Digital Achievement Motivation Scale for Mathematics Learning: Validity, Reliability, and Micro Testing Evidence
DOI:
https://doi.org/10.58524/oler.v5i2.835Keywords:
Achievement_Motivation, Mathematics_Learning, Scale_Instruments, Digital_QuestionnaireAbstract
Achievement motivation plays a crucial role in students' success in mathematics learning, yet valid and practical measurement instruments are still limited, especially those that utilize digital questionnaire platforms. This study aims to develop an Achievement Motivation Scale for High School Students in Mathematics Learning using a digital questionnaire platform. The research method used is the ADDIE development model, which includes the stages of analysis, design, development, implementation, and evaluation. A total of 30 items were constructed from five motivational dimensions and validated by 3 experts, resulting in 24 valid items (86.7%) and six revised items. Usability testing involving three Information Technology experts, three teachers, and three students yielded average scores of 73%, 93.3%, and 86.7%, respectively, indicating the instrument is user-friendly and well-received. Field testing with 57 students revealed 14 items met the discrimination index (r ≥ 0.30). Exploratory factor analysis showed factor loadings between 0.40–0.85, supporting construct validity. Reliability testing using Cronbach's Alpha yielded 0.89, indicating high internal consistency. Thus, 14 items were declared valid, reliable, and practical for measuring achievement motivation in mathematics learning using a digital platform
References
Açıksöz, A., Dökme, İ., & Önen, E. (2024). Development and validation of STEM motivation scale for middle school students. International Journal of Assessment Tools in Education, 11(4), 699–720. https://doi.org/10.21449/ijate.1401339
Azwar, S. (2004). Reliabilitas dan validitas. Pustaka Pelajar.
Badanbekkyzy, Z., Kalybekova, Z., Sholakhova, A., Saktaganov, B., & Akimbayev, Y. (2025). Online educational platforms as a tool for increasing the accessibility of higher education. Periodicals of Engineering and Natural Sciences, 13(4), 925–948. https://doi.org/10.21533/pen.v13.i4.923
Bichi, A. A., Ibrahim, R. H., & Ibrahim, F. B. (2018). Assessing students’ perception of difficult topics in mathematics at senior secondary schools in Kano, Nigeria. European Journal of Psychology and Educational Research, 1(2), 53–59. https://doi.org/10.12973/ejper.1.2.53
Branch, R. M. (2009). Instructional design: The ADDIE approach. Springer. https://doi.org/10.1007/978-0-387-09506-6
Buntins, K., Kerres, M., & Heinemann, A. (2021). A scoping review of research instruments for measuring student engagement: In need of convergence. International Journal of Educational Research Open, 2, Article 100099. https://doi.org/10.1016/j.ijedro.2021.100099
Chavez-Yacolca, D. R., Castro-Champión, R. B., Cisneros-Gonzales, N. M., Cunza-Aranzábal, D. F., Morales-García, M., & Abanto-Ramírez, C. D. (2025). Relationship between academic procrastination and internet addiction in Peruvian university students: The mediating role of academic self-efficacy. Frontiers in Psychology, 15, 1454234. https://doi.org/10.3389/fpsyg.2024.1454234
Deogratias, E., & Iddi, A. (2025). Investigation on the factors leading to negative attitudes towards mathematics among secondary school students in Tanzania. Union: Jurnal Ilmiah Pendidikan Matematika, 13(3), 761–788. https://doi.org/10.30738/union.v13i3.19952
DeVellis, R. F., & Thorpe, C. T. (2021). Scale development: Theory and applications (5th ed.). Sage.
Esteban, R. F. C., Mamani-Benito, O., Huancahuire-Vega, S., Casildo-Bedón, N., Cabrera-Orosco, I., & Turpo-Chaparro, J. E. (2024). Design and validation of a scale of motivation for scientific publication in university professors (MoSCPU-UP). Frontiers in Education, 9, 1378626. https://doi.org/10.3389/feduc.2024.1378626
Evans, J. R., & Mathur, A. (2018). The value of online surveys: A look back and a look ahead. Internet Research, 28(4), 854–887. https://doi.org/10.1108/IntR-03-2018-0089
Fernanda, F., & Lidiawati, K. R. (2025). The impact of anxiety on academic procrastination among university students in Indonesia. Jurnal Paedagogy, 12(2), 230–240. https://doi.org/10.33394/jp.v12i2.14841
Firman, M., Berliana, B., Sauri, R. S., & Wasliman, I. (2024). Manajemen pembelajaran terintegrasi dalam model pembelajaran blended learning, learning management system. Munaddhomah: Jurnal Manajemen Pendidikan Islam, 4(4), 1038–1046. https://doi.org/10.31538/munaddhomah.v4i4.869
Guilford, J. P. (1950). Fundamental statistics in psychology and education. McGraw-Hill.
Hocaoglu, N., & Ocak, G. (2024). Development and validation of a motivation scale for English listening. International Journal of Contemporary Educational Research, 11(4), 440–456.
Hossein-Mohand, H., & Hossein-Mohand, H. (2023). Influence of motivation on the perception of mathematics by secondary school students. Frontiers in Psychology, 13, 1111600. https://doi.org/10.3389/fpsyg.2022.1111600
Julianto, V., Sumintono, B., Almakhi, N. P. Z., Avetazain, H., Wilhelmina, T. M., & Wati, D. A. (2025). Academic Motivation Scale’s psychometric attribute: Analysis using Rasch measurement model. Current Psychology, 44(1), 114–124. https://doi.org/10.1007/s12144-024-07142-7
Kerlinger, F. N. (1966). Foundations of behavioral research. Holt, Rinehart and Winston.
Liou, P.-Y., Jang, J., & Myoung, E. (2024). Synergistic effects of students’ mathematics and science motivational beliefs on achievement, and their determinants. International Journal of STEM Education, 11(1), Article 50. https://doi.org/10.1186/s40594-024-00509-z
Mahmud, S., Akmal, S., & Arias, A. (2023). Is it more intrinsic or extrinsic? The motivation of Gayonese EFL students to learn English. Jurnal Ilmiah Peuradeun, 11(1), 253–278. https://doi.org/10.26811/peuradeun.v11i1.816
Maymone, M. B. C., Venkatesh, S., Secemsky, E., Reddy, K., & Vashi, N. A. (2018). Research techniques made simple: Web-based survey research in dermatology: Conduct and applications. Journal of Investigative Dermatology, 138(7), 1456–1462. https://doi.org/10.1016/j.jid.2018.02.032
McClelland, D. C. (1961). The achieving society. D. Van Nostrand. https://doi.org/10.1037/14359-000
Mohorko, A., & Hlebec, V. (2016). Degree of cognitive interviewer involvement in questionnaire pretesting on trending survey modes. Computers in Human Behavior, 62, 79–89. https://doi.org/10.1016/j.chb.2016.03.021
Murray, H. A., & McAdams, D. P. (2007). Explorations in personality. Oxford University Press.
Patrick, D. L., Burke, L. B., Gwaltney, C. J., Leidy, N. K., Martin, M. L., Molsen, E., & Ring, L. (2011). Content validity—Establishing and reporting evidence in newly developed patient-reported outcomes instruments. Value in Health, 14(8), 978–988. https://doi.org/10.1016/j.jval.2011.06.013
Prast, E. J., Van de Weijer-Bergsma, E., Miočević, M., Kroesbergen, E. H., & Van Luit, J. E. H. (2018). Relations between mathematics achievement and motivation in students of diverse achievement levels. Contemporary Educational Psychology, 55, 84–96. https://doi.org/10.1016/j.cedpsych.2018.08.002
Revilla, M., & Ochoa, C. (2017). Ideal and maximum length for a web survey. International Journal of Market Research, 59(5), 557–565. https://doi.org/10.2501/IJMR-2017-039
Rizal, S., Nahar, S., & Al Farabi, M. (2023). Islamic values: Integration in learning mathematics and science. Munaddhomah: Jurnal Manajemen Pendidikan Islam, 4(3), 732–745. https://doi.org/10.31538/munaddhomah.v4i3.653
Rosário, A. T., & Dias, J. C. (2022). Learning management systems in education: Research and challenges. In N. Geada & G. L. Jamil (Eds.), Advances in educational technologies and instructional design (pp. 47–77). IGI Global. https://doi.org/10.4018/978-1-6684-4706-2.ch003
Saadati, F., & Celis, S. (2022). Student motivation in learning mathematics in technical and vocational higher education: Development of an instrument. International Journal of Education in Mathematics, Science and Technology, 11(1), 156–178. https://doi.org/10.46328/ijemst.2194
Schuler, H., & Thorn, G. (2002). Achievement motivation inventory. Schuhfried.
Tawfik, A., Schmidt, M., Payne, L., & Huang, R. (2024). Advancing understanding of learning experience design: Refining and clarifying definitions using an eDelphi study approach. Educational Technology Research and Development, 72(3), 1539–1561. https://doi.org/10.1007/s11423-024-10355-z
Toohey, J., Carey, M. D., & Grainger, P. R. (2025). Development and validation of a scale to measure L2 motivation in Australian secondary students. Social Sciences & Humanities Open, 12, 101753. https://doi.org/10.1016/j.ssaho.2025.101753
Ulum, Ö. G. (2025). Cultural influences on learning motivation: A comparative study. Children and Youth Services Review, 173, 108316. https://doi.org/10.1016/j.childyouth.2025.108316
Vallerand, R. J., Pelletier, L. G., Blais, M. R., Briere, N. M., Senecal, C., & Vallieres, E. F. (1992). The Academic Motivation Scale: A measure of intrinsic, extrinsic, and amotivation in education. Educational and Psychological Measurement, 52(4), 1003–1017. https://doi.org/10.1177/0013164492052004025
Wang, C., Cho, H. J., Wiles, B., Moss, J. D., Bonem, E. M., Li, Q., Lu, Y., & Levesque-Bristol, C. (2022). Competence and autonomous motivation as motivational predictors of college students’ mathematics achievement. International Journal of STEM Education, 9(1), Article 41. https://doi.org/10.1186/s40594-022-00359-7
Widarti, H. R., Rokhim, D. A., Yamtinah, S., Shidiq, A. S., & Baharsyah, A. (2024). Instagram-based learning media: Improving student motivation. Jurnal Ilmiah Peuradeun, 12(1), 165–182. https://doi.org/10.26811/peuradeun.v12i1.957
Wisudawati, W. N., & Kirana, A. (2022). The relationship of achievement motivation and academic procrastination of high school students. Biopsikososial: Jurnal Ilmiah Psikologi Fakultas Psikologi Universitas Mercubuana Jakarta, 6(1), 602–614. https://doi.org/10.22441/biopsikososial.v6i1.15893
Wu, J., Qi, S., & Zhong, Y. (2022). Intrinsic motivation, need for cognition, grit, growth mindset and academic achievement in high school students: latent profiles and its predictive effects. arXiv. https://doi.org/10.48550/arXiv.2210.04552
Zanabazar, A., Deleg, A., Ravdan, M., & Tsogt-erdene, E. (2023). The relationship between mathematics anxiety and mathematical performance among undergraduate students. Jurnal Ilmiah Peuradeun, 11(1), 309–322. https://doi.org/10.26811/peuradeun.v11i1.780
Zhang, Z., Van Lieshout, L. L. F., Colizoli, O., Li, H., Yang, T., Liu, C., Qin, S., & Bekkering, H. (2025). A cross-cultural comparison of intrinsic and extrinsic motivational drives for learning. Cognitive, Affective, & Behavioral Neuroscience, 25(1), 25–44. https://doi.org/10.3758/s13415-024-01228-2
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Suciati Rahayu Widyastuti
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Online Learning in Educational Research is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with Online Learning in Educational Research agree to the following terms:
Copyright Retention: Authors retain the copyright of their work without any restrictions.
Publishing Rights: Authors retain the right to publish and distribute their work without any restrictions.
License Agreement: By publishing with Online Learning in Educational Research, authors agree that their work will be licensed under the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA). This license allows others to share and adapt the work, provided that appropriate credit is given, any changes are indicated, and the new creations are licensed under the same terms.
