Analisis Miskonsepsi Ungkapan Algebra melalui Ujian Diagnostik Kognitif Dua-Peringkat berasaskan Model Rasch (Analysis of Misconceptions in Algebraic Expressions through a Two-Tier Cognitive Diagnostic Test using the Rasch Model)

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Wei Seng Khong
Hooi Lian Lim
Xiao Xue Liu

Abstract

The Distractor Analysis based on Option Probability Curves (OPC) represents a systematic approach to identify students' misconceptions in basic operations of algebraic expressions. The cognitive diagnostic test was used in this study as an instrument to collect research data. The research instrument consists of 24 multiple-choice items in two-tier format. This study employed a survey method involving 1,029 Form One students from 10 secondary schools in Penang state. The content validity and construct validity of the research instrument recorded the lowest Item Content Validity Index (I-CVI) value of .83, Scale Content Validity Index/Average (S-CVI/Ave) value of .99, Scale Content Validity Index/Universal Agreement (S-CVI/UA) value of .96, with all 24 items (100%) and 18 items (75%) meeting the MNSQ infit and outfit requirements, standardised residual variance (PCA) recording 59.0%, PTMEA CORR values between .49 to .78, DIF contrast (Differential Item Functioning) values within the range of –.25 to +.26 logits, scale validity with the lowest observed count of 24 observations, instrument respondent distribution between –2.5 to +5.0 logits, and item difficulty distribution between –1.0 to +1.0 logits. The results of Rasch OPC misconception analysis revealed that among students demonstrating misconceptions in the basic operations of algebraic expressions, the majority experienced misconceptions in using algebra, and low-ability students did not understand concepts. This proves that most students faced assimilation pseudo-conceptions involving students' failures in basic operations between algebraic terms. The reliability indices of respondents (.92), items (.99) and Cronbach Alpha (KR-20) (.96) in this study demonstrate a very high level of instrument reliability and validity. Nevertheless, the findings of this study have limitations in terms of scope, time, and the topographical context of its implementation. In addition, the use of objective-type instruments may also restrict the types of student misconceptions identified in algebraic expressions.

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References

Adeniji, K. A. (2015). Analysis of misconceptions in algebraic expression among senior secondary school students of different ability levels in Katsina State. Journal of Science, Technology, Mathematics and Education, 11(2), 1–15.

Alattin, U. (2016). An examination of 7th grade students’ mistakes in algebraic expressions. In M. Shelley, S. Alan, & I. Celik (Ed.), Internatioal Conference on Education in Mathematics, Science & Technology Proceding Book (pp. 186–189). Bodrum, Turkey: International Society for Research in Education and Science (ISRES) Publishing.

Asdar, Badrullah, B. B., & Husnul, K. R. (2022). Misconception analysis of algebraic forms using three tier tests for class VII students. International Journal of Development Research, 12(3), 54563–54566. https://doi.org/10.37118/ijdr.24084.03.2022

Bahagian Pembangunan Kurikulum [BPK]. (2015). Kurikulum standard sekolah menengah: Matematik dokumen standard kurikulum dan pentaksiran tingkatan 1. Kementerian Pendidikan Malaysia.

Bush, S. (2011). Analying common algebra-related misconcptions and errors of middle school students [Doctoral dissertation, Department of Teaching and Learning, University of Louisville]. https://doi.org/10.18297/etd/187

Chandra, T., & Roohi, F. (2019). Secondary school students’ misconceptions in algebra cancepts. Mahatma Gandhi Central University Journal of Social Sciences, 1(1), 22–33.

Chang, L., & Lo, S. J. (2015). A Rasch model distractor analysis on ordered multiple-choice items of a fractional test. Journal of Education & Psychology, 38(2), 87–119.

Cheah, C. T., & John, A. M. (1996). Diagnosing misconceptions in elementary algebra. Journal of Science and Mathematics Education in Southeast ASIA, 19(1), 61–68.

Chin, S. F. (2017). Effects of computer-based testing feedback on students’ achievement and errors in algebraic expressions. [Doctoral dissertation, School of Educational Studies, Universiti Sains Malaysia].

Cristo, M. A., & Engr, G. S. (2020). Error analysis of engineering students’ misconceptions in algebra. International Journal of Engineering Trends and Technology, 68(12), 66–71. https://doi.org/10.14445/22315381/IJETT-V68I12P212

Daud, M. Y., & Ayub, A. S. (2019). Students error analysis in learning algebraic expression: A study in secondary school Putrajaya. Creative Education, 10, 2615–2630. https://doi.org/10.4236/ce.2019.1012189

Davis, L. L. (1992). Instrument review: Getting the most from your panel of experts. Applied Nursing Research, 5, 194–197. https://doi.org/10.1016/S0897-1897(05)80008-4

Dodzo, W. (2016). Secondary school students errors and misconceptions in algebra with specific reference to a school in Mashonaland East, Zimbabwe [Master thesis, Faculty of Science Education, Bindura University of Science Education].

Egodawatte, G. (2011). Secondary school students’ misconceptions in algebra [Doctoral dissertation, University of Toronto]. https://hdl.handle.net/1807/29712

Elango, P. (2014). Meramal proses kesilapan pemikiran untuk operasi penolakan nombor negatif melibatkan integer positif dengan negatif. Jurnal Personalia Pelajar, 17, 41–48.

Essuman, I. B., Kwakye, D. O., & Avorkpo, E. K. (2024). An analysis of pre-service mathematics teachers’ performance in algebraic expressions. Sociology International Journal, 8(2), 87–92. https://doi.org/10.15406/sij.2024.08.00379

Ferrer, G. (2020). Error analysis in the operations of algebraic expressions of grade 8 students at Kalinga state university laboratory high school. International Journal of English Literature and Social Sciences, 5(6), 2456–7620. https://doi.org/10.22161/ijels.56.89

Fleiss, J. (1981). Statistical methods for rates and proportions (2nd ed.). Hohn Wiley.

Fulmer, G. W., Chu, H. E., Treagust, D. F., & Neumann, K. (2015). Is it harder to know or to reason? Analyzing two-tier science assessment items using the Rasch measurement model. Asia-Pacific Science Education, 1(1), 1–16. https://doi.org/10.1186/s41029-015-0005-x

Gay, L. R., Mills, G. E., & Airasian, P. (2011). Educational research: Competencies for analysis and applications (10th ed.). Pearson.

Herrmann, C. F., & DeBoer, G. E. (2011). Using distractor-driven standards-based multiple-choice assessments and Rasch modeling to investigate hierarchies of chemistry misconceptions and detect structural problems with individual items. Chemistry Education Research and Practice, 12, 184–192. https://doi.org/10.1039/C1RP90023D

Herrmann, C. F., & DeBoer, G. E. (2016). Using Rasch Modeling and option probability curves to diagnose students’ misconceptions. AAAS Project 2061, Proceedings of 2016 AERA Annual Meeting, Washington, DC, 8–12 April, pp. 1–12.

Irawati, W., Zubainur, C. M., & Ali, R. M. (2018). Cognitive conflict strategy to minimize students’ misconception on the topic of addition of algebraic expression. Journal of Physics: Conference Series, 1088, 012084. https://doi.org/10.1088/1742-6596/1088/1/012084

Khiyarunnisa, A., & Retnawati, H. (2018). A two-tier diagnostic test instrument on calculus material: What, why, and how? [Paper presentation]. Proceedings of 5th International Conference on Research, Implementation and Education of Mathematics and Science (ICRIEMS), Yogyakarta State University, 7–8 May, pp. 479–485

Khong, W. S., & Lim, H. L. (2019). Penggunaan model Rasch untuk menganalisis miskonsepsi bagi topik nombor integer. Asia Pacific Journal of Educators and Education, 34, 105–128. https://doi.org/10.21315/apjee2019.34.6

Lai, S. C. (2018). Pembinaan dan pengesahan ujian diagnostik untuk mengenal pasti miskonsepsi bagi topik penambahan pecahan dalam kalangan murid tahun empat [Masters’ thesis, Universiti Sains Malaysia].

Lembaga Peperiksaan Malaysia. (1994). Laporan prestasi PMR 1993. Kementerian Pendidikan Malaysia.

Lembaga Peperiksaan Malaysia. (1996). Laporan prestasi PMR 1995. Kementerian Pendidikan Malaysia.

Lembaga Peperiksaan Malaysia. (1997). Laporan prestasi PMR 1996. Kementerian Pendidikan Malaysia.

Lembaga Peperiksaan Malaysia. (2014). Kupasan mutu jawapan SPM 2013. Kementerian Pendidikan Malaysia.

Lembaga Peperiksaan Malaysia. (2015). Kupasan mutu jawapan SPM 2014. Kementerian Pendidikan Malaysia.

Lembaga Peperiksaan Malaysia. (2017a). Kupasan mutu jawapan SPM 2016. Kementerian Pendidikan Malaysia.

Lembaga Peperiksaan Malaysia. (2017b). Laporan analisis keputusan Sijil Pelajaran Malaysia (SPM) tahun 2016. Kementerian Pendidikan Malaysia.

Lembaga Peperiksaan Malaysia. (2018). Kupasan mutu jawapan SPM 2017. Kementerian Pendidikan Malaysia.

Lembaga Peperiksaan Malaysia. (2019). Kupasan mutu jawapan SPM 2018. Kementerian Pendidikan Malaysia.

Lembaga Peperiksaan Malaysia. (2020). Laporan analisis keputusan Sijil Pelajaran Malaysia (SPM) tahun 2019. Kementerian Pendidikan Malaysia.

Lily, H. A., Maimun, A. L., Ashinida, A., & Mus’ab, S. (2018). Kesahan dan kebolehpercayaan instrumen strategi pembelajaran kolokasi bahasa arab: Analisis menggunakan model Rasch. Jurnal Pendidikan Malaysia, 43(3), 131–140. https://doi.org/10.17576/JPEN-2018-43.03

Lim, K. S. (2010). An error analysis of form 2 (grade 7) students in simplifying algebraic expressions: A descriptive study. Electronic Journal of Research in Educational Psychology, 8(1), 139–162. https://doi.org/10.25115/ejrep.v8i20.1398

Lin, S. (2004). Development and application of a two-tier diagnostic test for high school students’ understanding of flowering plant growth and development. International Journal of Science and Mathematics Education, 2, 175–199. https://doi.org/10.1007/s10763-004-6484-y

Linacre, J. M. (2020). A user’s guide to Winsteps ministep Rasch-model computer programs: Program manual 4.5.3. Retrieved 1 June 2020, from Winsteps and Facets User Manuals: https://www.winsteps.com/a/Winsteps-Manual.pdf

Lynn, M. R. (1986). Determination and quantification of content validity. Nursing Research, 35, 382–385. https://doi.org/10.1097/00006199-198611000-00017

Mary, M. M. (2016). Sources of students’ errors and misconceptions in algebra and influence of classroom practice remediation in secondary schools Machakos Sub-County, Kenya [Master's thesis, School of Education, Kenyatta University]. http://ir-library.ku.ac.ke/handle/123456789/15353

Mary, M. M., Miheso, O. C., & Ndethiu, S. (2016). Sources of students errors and misconceptions in algebra and effectiveness of classroom ptactice remediatin in Machakos County-Kenya. Journal of Education and Practice, 7(10), 31–33.

Mazlini, A., Zulhilmi, Z. A., Afian, A. M., Siti Mistima, M., Sutama, S., Martyana, P., & Hutkemri, Z. (2021). The ability and analysis of students’ errors in the topic of algebraic. Journal of Physics: Conference Series, 1988, 012049 https://doi.org/10.1088/1742-6596/1988/1/012049

Naseer, M. S. (2015). Analysis of students’ errors and misconceptions in pre-university mathematics courses. In M. N. Salleh, & N. Z. Abedin (Eds.), Proceedings: First International Conference on Teaching & Learning 2015 (pp. 34–39). Langkawi: Malaysia MNNF Publisher.

Nichols, P. (1994). A framework for developing cognitively diagnostic assessment. Review of Educational Research, 64(4), 575–603. https://doi.org/10.3102/00346543064004575

Nurzayani , Y., & Effandi, Z. (2016). Miskonsepsi dalam algebra – Sorotan analisis kajian lepas. Retrieved 2 May 2020, from https://icge.unespadang.ac.id/asset/file/files/icge%20IV/II/Untitled_43.pdf

Piaget, J. (1970). Handbook of child psychology (P. Musse, Ed.) New York: Wiley.

Poo, Y. P. (2018). Development and validation of a two-tier multiple choice diagnostic test to diagnose form four students’ misconceptions of photosynthesis and plant respiration [Master’s thesis, School of Educational Studies, Universiti Sains Malaysia].

Rabiu, A. U., & Zamri, A. K. (2024). Assessing item reliability, differential item functioning, and wright map analysis of the GSP122 test at a public university in Nigeria. Journal of Education for Sustainable Innovation, 2(2), 107–120. https://doi.org/10.56916/jesi.v2i2.934

Sarah, B. B. (2011). Analying common algebra-related misconceptions and errors of middle school students [Doctoral dissertation, Department of Teaching and Learning, University of Louisville].

Subanji, S., & Nusantara, T. (2016). Thinking process of Pseudo construction in mathematics concepts. International Education Studies, 9(2), 17–31. https://doi.org/10.5539/ies.v9n2p17

Suparno, P. (2005). Miskonsepsi dan perubahan konsep dalam pendidikan fisika. Grasindo.

Theba, N. M., Pournara, C., & Takker, S. (2024). Simplifying algebraic expressions with brackets: Insights into Grade 10 learners’ structure sense through a study of their errors. Pythagoras, 45(1), a783. https://doi.org/10.4102/pythagoras.v45i1.783

Ting, S. U., Ling, S. E., & Chen, C. K. (2019). Errors and misconceptions in algebra: A case study of pre-commerce students at UiTM Sarawak. Journal of Engineering and Applied Sciences, 14(3), 6165–6174. https://doi.org/10.36478/jeasci.2019.6165.6174

Treagust, D. F. (1988). Development and use of diagnostic tests to evaluate students’ misconceptions in science. International Journal of Science Education, 10(2), 159–169. https://doi.org/10.1080/0950069880100204

Vincheh, M. H., Mirzaei, A., & Roohani, A. (2024). A cognitive diagnostic approach to IELTS speaking test: Unveiling the subskills and test-takers’ perceptions. Language Testing in Asia, 14, 42. https://doi.org/10.1186/s40468-024-00311-2

Vinner, S. (1997). The pseudo-conceptual and the pseudo-analytical thought processes in mathematics learning. Educational Studies in Mathematics, 34(2), 97–129. https://doi.org/10.1023/A:1002998529016

Waltz, C. F., Strickland, O. L., & Lenz, E. R. (2005). Measurement in nursing and health research (3rd ed.). Springer.

Wang, W. (2008). Understanding rasch measurement: Assessment of differential item functioning. Journal of Applied Measurement, 9(4), 387–408.

Williamson, J. (2023). Cognitive diagnostic models and how they can be useful. Cambridge University Press & Assessment.

Wind, S. A., & Gale, J. D. (2015). Diagnostic opportunities using Rasch measurement in the context of a misconceptions-based physical science assessment. Science Education, 99(4), 721–741. https://doi.org/10.1002/sce.21172

Yang, T. C., Fu, H. T., Hwang, G. J., & Yang, S. J. (2017). Development of an interactive mathematics learning system based on a two-tier test diagnostic and guiding strategy. Australasian Journal of Educational Technology, 33(1), 62–80. https://doi.org/10.14742/ajet.2154

Yuznaili, S. (2016). Pembangunan ujian diagnostic kemahiran menulis mekanis bahasa Melayu [Doctoral dissertation, Universiti Pendidikan Sultan Idris].

Zainal, A., Muhammad, D., & Maya, S. (2022). An analysis of student misconceptions in learning algebra using conventional learning model by using three tier test. Advances in Social Science, Education and Humanities Research, 611, 238–245. https://doi.org/10.37118/ijdr.24084.03.2022