Realistic Mathematics Education Based Mobile Learning Media: Validity, Practicality, and Effectiveness in Teaching Compound Probability at Vocational High Schools

Tomi  Listiawan; Nanda  Oktavia; Djatmiko Djatmiko

doi:10.58524/jasme.v6i1.1019

Authors

Tomi Listiawan Universitas Negeri Malang, Indonesia
Nanda Oktavia Universitas Negeri Malang, Indonesia
Djatmiko Djatmiko Southwest University, China

DOI:

https://doi.org/10.58524/jasme.v6i1.1019

Keywords:

Compound Probability, Mobile Learning, Realistic Mathematics Education, Vocational High School

Abstract

Background: The teaching of compound probability in vocational high schools continues to face challenges due to the abstract nature of the concepts and the limited integration of mathematical content with students’ real-life experiences. These conditions often hinder students’ conceptual understanding and learning engagement. Therefore, innovative instructional media that combine technological advancement with contextual learning approaches are needed.

Aims: This study aimed to develop a mobile learning application based on the Realistic Mathematics Education (RME) approach for teaching compound probability and to evaluate its validity, practicality, and effectiveness.

Methods: This research employed a research and development (R&D) design using the ADDIE model, which consists of analysis, design, development, implementation, and evaluation stages. The participants included 35 eleventh-grade students from a vocational high school in Malang, Indonesia. Data were collected through validation sheets, student and teacher response questionnaires, and learning achievement tests. The developed application was validated by a mathematics education lecturer and a mathematics teacher.

Results: The findings indicated that the developed mobile learning application achieved a high level of validity, with an average score of 86.37%. The practicality assessment showed positive responses from both students (84.09%) and the teacher (85.71%). Furthermore, the effectiveness test revealed that 85.71% of students achieved the minimum learning mastery criterion, with an average achievement score of 86.49.

Conclusion: The RME-based mobile learning application was found to be valid, practical, and effective for teaching compound probability in vocational high schools. By integrating contextual problems, interactive multimedia, and flexible learning opportunities, the application has the potential to enhance students’ mathematical understanding and support innovative mathematics instruction in the digital era.

References

Abdulrahaman, M. D., Faruk, N., Oloyede, A. A., Surajudeen-Bakinde, N. T., Olawoyin, L. A., Mejabi, O. V., Imam-Fulani, Y. O., Fahm, A. O., & Azeez, A. L. (2020). Multimedia tools in the teaching and learning processes: A systematic review. Heliyon, 6(11). https://doi.org/10.1016/j.heliyon.2020.e05312

Abrahamson, D., Nathan, M. J., Williams-Pierce, C., Walkington, C., Ottmar, E. R., Soto, H., & Alibali, M. W. (2020). The future of embodied design for mathematics teaching and learning. Frontiers in Education, 5. https://doi.org/10.3389/feduc.2020.00147

Ahmed, V., & Opoku, A. (2022). Technology supported learning and pedagogy in times of crisis: The case of COVID-19 pandemic. Education and Information Technologies, 27(1), 365–405. https://doi.org/10.1007/s10639-021-10706-w

A’la, N., Morina, Z. C., & Elizar, E. (2025). The relationship between mathematical literacy and the realistic mathematic education approach: A systematic literature review. Beta: Jurnal Tadris Matematika, 18(1), 49–66. https://doi.org/10.20414/betajtm.v18i1.696

Anugraheni, I., Gufron, A., & Purnomo, Y. W. (2025). The impact of realistic problem-based learning on mathematical connection abilities: Evidence from elementary schools in Indonesia. Cogent Education, 12(1), 2523078. https://doi.org/10.1080/2331186X.2025.2523078

Arifin, S., & Efriani, A. (2025). Integrating augmented reality in RME-based digital learning: Impact on students’ problem-solving ability. Hipotenusa: Journal of Mathematical Society, 7(1), 32–53. https://doi.org/10.18326/hipotenusa.v7i1.3768

Ariza, J. Á. (2023). Bringing active learning, experimentation, and student-created videos in engineering: A study about teaching electronics and physical computing integrating online and mobile learning. Computer Applications in Engineering Education, 31(6), 1723–1749. https://doi.org/10.1002/cae.22673

Bopardikar, A., Bernstein, D., Drayton, B., & McKenney, S. (2021). Designing educative curriculum materials in interdisciplinary teams: Designer processes and contributions. Instructional Science, 49(2), 249–286. https://doi.org/10.1007/s11251-021-09538-5

Carpenter, S. K., Endres, T., & Hui, L. (2020). Students’ use of retrieval in self-regulated learning: Implications for monitoring and regulating effortful learning experiences. Educational Psychology Review, 32(4), 1029–1054. https://doi.org/10.1007/s10648-020-09562-w

Carroll, M., Lindsey, S., Chaparro, M., & Winslow, B. (2021). An applied model of learner engagement and strategies for increasing learner engagement in the modern educational environment. Interactive Learning Environments, 29(5), 757–771. https://doi.org/10.1080/10494820.2019.1636083

Clarke, D., & Roche, A. (2018). Using contextualized tasks to engage students in meaningful and worthwhile mathematics learning. The Journal of Mathematical Behavior, 51, 95–108. https://doi.org/10.1016/j.jmathb.2017.11.006

Engelbrecht, J., & Borba, M. C. (2024). Recent developments in using digital technology in mathematics education. ZDM – Mathematics Education, 56(2), 281–292. https://doi.org/10.1007/s11858-023-01530-2

Fischer, C., McPartlan, P., Orona, G. A., Yu, R., Xu, D., & Warschauer, M. (2022). Salient syllabi: Examining design characteristics of science online courses in higher education. PLOS ONE, 17(11), e0276839. https://doi.org/10.1371/journal.pone.0276839

Garzón, J., Burgos, D., Kinshuk, & Tlili, A. (2025). Mobile learning significantly enhances student learning gains: A meta-analysis and research synthesis. Computers & Education, 238, 105415. https://doi.org/10.1016/j.compedu.2025.105415

Hidayat-Ur-Rehman, I. (2024). Digital competence and students’ engagement: A comprehensive analysis of smartphone utilization, perceived autonomy and formal digital learning as mediators. Interactive Technology and Smart Education, 21(3), 461–488. https://doi.org/10.1108/ITSE-09-2023-0189

Huang, K., & Chen, C.-H. (2025). Instructional video and GenAI-supported chatbot in digital game-based learning: Influences on science learning, cognitive load and game behaviours. Journal of Computer Assisted Learning, 41(4), e70094. https://doi.org/10.1111/jcal.70094

Jelatu, S., Kurniawan, Y., Kurnila, V. S., Mandur, K., & Jundu, R. (2019). Collaboration TPS learning model and m-learning based on Android for understanding of trigonometry concepts with different cognitive style. International Journal of Instruction, 12(4), 545–560.

Khairunnisa, E., & Suryaningsih, F. (2025). Development and implementation of Android-based interactive e-modules to improve mathematical problem-solving skills at secondary schools Hamid Khan Pulau Pinang Malaysia. Journal of Science and Mathematics Education, 1(3), 61–67. https://doi.org/10.70716/josme.v1i3.238

Koerunnisa, K., Rianto, R., Novita, S. D., Nurasih, Z., Abdullah, A., Aliah, A., Fallo, H., & Rasilah, R. (2025). The influence of a realistic mathematical approach on student learning in elementary schools. Journal of Mathematics Instruction, Social Research and Opinion, 4(1), 105–114. https://doi.org/10.58421/misro.v4i1.282

Koskinen, R., & Pitkäniemi, H. (2022). Meaningful learning in mathematics: A research synthesis of teaching approaches. International Electronic Journal of Mathematics Education, 17(2). https://doi.org/10.29333/iejme/11715

Kumar, B. S., Hemawathi, M. S., Dhanasekaran, P., Kaliappan, V. K., & Sivaganesan, D. (2024). Maximizing learning outcomes while minimizing costs: A cost-effective approach to m-learning. International Journal of Interactive Mobile Technologies, 18(11), 4. https://doi.org/10.3991/ijim.v18i11.49095

Liu, C.-C., Wang, D., Gu, X., Hwang, G.-J., Tu, Y.-F., & Wang, Y. (2026). Facilitating pre-service teachers’ instructional design and higher-order thinking with generative AI: An integrated approach with the peer assessment and concept map. Journal of Research on Technology in Education, 58(4), 880–905. https://doi.org/10.1080/15391523.2025.2474528

Major, L., Francis, G. A., & Tsapali, M. (2021). The effectiveness of technology-supported personalised learning in low- and middle-income countries: A meta-analysis. British Journal of Educational Technology, 52(5), 1935–1964. https://doi.org/10.1111/bjet.13116

Memon, M. Q., Lu, Y., Memon, A. R., Memon, A., Munshi, P., & Shah, S. F. A. (2022). Does the impact of technology sustain students’ satisfaction, academic and functional performance: An analysis via interactive and self-regulated learning? Sustainability, 14(12), 7226. https://doi.org/10.3390/su14127226

Mendoza, W., Ramírez, G. M., González, C., & Moreira, F. (2022). Assessment of curriculum design by learning outcomes (LO). Education Sciences, 12(8), 541. https://doi.org/10.3390/educsci12080541

Mudjisusatyo, Y., Darwin, D., & Kisno, K. (2024). The use ADDIE model to improve the competence of the higher education task force in obtaining competitive funding for the independent campus program. Journal of Applied Research in Higher Education, 17(5), 2109–2138. https://doi.org/10.1108/JARHE-12-2023-0580

Nguyen, N. N., & Chen, H.-L. (2026). Toward deeper learning: A systematic review of cognitive load management in mobile learning. Journal of Educational Computing Research. https://doi.org/10.1177/07356331261445821

Nikolopoulou, K. (2023). Self-regulated and mobile-mediated learning in blended tertiary education environments: Student insights from a pilot study. Sustainability, 15(16), 12284. https://doi.org/10.3390/su151612284

Okai-Ugbaje, S., Ardzejewska, K., & Imran, A. (2022). A mobile learning framework for higher education in resource constrained environments. Education and Information Technologies, 27(8), 11947–11969. https://doi.org/10.1007/s10639-022-11094-5

Palalas, A., & Wark, N. (2020). The relationship between mobile learning and self-regulated learning: A systematic review. Australasian Journal of Educational Technology, 36(4), 151–172. https://doi.org/10.14742/ajet.5650

Rehman, N., Huang, X., Mahmood, A., AlGerafi, M. A. M., & Javed, S. (2024). Project-based learning as a catalyst for 21st-century skills and student engagement in the math classroom. Heliyon, 10(23). https://doi.org/10.1016/j.heliyon.2024.e39988

Reyna, V. F., & Brainerd, C. J. (2023). Numeracy, gist, literal thinking and the value of nothing in decision making. Nature Reviews Psychology, 2(7), 421–439. https://doi.org/10.1038/s44159-023-00188-7

Schorr, I., Plecher, D. A., Eichhorn, C., & Klinker, G. (2024). Foreign language learning using augmented reality environments: A systematic review. Frontiers in Virtual Reality, 5. https://doi.org/10.3389/frvir.2024.1288824

Soboleva, E. V., Chirkina, S. E., Kalugina, O. A., Shvetsov, M. Y., Kazinets, V. A., & Pokaninova, E. B. (2020). Didactic potential of using mobile technologies in the development of mathematical thinking. Eurasia Journal of Mathematics, Science and Technology Education, 16(5), em1842. https://doi.org/10.29333/ejmste/118214

Son, A. L. (2022). The students’ abilities on mathematical connections: A comparative study based on learning models intervention. Mathematics Teaching Research Journal, 14(2), 72–87.

Staneviciene, E., & Žekienė, G. (2025). The use of multimedia in the teaching and learning process of higher education: A systematic review. Sustainability, 17(19), 8859. https://doi.org/10.3390/su17198859

To, J. (2022). Using learner-centred feedback design to promote students’ engagement with feedback. Higher Education Research & Development, 41(4), 1309–1324. https://doi.org/10.1080/07294360.2021.1882403

Wahira, W., Ansar, A., & Tolla, I. (2023). Analysis of the needs for developing the competence of elementary school supervisors through analysis design development implementation evaluation (ADDIE) model. Kasetsart Journal of Social Sciences, 44(4), 1303–1312.

Wang, X., Sun, N., & Wickersham, K. (2017). Turning math remediation into “homeroom”: Contextualization as a motivational environment for community college students in remedial math. The Review of Higher Education, 40(3), 427–464.

Yilmaz, R. (2020). Prospective mathematics teachers’ cognitive competencies on realistic mathematics education. Journal on Mathematics Education, 11(1), 17–44.

Zhang, Z. (Victor), & Hyland, K. (2022). Fostering student engagement with feedback: An integrated approach. Assessing Writing, 51, 100586. https://doi.org/10.1016/j.asw.2021.100586