative AI in the Digital Era</dc:title>
	<dc:creator xml:lang="en">Ruslaini, Ruslaini</dc:creator>
	<dc:creator xml:lang="en">Mukhlis, Amir</dc:creator>
	<dc:creator xml:lang="en">Tindaon, Juwita</dc:creator>
	<dc:creator xml:lang="en">Isa, Muhammad</dc:creator>
	<dc:subject xml:lang="en">Artificial Intelligence</dc:subject>
	<dc:subject xml:lang="en">Prospective Teachers’ Learning</dc:subject>
	<dc:subject xml:lang="en">Social Studies Education</dc:subject>
	<dc:subject xml:lang="en">Critical Thinking</dc:subject>
	<dc:subject xml:lang="en">AI Literacy</dc:subject>
	<dc:description xml:lang="en">The rapid integration of Artificial Intelligence (AI) into higher education is transforming how prospective elementary school teachers access, interpret, and construct knowledge in Social Studies education. This study examines changes in learning patterns among prospective elementary school teachers in AI-supported Social Studies education, identifies factors associated with these changes, and explores instructional strategies used to maintain critical and reflective learning. Using a qualitative exploratory design, the study was conducted at Universitas Iskandar Muda, Banda Aceh, Indonesia. Data were collected through classroom observations, in-depth interviews with two lecturers and two prospective teachers, and document analysis. Data were analyzed interactively through data reduction, data display, and conclusion drawing. The findings reveal a shift from predominantly literature-based and reflective learning toward faster, AI-assisted information seeking and knowledge production. Participants associated this transformation with technological development, digital learning culture, academic workload, limited academic literacy, generational characteristics, and lecturers’ pedagogical practices. Although AI was perceived to improve the efficiency of information retrieval and broaden access to learning resources, participants also expressed concerns about reduced critical reflection, weaker social argumentation, and less intensive academic interaction when AI was used uncritically. In response, lecturers employed problem-based, inquiry-based, reflective, and collaborative learning, supported by AI literacy development, to encourage verification, interpretation, and critical engagement with AI-generated information. These findings highlight the importance of pedagogically guided AI integration in developing adaptive, critical, reflective, and human-centered Social Studies education.</dc:description>
	<dc:publisher xml:lang="en">Universitas Negeri Medan</dc:publisher>
	<dc:date>2026-08-27</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jurnal.unimed.ac.id/2012/index.php/geo/article/view/74429</dc:identifier>
	<dc:identifier>10.24114/jg.v18i2.74429</dc:identifier>
	<dc:source xml:lang="en">JURNAL GEOGRAFI; Vol. 18 No. 2 (2026): JURNAL GEOGRAFI; 352-369</dc:source>
	<dc:source>2549-7057</dc:source>
	<dc:source>2085-8167</dc:source>
	<dc:source>10.24114/2</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://jurnal.unimed.ac.id/2012/index.php/geo/article/view/74429/30613</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2026 Ruslaini Ruslaini, Amir Mukhlis, Juwita Tindaon, Muhammad Isa</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
</oai_dc:dc>