Developing of Computerized Adaptive Testing to Measure Physics Higher Order Thinking Skills of Senior High School Students and its Feasibility of Use
Edi Istiyono
,
Wipsar Sunu Brams Dwandaru
,
Risky Setiawan
,
Intan Megawati
The Computer has occupied a comprehensive coverage, especially in education scopes, including in learning-teaching processes, testing, and evaluating..
- Pub. date: January 15, 2020
- Pages: 91-101
- 1148 Downloads
- 970 Views
- 24 Citations
The Computer has occupied a comprehensive coverage, especially in education scopes, including in learning-teaching processes, testing, and evaluating. This research aimed to develop computerized adaptive testing (CAT) to measure physics higher-order thinking skills (HOTS), namely PhysTHOTS-CAT. The Research Development used the 4-D developmental model carrying the four phases of define, design, development, and dissemination (4D) developed by Thiagarajan. This testing instrument can give the item test based on the student’s abilities. The research phases include (1) needs analysis and definition, (2) development design (3) development of CAT and assemble the test items into CAT, (4) validation by experts, and (5) feasibility try-out. The findings show that PhysTHOTS-CAT is valid to measure physics HOTS of the 10th-grade students of Senior High School according to 82.28% of teachers and students assessment on PhysTHOTS-CAT content and media. Therefore, it can conclude that PhysTHOTS-CAT can be used and feasible to measure physics HOTS of the 10th-grade students of the Senior High School.
Keywords: Computerized adaptive testing, HOTS, partial credit model, item response theory.
References
Ahmad, N. B., Ishak, M. K., Alias, U. F., & Mohamad, N. (2015). An approach for e-learning data analytics using SOM clustering. International. Journal of Advances Soft Computing and its Application, 7(3), 94-112.
Angell, C., Guttersrud, O., Henriksen, E. K. & Isnes, A. (2004). Physics: Frightful, but fun, pupils’ and teachers’ views of physics and physics teaching (Electronic version). Science Education, 88, 683-706.
Alwi, A., Mehat, M., & Arshad, N. I. (2016). E-semai teaching portal (ESTP): A preliminary study in assisting the teaching of Bahasa Semai. International. Journal of Advances Soft Computing and its Application, 8(1), 57-69.
Anderson, L. W. & Krathwohl, D.R (Eds). (2010). Kerangka landasan untuk pembelajaran, pengajaran, dan asesmen: revisi taksonomi pendidikan Bloomian [A framework for learning, teaching and assessment: a revision of the Bloomian educational taxonomy]. Yogyakarta, Indonesia: Pustaka Pelajar.
Andrian, D., Kartowagiran, B., & Hadi, S. (2018). The instrument development to evaluate local curriculum in indonesia. International Journal of Instruction, 11(4), 922–934. https://doi.org/10.12973/iji.2016.9115a
Azwar, S. (2015). Reliabilitas dan validitas [Reliability and validity]. Yogyakarta, Indonesia: Pustaka Pelajar.
Baker, F. B. (1983). The basic of Item response theory. Portmouth, NH: Heinemann.
Bennett, R. E. (2012). Inexorable and inevitable: The continuing story of technology and assessment. The Journal of Technology, Learning and Assessment, 1(1), 1-23.
Boo, J. & Vispoel, W. (2012). Computer versus Paper-and-Pencil assessment of educational development: A comparison of psychometric features and examinee preferences. Psychological Reports 111, 443-460.
Cisar, S.M., Radosav, D., Markoski, B., Pinter, R., & Cisar, P. (2010). Computerized adaptive testing of student knowledge. Acta Polytecnical Hungaria ,7(4), 139-152.
Cella, D., Gershon, R., Lai, J. S., & Choi, S. (2007). The future of outcomes measurement: Item banking, tailored short-forms, and computerized adaptive assessment. Quality of Life Research, 16(SUPPL. 1), 133–141. https://doi.org/10.1007/s11136-007-9204-6
Cavallo, A. M. L., Potter, W. H., & Rozman, M. (2004). Gender differences in learning constructs, shifts in learning constructs, and their relationship to course achievement in a structured inquiry, yearlong college physics course for life science majors. School Science and Mathematics, 104(6), 288–300. https://doi.org/10.1111/j.1949-8594.2004.tb18000.x
Depdikbud. (2003). Republic of Indonesia Law Number 20, 2003, about the National Education System. Jakarta, Indonesia: Ministry of Education and Culture.
Demkanin, P. (2018). Concept formation : Physics teacher and his know-how and know-why. Journal of Baltic Science Education, 17(1), 4–7.
Dunkel, P. (1999). Considerations in developing or using second/foreign language proficiency computer-adaptive tests. Language Learning & Technology, 2(2), 77–93.
Ekici, E. (2016). “Why do i slog through the physics?” understanding high school students’ difficulties in learning Physics. Journal of Education and Practice , 7(7), 95–107. https://doi.org/10.1016/j.pec.2014.12.003
Fadzil, H. M. (2018). Designing infographics for the educational technology course: Perspectives of pre-service science teacher. Journal of Baltic Science Education, 7(1), 8-18.
Feyzioglu, E. Y., Akpinar, E., & Tatar, N. (2018). Effect of technology-enchanged metacognitive learning platform on accuracy and understanding of electricity. Journal of Baltic Science Education, 7(1), 43-64.
Folashade, A., & Akinbobola, A. O. (2009). Constructivist problem based learning technique and the academic achievement of physics students with low ability level in nigerian secondary schools. Eurasian Journal of Physics and Chemistry Education, 1(1), 45–51.https://doi.org/10.1111/j.1469-8749.2011.04107.x
Haley, S. M., Coster, W. J., Dumas, H. M., Fragala-Pinkham, M. A., Kramer, J., Ni, P., … Ludlow, L. H. (2011). Accuracy and precision of the Pediatric Evaluation of Disability Inventory computer-adaptive tests (PEDI-CAT). Developmental Medicine and Child Neurology, 53(12), 1100–1106. https://doi.org/10.1111/j.1469-8749.2011.04107.x
Istiyono, E., Dwandaru, W. S. B., Megawati, I., & Ermansah. (2017). Application of Bloomian and Marzanoian higher order thinking skills in the physics learning assessment: An Inevitability. In Proceedings of the International Conference on Learning Innovation (ICLI 2017) (pp. 136-142). Paris, France: Atlantis Press. https://doi.org/10.2991/icli-17.2018.26
Jamieson, J.M. (2009). Trends in computer-based second language assessment. Journal of Applied Linguistics, 25, 228-242.
Johnson, D., & May, I. M. (2008). The teaching of structural analysis: A report to the Ove Arup Foundation. London: UK: The Ove Arup Foundation
Koponen, I. T., Mantyla, T., & Lavonen, J. (2002). Challenges of web-based education in physics teachers’ training. In Proceedings of ICTE - 2002 (International Conference on Information Communication Technology in Education) (pp.291-295).
Lord, F.M. (1980). Applications of item response theory to practical testing problems. Hillsdale, NJ: Lawrence Erlbaum.
OECD (2018). PISA 2015: PISA Results in focus. Retrieved from https://www.oecd.org/pisa/pisa-2015-results-in-focus.pdf
Pommerich, M. (2004). Developing computerized versions of paper-and pencil tests: Mode effects for passage-based tests. The Journal of Technology, Learning and Assessment, 2(6), 3-44.
Ramadhan, S., Mardapi, D., Prasetyo, Z.K., & Utomo, H.B. (2019). The development of an instrument to measure the higher order thinking skill in physics. European Journal of Educational Research, 8(3), 743-751. doi:10.12973/eu-jer.8.3.743
Reckase, M.D. (2009). Multidimensional item response theory (statistic for social and behavioral sciences). London, UK: Springer Science and Bussines Media.
Setiawan, R. (2019). A comparison of score equating conducted using haebara and stocking lord method for polytomous. European Journal of Educational Research, 8(4), 1071-1079. doi:10.12973/eu-jer.8.4.1071
Thiagarajan, S., Semmel, D. D., & Semmel, M. I. (1974). Instructional development for training teacher of expectional children. Minneapolis, MN: University of Minnesota.
Weiss, D. J. (2011). Better data from better measurements using computerized adaptive testing. Journal of Methods and Measurement in the Social Sciences, 2(1), 1-27.
Winarno. (2012). Pengembangan computerized adaptive testing menggunakan metode pohon segitiga keputusan [Development of computerized adaptive test using the decision triangle tree method]. Journal of Education and Educational Evaluation/Jurnal Pendidikan dan Evaluasi Pendidikan, 16(2), 574-592.
Wynd, C. A., Schmidt, B., & Schaefer, M. A. (2003). Two quantitative approaches for estimating content validity. Western Journal of Nursing Research, 25(5), 508–518. https://doi.org/10.1177/0193945903252998