Rasch-Based Assessment of Collaborative Problem-Solving Skills in Sound Waves among Senior High School Students
DOI:
https://doi.org/10.21009/1.12102Keywords:
collaborative problem-solving, Rasch model, sound waves, physics education, OECD/PISA 2015, educational assessment, senior high school studentsAbstract
Collaborative Problem-Solving (CPS) is acknowledged as an essential twenty-first-century ability, as underlined by the Programme for International Student Assessment framework. However, physics examinations in schools continue to emphasize on individual cognitive accomplishment, while valid and reliable instruments for testing students' CPS skills are rare, notably in sound wave learning. As a result, the purpose of this study was to create and test a Rasch-based assessment tool for testing senior high school students' collaborative problem-solving abilities in sound wave material. This study employed a quantitative descriptive design using the Rasch measurement model. The study included 185 eleventh-grade students participating in physics lessons. The CPS instrument was created using the OECD/PISA 2015 framework and consists of three collaborative competencies: developing and sustaining common knowledge, taking appropriate action, and establishing and maintaining team organization. Data were analyzed using Winsteps software through reliability, separation, item fit, person fit, Wright map, item difficulty, and person ability analyses.The results showed that the instrument had proper measurement quality, with a Cronbach's Alpha of 0.72 and person reliability of 0.68. The majority of students' answers were in line with the Rasch model. Students performed better when it came to taking appropriate action during experimental activities, but there were problems in teamwork and collaborative reflection. Overall, the Rasch-based CPS instrument was proven to be valid and reliable in assessing students' collaborative problem-solving abilities in sound wave learning contexts.
References
Alanazi, A A, Osman, K & Halim, L 2024, ‘Integrating digital assessment in physics education: enhancing higher-order thinking and problem-solving skills of students in technical colleges in the Kingdom of Saudi Arabia’, in Digital assessment in higher education: navigating and researching challenges and opportunities, Springer Nature Singapore, Singapore, pp. 327–347, https://doi.org/10.1007/978-981-97-6136-4_15
Badmus, O T & Jita, L C 2025, ‘Nature of science representations in South African Grade 10 physical sciences textbook on waves, sound and light’, Social Sciences & Humanities Open, vol. 12, 101848, https://doi.org/10.1016/j.ssaho.2025.101848
Barker Scott, B A & Manning, M R 2024, ‘Designing the collaborative organization: a framework for how collaborative work, relationships, and behaviors generate collaborative capacity’, The Journal of Applied Behavioral Science, vol. 60, no. 1, pp. 149–193, https://doi.org/10.1177/00218863221106245
Caronni, A, Picardi, M, Scarano, S, Rota, V & Amadei, M 2026, ‘Improving single-subject change assessment: deriving the minimal detectable change of questionnaires’ ordinal scores from Rasch analysis measures’, Disability and Rehabilitation, vol. 48, no. 7, pp. 2169–2186, https://doi.org/10.1080/09638288.2025.2547398
Farida, F, Aspat Alamsyah, Y, Anggoro, B S, Andari, T & Lusiana, R 2024, ‘Rasch measurement validation of an assessment tool for measuring students’ creative problem-solving through the use of ICT’, Pixel-Bit. Revista de Medios y Educación, no. 71, pp. 83–106, https://doi.org/10.12795/pixelbit.107973
Fisher, WP Jr 1992, ‘Reliability, separation, strata statistics’, Rasch Measurement Transactions, vol. 6, no. 3, p. 238.
He, J, Ren, S & Zhang, D 2024, ‘The relationship between personal-collaborative motivation profiles and students’ performance in collaborative problem solving’, Large-Scale Assessments in Education, vol. 12, no. 1, 34, https://doi.org/10.1186/s40536-024-00219-6
Kalyani, L K 2024, ‘The role of technology in education: enhancing learning outcomes and 21st century skills’, International Journal of Scientific Research in Modern Science and Technology, vol. 3, no. 4, pp. 5–10, https://doi.org/10.59828/ijsrmst.v3i4.199
Kim, H J, Lee, S J & Kam, K Y 2023, ‘Reliability and validity of the School Function Assessment for children with disabilities in Korea: applying Rasch analysis’, International Journal of Disability, Development and Education, vol. 70, no. 1, pp. 32–44, https://doi.org/10.1080/1034912X.2020.1870665
Mahtari, S, Syihabuddin, S, Setiawan, A & Wati, M 2024, ‘Effectiveness of collaboration skills assessment instrument in physics practicum: a case study with the Rasch model’, Dinasti International Journal of Education Management and Social Science, vol. 6, no. 2, pp. 1270–1278, https://doi.org/10.38035/dijemss.v6i2.3661
OECD 2017, PISA 2015 results (volume V): collaborative problem solving, OECD Publishing, Paris, https://doi.org/10.1787/9789264285521-en
Oktaviana, S & Putranta, H 2024, ‘Identification of students’ conceptual understanding of sound wave materials through the contextual teaching and learning (CTL) model’, Research and Education, no. 10, pp. 124–145, https://doi.org/10.56177/red.10.2024.art.7
Rojas, M, Nussbaum, M & Moreno, C 2025, ‘Validating a collaborative problem-solving assessment tool across educational stages’, Computers & Education, vol. 227, 105228, https://doi.org/10.1016/j.compedu.2024.105228
Setyawarno, D, Maryati & Natadiwijaya, I F 2025, ‘Promoting a valid question model for measuring computational thinking skills based on confirmatory factor analysis and Rasch model’, Cogent Education, vol. 12, no. 1, 2505339, https://doi.org/10.1080/2331186X.2025.2505339
Suryadi, B, Hayat, B & Putra, M D K 2020, ‘Evaluating psychometric properties of the Muslim daily religiosity assessment scale (MUDRAS) in Indonesian samples using the Rasch model’, Mental Health, Religion & Culture, pp. 1–16, https://doi.org/10.1080/13674676.2020.1795822
Wallace, G H 2020, ‘Improving Spanish classroom assessment via logistic regression: lessons from the Rasch model’, Journal of Spanish Language Teaching, vol. 7, no. 1, pp. 51–63, https://doi.org/10.1080/23247797.2020.1771009
Wei, X, Wang, L, Lee, L K & Liu, R 2025, ‘The effects of generative AI on collaborative problem-solving and team creativity performance in digital story creation: an experimental study’, International Journal of Educational Technology in Higher Education, vol. 22, no. 1, 23, https://doi.org/10.1186/s41239-025-00526-0
Wright, BD 1996, ‘Reliability and separation’, Rasch Measurement Transactions, vol. 9, no. 4, p. 472.
Ying, Y & Tiemann, R 2024, ‘Development of an assessment tool for collaborative problem-solving skills in chemistry’, Disciplinary and Interdisciplinary Science Education Research, vol. 6, no. 1, 25, https://doi.org/10.1186/s43031-024-00116-6
Ying, Y & Tiemann, R 2026, ‘Investigating the factors influencing collaborative problem-solving in chemistry education: a cross-national study of German and Chinese students’, International Journal of Science and Mathematics Education, vol. 24, no. 2, 11, https://doi.org/10.1007/s10763-025-10629-9
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