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RESEARCH PAPER
Validation of the Mathematical Modeling Attitude Scale for Malaysian Mathematics Teachers
1
Department of Mathematics, Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris, 35900, Perak, MALAYSIA
2
Bahagian Pengurusan Sekolah Harian, Kementerian Pendidikan Malaysia, MALAYSIA
3
Department of Mathematics and Science Education, Faculty Education, Universiti Malaya, 50603, Kuala Lumpur, MALAYSIA
4
Department of Planning, Research and Innovation, Institute of Teachers Education, MALAYSIA
Publication date: 2021-11-26
EURASIA J. Math., Sci Tech. Ed 2021;17(12):em2047
KEYWORDS
ABSTRACT
This work sets out to examine the validity and reliability of the Mathematical Modeling Attitude
Scale (MMAS), a instrument measuring teachers’ attitude towards mathematical modeling. A
cross-sectional survey research was utilised to describe the validity and reliability of the MMAS.
The population of the present study focused on Malaysian mathematics teacher in primary and
secondary schools (N = 171) and this was achieved using convenience sampling. Exploratory
factor analysis (EFA), confirmatory factor analysis (CFA) and Rasch analysis were utilised in
analysing the data in the present work. EFA revealed that the data from the teachers had a four-factor structure: constructivism, relevance and real-life, understanding and motivation and
interest. The CFA confirmed that the model fit indices established the four-factor structure of the
first- and second-order model. Although the Rasch analysis generally supported the finding of
EFA and CFA, there was still room for improvement in terms of the rating scale and DIF criterion.
REFERENCES (86)
1.
A Aziz, N. F., Ahmad, H., & Mat Nashir, I. (2019). Validation of technical and vocational teachers’ competency evaluation instrument using the rasch model. Jurnal Pendidikan Sains Dan Matematik Malaysia, 9(1), 18-25. https://doi.org/10.37134/jpsmm....
2.
Ab Hamid, M. R., Sami, W., & Sidek, M. M. (2017). Discriminant validity assessment: Use of Fornell & Larcker criterion versus HTMT criterion. Journal of Physics: Conference Series, 890(1), 012163. https://doi.org/10.1088/1742-6....
3.
Adams, D., Chuah, K. M., Sumintono, B., & Mohamed, A. (2021). Students’ readiness for e-learning during the COVID-19 pandemic in a South-East Asian university: A Rasch analysis pandemic. Asian Education and Development Studies. https://doi.org/10.1108/AEDS-0....
4.
Aiken Jr, L. R. (1970). Attitudes toward mathematics. Review of Educational Research, 40(4), 551-596. https://doi.org/10.3102/003465....
5.
Albarracín, D., Johnson, B. T., & Zanna, M. P. (Eds.). (2005). The handbook of attitudes (pp. 223-271). Lawrence Erlbaum.
6.
Albarracín, L. (2021). Large number estimation as a vehicle to promote mathematical modeling. Early Childhood Education Journal, 49(4), 681-691. https://doi.org/10.1007/s10643....
7.
Albarracín, L., & Gorgorió, N. (2020). Mathematical modeling projects oriented towards social impact as generators of learning opportunities: A case study. Mathematics, 8(11), 2034. https://doi.org/10.3390/math81....
8.
Ali, A. R., Endut, A., & Embong, R. (2019). Attitude of undergraduate students towards gamification: A case study of Northwest Geo-Political Zone, Nigeria. Journal of ICT in Education, 5, 9-13. https://doi.org/10.37134/jicti....
9.
Alkhadim, G. S., Cimetta, A. D., Marx, R. W., Cutshaw, C. A., & Yaden, D. B. (2021). Studies in educational evaluation validating the research-based early math assessment (REMA) among rural children in Southwest United States. Studies in Educational Evaluation, 68(2020), 100944. https://doi.org/10.1016/j.stue....
10.
Alnahdi, A. H. (2018). Rasch validation of the Arabic version of the lower extremity functional scale. Disability and Rehabilitation, 40, 353-359. https://doi.org/10.1080/096382....
11.
Anderson, E. W., & Mittal, V. (2000). Strengthening the satisfaction-profit chain. Journal of Service Research, 3(2), 107-120. https://doi.org/10.1177/109467....
12.
Araújo, J. D. L., & Lima, F. H. D. (2020). The mathematization process as object-oriented actions of a modelling activity system. Bolema: Boletim de Educação Matemática, 34(68), 847-868. https://doi.org/10.1590/1980-4....
13.
Asempapa, R. S. (2018). Development and initial psychometric properties of the mathematical modeling attitude scale. School Science and Mathematics, 119(1), 14-23. https://doi.org/10.1111/ssm.12....
14.
Asempapa, R. S., & Brooks, G. P. (2020). Factor analysis and psychometric evaluation of the mathematical modeling attitude scale for teachers of mathematics. Journal of Mathematics Teacher Education. https://doi.org/10.1007/s10857....
16.
Ayob, A., & Yasin, R. M. (2017). Factors affecting attitudes towards mathematics. International Journal of Academic Research in Business and Social Sciences, 7(11), 1100-1109. https://doi.org/10.6007/IJARBS....
17.
Barquero, B., Bosch, M., & Romo, A. (2018). Mathematical modelling in teacher education: Dealing with institutional constraints. ZDM, 50(1), 31-43. https://doi.org/10.1007/s11858....
18.
Blum, W., & Leiss, D. (2007). How do students’ and teachers deal with modelling problems? In C. Haines, P. Galbraith, W. Blum, & S. Khan (Eds.), Mathematical modelling: Education, engineering and economics, ICTMA (vol. 12, pp. 222-231). Horwood Publishing. https://doi.org/10.1533/978085....
19.
Blum, W., Galbraith, P. L., Henn, H. W., & Niss, M. (2007). Modelling and applications in mathematics education: The 14 ICMI study (Vol. 10). Springer Science+Business Media. https://doi.org/10.1007/978-0-....
20.
Brown, S. C., & Greene, J. A. (2006). The wisdom development scale: Translating the conceptual to the concrete. Journal of College Student Development, 47(1), 1-19. https://doi.org/10.1353/csd.20....
21.
Burkhardt, H. (2006). Modelling in mathematics classrooms: Reflections on past developments and the future. Zentralblatt Fur Didaktik Der Matematik (ZDM): The International Journal on Mathematics Education, 38(2), 178-195. https://doi.org/10.1007/BF0265....
22.
Campbell, M. J., Machin, D., & Walters, S. J. (2007). Medical statistics: a textbook for the health sciences (4th ed.). Wiley.
23.
Clarke, D. J. (2013). Contingent conceptions of accomplished practice: The cultural specificity of discourse in and about the mathematics classroom. ZDM Mathematics Education, 45, 21-33. https://doi.org/10.1007/s11858....
24.
Cobb, P., & Gravemeijer, K. (2008). Experimenting to support and understand learning processes. In A. E. Kelly, R. A. Lesh, & J. Y. Baek (Eds.), Handbook of design research methods in education: Innovations in science, technology, engineering, and mathematics learning and teaching (pp. 68-95). Routledge.
25.
Common Core State Standards Initiative (CCSSI). (2010). Common Core State Standards for Mathematics. National Governors Association Center for Best Practices and the Council of Chief State School Officers. http://www.corestandards.org/w....
26.
Creswell, J. W. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative research. Educational Research (vol. 4). Pearson.
27.
Creswell, J. W. (2014). Research design: qualitative, quantitative, and mixed methods approaches. SAGE Publications, Inc.
28.
Di Martino, P. (2016). Attitudes, beliefs, motivation, and identity in mathematics education. In Attitudes, beliefs, motivation and identity in mathematics education (pp. 2-6). Springer.
29.
Di Martino, P. (2019). The complex relationship between mathematical modeling and attitude towards mathematics. In S. A. Chamberlin, B. & Sriraman (Eds), Affect in mathematical modeling (pp. 219-234). Springer. https://doi.org/10.1007/978-3-....
30.
Di Martino, P., & Zan, R. (2001). Attitude toward mathematics: some theoretical issues. In M. van den Heuvel-Panhuizen (Ed.), Proceedings of the 25th conference of the international group for the psychology of mathematics education (vol. 3, pp. 351-358). PME.
31.
Doerr, H. M., Ärlebäck, J. B., & Costello Staniec, A. (2014). Design and effectiveness of modeling-based mathematics in a summer bridge program. Journal of Engineering Education, 103(1), 92-114. https://doi.org/10.1002/jee.20....
32.
Doruk, B. K. (2012). Mathematical modeling activities as a useful tool for values education. Educational Sciences: Theory and Practice, 12(2), 1667-1672.
33.
English, L. (2003). Mathematical modeling with young learners. In S. J. Lamon, W. A. Parker, & S. K. Houston (Eds.), Mathematical modelling: A way of life. ICTMA11 (pp. 3-7). Horwood.
34.
Ferri, R. B. (2014). Mathematical modeling—the teacher’s responsibility. In Proceedings from the teachers college mathematical modeling Oktoberfest. Teachers College, Columbia University.
35.
Fornell C, Larcker DF. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 19, 39-50. https://doi.org/10.1177/002224....
36.
Galbraith, P. (2017). Forty years on: Mathematical modelling in and for education. In A. Downton, S. Livy, & J. Hall (Eds.), 40 years on: We are still learning! Proceedings of the 40th annual conference of the mathematics education research group of Australasia (pp. 47-50). MERGA.
37.
Goretzko, D., Pham, T. T. H., & Bühner, M. (2019). Exploratory factor analysis: Current use, methodological developments and recommendations for good practice. Current Psychology, 40, 3510-3521. https://doi.org/10.1007/s12144....
38.
Hair, J. F. Jr., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2017). Advanced issues in partial least squares structural equation modeling. Sage publications.
39.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Pearson.
40.
Hair, J. F., Celsi, M., Money, A., Samouel, P., & Page, M. (2015). The essentials of business research method (3rd ed.). 2016 Faculty Bookshelf. 2. https://doi.org/10.4324/978131....
41.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. M. (2014). A Premier on partial least squares structural equation modeling (PLS-SEM). SAGE Publications.
42.
Hallström, J., & Schönborn, K. J. (2019). Models and modelling for authentic STEM education: Reinforcing the argument. International Journal of STEM Education, 6(2), 1-10. https://doi.org/10.1186/s40594....
43.
Hamed, S., Bahari, P., & Abdullah, A. G. K. (2008). Korelasi antara persekitaran pembelajaran matematik, sikap pelajar terhadap matematik, dan pencapaian pelajar dalam matematik: Satu kajian kes [Correlation between mathematics learning environment, students ‘attitudes toward mathematics, and student achievement in mathematics: A case study]. ESTEEM, 4(2), 91-103.
44.
Hannula, M. S. (2002). Attitude towards mathematics: Emotions, expectations and values. Educational studies in Mathematics, 49(1), 25-46. https://doi.org/10.1023/A:1016....
45.
He, J., Sun, S., & Fan, X. (2021). Validation of the 12-item short form of the eating disorder examination questionnaire in the Chinese context: Confirmatory factor analysis and Rasch analysis. Eating and Weight Disorders, 26(1), 201-209. https://doi.org/10.1007/s40519....
46.
Hennig, C. (2010). Mathematical models and reality: a constructivist perspective. Foundations of Science, 15, 29-48. https://doi.org/10.1007/S10699....
47.
Hidayat, R., Qudratuddarsi, H., Mazlan, N. H., & Zeki, M. Z. M. (2021). Evaluation of a test measuring mathematical modelling competency for Indonesian college students. Journal of Nusantara Studies, 6(2), 133-155. https://doi.org/10.24200/jonus....
48.
Hidayat, R., Zamri, S. N. A. S, Zulnaidi, H., Abdullah, M. F. N. L., & Adnan, M. (2021). The interrelationships between metacognition and modeling competency: the moderating role of the academic year. European Journal of Educational Research, 10(4), 1853-1866. https://doi.org/10.12973/eu-je....
49.
Hidayat, R., Zamri, S. N. A. S., & Zulnaidi, H. (2018). Exploratory and confirmatory factor analysis of achievement goals for Indonesian students in mathematics education programmes. EURASIA Journal of Mathematics, Science and Technology Education, 14(12), em1648. https://doi.org/10.29333/ejmst....
50.
Hidayat, R., Zulnaidi, H., & Syed Zamri, S. N. A. (2018). Roles of metacognition and achievement goals in mathematical modeling competency: A structural equation modeling analysis. PloS One, 13(11), e0206211. https://doi.org/10.1371/journa....
51.
Hooper, D., Coughlan, J., & Mullen, M. (2008). Structural equation modelling: Guidelines for determining model fit. The Electronic Journal of Business Research Methods, 6, 53-60.
52.
Hunt J. (2007). Communicating big themes in applied mathematics. In P. Haines, W. Galbraith, W. Blum, & S. Khan (Eds.), Mathematical modeling (ICTMA12): Education, engineering and economics (pp. 2-24). Horwood Publishing. https://doi.org/10.1533/978085....
53.
Iseppi, L., Rizzo, M., Gori, E., Nassivera, F., Bassi, I., & Scuderi, A. (2021). Rasch model for assessing propensity to entomophagy. Sustainability, 13(8), 4346. https://doi.org/10.3390/su1308....
54.
Kasmin, F., Othman, Z., & Syed Ahmad, S. S. (2019). Improving students’ perception towards learning mathematics: impact of teaching application of mathematics. EDUCATUM Journal of Science, Mathematics and Technology, 6(1), 29-34. https://doi.org/10.37134/ejsmt....
55.
Khairani, A. Z. (2017). Assessing urban and rural teachers’ competencies in STEM integrated education in Malaysia. In MATEC Web of Conferences (vol. 87, p. 04004). EDP Sciences. https://doi.org/10.1051/matecc....
56.
Kline, R. B. (2005). Principles and practice of structural equation modeling. The Guilford Press.
57.
Kohen, Z., & Orenstein, D. (2021). Mathematical modeling of tech-related real-world problems for secondary school-level mathematics. Educational Studies in Mathematics, 107(1), 71-91. https://doi.org/10.1007/s10649....
58.
Leavy, A., Hourigan, M., & Carroll, C. (2017). Exploring the impact of reform mathematics on entry-level pre-service primary teachers attitudes towards mathematics. International Journal of Science and Mathematics Education, 15(3), 509-526. https://doi.org/10.1007/s10763....
59.
Lee, J., & Paek, I. (2014). In search of the optimal number of response categories in a rating scale. Journal of Psychoeducational Assessment, 32(7), 663-673. https://doi.org/10.1177/073428....
60.
Leong, K. E., & Tan, J. Y. (2020). Exploring secondary students’ modelling competencies. The Mathematics Enthusiast, 17(1), 85-107.
61.
Leung, A. (2019). Exploring STEM pedagogy in the mathematics classroom: A tool-based experiment lesson on estimation. International Journal of Science and Mathematics Education, 17(7), 1339-1358. https://doi.org/10.1007/s10763....
62.
Leung, S. O. (2011). A comparison of psychometric properties and normality in 4-, 5-, 6-, and 11-point likert scales. Journal of Social Service Research, 37(4), 412-421. https://doi.org/10.1080/014883....
63.
Lozano, L. M., García-Cueto, E., & Muñiz, J. (2008). Effect of the number of response categories on the reliability and validity of rating scales. Methodology, 4(2), 73-79. https://doi.org/10.1027/1614-2....
64.
Maaβ, K. (2006). What are modeling competencies? Zentralblatt FüR Didaktik Der Mathematik, 38(2), 113-142. https://doi.org/10.1007/BF0265....
65.
Mardia, K. V. (1974). Applications of some measures of multivariate skewness and kurtosis in testing normality and robustness studies. Sankhyā: The Indian Journal of Statistics, Series B, 36(2), 115-128.
66.
McLeod, D. (1992). Research on affect in mathematics education: a reconceptualization. In D. Grows (Ed.), Handbook of research on mathematics teaching and learning (pp. 575-596). McMillan.
67.
Obrad, C. (2020). Constraints and consequences of online teaching. Sustainability, 12(17), 6982. https://doi.org/10.3390/su1217....
68.
Osbourne, J. W. (2015). What is rotating in exploratory factor analysis? Practical Assessment, Research, and Evaluation, 20(2), 1-7.
69.
Pollak, H. O. (2011). What is mathematical modeling? Journal of Mathematics Education at Teachers College, 2(1), 64.
70.
Purnami, W., Sumintono, B., & Wahyu, Y. (2021). Investigation of person ability and item fit instruments of eco critical thinking skills in basic science concept materials for elementary pre-service teachers. Jurnal Pendidikan IPA Indonesia, 10(1), 127-137. https://doi.org/10.15294/jpii.....
71.
Raykov, T. (2004). Behavioral scale reliability and measurement invariance evaluation using latent variable modeling. Behavior Therapy, 35, 299-331. https://doi.org/10.1037/cou000....
72.
Rouquette, A., Hardouin, J. B., Vanhaesebrouck, A., Sébille, V., & Coste, J. (2019). Differential item functioning (DIF) in composite health measurement scale: Recommendations for characterizing DIF with meaningful consequences within the Rasch model framework. PLoS ONE, 14(4), 1-16. https://doi.org/10.1371/journa....
73.
Sabudin, G., & Halim, L. (2020). Kajian sistematik: pendekatan pengajaran dan impak khazanah pengetahuan dalam pembelajaran sains. Jurnal Pendidikan Sains Dan Matematik Malaysia, 10(1), 21-38. https://doi.org/10.37134/jpsmm....
74.
Sahin, S., Dogan, M. F., Cavus Erdem, Z., Gurbuz, R., & Temurtas, A. (2019). Prospective teachers’ criteria for evaluating mathematical modeling problems. International Journal of Research in Education and Science, 5(2), 730-743.
75.
Scoulas, J. M., Aksu Dunya, B., & De Groote, S. L. (2021). Validating students’ library experience survey using rasch model. Library and Information Science Research, 43(1), 101071. https://doi.org/10.1016/j.lisr....
76.
Shahbari, J. A., & Peled, I. (2015). Resolving cognitive conflict in a realistic situation with modeling characteristics: Coping with a changing reference in fractions. International Journal of Science and Mathematics Education, 13(4), 891-907. https://doi.org/10.1007/s10763....
77.
Singer, F. M., & Moscovici, H. (2008). Teaching and learning cycles in a constructivist approach to instruction. Teaching and Teacher Education, 24(6), 1613-1634. https://doi.org/10.1016/j.tate....
78.
Stillman, G., Kaiser, G., Blum, W., & Brown, J. (Eds, 2013). Teaching mathematical modelling: connecting to research and practice. Springer. https://doi.org/10.1007/978-94....
79.
Suryadi, B., Hayat, B., Dwirifqi, M., & Putra, K. (2021). The Indonesian version of the life orientation test-revised (LOT-R): psychometric properties based on the Rasch model The Indonesian version of the life orientation test-revised (LOT-R): Psychometric properties based on the Rasch model. Cogent Psychology, 8(1), 1869375. https://doi.org/10.1080/233119....
80.
Tajudin, A., & Abdullah, N. (2018). Kesediaan guru sains sekolah rendah terhadap pelaksanaan pembelajaran abad ke-21 [The readiness of primary school science teachers towards the implementation of 21st century learning]. Jurnal Pendidikan Sains Dan Matematik Malaysia, 8(1), 82-97. https://doi.org/10.37134/jpsmm....
81.
Tennant, A., & Conaghan, P. G. (2007). The Rasch measurement model in rheumatology: What is it and why use it ? when should it be applied, and what should one look for in a Rasch paper ? Arthritis & Rheumatism, 57(8), 1358-1362. https://doi.org/10.1002/art.23....
82.
Tiilikainen, M., Karjalainen, J., Toom, A., Lepola, J., & Husu, J. (2019). The complex zone of constructivist teaching: a multi-case exploration in primary classrooms. Research Papers in Education, 34(1), 38-60. https://doi.org/10.1080/026715....
83.
Van Zile-tamsen, C. (2019). Using Rasch analysis to inform rating scale development. Research in Higher Education, 58(8), 922-933. https://doi.org/10.1007/s11162....
84.
Wang, J. & Wang, X. (2019). Structural equation modeling: applications using mplus (2nd ed.). John Wiley & Sons Ltd. https://doi.org/10.1002/978111....
85.
Yong, W., Hutagalung, F. D., Hidayat, R., & Zulnaidi, H. (2020). A comparison study of Chinese and Indonesia EFL teachers’ well-being. Psychology and Education, 57(4), 233-238.
86.
Zainudin Awang, Lim, S., & Nur Fairuza Syahira. (2018). Pendekatan mudah SEM (Structural Equation Modelling). MPWS.
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