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Volume 13, Issue 8 (August 2026), Pages: 226-233
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Original Research Paper
Academic procrastination profiles among university students: A multivariate cluster-based analysis
Author(s):
Katty Maribel Calderon-Quino 1, Yolanda Lujano-Ortega 2, Sonia Agley Bustinza-Choquehuanca 2, Vidnay Noel Valero-Ancco 1, *
Affiliation(s):
1Grupo de Investigación Educativa Rikch’ariy, Universidad Nacional del Altiplano, Puno, Peru 2Facultad de Ciencias de la Educación, Universidad Nacional del Altiplano, Puno, Peru
Full text
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* Corresponding Author.
Corresponding author's ORCID profile: https://orcid.org/0000-0002-7980-0339
Digital Object Identifier (DOI)
https://doi.org/10.21833/ijaas.2026.08.022
Abstract
The objectives of this study were to identify and characterize profiles of academic procrastination among university students using cluster analysis and to examine differences between these profiles based on various sociodemographic and academic variables. A quantitative approach was adopted, using a nonexperimental, cross-sectional design with a descriptive-comparative scope. The sample comprised 906 university students from different study programs. Data were collected using the Multidimensional Procrastination Scale (MPS), which consists of 20 items distributed across four dimensions: planning, responsibility, negative beliefs, and determination. The data were presented using descriptive statistics and analyzed through hierarchical cluster analysis using Ward's method, factor analysis to represent the profiles, and analyses of variance (ANOVAs) to compare the groups. The results revealed three clearly differentiated profiles: low, moderate, and high procrastination. Significant differences in procrastination levels were also observed according to sex, age, study program, and academic semester, whereas employment status had no significant effect on procrastination levels. In conclusion, academic procrastination has a heterogeneous and multidimensional structure, which can inform the design of educational interventions tailored to different academic procrastination profiles.
© 2026 The Authors. Published by IASE.
This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords
Academic procrastination, University students, Cluster analysis, Sociodemographic variables, Higher education
Article history
Received 22 April 2026, Received in revised form 27 July 2026, Accepted 26 August 2026
Acknowledgment
We would like to thank the Research Institute of the National University of the Altiplano of Puno for the funding that they provided for the execution of this research (Universidad Nacional del Altiplano R.R. N° 1951-2025-R-UNA).
Compliance with ethical standards
Ethical considerations
This study was conducted in accordance with the ethical principles applicable to research involving human participants. The research project was selected and approved through a competitive process administered by the FEDU 2025 Research Project Evaluation Committee of the Research Institute of the National University of the Altiplano. This approval corresponded to the scientific and institutional evaluation of the project and did not constitute approval by an institutional ethics committee. The participants were university students who met the established eligibility criteria, including enrollment in the first or second academic semester. Consequently, the sample included students aged 17 years and older. All participants received information about the purpose and procedures of the study and voluntarily agreed to participate. Confidentiality and anonymity were ensured throughout the research process, and the collected data were used exclusively for research purposes.
Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Citation:
Calderon-Quino KM, Lujano-Ortega Y, Bustinza-Choquehuanca SA, and Valero-Ancco VN (2026). Academic procrastination profiles among university students: A multivariate cluster-based analysis. International Journal of Advanced and Applied Sciences, 13(8): 226-233
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