Using Rasch Analysis to Develop Multi- representation of Tier Instrument on Newton’s law (MOTION)

Authors

  • Achmad , Samsudin Department of Physics Education, Universitas Pendidikan Indonesia, Bandung, Indonesia. Author

DOI:

https://doi.org/10.61841/gkerga04

Keywords:

Multi-representation,, Newton’s Law, , Rasch Analysis, Tier Instrument, Students’ Conceptions

Abstract

The purpose of this research was to develop Multi-representation of Tier Instrument on Newton’s law (MOTION) using Rasch analysis. This instrument can be used to diagnose students’ conceptions, especially on Newton’s laws. Multi-representation of tier instrument also can be used for three forms of tests (pre-, post- and delayed test), thus students do not realize they have done the same problem. The research method was used ADDIE (Analyse, Design, Develop, Implement and Evaluation) model. The participants were students at one of senior high school at Sukabumi. West Java, as much as 92 students (41 male students and 51 female students, with an average age of 15-17 years) who were in K-11. At evaluating stage, all students’ answers were analysed based on the student’s conception category, scored, then evaluated using Rasch analysis with Winstep 4.4.5 software. The data analysis including validity and reliability of MOTION. Based on the Rasch analysis, it can be concluded that MOTION was valid and reliable to use, although there are a few questions that need to be minor revised. Other researchers can use MOTION to diagnose students’ conceptions of Newton’s law material and can also use Rasch analysis to develop a research instrument.

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References

[1] Adadan, E. (2013). Using multiple representations to promote grade 11 students’ scientific understanding of the particle theory of matter. Research in Science Education, 43(3).

[2] Adadan, E., & Savasci, F. (2012). An analysis of 16-17-year-old students’ understanding of solution chemistry concepts using a two-tier diagnostic instrument. International Journal of Science Education, 34(4), 513–544.

[3] Adams, D., Sumintono, B., Mohamed, A., & Noor, N. S. M. (2018). E-learning readiness among students of diverse backgrounds in a leading Malaysian higher education institution. Malaysian Journal of Learning and Instruction, 15(2), 227–256.

[4] Adimayuda, R., Aminudin, A. H., Kaniawati, I., Suhendi, E., Samsudin, A. (2020). A multitier open-ended momentum and impuls (MOMI) instrument: Developing and assesing quality of conception of 11th grade sundanese students with rasch analysis. International Journal of Scientific & Technology Research, 9(2), 4799- 4804.

[5] Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16, 183–198.

[6] Al-Kalbani, M., Al Barwani, T., & Neisler, O. (2020). Psychometric properties and factor structure of the university readiness survey. International Journal of Psychosocial Rehabilitation, 24(1), 1-8.

[7] Aminudin, A. H., Kaniawati, I., Suhendi, E., Samsudin, A., Coştu, B., & Adimayuda, R. (2019). Rasch Analysis of Multitier Open-ended Light-Wave Instrument (MOLWI): Developing and Assessing Second-Years Sundanese-Scholars Alternative Conceptions. Journal for the Education of Gifted Young Scientists, 7(3), 607– 629.

[8] Arsad, N., Kamal, N., Ayob, A., Sarbani, N., Tsuey, C. S., Misran, N., & Husain, H. (2013). Rasch model analysis on the effectiveness of early evaluation questions as a benchmark for new students ability. International Education Studies, 6(6), 185–190.

[9] Boone, W. J., Abell, S. K., Volkmann, M. J., Arbaugh, F., & Lannin, J. K. (2011). Evaluating Selected Perceptions of Science and Mathematics Teachers in an Alternative Certification Program. International Journal of Science and Mathematics Education, 9, 551–569.

[10] Brass, C., Gunstone, R., & Fensham, P. (2003). Quality learning of physics: Conceptions held by high school and university teachers. Research in Science Education, 33(2), 245–271.

[11] Caleon, I., & Subramaniam, R. (2010). Development and application of a three-tier diagnostic test to assess secondary students’ understanding of waves. International Journal of Science Education, 32(7), 939–961.

[12] Chen, C. H. H. I. H., Lin, H. U. H., & Lin, M. I. N. G. I. (2003). Developing a Two-Tier Diagnostic Instrument to Assess High School Students ’ Understanding − The Formation of Images by a Plane Mirror. Proceedings of the National Science Council, 106–121.

[13] Ding, L., Wei, X., & Mollohan, K. (2016). Does Higher Education Improve Student Scientific Reasoning Skills? International Journal of Science and Mathematics Education, 14(4), 619–634.

[14] Eymur, G., & Geban, Ö. (2017). The Collaboration of Cooperative Learning and Conceptual Change: Enhancing the Students’ Understanding of Chemical Bonding Concepts. International Journal of Science and Mathematics Education, 15(5), 853–871.

[15] Fisher, W. P. (2007). Rating Scale Instrument Quality Criteria. Rasch Measurement Transactions, 21(1), 1095.

[16] Fratiwi, N. J., Kaniawati, I., Suhendi, E., Suyana, I., & Samsudin, A. (2017). The transformation of two-tier test into four-tier test on Newton’s laws concepts. AIP Conference Proceedings, 1848.

[17] Fratiwi, N. J., Utari, S., & Samsudin, A. (2019). Study of concept mastery of binocular K-11 students through the implementation of A multi-representative approach. International Journal of Scientific and Technology Research, 8(8), 1637–1642.

[18] Fratiwi, N. J., Samsudin, A., Ramalis, T. R., Saregar, A., Diani, R., Irwandani, I., Rasmitadila, & Ravanis, K. (2020). Developing MeMoRI on Newton’s laws: for identifying students’ mental models. European Journal of Educational Research, 9(2), 699-708.

[19] Galili, I. (2019). Towards a refined depiction of nature of science. Science & Education, 28(3–5), 503–537.

[20] Gurel, D. K., Eryilmaz, A., & McDermott, L. C. (2015). A review and comparison of diagnostic instruments to identify students’ misconceptions in science. Eurasia Journal of Mathematics, Science and Technology Education, 11(5), 989–1008.

[21] Henke, A., & Höttecke, D. (2015). Physics teachers’ challenges in using history and philosophy of science in teaching. Science and Education, 24, 349–385.

[22] Hermanto, I. M., Muslim, M., Samsudin, A., & Maknun, J. (2019). K-10 students ’ conceptual understanding on Newton ’ s laws : current and future directions. Journal of Physics: Conference Series, 1280, 1–6.

[23] Hermita, N., Suhandi, A., Syaodih, E., Samsudin, A., Mahbubah, K., Noviana, E., & Kurniaman, O. (2018). Constructing VMMSCCText for re-conceptualizing students ’ conception. Journal of Applied Environmental and Biological Sciences, 8(3), 102–110.

[24] Hutajulu, M., Minarti, E. D., & Senjayawati, E. (2019). Improving of mathematical proficiency and disposition using multi representation approach on vocational students. Journal of Physics: Conference Series, 1–6.

[25] Kaltakci-Gurel, D., Eryilmaz, A., & McDermott, L. C. (2017). Development and application of a four-tier test to assess pre-service physics teachers’ misconceptions about geometrical optics. Research in Science and Technological Education, 35(2), 238–260.

[26] Kaniawati, I., Fratiwi, N. J., Danawan, A., Suyana, I., Samsudin, A., & Suhendi, E. (2019). Analyzing students’ misconceptions about Newton’s laws through four-tier Newtonian test ( FTNT ). Journal of Turkish Science Education, 16(1), 110–122.

[27] Kohl, P. B., Rosengrant, D., & Finkelstein, N. D. (2007). Strongly and weakly directed approaches to teaching multiple representation use in physics. Physical Review Special Topics - Physics Education Research, 3(010108).

[28] Krell, M., Redman, C., Mathesius, S., Krüger, D., & van Driel, J. (2018). Assessing Pre-Service Science Teachers’ Scientific Reasoning Competencies. Research in Science Education.

[29] Kurnaz, M. A., & Arslan, A. S. (2014). Effectiveness of Multiple Representations for Learning Energy Concepts: Case of Turkey. Procedia - Social and Behavioral Sciences, 116, 627–632.

[30] Lamb, R. L., Annetta, L., Meldrum, J., & Vallett, D. (2012). Measuring Science Interest: Rasch Validation of The Science Interest Survey. International Journal of Science and Mathematics Education, 10, 643–668.

[31] Laszlo, P. (2013). Towards Teaching Chemistry as a Language. Science and Education, 22(7), 1669–1706.

[32] Lee, H. S., & Park, J. (2013). Deductive Reasoning to Teach Newton’s Law of Motion. International Journal of Science and Mathematics Education, 11, 1391–1414.

[33] Liampa, V., Malandrakis, G. N., Papadopoulou, P., & Pnevmatikos, D. (2019). Development and Evaluation of a Three-Tier Diagnostic Test to Assess Undergraduate Primary Teachers’ Understanding of Ecological Footprint. Research in Science Education, 49(3), 711–736.

[34] Liou, P. Y., & Hung, Y. C. (2015). Statistical Techniques Utilized in Aanalyzing PISA and TIMSS Data in Science Education from1996 to 2013: A Methodological Review. International Journal of Science and Mathematics Education, 13(6), 1449–1468.

[35] Liu, G., & Fang, N. (2016). Student misconceptions about force and acceleration in physics and engineering mechanics education. International Journal of Engineering Education, 32(1), 19–29.

[36] López-Lozano, L., Solís, E., & Azcárate, P. (2018). Evolution of Ideas About Assessment in Science: Incidence of a Formative Process. Research in Science Education, 48(5), 915–937.

[37] Ludwig, T., Priemer, B., & Lewalter, D. (2019). Assessing Secondary School Students’ Justifications for Supporting or Rejecting a Scientific Hypothesis in the Physics Lab. Research in Science Education, 1–26.

[38] Malone, K. L. (2008). Correlations among knowledge structures, force concept inventory, and problem-solving behaviors. Physical Review Special Topics - Physics Education Research, 4(020107).

[39] Murshed, M. B., Phang, F. A., Bunyamin, M. A. H. B., & Binti, I. J. (2020). The reliability analysis for force concept inventory. International Journal of Psychosocial Rehabilitation, 24(5), 143-151.

[40] Özcan, Ö., & Bezen, S. (2016). Students’ mental models about the relationship between force and velo city concepts. Journal of Baltic Science Education, 15(5), 630–641.

[41] Panaoura, A., Michael-Chrysanthou, P., Gagatsis, A., Elia, I., & Philippou, A. (2017). A Structural Model Related to the Understanding of the Concept of Function: Definition and Problem Solving. International Journal of Science and Mathematics Education, 15, 723–740.

[42] Park, M., & Liu, X. (2019). An Investigation of Item Difficulties in Energy Aspects Across Biology, Chemistry, Environmental Science, and Physics. Research in Science Education.

[43] Perry, L. (2019). Development of an early grade relational reasoning subtask: collecting validity evidence on technical adequacy and reliability. International Journal of Science and Mathematics Education.

[44] Peşman, H., & Eryilmaz, A. (2010). Development of a three-tier test to assess misconceptions about simple electric circuits. Journal of Educational Research, 103(3), 208–222.

[45] Peter, J. P. (1981). Construct validity: A review of basic issues and marketing practices. Journal of Marketing Research, 18(2), 133–145.

[46] Rasch, G. (1960). Studies in mathematical psychology: I. Probabilistic models for some intelligence and attainment tests.

[47] Romine, W. L., & Sadler, T. D. (2016). Measuring changes in interest in science and technology at the college level in response to two instructional interventions. Research in Science Education, 46, 309–327.

[48] Saglam-Arslan, A., & Devecioglu, Y. (2010). Student teachers’ levels of understanding and model of understanding about Newton’s laws of motion. Asia-Pacific Forum on Science Learning and Teaching, 11(1), 1– 20.

[49] Samsudin, A., Azura, Kaniawati, I., Suhandi, A., Fratiwi, N. J., Supriyatman, Wibowo, F. C., Malik, A., & Costu,

B. (2019). Unveiling students’ misconceptions through computer simulation-based PDEODE learning strategy on dynamic electricity. Journal of Physics: Conference Series, 1280, 1-8.

[50] Samsudin, A., Azizah, N., Sasmita, D., Rasmitadila, Fatkhurrohman, M. A., Supriyatman, Wibowo, F. C. (2020). Analyzing the students’ conceptual change on kinetic theory of gases as a learning effect through computer simulations-assisted conceptual change model. Universal Journal of Educational Research, 8(2), 425-437.

[51] Saputra, O., Setiawan, A., Rusdiana, D., & Muslim. (2020). Analysis of students’ misconception using four tier diagnostic test on fluid topics. International Journal of Advanced Science and Technology, 29(1), 1256-1266.

[52] Setiawan, B., Panduwangi, M., & Sumintono, B. (2018). A Rasch analysis of the community’s preference for different attributes of Islamic banks in Indonesia. International Journal of Social Economics, 45(12), 1647–1662.

[53] Sia, D. T., Treagust, D. F., & Chandrasegaran, A. L. (2012). High school students’ proficiency and confidence levels in displaying their understanding of basic electrolysis concepts. International Journal of Science and Mathematics Education, 10, 1325–1345.

[54] Stein, H., & Galili, I. (2015). the Impact of an Operational Definition of the Weight Concept on Students’ Understanding. International Journal of Science and Mathematics Education, 13(6), 1487–1515.

[55] Summers, R., Wang, S., Abd-El-Khalick, F., & Said, Z. (2019). Comparing Likert Scale Functionality Across Culturally and Linguistically Diverse Groups in Science Education Research: an Illustration Using Qatari Students’ Responses to an Attitude Toward Science Survey. International Journal of Science and Mathematics Education, 17, 885–903.

[56] Sutopo, & Waldrip, B. (2014). Impact of a Representational Approach on Students’ Reasoning and Conceptual Understanding in Learning Mechanics. International Journal of Science and Mathematics Education, 12, 741– 766.

[57] Taber, K. S. (2013). Upper Secondary Students’ Understanding of the Basic Physical Interactions in Analogous Atomic and Solar Systems. Research in Science Education, 43(4), 1377–1406.

[58] Tesio, L. (2003). Measuring behaviours and perceptions: Rasch analysis as a tool for rehabilitation research. Journal of Rehabilitation Medicine, 35(3), 105–115.

[59] Theasy, Y., Wiyanto, & Sujarwata. (2018). Multi-representation ability of students on the problem solving physics. Journal of Physics: Conference Series, 1–4.

[60] Tiruneh, D. T., De Cock, M., Weldeslassie, A. G., Elen, J., & Janssen, R. (2017). Measuring critical thinking in physics: Development and validation of a critical thinking test in electricity and magnetism. International Journal of Science and Mathematics Education, 15(4), 663–682.

[61] Treagust, D. (1986). Evaluating Students’ Misconceptions by Means of Diagnostic Multiple Choice Items. Research in Science Education, 16, 199–207.

[62] Treagust, D. (1988). Development and use of diagnostic tests to evaluate students’ misconceptions in science. International Journal of Science Education, 10(2), 159–169.

[63] Ursachi, G., Horodnic, I. A., & Zait, A. (2015). How Reliable are Measurement Scales? External Factors with Indirect Influence on Reliability Estimators. Procedia Economics and Finance, 20(15), 679–686.

[64] Van Zile-Tamsen, C. (2017). Using rasch analysis to inform rating scale development. Research in Higher Education, 58(8), 922–933.

[65] Velentzas, A., & Halkia, K. (2013). From earth to heaven: Using “Newton’s Cannon” thought experiment for teaching satellite physics. Science and Education, 22(10), 2621–2640.

[66] Yang, D. C., & Sianturi, I. A. J. (2019). Sixth grade students’ performance, misconceptions, and confidence when judging the reasonableness of computational results. International Journal of Science and Mathematics Education, 17(8), 1519–1540.

[67] You, H. S., Marshall, J. A., & Delgado, C. (2018). Assessing students’ disciplinary and interdisciplinary understanding of global carbon cycling. Journal of Research in Science Teaching, 1–25.

[68] Yuruk, N., Beeth, M. E., & Andersen, C. (2009). Analyzing the effect of metaconceptual teaching practices on students’ understanding of force and motion concepts. Research in Science Education, 39, 449–475.

[69] Zhu, J., & Han, L. (2011). Analysis on the main factors affecting the reliability of test papers. Journal of Language Teaching and Research, 2(1), 236–238.

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Published

30.06.2020

How to Cite

Samsudin, A. ,. (2020). Using Rasch Analysis to Develop Multi- representation of Tier Instrument on Newton’s law (MOTION). International Journal of Psychosocial Rehabilitation, 24(6), 8542-8556. https://doi.org/10.61841/gkerga04