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AI-based scaffolding and conceptual understanding: evidence from Indonesian students using PLS-SEM

International Journal of Evaluation and Research in Education (IJERE) · Vol. 15 No. 2 (2026) · hlm. 1060–1078

DOI
10.11591/ijere.v15i2.38450
ISSN
2620-5440, 2252-8822
Terbit
2026-04-01
Penerbit
Institute of Advanced Engineering and Science
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-nc/4.0

Abstrak

The rapid integration of artificial intelligence (AI) in higher education has increased interest in AI-based scaffolding (AIS) to support conceptual learning, particularly in teacher education. However, empirical evidence explaining how learners’ cognitive, self-regulatory, and technological characteristics jointly shape perceptions of AIS remains limited, especially in developing country contexts. This study examines the predictive relationships among conceptual understanding (CU), cognitive engagement (CE), self-regulated learning (SRL), perceived ease of use (PEOU), AI self-efficacy (AISE), and perceived scaffolding quality in explaining Indonesian undergraduate teacher education students’ perceptions of AIS. Using a quantitative explanatory–predictive design, data were collected from 157 students and analyzed using partial least squares structural equation modeling (PLS-SEM). The results indicate that SRL, PEOU, and AISE are the strongest predictors of perceived AIS, while CU, CE, and scaffolding quality also show significant positive associations. These findings highlight the importance of learner readiness and instructional design in AI-enhanced learning environments. Practically, teacher education programs should integrate AI scaffolding that explicitly supports self-regulation, builds students’ confidence in using AI tools, and promotes sustained CE in complex learning tasks.

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  • State University of Malang
  • Universiti Putra Malaysia
  • Universitas Tamansiswa Padang
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Rekan penulisOrganisasiArtikel bersama
Susiswo SusiswoState University of Malang2
Siti Salina MustakimUniversiti Putra Malaysia2
Yusuf HanafiAfiliasi tidak diketahui2
P. SetyosariAfiliasi tidak diketahui1
S. SafaruddinState University of Malang1
I Nyoman DegengState University of Malang1
Tsania Nur DiyanaState University of Malang1
Muhammad SaefiAfiliasi tidak diketahui1
M. Alifudin IkhsanAfiliasi tidak diketahui1
Abd Rauf HassanAfiliasi tidak diketahui1
Sisworo SisworoAfiliasi tidak diketahui1
Shofi Farihah MuazarahAfiliasi tidak diketahui1
Mohammad Imam UtoyoAfiliasi tidak diketahui1
Yuni ZahrinaAfiliasi tidak diketahui1
Ria CerianaAfiliasi tidak diketahui1
Widya SariAfiliasi tidak diketahui1
Dilla SriwahyuniAfiliasi tidak diketahui1
Rafika Nila KandiAfiliasi tidak diketahui1
Alfinatul RahmiAfiliasi tidak diketahui1
Lisa MaulidinaAfiliasi tidak diketahui1
Syahrial SyahrialUniversitas Tamansiswa Padang1
Subanji SubanjiState University of Malang1
Sukoriyanto SukoriyantoState University of Malang1
Satriya Adika Arif AtmajaAfiliasi tidak diketahui1
Makbul MuksarAfiliasi tidak diketahui1
Enditiyas PratiwiAfiliasi tidak diketahui1
Ade Eka AnggrainiAfiliasi tidak diketahui1
Norliza GhazaliAfiliasi tidak diketahui1
Farah Damia Mohd NasirAfiliasi tidak diketahui1
Muhammad AlfanAfiliasi tidak diketahui1
Muslihati MuslihatiAfiliasi tidak diketahui1
Asnul Dahar MinghatAfiliasi tidak diketahui1
Mujahidin FaridAfiliasi tidak diketahui1
Nooraini OthmanAfiliasi tidak diketahui1
SUDIRMAN SUDIRMANState University of Malang1
Yustinus WangguwayAfiliasi tidak diketahui1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) http://ijere.iaescore.com/index.php/IJERE/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">AI-based scaffolding and conceptual understanding: evidence from Indonesian students using PLS-SEM</dc:title>
	<dc:creator>Nuryanis, Nuryanis</dc:creator>
	<dc:creator>Nusantara, Toto</dc:creator>
	<dc:creator>Murtadho, Nurul</dc:creator>
	<dc:creator>Faizah, Siti</dc:creator>
	<dc:subject xml:lang="en-US">AI self-efficacy; AI-based scaffolding; conceptual understanding; PLS-SEM; self-regulated learning</dc:subject>
	<dc:description xml:lang="en-US">The rapid integration of artificial intelligence (AI) in higher education has increased interest in AI-based scaffolding (AIS) to support conceptual learning, particularly in teacher education. However, empirical evidence explaining how learners’ cognitive, self-regulatory, and technological characteristics jointly shape perceptions of AIS remains limited, especially in developing country contexts. This study examines the predictive relationships among conceptual understanding (CU), cognitive engagement (CE), self-regulated learning (SRL), perceived ease of use (PEOU), AI self-efficacy (AISE), and perceived scaffolding quality in explaining Indonesian undergraduate teacher education students’ perceptions of AIS. Using a quantitative explanatory–predictive design, data were collected from 157 students and analyzed using partial least squares structural equation modeling (PLS-SEM). The results indicate that SRL, PEOU, and AISE are the strongest predictors of perceived AIS, while CU, CE, and scaffolding quality also show significant positive associations. These findings highlight the importance of learner readiness and instructional design in AI-enhanced learning environments. Practically, teacher education programs should integrate AI scaffolding that explicitly supports self-regulation, builds students’ confidence in using AI tools, and promotes sustained CE in complex learning tasks.</dc:description>
	<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2026-04-01</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-US"></dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ijere.iaescore.com/index.php/IJERE/article/view/38450</dc:identifier>
	<dc:identifier>10.11591/ijere.v15i2.38450</dc:identifier>
	<dc:source xml:lang="en-US">International Journal of Evaluation and Research in Education (IJERE); Vol 15, No 2: April 2026; 1060-1078</dc:source>
	<dc:source>2620-5440</dc:source>
	<dc:source>2252-8822</dc:source>
	<dc:source>10.11591/ijere.v15i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijere.iaescore.com/index.php/IJERE/article/view/38450/14944</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2026 Nuryanis, Toto Nusantara, Nurul Murtadho, Siti Faizah</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-nc/4.0</dc:rights>
</oai_dc:dc>