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Procrastination trap: how personality traits fuel generative artificial intelligence over-reliance and erode academic performance

International Journal of Evaluation and Research in Education (IJERE) · Vol. 15 No. 4 (2026) · hlm. 3362–3374

DOI
10.11591/ijere.v15i4.39382
ISSN
2620-5440, 2252-8822
Terbit
2026-08-01
Penerbit
Institute of Advanced Engineering and Science
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-nc/4.0

Abstrak

This study investigates how long-term personality traits contribute to generative artificial intelligence (GenAI) use and whether these traits have an impact on academic procrastination and performance. The Big five personality model was used for this investigation, and a quantitative methodology was employed to analyze data from 200 undergraduate students in East Malaysia via partial least squares structural equation modeling (PLS-SEM). Findings indicated that while neuroticism and openness were associated with increased levels of GenAI use, conscientiousness was found to be a protective factor against GenAI dependency. In addition, results showed that when students excessively utilize GenAI, they experience increased levels of procrastination which leads to longer procrastination periods and decreased levels of deep learning engagement. Finally, procrastination was identified as a partial mediator between GenAI use and poor academic performance. Thus, GenAI dependency produces a ‘competence illusion’, causing a decline in students’ academic abilities over time. Ultimately, this study supports the need for interventions designed to help students learn self-regulation and develop critical AI literacy skills to enable technology to serve as a cognitive scaffold as opposed to a replacement for students’ own cognitive efforts.

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  • Universiti of Malaysia Sabah
  • Universiti Malaysia Kelantan
  • Universitas Slamet Riyadi
  • University of Malaya
  • Southern University College
  • University of South Australia
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Rekan penulisOrganisasiArtikel bersama
Kamaruzaman NoordinUniversity of Malaya2
Swee Mee TanSouthern University College2
Anna Lynn Abu BakarUniversiti of Malaysia Sabah2
Zi Xian YongUniversiti of Malaysia Sabah2
Zi Hong YongUniversiti of Malaysia Sabah2
Ernahwatikah NasirUniversiti of Malaysia Sabah2
Azwan AbdullahUniversiti Malaysia Kelantan1
Mohammad IsmailUniversiti Malaysia Kelantan1
Mohd Rafi YaacobUniversiti Malaysia Kelantan1
Mohd Khairy KamarudinUniversiti Malaysia Kelantan1
Mohd Afifie Mohd AlwiUniversiti Malaysia Kelantan1
Wan Nadiah Wan Mohd NasirUniversiti Malaysia Kelantan1
Nusaibah HilaluddinUniversiti Malaysia Kelantan1
Hanudin AminUniversiti of Malaysia Sabah1
Junaid Mehboob ShaikhUniversity of South Australia1

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">Procrastination trap: how personality traits fuel generative artificial intelligence over-reliance and erode academic performance</dc:title>
	<dc:creator>Hamid, Mohamad Rizal Abdul</dc:creator>
	<dc:creator>Ku, Chen Jung</dc:creator>
	<dc:creator>Krishnan, Anath Rau</dc:creator>
	<dc:creator>Shaikh, Imran Mehboob</dc:creator>
	<dc:creator>Lau, Yoke Lian</dc:creator>
	<dc:creator>Muhammad, Mohd Zulkifli</dc:creator>
	<dc:creator>Bahri, Saiful</dc:creator>
	<dc:subject xml:lang="en-US">AI over-reliance; Conscientiousness; Generative AI; Neuroticism; Procrastination</dc:subject>
	<dc:description xml:lang="en-US">This study investigates how long-term personality traits contribute to generative artificial intelligence (GenAI) use and whether these traits have an impact on academic procrastination and performance. The Big five personality model was used for this investigation, and a quantitative methodology was employed to analyze data from 200 undergraduate students in East Malaysia via partial least squares structural equation modeling (PLS-SEM). Findings indicated that while neuroticism and openness were associated with increased levels of GenAI use, conscientiousness was found to be a protective factor against GenAI dependency. In addition, results showed that when students excessively utilize GenAI, they experience increased levels of procrastination which leads to longer procrastination periods and decreased levels of deep learning engagement. Finally, procrastination was identified as a partial mediator between GenAI use and poor academic performance. Thus, GenAI dependency produces a ‘competence illusion’, causing a decline in students’ academic abilities over time. Ultimately, this study supports the need for interventions designed to help students learn self-regulation and develop critical AI literacy skills to enable technology to serve as a cognitive scaffold as opposed to a replacement for students’ own cognitive efforts.</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>2026-08-01</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/39382</dc:identifier>
	<dc:identifier>10.11591/ijere.v15i4.39382</dc:identifier>
	<dc:source xml:lang="en-US">International Journal of Evaluation and Research in Education (IJERE); Vol 15, No 4: August 2026; 3362-3374</dc:source>
	<dc:source>2620-5440</dc:source>
	<dc:source>2252-8822</dc:source>
	<dc:source>10.11591/ijere.v15i4</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijere.iaescore.com/index.php/IJERE/article/view/39382/15162</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2026 Mohamad Rizal Abdul Hamid, Chen Jung Ku, Anath Rau Krishnan, Imran Mehboob Shaikh, Yoke Lian Lau, Mohd Zulkifli Muhammad, Saiful Bahri</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-nc/4.0</dc:rights>
</oai_dc:dc>