UPSI Digital Repository (UDRep)
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Abstract : Universiti Pendidikan Sultan Idris |
The main purpose of this study is to develop a teaching framework for pre-service
mathematics teachers. Specifically, this study validates the items that measure the constructs of
the Teaching Framework for Pre-service Mathematics Teachers (TF@Maths) and examines whether
mathematics content knowledge (MCK), mathematical pedagogical knowledge (MPK), general pedagogical
knowledge (GPK), classroom management skills (CMS), and mathematical disposition (MDP)
significantly relate to quality mathematics teacher (QMT). This study employed a quantitative
approach to look at the constructs of a quality mathematics teacher from the perspective of the
pre-service teachers. Data were collected using a questionnaire from a sample of 400 students which
were randomly selected from three Public Universities (PUs) and seven Institutes of Teacher
Education (ITEs). Structural Equation Modelling (SEM) was applied to analyse the data. The results
reveal an acceptable fit of the TF@Maths framework with satisfactory convergent validity,
discriminant validity and reliability. All confirmatory factor analysis (CFA) models achieved
convergent validity with Average Variance Extracted above 0.50 and the value of construct
reliability exceeded 0.70. These indicated that all items of each constructs could measure the same
traits. The Structural Equation Modeling analysis indicated significant overall fit of the model
and the discriminant validity showed that all correlation coefficient values were less than 0.90
which indicated that all constructs were different significantly. The results also showed that MCK,
MPK, GPK, CMS, and MDP are significant predictors of QMT. In conclusion, this study showed that
TF@Maths is well fitted and can be accepted as a valid and reliable instrument to determine a
quality mathematics teacher. The study implicates that the TF@Maths framework and findings could
provide a new instrument to help stakeholders in designing mathematics curriculum.
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References |
Alton-Lee, A. (2003). Best evidence synthesis: Quality teaching for diverse students in schooling. Wellington: Ministry of Education.
Anthony, G., & Walshaw, M. (2009). Characteristics of effective teaching of mathematics: A view from the West. Journal of Mathematics Education, 2(2), 147–164.
Asri, R. (2005). Belajar dan Pembelajaran. Jakarta: Rineka Cipta.
Australian Association of Mathematics Teacher. (2006). Standards for Excellence in Teaching Mathematics in Australian School. Adelaide: The Australian Association of Mathematics Teachers Inc.
Ausubel, D. P. (1967). A cognitive structure theory of school learning. Instruction: Some Contemporary Viewpoints. San Francisco: Chandler.
Awang, Z. (2012). A Handbook on SEM (Structural Equation Modeling), Using AMOS Graphic. Kota Bharu: Universiti Teknologi Mara Kelantan.
Bagozzi, R. P., & Yi, Y. (2012). Specification, evaluation, and interpretation of structural equation models. Journal of the Academy of Marketing Science, 40(1), 8–34.
Ball, D., Bass, H., & Hill, H. (2004). Knowing and using mathematical knowledge in teaching: Learning what matters. In Proceedings for the 12th Annual Conference of the South African Association for Research in Mathematics, Science and Technology Education. Durban: SAARMSTE.
Barber, M., & Mourshed, M. (2009). Shaping the future: How good education systems can become great in the decade ahead. Report on the International Education Roundtable, 7.
Barlett, J. E., Kotrlik, J. W., & Higgins, C. C. (2001). Organizational research: Determining appropriate sample size in survey research. Information Technology, Learning, and Performance Journal, 19(1), 43.
Beauchamp, G., & Parkinson, J. (2008). Pupils’ attitudes towards school science as they transfer from an ICT-rich primary school to a secondary school with fewer ICT resources: Does ICT matter? Education and Information Technologies, 13(2), 103–118. doi: 10.1007/s10639-007-9053-5
Bernardo, A. B. (1998). The learning process: The neglected phenomenon in science and mathematics education refrom in the Philippines. Science Education in the Philippnines: Challenges for Development, 27-28.
Bhattacherjee, A. (2012). Social science research: principles, methods, and practices. 2nd edition. Zurich, Switzerland: Creative Commons Attribution.
Bolyard, J. J., & Moyer-Packenham, P. S. (2008). A review of the literature on mathematics and science teacher quality. Peabody Journal of Education, 83(4), 509–535.
Bransford, J., Darling-Hammond, L., & LePage, K. (2005). Preparing teachers for a changing world. San Francisco: Jossey-Bass.
Brophy, J. E. (1983). Classroom organization and management. The Elementary School Journal, 83(4), 265–285.
Brown, T. A. (2014). Confirmatory factor analysis for applied research. New York: Guilford Publications.
Brownell, W. A. (2007). The progressive nature of learning in mathematics. The Mathematics Teacher, 100, 26–34.
Bruner, J. S. (1966). Toward a theory of instruction. Cambridge: Harvard University Press.
Bruning, R. H., Schraw, J. G., Norby, M. M., & Ronning, R. (2004). Cognitive psychology and instruction. Columbus, OH: Pearson.
Byrne, B. M. (2013). Structural equation modeling with EQS: Basic concepts, applications, and programming. UK: Routledge.
Campbell, J., Kyriakides, L., Muijs, D., & Robinson, W. (2012). Assessing teacher effectiveness: different models. UK: Routledge.
Carpenter, T. P., & Lehrer, R. (1999). Teaching and learning mathematics with understanding. Mathematics Classrooms That Promote Understanding, 19–32.
Carraher, T. N., Carraher, D. W., & Schliemann, A. D. (1985). Mathematics in the streets and in schools. British Journal of Developmental Psychology, 3(1), 21–29.
Casey, C., & Childs, R. (2017). Teacher education program admission criteria and what beginning teachers need to know to be successful teachers. Canadian Journal of Educational Administration and Policy, (67). Cha, E., Kim, K. H., & Erlen, J. A. (2007). Translation of scales in cross‐ cultural research: issues and techniques. Journal of Advanced Nursing, 58(4), 386–395.
Chua, Y. P. (2012). Mastering research methods. Malaysia: Mcgraw-Hill Education.
Chua, Y. P. (2014). Statistik Penyelidikan Lanjutan: Ujian Regresi, Analisis Faktor dan analisis Sem. Malaysia: McGraw Hill (Malaysia) Sdn Bhd.
Coakes, S. J., Steed, L. G., Coakes, S. J., & Steed, L. G. (2003). Multiple response and multiple dichotomy analysis. SPSS: Analysis without Anguish: Version 11.0 for Windows, 215–224.
Cox. (2004). What sort of of “teacher training” do mathematics lecturers want? MSOR Connections, 4(4), 23-26.
Creswell, J. W. (2005). Research design: Planning, conducting, and evaluating quantitative and qualitative research. Upper Saddle River, NJ: Pearson/Merrill Prentice Hall.
Darling-Hammond, L. (2000). Teacher quality and student achievement. Education Policy Analysis Archives, 8, 1.
Darling-Hammond, L., & Bransford, J. (2007). Preparing teachers for a changing world: What teachers should learn and be able to do. New York: John Wiley & Sons.
Dienes, Z. P. (1969). Building up mathematics. United Kingdom: Hutchinson & Co. (Publishers) Ltd..
Doyle, W. (1985). Recent Research on Classroom Management Implications for Teacher Education. Journal of Teacher Education, 36(3), 31–35.
Duit, R., & Treagust, D. F. (2003). Conceptual change: A powerful framework for improving science teaching and learning. International Journal of Science Education, 25(6), 671–688.
Elliot, S. N. (2000). Education Pycology:Effective Teaching and Effective Learning. Singapore: Mc Graw-Hill.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 39–50.
Gagné, R. M. (1975). Essentials of learning for instruction. New York: Dryden Press.
Gao, S., Mokhtarian, P., & Johnston, R. (2008). Nonnormality of data in structural equation models. Transportation Research Record: Journal of the Transportation Research Board, 2082(1), 116–124.
Garson, G. D. (2012a). Structural Equation Modeling. Asheboro, NC: Statistical Associates Publishing.
Garson, G. D. (2012b). Testing statistical assumptions. Asheboro, NC: Statistical Associates Publishing.
Gaskin, J. (2012). Confirmatory factor analysis. Gaskination’s StatWiki. Retrieved from http://statwiki.kolobkreations.com/wiki /Structural_Equation_ Modeling# Mediation
Gates, P., & Vistro-Yu, C. P. (2003). Is mathematics for all? In Second international handbook of mathematics education (pp. 31–73). New York: Springer, Dordrecht.
Gay, L. R., Mills, G. E., & Airasian, P. W. (2009). Educational research: Competencies for analysis and applications, student value edition. Upper Saddle River, NJ: Merrill.
Ghazali, D., & Sufean, H. (2016). Metodologi penyelidikan dalam pendidikan: amalan dan analisis kajian. Kuala Lumpur: Penerbit Universiti Malaya.
Goh, P. S. C. (2012). The Malaysian Teacher Standards: A look at the challenges and implications for teacher educators. Educational Research for Policy and Practice, 11(2), 73–87.
Goh, P. S. C. (2013). Conceptions of Competency: A Phenomenographic Investigation of Beginning Teachers in Malaysia. Qualitative Report, 18(20), 1–16.
Goh, P. S., & Matthews, B. (2011). Listening to the concerns of student teachers in Malaysia during teaching practice. Australian Journal of Teacher Education (Online), 36(3), 12.
Graham, K. J., Li, Y., & Buck, J. C. (2000). Characteristics of mathematics teacher preparation programs in the United States: An exploratory study. Mathematics Educator. Retrieved June 20, 2016, from: http://math.nie.edu.sg/ame /matheduc/ tme/ tmeV5_12/ Doc2.pdf
Grasha, A. F. (1996). Teaching with style: Enhancing learning by understanding teaching and learning styles. Pittsburgh. PA: Alliance Publishers.
Groenland, E. A. G., & Stalpers, J. (2012). Structural equation modeling: A verbal approach Nyenrode Research Paper Series. Breukelen, The Netherlands, Nyenrode Business University.
Gwinner, C. (2006). Infosurv white paper 5-point vs. 6-point likert scales. Infosurv Online Research Service. Retrieved November 5, 2016, from http:// www. infosurv.com/wp-content/uploads/2011/01/Likert_Scale_Debate.pdf
Hair, J. F. (2014). AMOS covariance-based structural equation modeling (CB-SEM): guidelines on its application as a marketing research tool. New Jersey: Prentice Hall.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (2006). Multivariate data analysis (5th ed.). New Jersey: Prentice Hall.
Hair, J. F., Black, W. C., & Babin, B. J. (2010). RE Anderson Multivariate data analysis: A global perspective. New Jersey: Pearson Prentice Hall.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (Vol. 6). Upper Saddle River, NJ: Pearson Prentice Hall.
Hatcher, R. L., & Barends, A. W. (1996). Patients’ view of the alliance in psychotherapy: Exploratory factor analysis of three alliance measures. Journal of Consulting and Clinical Psychology, 64(6), 1326.
Heid, M. K. (2005). Technology in mathematics education: Tapping into visions of the future. Technology-Supported Mathematics Learning Environments, 67, 345.
Hill. (1990). Order in the Classroom. Teacher Magazine 1(7), 70-77.
Hill, H. C., Rowan, B., & Ball, D. L. (2005). Effects of teachers’ mathematical knowledge for teaching on student achievement. American Educational Research Journal, 42(2), 371–406.
Ho, R. (2006). Handbook of univariate and multivariate data analysis and interpretation with SPSS. Florida: CRC Press.
JPNIN, J. P. M. (2016). JPNIN Negeri Mengikut Zon-zon. Retrieved from http://www.jpnin.gov.my/en
Kaino, L. M. (2015). Towards a Framework for Effective Mathematics Continuous Professional Development. International Journal of Educational Sciences, 8(1), 223–228.
Kinoshita. (2000). Kyoto academia turns to private sector for help. Retrieved from http://www.yomiuri.co.jp/newse/0605so13.htm
Kirk, J., & Miller, M. L. (1986). Reliability and validity in qualitative research. Califonia: Sage Publications Inc.
Kline, R. B. (2011). Convergence of structural equation modeling and multilevel modeling. Califonia: Sage Publications Inc.
Krejcie, R. V, & Morgan, D. W. (1970). Determining sample size for research activities. Educational and psychological measurement, 30(3), 607-610.
Lee, M. N. N. (2002). Teacher education in Malaysia: Current issues and future prospects. Teacher Education: Dilemmas and Prospects, 8, 57.
Lei, P., & Wu, Q. (2007). Introduction to structural equation modeling: Issues and practical considerations. Educational Measurement: Issues and Practice, 26(3), 33–43.
Leong, K. E., Chew, C. M., & Suzieleez, S. A. R. (2015). Understanding Malaysian Pre-Service Teachers Mathematical Content Knowledge and Pedagogical Content Knowledge. Eurasia Journal of Mathematics, Science and Technology Education, 11(3), 363–370. doi: 10.12973/eurasia. 2015.1346a
Lim, S. K., & Chan, T. B. (1993). A case study comparing the learning of mathematics among Malay pupils in primary national schools and primary national schools. Journal of Science and Mathematics Education in South East Asia.
Lomax, R. G., & Schumacker, R. E. (2004). A beginner’s guide to structural equation modeling. UK: Psychology Press.
Lucas. (2000). Hong Kong set to abandon rote learning. The Financial Times. Retrieved from https://www.ft.com/louise-lucas
Lynn, M. R. (1986). Determination and quantification of content validity. Nursing Research, 35(6), 382–386.
Maat, S. M., & Zakaria, E. (2011). Hubungan antara kepercayaan matematik, amalan pengajaran dan pengetahuan pedagogi kandungan guru-guru matematik sekolah menengah. (Unpublished doctoral thesis): Universiti Kebangsaan Malaysia, Bangi.
Maat, S. M., Zakaria, E., Nordin, N. M., & Meerah, T. S. M. (2011). Confirmatory factor analysis of the mathematics teachers’ teaching practices instrument. World Applied Sciences Journal, 12(11), 2092–2096.
MacCallum, R. C., Widaman, K. F., Zhang, S., & Hong, S. (1999). Sample size in factor analysis. Psychological Methods, 4(1), 84.
Malaysia Education Blueprint, M. (2013). Malaysia Education Blueprint 2013 - 2025. Ministry of Education Malaysia, 27(1), 1–268. doi: 10.1016/j.tate.2010.08.007
Malaysia Ministry of Education. (2016). PISA 2015. Putrajaya: Bahagian Perancangan dan Penyelidikan Dasar Pendidikan, KPM.
MATHTED & SEI. (2011). Framework for Philippine Mathematics Teacher Education. Manila: SEI-DOST & MATHTED.
Mundfrom, D. J., Shaw, D. G., & Ke, T. L. (2005). Minimum sample size recommendations for conducting factor analyses. International Journal of Testing, 5(2), 159–168.
Nagendralingan, R., Chang, L. H., Maria, S., Low, J., Nagalingam, K., Ainon, O., ... & Abdul, T. M. H. (2014). Curriculum framework for preparing quality teachers for the future : Developing guiding principles. Journal of Research, Policy & Practice of Teachers & Teacher Education, 4(2), 32–44.
Naing, L., Winn, T., & Rusli, B. N. (2006). Practical issues in calculating the sample size for prevalence studies. Archives of Orofacial Sciences, 1, 9–14.
National Council for Teachers of Mathematics. (2000). Principles and Standards for School Mathematics. New York: Guilford Press.
National Institute of Education, S. (2007). Mathematics Framework. Retrieved from http://www.nie.edu.sg/research/research-offices/office-of-education-research/rese arch-development-framework/mathematics
National Research Council. (2001). Adding it up: Helping children learn mathematics. Mathematics Learning Study Committee, Center for Education, Division of Behavioral and Social Sciences and Education. DC: National Academies Press Washington.
NCTM. (1991). Professional Standard of Teaching Mathematics. VA: The Council.
Nik Aziz, N. P. (1999). Pendekatan konstruktivisme radikal dalam pendidikan matematik. Kuala Lumpur: Penerbit Universiti Malaya.
Noor Shah, S., Mohd, D., & Zulkifley, M. (2013). Pengetahuan dalam kalangan guru matematik sekolah rendah berdasarkan standard pengajaran matematik. Jurnal Pendidikan Sains & Matematik Malaysia, 3(2), 43–62.
Noor Shah, S., Nor’ain, M. T., Zulkifley, M., Muzirah, M., & Lim, K. B. (2009). Standard Kecemerlangan Pengajaran Matematik (SET@MATH): Satu Cadangan bagi Meningkatkan Kualiti Pengajaran Guru Matematik. UPSI: Fakulti Sains & Teknologi.
Noor Shah, S., & Sazelli, A. G. (2010). Teaching Mathematics in Secondary School: Theories and Practices. UPSI: Ampang Press Sdn. Bhd.
Noraini, I. (2006). Teaching and Learning of Mathematics. Kuala Lumpur: Utusan Publications & Distributors Sdn Bhd.
Noraini, I. (2013). Penyelidikan dalam pendidikan (Edisi Kedua). Kuala Lumpur: McGraw Hill.
Norhayati, A., Aida Suraya, M. Y., Rohani, A. T., Kamisah, O., & Lilia, H. (2006). Perancangan Kurikulum Pendidikan Matematik. OUM: Meteor Doc. Snd. Bhd.
Novak, J. D., & Gowin, D. B. (1984). Learning how to learn. UK: Cambridge University.
Oke, A. E., Ogunsami, D. R., & Ogunlana, S. (2012). Establishing a common ground for the use of structural equation modelling for construction related research studies. Australasian Journal of Construction Economics and Building,12(3), 89.
Oluwatayo, J. A. (2012). Validity and reliability issues in educational research. Journal of Educational and Social Research, 2(2), 391–400.
Onno, D. J., & Lilia, H. (2009). Teachers’ professional knowledge in science and mathematics education: Views from Malaysia and abroad. Bangi: Faculty of Education, Universiti Kebangsaan Malaysia.
Pallant, J. (2007). SPSS survival manual, 3rd. Edition. New York: McGrath Hill.
Pallant, J. F. (2000). Development and validation of a scale to measure perceived control of internal states. Journal of Personality Assessment, 75(2), 308–337.
Piaget, J. (1971). The theory of stages in cognitive development. Retrieved from https://www.researchgate.net/publication/232574518_The_theory_of_stages_in_ cognitive_development
Putnam, R. T., Heaton, R. M., Prawat, R. S., & Remillard, J. (1992). Teaching mathematics for understanding: Discussing case studies of four fifth-grade teachers. The Elementary School Journal, 93(2), 213-228.
Reisinger, Y., & Mavondo, F. (2007). Structural equation modeling: Critical issues and new developments. Journal of Travel & Tourism Marketing, 21(4), 41–71.
Rivkin, S. G., Hanushek, E. A., & Kain, J. F. (2005). Teachers, schools, and academic achievement. Econometrica, 73(2), 417–458.
Sam, F. (2015). Self-regulated Learning Predictors of Academic Performance and Strategies in Resolving Barriers to Learning. (Unpublished PhD thesis): Faculty of Education and Human Development, Universiti Pendidikan Sultan Idris, Perak.
Saunders, M. N. K. (2011). Research methods for business students. 5th edition. India: Pearson Education Limited.
SEAMEO RECSAM. (2016a). Malaysian Mathematics Teacher Quality Standards. Peneng: Publication Unit, SEAMEO RECSAM.
SEAMEO RECSAM. (2016b). Southeast Asia Regional Standards-Mathematics Teacher (SEARS-MT). Peneng: Publication Unit, SEAMEO RECSAM.
Tabachnick, B. G., & Fidell, L. S. (2007). Using Multivariate Statistics. 5th edition. Boston, MA: Pearson Education. Inc.
Tajudin, N. M., Saad, N. S., Rahman, N. A., Yahaya, A., Alimon, H., Dollah, M. U., & Abd Karim, M. M. (2012). Mapping the level of scientific reasoning skills to instructional methodologies among Malaysian science-mathematics-engineering undergraduates. In AIP Conference Proceedings (Vol. 1450, pp. 262–265). AIP.
Tam, W., & Cheng, Y. C. (2007). Teacher education and professional development for sustainable school effectiveness. International Handbook of School Effectiveness and Improvement, pp. 751–766. New York: Springer, Dordrecht.
Turmudi. (2001). Strategi Pembelajaran Matematika Kontemporer. Bandung: JICAUPI.
Vagias, W. M. (2006). Likert-type scale response anchors. USA: Clemson International Institute for Tourism & Research Development, Department of Parks, Recreation and Tourism Management. Clemson University.
Vethamani, M. E. (2011). Teacher education in Malaysia: Preparing and training of English language teacher educators. The Journal of AsiaTEFL, 8(4), 85–110.
Von Glasersfeld, E. (1991). An exposition of constructivism: Why some like it radical. In Facets of systems science (pp. 229–238). New York: Springer, Dordrecht.
Wang, C. L., & Ahmed, P. K. (2004). The development and validation of the organisational innovativeness construct using confirmatory factor analysis. European Journal of Innovation Management, 7(4), 303–313.
Wayne, A. J., & Youngs, P. (2003). Teacher characteristics and student achievement gains: A review. Review of Educational Research, 73(1), 89–122.
Wilson, K. L., Lizzio, A., & Ramsden, P. (1997). The development, validation and application of the Course Experience Questionnaire. Studies in Higher Education, 22(1), 33–53.
Yunus, A. S. M., Hamzah, R., & Ismail, H. (2007). Mathematics Education Program in Malaysian Universities: Curriculum Emphasis and Preparedness of Students to Become Teachers. Proceedings of the Ninth International Conference-The Mathematics Education into the 21st Century Project, 6(Grade 7), 425–430.
Zainudin, A. (2015). SEM Made Simple: A Gentle Approach to Learning Structural Equation Modeling. Bangi: MPWS Rich Publication.
Zeichner, K. M., & Cochran-Smith, M. (2005). Studying teacher education: The report of the AERA panel on research and teacher education. UK: Routledge.
Zhao, J., & Gallant, D. J. (2012). Student evaluation of instruction in higher education: Exploring issues of validity and reliability. Assessment & Evaluation in Higher Education, 37(2), 227–235.
Zheng, H. (2009). A review of research on EFL pre-service teachers’ beliefs and practices. Journal of Cambridge Studies, 4 (1), 73-81. doi: 10.17863 / CAM. 1579
Zuraidah, Z. (2014). The Effects Of Customer-Brand Relationship Investment On Customer Engagement (Unpublised PhD Thesis): Universiti Kebangsaan Malaysia, Bangi.
Zuraidah, Z. (2016). Structural Equation Modeling ( SEM ): A Step By Step Approach (PART 1). Retrieved from https://www.researchgate. net/ profile/ Zuraidah_ Zainol /contributions. doi: 10.13140/RG.2.1.1238.6809
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