International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12

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 Volume 13, Issue 1 (January 2026), Pages: 144-153

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 Original Research Paper

Utilizing machine learning to align exam questions with program learning outcomes

 Author(s): 

 Haifa Alharthi 1, *, Ashwaq Alhargan 1, Mohamed Habib 1, 2

 Affiliation(s):

  1College of Computing and Informatics, Saudi Electronic University, Riyadh, Saudi Arabia
  2Faculty of Engineering, Portsaid University, Port Said, Egypt

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 * Corresponding Author. 

   Corresponding author's ORCID profile:  https://orcid.org/0000-0002-9267-8497

 Digital Object Identifier (DOI)

  https://doi.org/10.21833/ijaas.2026.01.015

 Abstract

Aligning exam questions with course learning outcomes and linking them to program learning outcomes is often a time-consuming process that is prone to human error. This study examines the effectiveness of machine learning techniques for automatically mapping exam questions to Program Learning Outcomes (PLOs) and performance levels. A dataset of 414 multiple-choice questions was used to develop prediction models based on both joint and single-model architectures. The results show that the automated models achieved higher accuracy than human evaluations, indicating strong potential for the use of AI-based tools in educational quality assurance. The proposed approach can support academic institutions by automating assessment-related tasks, reducing faculty workload, and improving curriculum alignment. To the best of our knowledge, this study is the first to address the automated mapping of exam questions to program learning outcomes using machine learning methods.

 © 2026 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

 Machine learning, Program learning outcomes, Exam question mapping, Educational assessment, Quality assurance

 Article history

 Received 3 August 2025, Received in revised form 20 December 2025, Accepted 3 January 2026

 Acknowledgment

No Acknowledgment. 

 Compliance with ethical standards

 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:

 Alharthi H, Alhargan A, and Habib M (2026). Utilizing machine learning to align exam questions with program learning outcomes. International Journal of Advanced and Applied Sciences, 13(1): 144-153

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 Figures

  Fig. 1  Fig. 2  Fig. 3  Fig. 4  Fig. 5 

 Tables

  Table 1   Table 2   Table 3  Table 4 Table 5  Table 6  Table 7  Table 8 

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