doi: 10.18178/ijiet.2026.16.6.2631
Brain-Based Deep Learning Model Assisted by GeoGebra to Enhance Mathematical Problem-Solving Skills of Prospective Elementary School Teachers
Adi Apriadi Adiansha1,*
,
Asriyadin2 ,
Azra Fauzi3
- 1Elementary School Teacher Education Program, STKIP Taman Siswa Bima, Bima, Indonesia
- 2Physics Education Study Program, STKIP Taman Siswa Bima, Bima, Indonesia
- 3Elementary School Teacher Education Program, STKIP Harapan Bima, Bima, Indonesia
- Manuscript receivedSeptember 22, 2025
- revisedOctober 13, 2025
- acceptedFebruary 25, 2026
- publishedJune 24, 2026
Abstract
This study aims to (1) develop a valid and practical Brain-Based Deep Learning model supported by GeoGebra for enhancing mathematical problem-solving skills; (2) examine its effectiveness in improving the performance of prospective elementary school teachers; and (3) evaluate its impact on self-efficacy and conceptual understanding. The research employed a Research and Development (R&D) design involving 250 students divided equally into experimental and control groups. Expert validation confirmed the model’s high validity and practicality. The effectiveness test indicated a significant improvement in problem-solving skills for the experimental group compared to the control group. Qualitative analysis using NVivo identified five major themes: enhanced conceptual understanding, visualization experiences through GeoGebra, increased self-confidence, alternative strategy development, and collaborative reflection. These findings demonstrate that the developed model not only strengthens cognitive performance but also fosters affective growth, particularly in self-efficacy, offering a valuable contribution to innovative mathematics education for prospective teachers.
Keywords
- problem solving skills
- brain-based learning
- deep learning
- GeoGebra
- teacher education
How to Cite
Adi Apriadi Adiansha, Asriyadin, and Azra Fauzi, "Brain-Based Deep Learning Model Assisted by GeoGebra to Enhance Mathematical Problem-Solving Skills of Prospective Elementary School Teachers," International Journal of Information and Education Technology, vol. 16, no. 6, pp. 1662-1676, 2026. https://doi.org/10.18178/ijiet.2026.16.6.2631
Copyright & License
Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).