Investigating the Impact of Continuous Professional Development Model of Mathematics Teachers Based on Brain Education Approach on Mathematical Learning and Self-Concept in High School Female Students of the City of Isfahan
Subject Areas : Research in Curriculum Planningsaeedeh shahsavani 1 , Maryam Baratali 2 , Narges Keshtiaray 3
1 - PhD Student, Department of Curriculum Planning, Islamic Azad University of Isfahan Branch, Isfahan, Iran.
2 - Assistant Professor, Department of Curriculum Planning, Islamic Azad University of Isfahan Branch, Isfahan, Iran.
3 - Associate Professor, Department of Curriculum Planning, Islamic Azad University of Isfahan Branch, Isfahan, Iran.
Keywords: continuous teachers’ professional development, mathematical self-concept, mathematical learning, brain education -based approach,
Abstract :
The purpose of current study was to investigate the effectiveness of the continuous professional development model of mathematics teachers based on the Brain Education Approach on the mathematical learning and mathematical self-concept of second grade female student (academic year2019-2020)in Isfahan.The sample consisted of 44 female students and they were selected via non-probability and convenience sampling from Isfahan Public School District 3 whose principal,deputy principal and math teacher were willing to coopetate with the researchers.The instruments used in the research are:Continuous professional development educational package for math teachers based on brain education approach, prepared by Shahsavani et al.(2019)for teacher education in the experimental group, Researcher-made checklist in math lesson and 7-item mathematical self-concept questionnaire of Pahlavan.The reliability of the tools was determined by calculating the Cronbach's alpha coefficient.This coefficient was obtained 0.87 for the mathematics self-concept questionnaire and 0.71 for the mathematics checklist.In this study a pretest-posttest design with a control group was used.First,the pre-test was performed on the subjects and then in 24 sessions of 90 minutes,the experimental group was trained by a teacher who had undergone a continuous professional development course for teachers based on the brain education approach,while the control group was trained by a teacher who had not undergone this course.At the end of the course,the post-test was taken from all students for learning and math self-concept.To analyze the data,the univariate analysis of covariance was used.The results showed that this pattern increased students'learning and math self-concept relative to the pre-test and this change was statistically significant.
Ansari, D., & Lyons, I. M. (2016). Cognitive neuroscience and mathematics learning: How far have we come? Where do we need to go? ZDM Mathematics Education, 48, 379–383.
Babai, R., Nattiv, L., & Stavy, R. (2016). Comparison of perimeters: improving students’ performance by increasing the salience of the relevant variable. ZDM Mathematics Education. doi: 10. 1007/ s11858-016-0766-z.
Constance, D. J. (2010). Exploring brain-based instructional practices in secondary education classes (Doctoral dissertation). Available from https: //pdfs. semanticscholar. org/
Caine, G., & Caine, R. N. (1990). Making connections: Teaching & The human brain. Available at: https: //www. amazon. Com.
Doris, B. (2007). The effect of brain-based learning with teacher trianing in division and fractions in fifth grade students of a private school, Doctoral Dissertation, capella university.
De Smedt, B., & Grabner, R. (2016). Applications of neuroscience to mathematics education. In A. Dowker & R. Cohen-Kadosh (Eds.), Oxford handbook of mathematical cognition (pp. 613– 636). Oxford, United Kingdom: Oxford University Press.
Glover, J. E., & Weratrich, B. (1990). Educational Psychology (3rd ed.). (A. Kharrazi, Trans.). Tehran: Academic Publishing Center.
Hassani, M., Dastjerdi, R., & Pakdaman, M. (2015). The Impact of Brain-Based Learning (B. B. L. ) on Attitude and Educational Achievement in Mathematics. Research in Curriculum, 20(47), 61-73.
Jenson, A. (2004a). Brain and Education. (L. Mohammad Hossein, and S. Razavi, Trans.). Tehran: Madreseh Publications.
Jenson, E. (2004b). Braine- based learning. Del Mar, CA: Turning Publishing.
Jensen, E. P. (2005). Teaching with the brain in mind (2nd ed. ). Alexandria, VA: ASCD Publishing.
Johnson, T. (2003). Teaching mathematics with the brain in mind: learning pure mathematics with meaning and understanding (Msc Thesis). University of Lethbridge Research Repository OPUS. Available from https: //opus. uleth. ca/
Jenson, A. (2010). Brain-Based Learning (New Paradigm of Education). (S. Seifi, and N. Nosrati, Trans.). Tehran: Farhang Roshd Publications.
Kamali, F., Ghanaei, A., & Asgharei, M. (2016). Investigating the Impact of Brain-Based Teaching on Elementary Students’ Educational Achievement in Mathematics. Available from profdoc. um. ac. ir/paper-abstract-1063955. html
Karimzadeh, M. (2001). Investigating the relationship between self-concept (academic and non-academic) and self-efficacy and mathematical achievement in girl students in Tehran (mathematics and humanities fields) (MSc Thesis). University of Tehran.
Kiamanesh, A., & Purasghar, N. (2006). The Role of Mathematical Self-Concept, Mathematical Learning Motivation, Previous Mathematical Performance, and Gender in Mathematical Achievement. Journal of Educational Sciences and Psychology of Shahid Chamran University of Ahvaz, 3(2), 77-94.
Kiedinger, R. S. (2011). Brain-based Learning and its Effects on Student Outcome In Elementary Aged Students Graduate Degree/Major: MS Education Research Adviser: Karen Zimmerman (Doctoral dissertation). University of Wisconsin-Stout.
Lee, K. (2018). Neuroscience and the Teaching of Mathematics, Available at: https: //www. researchgate. net/publication/230010051
Mekarina, M., & Ningsih, Y. P. (2017). The Effects of Brain Based Learning Approach on
Motivation and Students Achievement in Mathematics. Learning Journal of Physics Conference Series, 895(1), 012057
Leikin, R., Waisman, I., & Leikin, M. (2016). Does solving insightbased problems differ from solving learning-based problems? Some evidence from an ERP study. ZDM Mathematics Education. doi: 10. 1007/s11858-016-0767-y.
Momeni, H., Zangouei, A., & Dehghani, M. (2014). The Impact of Teaching George Polya’s Problem Solving Strategies on Self-Concept and Mathematical Educational Achievement of Elementary Fifth Grade Male Students. Journal of Research in Curriculum Planning, 11(43), 46-57.
Merkley, R., Shimi, A., & Scerif, G. (2016). Electrophysiological markers of newly acquired symbolic numerical representations: the role of magnitude and ordinal information. ZDM Mathematics Education. doi: 10. 1007/s11858-015-0751-y.
Pollack, C., Leon, S. L., & Star, J. R. (2016). Exploring mental representations for literal symbols using priming and comparison distance effects. ZDM Mathematics Education. doi: 10. 1007/ s11858-015-0745-9.
Saki, Sh., Fallah, M., & Zare, H. (2014). The Role of Mathematical Self-Efficacy, Mathematical Self-Concept, and Perception of Classroom Environment in Mathematical Achievement of Students with Controlling Gender. Journal of Research in School Learning, 1(4), 19-28.
Samadi, M. (2013). Effectiveness of Brain-Based Teaching on Improved Mathematical Performance of Elementary Fifth-Grade Students with Mathematical Learning Disability in Isfahan: A Case Study. Master’s thesis, Faculty of Educational Sciences and Psychology, University of Isfahan.
Seifi, S., Ebrahimi Qavam, S., & Farrokhi, N. (2010). Investigating the Effect of Teaching Brain-Based Learning on Elementary Third-Grade Students’ Reading Comprehension and Learning Speed; Quarterly Journal of Educational Innovations, 9 (34), 45-60.
Shahsavani, S., Baratali, M., & Kashti Aray, N. (2019). Presentation of Professional Development Model of Mathematics Teachers Based on Brain Teaching Approach. (Doctoral Dissertation). Azad University of Isfahan.
Shir Alipour, Farzad, V., Hajei Hosein Nejad, GH., & Asadi, M. (2014). The Structural Model of the Role of Creativity, Philosophical Mindset, Self-Efficacy, and Mathematical Self-Concept on Mathematical Achievement. Journal of Initiative and Creativity in Humanities, 3(4), 55-78.
Spüler, M., Walter, C., Rosentiel, W., Moeller, K., & Klein, E. (2016). EEG-based prediction of cognitive workload induced by arithmetic: a step towards online adaptation in numerical learning. ZDM Mathematics Education. doi: 10. 1007/s11858-015-0754-8.
Schillinger, F., De Smedt, B., & Grabner, R. H. (2016). When errors count: an EEG study on numerical error monitoring under performance pressure. ZDM Mathematics Education. doi: 10. 1007/ s11858-015-0746-8.
Tumpek, C., & Obersteiner, A. (2016). Measuring fraction comparison strategies with eye-tracking. ZDM Mathematics Education. doi: 10. 1007/s11858-015-0742-z.
Verschaffel, L. , Lehtinen, E. , Van Dooren, W. (2016). Neuroscientific studies of mathematical thinking and learning: a critical look from a mathematics education. ZDM Mathematics Education, 48, 385–391.
Vogel, S., Keller, C., Koschutnig, G., Ebner, F., Dohle, S., Siegrist, M., & Grabner, R. H. (2016). The neural correlates of health risk perception in individuals with low and high numeracy. ZDM Mathematics Education. doi: 10. 1007/s11858-016-0761-4.
_||_