The problem and the aim of the study. The development of digital technology demands innovation in mathematics learning that focuses not only on cognitive abilities but also on students’ computational thinking skills. however, the reality on the ground shows that mathematics learning in schools remains conventional, lacks contextualization, and fails to leverage the potential of local culture and technology fully. The study aims to describe the effectiveness of developing a realistic mathematics learning model based on Mandailing culture assisted by the Internet of Things (IoT) in improving students’ mathematical computational thinking skills.
Research methods. The research was carried out using the Plomp model, which put an emphasis on the Assessment Stage. The data collection approach involved a quasi-experimental design with a pretest-posttest control group design. The study population comprised all seventh-grade students at SMP Negeri 3 Padangsidimpuan, divided into five study groups. The sample was then selected using a purposive sampling technique, with class VII-3 as the experimental class and class VII-4 as the control class, with 31 students in each class. The research instruments included observation sheets for learning management and tests for students’ mathematical computational thinking skills. As for analyzing the data, it used descriptive analysis of the achievement of learning management and students’ mathematical computational thinking skills. Furthermore, in gauging students’ computational thinking skills, the study also conducted an inferential statistical analysis.
Results. The results showed that learning management obtained a score of 4.52, indicating a very effective criterion. The increase in computational thinking skills from pretest to posttest in the experimental class (24.79%) was higher than in the control class (17.94%). Furthermore, the significance value of the computational thinking skills of the experimental class with the control class was 0.00 <0.05 (alpha level) with a t-count of 3.407>2.000 (t-table). It was then concluded that there was a significant difference in the computational thinking achievements of the experimental class and the control class, while the n-gain value of the experimental class was 0.49 (moderate), which was better than the control class of 0.38 (moderate).
Conclusion. Thus, the IoT-assisted mathematical learning Based on Mandailing Culture is effective in improving mathematical computational thinking skills. Therefore, implementing the Mandailing Culture-Based Realistic Mathematics Learning Model, supported by IoT, can be an innovative strategy for integrating local culture and digital technology into mathematics learning to foster students’ computational thinking skills effectively.
Keywords: realistic mathematics, mandailing culture, internet of things; computational thinking; learning models
For Citation: Ahmad, M., Ermawita, Lubis, M. S., & Rohani. (2026). IoT-Assisted Realistic Mathematics Learning Based on Mandailing Culture: A Study of the Effectiveness of Learning Model Development in Improving Mathematical Computational Thinking Skills. Perspektivy nauki i obrazovania = Perspectives of Science and Education, (3), 649–664. https://doi.org/10.32744/pse.2026.3.41
Authors:
Marzuki Ahmad [Corresponding author] (Padangsidimpuan, Indonesia) — Lecturer in Mathematics Education Study Program. Institut Pendidikan Tapanuli Selatan. Email: marzukia686@gmail.com
Ermawita (Padangsidimpuan, Indonesia) — Lecturer in Vocational Informatics Education Study Program. Institut Pendidikan Tapanuli Selatan. Email: ermajuwita91@gmail.com
Mina Syanti Lubis (Padangsidimpuan, Indonesia) — Lecturer in Indonesian Language and Literature Education Study Program. Institut Pendidikan Tapanuli Selatan. Email: minasyanti.lubis@gmail.com
Rohani (Labuhanbatu, Indonesia) — Lecturer in Information Technology Study Program. Universitas Labuhanbatu. E-mail: pasariburohani@gmail.com
© Marzuki Ahmad, Ermawita, Mina Syanti Lubis, Rohani, 2026
The author’s declared no conflicts of interest
Received: 25 December 2025 | Approved: 14 March 2026 | Published: 30 June 2026
This is an open access article distributed under a Creative Commons Attribution-ShareAlike International License (CC-BY-SA 4.0)
that allows others to share the work with an acknowledgement of the work’s authorship and initial publication in this journal
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