Development of assessment instruments for students’ graphical representation abilities in the topic of dynamic electricity

Authors

DOI:

https://doi.org/10.21067/mpej.v10i1.13759

Keywords:

Assessment, Dynamic electricity, Graphical representation, Instruments, Physics test

Abstract

This study focuses on the development of physics test instruments for high school students on the topic of Dynamic Electricity. This study aims to analyze the content quality of the test instrument context, evaluate the the feasibility of the test instrument, and the student’s graphical representation abilities on the topic of Dynamic Electricity. This research and development studiy implemented the R&D method with the 4D model (Define, Design, Development, and Disseminate). The test instrument was trialed in class XII IPA at Karya Pembangunan 1 Ciparay High School with a total of 50 students as research subjects. Item analysis was conducted using Classical Test Teory (CTT) using SPSS 29.0 and Rasch Modeling using MINISTEP software to evaluate validity, reliability, difficulty level, and anad student response patterns for 12 item (6 items type A and 6 items type B). The results demonstrated that the test instrument possesses good content validity with overall adequate psychometric estimates. Out of 12 items tested, 7 items proved feasible and were retained, while 5 items required revision or elimination due to significant misfit, overfit, and cognitive redundancy. Students' graphical representation ability was predominantly in the fair category (46%), with 72% of students falling into the high-ability category, indicating a ceiling effect. These findings highlight the necessity of refining instrument design by incorporating non-linear graphs and higher difficulty levels to effectively measure higher-order thinking skills and support diagnostic assessment in physics learning.

Downloads

Download data is not yet available.

References

Altindis, N., Bowe, K. A., Bauer, C. F., & Aikens, M. L. (2026). Graphical chunking strategies in students’ interpretation of a logistic function titration graph. The Journal of Mathematical Behavior, 83, 101332.

Aprilia, A., & Dwandaru, W. S. B. (2024). Empirical Analysis of Physics Test Instruments to Measure Graphical Representation Abilities in “Temperature and Heat” Topics. Science Education International, 35(3), 240–249. https://doi.org/10.33828/sei.v35.i3.7

Apriliani, S. S., Saepuzaman, D., & Suwarma, I. R. (2026). Characteristic of critical thinking test instrument and analysis students’ ability using Rasch model Article History. Momentum: Physics Education Journal, 10(1), 121–134. https://doi.org/10.21067/mpej.v10i1.13455

Ayeh, I. G. (2025). Students’ mathematics conceptual challenges: Exploring students’ thinking, understanding, and misconceptions in functions and graphs. European Journal of Science and Mathematics Education, 13(3), 191–206.

Bintang, R. S., & Suprananto. (2024). The Impact of Sample Size, Test Length, and Person-Item Targeting on The Separation Reliability in Rasch Model: A Simulation Study. Jurnal Pengukuran Psikologi Dan Pendidikan Indonesia, 13(1), 1–13. https://doi.org/10.15408/jp3i.v13i1.27975

Boone, W. J., & Staver, J. R. (2020). Advances in Rasch analyses in the human sciences. Springer. https://doi.org/https://doi.org/10.1007/978-3-030-43420-5

Boone, W. J., Staver, J. R., & Yale, M. S. (2014). Rasch analysis in the human sciences (Vol. 10). Springer. https://doi.org/https://doi.org/10.1007/978-3-030-43420-5

Busnawir, B., Kodirun, K., Zamsir, Z., Samparadja, H., & Hasnawati, H. (2023). Trends Stability of Reliability Coefficient Based on Sample Size and Ability of Test-takers. PYTHAGORAS Jurnal Pendidikan Matematika, 18(2), 97–111. https://doi.org/10.21831/pythagoras.v18i2.59392

Choi, S., & Jung, Y. (2025). Knowledge graph construction: Extraction, learning, and evaluation. Applied Sciences, 15(7), 3727.

DeVon, H. A., Block, M. E., Moyle‐Wright, P., Ernst, D. M., Hayden, S. J., Lazzara, D. J., Savoy, S. M., & Kostas‐Polston, E. (2007). A psychometric toolbox for testing validity and reliability. Journal of Nursing Scholarship, 39(2), 155–164. https://doi.org/10.1111/j.1547-5069.2007.00161.x

Ellis, J. L. (2013). A standard for test reliability in group research. Behavior Research Methods, 45(1), 16–24. https://doi.org/10.3758/s13428-012-0223-z

Fisher, M., Volfson, A., Eshach, H., & Ben-Abu, Y. (2026). Visualizing Physics: Boosting Argumentation Skills Through Representation. Journal of Science Education and Technology, 1–20. https://doi.org/10.1007/s10956-025-10291-4

Hambleton, R. K., Swaminathan, H., & Rogers, H. J. (1991). Fundamentals of item response theory (Vol. 2). Sage.

Hermawati, T. (2022). Analysing science teachers’ difficulties in teaching the concept of electricity in junior high school. Research in Physics Education, 1(1), 33–44.

Hrnjicic, A., & Alihodžic, A. (2024). Measuring Students’ Conceptual Understanding of Real Functions: A Rasch Model Analysis. International Electronic Journal of Mathematics Education, 19(1).

Istiyono, E., & Fenditasari, K. (2021). Physics Graphical Representation Test of Straight Motion Kinematics Based on Boti Boat Local Wisdom: Development and Validity. 6th International Seminar on Science Education (ISSE 2020), 350–357. https://doi.org/10.2991/assehr.k.210326.050

JM, L. (2013). A user’s guide to WINSTEPS, MINISTEP Rasch-Model computer programs.

Khotimah, K., & Fariyani, Q. (2025). Development of a Physics Assessment Instrument to Measure High School Students Multirepresentation Skills in Momentum and Impulse. Impulse: Journal of Research and Innovation in Physics Education, 5(1), 49–61. https://doi.org/https://doi.org/10.14421/impulse.2025.51-04

Kim, J.-H., & Nam, J. (2021). Thermodynamic identities with sunray diagrams. European Journal of Physics, 42(3), 035101. https://doi.org/https://doi.org/10.48550/arXiv.1912.11485

Kusumaningtyas, D. A., Manyunu, M., Kurniasari, E., Awalin, A. N., Rahmaniati, R., & Febriyanti, A. (2024). Enhancing Learning Outcomes: A Study on the Development of Higher Order Thinking Skills based Evaluation Instruments for Work and Energy in High School Physics. Indonesian Journal on Learning and Advanced Education (IJOLAE), 14–31. https://doi.org/10.23917/ijolae.v6i1.23125

Lichtenberger, A., Hofer, S. I., Stern, E., & Vaterlaus, A. (2025). Enhanced conceptual understanding through formative assessment: results of a randomized controlled intervention study in physics classes. Educational Assessment, Evaluation and Accountability, 37(1), 5–33. https://doi.org/https://doi.org/10.1007/s11092-024-09445-6

Linacre, J. M. (2002). What do infit and outfit, mean-square and standardized mean. Rasch Measurement Transactions, 16(2), 878.

Munfaridah, N., Avraamidou, L., & Goedhart, M. (2021). The Use of Multiple Representations in Undergraduate Physics Education: What Do we Know and Where Do we Go from Here? Eurasia Journal of Mathematics, Science and Technology Education, 17(1), 1–19. https://doi.org/10.29333/ejmste/9577

Niyomufasha, T., Ntivuguruzwa, C., & Mugabo, L. R. (2024). The engineering students’ use of multiple representations in mechanics problems solving at a selected public university in Rwanda. Cogent Education, 11(1), 2372941. https://doi.org/10.1080/2331186X.2024.2372941

Noperi, H., Diani, R., Irwandani, I., Suryani, Y., Sodikin, S., & Saputro, T. (2025). Psychometric analysis of the critical thinking skills instrument in physics learning using the Rasch model. Indonesian Journal of Science and Mathematics Education, 8(3), 627–641. https://doi.org/https://doi.org/10.24042/ijsme.v8i3.28770

Nurussaniah, N., Setyosari, P., Kuswandi, D., & Ulfa, S. (2025). Psychometric Validation of an Analytical Skills Test in Physics Using the Rasch Model. Journal of Baltic Science Education, 24(3), 522–537. https://doi.org/10.33225/jbse/25.24.522

Pradana, P. W. (2025). Assessment Instrument of Graph Representations on Sound Wave Topic: Development and Measurement Implementation. Knowledge Management & E-Learning, 17(2), 352–371. https://doi.org/https://doi.org/10.34105/j.kmel.2025.17.016

Rangkuti, M. A., & Karam, R. (2022). Conceptual challenges with the graphical representation of the propagation of a pulse in a string. Physical Review Physics Education Research, 18(2), 020119. https://doi.org/https://doi.org/10.1103/PhysRevPhysEducRes.18.020119

Rizbudiani, A. D., Jaedun, A., Rahim, A., & Nurrahman, A. (2021). Rasch model item response theory (IRT) to analyze the quality of mathematics final semester exam test on system of linear equations in two variables (SLETV). Al-Jabar: Jurnal Pendidikan Matematika, 12(2), 399–412.

Royani, S. N. M., Irvaniyah, B. N., & Kusairi, S. (2025). A Revealing Students’ Struggles and Misconceptions in Kinematics through Multi-Representation Assignments. JPI (Jurnal Pendidikan Indonesia), 14(4), 810–821.

Shang, Y., Aryadoust, V., & Hou, Z. (2024). A Meta-Analysis of the Reliability of Second Language Listening Tests (1991–2022). In Brain Sciences (Vol. 14, Number 8). Multidisciplinary Digital Publishing Institute (MDPI). https://doi.org/10.3390/brainsci14080746

Sharma, A. K. (2025). Cognitive and psychological aspects of physics learning. Physics Journal| Farhangian University, 2(1), 28–39. https://doi.org/10.48310/esip.2025.18642.1011

Termini, G., Battaglia, O. R., Grazia, I., & Fazio, C. (2025). Gaining insights through thematic analysis about learning dimensions in teaching learning sequences on surface phenomena in liquids. Physical Review Physics Education Research, 21(2), 020143.

Tesfaye, D. (2025). Enhancing Secondary School Students’ Conceptual Understanding and Problem-Solving Performance in Electricity Using Multiple Representations-Based Instruction Integrated with Formative Assessment Practice.

Tesio, L., Caronni, A., Kumbhare, D., & Scarano, S. (2024). Interpreting results from Rasch analysis 1. The “most likely” measures coming from the model. Disability and Rehabilitation, 46(3), 591–603. https://doi.org/10.1080/09638288.2023.2169771

Thiagarajan, S. (1974). Instructional development for training teachers of exceptional children: A sourcebook.

Vrbanović Lisac, D., Radanović, I., & Šimić Šašić, S. (2025). Enhancing higher order thinking skills to improve understanding of biological content: A quasi‐experimental study. Natural Sciences Education, 54(2), e70023.

Worku, D. T., Ejigu, M. A., Gebremeskal, T. G., & Kassa Gogie, T. (2026). Assessing the impact of multiple representations based instruction integrated with formative assessment practice on secondary school students’ problem-solving performance in Physics. Research in Science & Technological Education, 44(1), 224–249.

Zhao, H., & Aryadoust, V. (2025). A meta-analysis of the reliability of second language reading comprehension assessment tools. Studies in Second Language Acquisition, 47(1), 388–416. https://doi.org/DOI: 10.1017/S0272263124000627

Downloads

Published

2026-07-30

How to Cite

Solehayati, R., Nuryantini, A. Y., & Chaidir, I. F. (2026). Development of assessment instruments for students’ graphical representation abilities in the topic of dynamic electricity. Momentum: Physics Education Journal, 10(1), 214–229. https://doi.org/10.21067/mpej.v10i1.13759

Issue

Section

Articles