Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2021, Cilt: 8 Sayı: 1, 90 - 108, 01.01.2021
https://doi.org/10.17275/per.21.5.8.1

Öz

Kaynakça

  • Açıkbaş, N. (2002). The Relationship between mathematics performance, attitudes toward mathematics, grade level and gender. Published Master's Thesis, Boğaziçi University, Institute of Natural and Applied Sciences, İstanbul.
  • Akyüz, G. ve Pala, N.M. (2010). The Effect of Student and Class Characteristics on Mathematics Literacy and Problem Solving in PISA 2003. Elementary Education Online, 9(2), 668-678.
  • Alpan, G. (2008). Vısual lıteracy and ınstructıonal technology. Yüzüncü Yıl University Journal of Education Faculty, 5(1), 74-102.
  • Amsterlaw, J.A. (2004). Development of children’s beliefs about everyday reasoning. Publishing Doctoral Thesis, University of Michigan. Available from ProQuest Dissertations and Theses database, (UMI Microform 3138102).
  • Areepattamannil, S. (2014). International Note: What factors are associated with reading, mathematics and science literacy of Indian adolescents? A multilevel examination. Journal of Adolescence, 37(2014), 367–372.
  • Baki, A. (2001). Evaluation of mathematics education in the light of information technology. Journal of Ministry of National Education, 149(1), 26-31.
  • Bal A.P. (2012). Primary school students’ views and challenges on performance task preparation process in mathematics course. Pegem Journal of Education and Instructıon, 2(1), 11-23.
  • Bates, A.B. & Latham, N. (2009). Linking preservice teachers’ mathematics self-efficacy and mathematics teaching efficacy to their mathematical performance. School Science and Mathematics, 109(7), 325-333.
  • Battista, M.T. (1994). On Greene’s Environmental/model view of conceptual domains: A spatial/geometric perspective. Journal for Research in Mathematics Education, 25(1), 86-99.
  • Baykul, Y. (2014). Teaching Mathematics in Primary School (12th Edition). Ankara: Pegem Akademy Publishing.
  • Bekdemir M. ve Duran, M. (2012). Development of a vısual math lıteracy self effıcacy perceptıon scale (VMLSEPS) for elementary students. On Dokuz Mayıs Üniversity Journal of Education Faculty, 31(1), 89-115.
  • Bentler, P.M. & Chou, C.P. (1987). Practical issues in structural modeling. Sociological Methods & Research, 16(1), 78-117.
  • Bollen, K.A. (1989). Structural equations with latent variable. Newyork: Wiley Publisher.
  • Brown, T.A. (2006). Confirmatory faktor analysis for applied research. Newyork: The Guilford press.
  • Buckley, J., Seery, N., & Canty, D. (2018). Investigating the use of spatial reasoning strategies in geometric problem solving. International Journal of Technology and Design Education, 2018(1), 1-22.
  • Büyüköztürk, Ş. (2015). Data analysis handbook for social sciences (10th edition). Ankara: Pegem Academy Publishing.
  • Chen, X., Dipinto, V., & Newman, M. (2017). Faculty research residency report: teachers’ visual literacy practices in middle and high school science classrooms. NCE Research Residencies, 10(1), 1-32.
  • Clements, D. & Battista, M. (1992). Geometry and spatial reasoning. In D. A. Grows (Ed.), Hand¬book of research on mathematics teaching and learning, 420-464, Toronto: Macmillan.
  • Çakmak, Z. (2013). An investigation of the variables related to 8th grade students' mathematical language skills in statistics through structural equitation model. Published Master's Thesis, Erzincan Üniversity, Institute of Natural and Applied Sciences, Erzincan.
  • Çalışkan, M. (2016). esearching the effects of the instruction of the solid matters assisted with dynamic geometry softwares on the 7th graders' attitudes towards geometry and spatial thinking. Published Master's Thesis, Dokuz Eylül University, Institute of Educational Sciences, İzmir.
  • Çelik, H.C. Bindak, R., & Özdemir, F. (2018). Development of a vısual mathematıcs lıteracy scale and ınvestıgatıon of vısual mathematıcs lıteracy perceptıon accordıng to varıous varıables. In: Yıldız, Karagöz, Yeke, Tarkan, Yazıcı & Onur Hayırlı (Eds), Innovative Approaches in Educatıonal Sciences, December, 2018, Ankara, Turkey, 63-76.
  • Çelik, A. & Özdemir, E.Y. (2011). The relationship between elementary school students’ proportional reasoning skills and problem posing skills ınvolving ratio and proportion. Pamukkale Üniversity Journal of Education Faculty, 30(30), 1-11.
  • Çelik, E.H. & Yılmaz, V. (2013). Structural equation modeling with Lisrel 9.1, Basic concepts- applications- programming (2th edition). Ankara: Anı Publishing.
  • Çetin, H. (2009). A study on the relation between proportional reasoning skills and the successes of solving equation of elementary school secondary stage students. Published Master's Thesis, Selçuk Üniversity, Institute of Natural and Applied Sciences, Konya.
  • Duran, M. (2011). Relationship between visual math literacy self efficacy perceptions with visual mathematic achievements of elementary 7th grade students. Published Master's Thesis, Erzincan Üniversity, Institute of Natural and Applied Sciences, Erzincan.
  • Duran, M. ve Bekdemir, M. (2013). Evaluation of visual math literacy self efficacy perception with wisual mathematics accomplishment. Pegem Journal of Education and Instructıon, 3(3), 27-40.
  • Durmus, S., Toluk, Z. and Olkun, S. (2002). Determining the geometry field knowledge levels of first year students of mathematics teaching, researches and results for the improvement of the levels. V. National Science and Mathematics Education Congress, 16-18 September, Ankara, 28-30.
  • Erdoğan, T. (2006). The Effect of Van hiele model based instruction process on primary candidate teachers' level of readiness towards new geometry subjects. Published Master's Thesis, Abant İzzet Baysal University, Institute of Social Sciences, Bolu.
  • Ev Çimen, E. ve Aygüner, E. (2018). An analysis of eight grade students’ self-efficacy perception of visual mathematics literacy and their actual performance. Elementary Education Online, 17(2), 675-696.
  • Gallant, D.J. (2009). Predictive validity evidence for an assessment program based on the work sampling system in mathematics and language and literacy. Early Childhood Research Quarterly, 24(1), 133–141.
  • Geer, E.A., Quinn, J.M., & Ganley, C.M. (2018). Relations between spatial skills and math performance in elementary school children: A longitudinal investigation. Developmental Psychology, 54(12), 1-22.
  • Güleş, H.K., Akgemci, T. and Türkmen, M. (2011). Strategic production-business performance relationship: an analysis of structural equation modeling. Istanbul University Journal of Econometrics and Statistics, 13(2011), 62-79.
  • Hair, J.F., Anderson, R., Tahtam, R.L., & Black W.C. (1998). Multivariate Data Analysis. Fifth Edition. New Jersey: Prentice-Hall International Inc.
  • Hohenwarter, M. & Preiner, J. (2007). Dynamic mathematics with geogebra. The Journal of Online Mathematics and its Applications, 7(1). 1-21.
  • Hu, L., & Bentler, P.M. (1999). Cut off criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1-55.
  • Authors. (2015). Development of visual mathematics literacy scale towards.
  • Authors. (2019). Investigation of the relationship between visual mathematics literacy perception level, reasoning skill on geometry and performance levels.
  • Authors. (2018). Examination of reasoning skills on geometric shapes.
  • Jadallah, M. (2009). Teacher scaffolding moves and children’s talk in collaborative reasoning discussions. Publishing Doctoral Thesis, University of Illinois, Available from ProQuest Dissertations and Theses database. (UMI Microform 3392077).
  • Jayaram, J., Kannan, V.R., & Tan, K.C. (2004). Influence of initiators on supply chain value creation. International Journal of Production Research, 42(20), 4377-4399.
  • Jöreskog, K.G. & Sörbom, D. (1993). Lisrel 8 user’s reference guide; PRELIS 2 user’s reference guide. Incorporat: Scientific software international.
  • Karadağ, E., Baloglu, N. and Küçük, E. (2010). The effect of perception of manager supervision on teachers' professional motivation level: A path analysis study. Turkish Journal of Educational Sciences, 8(2), 417-437.
  • Karasar, N. (1999). Scientific research methods. Ankara: Nobel Publication Distribution.
  • Keskin, S. (1998). Path coefficients and path analysis. Published Master's Thesis, Ankara University, Institute of Natural and Applied Sciences, Ankara.
  • Kılıç, S. (2015). Statistical Expression. Journal of Mood Disorders, 5(3), 142-150.
  • Kline, R.B. (2011). Principles and Practice of Structural Equation Modeling (3nd Edition ed.). New York: The Guilford Press.
  • Kocakaya, S. (2008). Investigation of relations among the factors that affect physics course achievement of high school students using path analysis technique. Published Doctoral Thesis, Dicle University, Institute of Natural and Applied Sciences, Diyarbakır.
  • Koğar, H. (2015). Investigation of the factors affecting PISA 2012 mathematics literacy with mediation model. Journal of Education and Science, 40(179), 45-55.
  • Konyalıoğlu, A.C. (2003). Investigation of effectiveness of visualization approach on understanding of concepts in vector spaces at the university level. Unpublished doctoral dissertation, Atatürk University, Institute of Natural and Applied Sciences, Erzurum.
  • Kukey, E. (2013). The effects of the mathematics literacy level of the secondary school 8th grade students to mathematics achievement. Published Master's Thesis, Fırat University, Institute of Educational Sciences, Elazığ.
  • Kurtz, K.J., Gentner, D., & Gunn, V. (1999). Reasoning. San Diego: Hanbook of perception and cognition.
  • Kyttälä, M., & Lehto, J.E. (2008). Some factors underlying mathematical performance: The role of visuospatial working memory and non-verbal intelligence. European Journal of Psychology of Education, 23(1), 77-94.
  • Kyttälä, M. & Björn, P.M. (2014). The role of literacy skills in adolescents’ mathematics word problem performance: Controlling for visuo-spatial ability and mathematics anxiety. Learning and Individual Differences, 29(1), 59–66.
  • Loehlin, J.C.(2004). Latent variable models: an introduction to factor, path, and structural analysis. Mahwah, NJ: Lawrence Erlbaum Associates.
  • Meaney, T. (2007). Weighing up the ınfluence of context on judgements of mathematical literacy. International Journal of Science and Mathematics Education, 5(1), 681-704.
  • Ministry of National Education [MoNE] (2005). Elementary mathematics lesson 1-8. classes curriculum. Ankara: Board of Education and Training.
  • Ministry of National Education [MoNE] (2009). Secondary mathematics lesson 5-8. classes curriculum. Ankara: Board of Education and Training.
  • Ministry of National Education [MoNE] (2011). Secondary mathematics lesson 5-8. classes curriculum. Ankara: Board of Education and Training.
  • Ministry of National Education [MoNE] (2013). Secondary mathematics lesson 5-8. classes curriculum. Ankara: Board of Education and Training.
  • Ministry of National Education [MoNE] (2017). Board of education and training, mathematics teacher special field competencies. Retrieved from http://otmg.meb.gov.tr/alanmatematik.html at 02.04.2017.
  • Ministry of National Education [MoNE] (2018). Primary and secondary school mathematics 1-8. classes curriculum. Ankara: Board of Education and Training.
  • Oaksford, M. (2005). Reasoning. In Nick Brais by & Angus Gellatly, Cognitive psychology. New York: Oxford University Press Inc.
  • Olkun, S. (2003). Making Connections: ımproving spatial abilities with engineering drawing activities. International Journal of Mathematics Teaching and Learning, Aprıl(1), 1-10.
  • Özdemir, F., Duran, M. ve Kaplan, A. (2015). Investigation of middle school students’ self-efficacy perceptions of visual mathematics literacy and perceptions of problem-solving skill. Journal of Theoretical Educational Science, 9(4), 532-554.
  • Özsoy, G. (2005). The relationship between problem solving skills and mathematical achievement. Journal of Gazi University Education Faculty, 25(3), 179-190.
  • Pajares, F. & Kranzler, J. (1995). Self-efficacy beliefs and general mental ability in mathematical problem-solving. Contemporary Educational Psychology, 20(1), 426-443.
  • Paksu, A.D. (2013). Investıgatıon of preservıce elementary teachers' abılıtıes on drawıng geometrıc constructıon. Kastamonu Education Journal, 21(3), 827-840.
  • Pellegrino, J.W., Alderton, D.L. & Shute, V.J. (1984). Understandings patialability. Educational Psychologist, 19(3), 239-253.
  • Rapp, W.H. (2009). Avoiding math taboos: effective math strategies for visual-spatial learners. Journal of Teachıng Exceptional Children Plus, 6(2), 2-12.
  • Schermelleh E.K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Test of significance and descriptive goodness of fit measures. Methods of Psychological Research Online, 8(2), 23-74.
  • Suhr, D. (2008). Step your way through path analysis. Western Users of SAS Software Conference Proceedings. 15.08.2017. Retrieved from, www.wuss.org/ proceedings 08/08WUSS%20Proceedings/papers/pos/pos04.pdf.
  • Şahin, Y. (2012). An investigation on geometric reasoning of pre-service elementary mathematics teachers in terms of some variables. Published Master's Thesis, Hacettepe University, Institute of Educational Sciences, Ankara.
  • Umay, A. Duatepe, A. and Akkus, Cıkla, O. (2005). Readiness levels for new mathematical content in the curriculum of primary teacher candidates. XIV. National Educational Sciences Congress Pamukkale University, Faculty of Education, 28-30 September, Denizli, 456-458.
  • Webb, N.L. (1993). Assesment for the mathematics clasroom. Reston, VA: NCTM.
  • Yore, L.D., Pimm, D., & Tuan, H.L. (2007). The literacy component of mathematical and scientific literacy. International Journal of Science and Mathematics Education, 5(1), 559-589.

Analysis of the Correlations Between Visual Mathematics Literacy Perceptions, Reasoning Skills on Geometric Shapes and Geometry Performances of Pre-Service Mathematics Teachers

Yıl 2021, Cilt: 8 Sayı: 1, 90 - 108, 01.01.2021
https://doi.org/10.17275/per.21.5.8.1

Öz

In the study, the correlations between visual mathematics literacy perceptions, reasoning skills on geometrical shapes and geometrical performances of pre-service mathematics teachers were investigated. The study participants included 384 pre-service mathematics teachers, who were attending education departments in two universities located in Eastern and Southeastern Anatolia regions in Turkey. In the study, due to time and workforce limitations, convenience sampling method was preferred, and relational screening model was adopted. The study data was collected with visual mathematics literacy perception scale, reasoning skills on geometric shapes and geometry performance tests developed by the authors. Analysis of the correlation between the variables demonstrated that there was a moderate correlation between visual mathematics literacy perception and both the reasoning skills on geometrical shapes and the geometry performance, and there was a high correlation between the reasoning skills on geometric shapes and geometry performance. Primary model path analysis demonstrated that visual mathematics literacy perception had a moderate effect on reasoning skills on geometrical shapes and geometry performance. It was also determined that reasoning skills on geometric shapes had a strong effect on geometry performance. The findings of the path analysis conducted on the sub-dimensions revealed that all sub-dimensions had a moderate positive effect on reasoning skills on geometric shapes. It was also found that visual mathematics literacy perception had a moderate positive effect on visual perception, geometry knowledge, spatial intelligence and concretization sub-dimensions and geometry performance.

Kaynakça

  • Açıkbaş, N. (2002). The Relationship between mathematics performance, attitudes toward mathematics, grade level and gender. Published Master's Thesis, Boğaziçi University, Institute of Natural and Applied Sciences, İstanbul.
  • Akyüz, G. ve Pala, N.M. (2010). The Effect of Student and Class Characteristics on Mathematics Literacy and Problem Solving in PISA 2003. Elementary Education Online, 9(2), 668-678.
  • Alpan, G. (2008). Vısual lıteracy and ınstructıonal technology. Yüzüncü Yıl University Journal of Education Faculty, 5(1), 74-102.
  • Amsterlaw, J.A. (2004). Development of children’s beliefs about everyday reasoning. Publishing Doctoral Thesis, University of Michigan. Available from ProQuest Dissertations and Theses database, (UMI Microform 3138102).
  • Areepattamannil, S. (2014). International Note: What factors are associated with reading, mathematics and science literacy of Indian adolescents? A multilevel examination. Journal of Adolescence, 37(2014), 367–372.
  • Baki, A. (2001). Evaluation of mathematics education in the light of information technology. Journal of Ministry of National Education, 149(1), 26-31.
  • Bal A.P. (2012). Primary school students’ views and challenges on performance task preparation process in mathematics course. Pegem Journal of Education and Instructıon, 2(1), 11-23.
  • Bates, A.B. & Latham, N. (2009). Linking preservice teachers’ mathematics self-efficacy and mathematics teaching efficacy to their mathematical performance. School Science and Mathematics, 109(7), 325-333.
  • Battista, M.T. (1994). On Greene’s Environmental/model view of conceptual domains: A spatial/geometric perspective. Journal for Research in Mathematics Education, 25(1), 86-99.
  • Baykul, Y. (2014). Teaching Mathematics in Primary School (12th Edition). Ankara: Pegem Akademy Publishing.
  • Bekdemir M. ve Duran, M. (2012). Development of a vısual math lıteracy self effıcacy perceptıon scale (VMLSEPS) for elementary students. On Dokuz Mayıs Üniversity Journal of Education Faculty, 31(1), 89-115.
  • Bentler, P.M. & Chou, C.P. (1987). Practical issues in structural modeling. Sociological Methods & Research, 16(1), 78-117.
  • Bollen, K.A. (1989). Structural equations with latent variable. Newyork: Wiley Publisher.
  • Brown, T.A. (2006). Confirmatory faktor analysis for applied research. Newyork: The Guilford press.
  • Buckley, J., Seery, N., & Canty, D. (2018). Investigating the use of spatial reasoning strategies in geometric problem solving. International Journal of Technology and Design Education, 2018(1), 1-22.
  • Büyüköztürk, Ş. (2015). Data analysis handbook for social sciences (10th edition). Ankara: Pegem Academy Publishing.
  • Chen, X., Dipinto, V., & Newman, M. (2017). Faculty research residency report: teachers’ visual literacy practices in middle and high school science classrooms. NCE Research Residencies, 10(1), 1-32.
  • Clements, D. & Battista, M. (1992). Geometry and spatial reasoning. In D. A. Grows (Ed.), Hand¬book of research on mathematics teaching and learning, 420-464, Toronto: Macmillan.
  • Çakmak, Z. (2013). An investigation of the variables related to 8th grade students' mathematical language skills in statistics through structural equitation model. Published Master's Thesis, Erzincan Üniversity, Institute of Natural and Applied Sciences, Erzincan.
  • Çalışkan, M. (2016). esearching the effects of the instruction of the solid matters assisted with dynamic geometry softwares on the 7th graders' attitudes towards geometry and spatial thinking. Published Master's Thesis, Dokuz Eylül University, Institute of Educational Sciences, İzmir.
  • Çelik, H.C. Bindak, R., & Özdemir, F. (2018). Development of a vısual mathematıcs lıteracy scale and ınvestıgatıon of vısual mathematıcs lıteracy perceptıon accordıng to varıous varıables. In: Yıldız, Karagöz, Yeke, Tarkan, Yazıcı & Onur Hayırlı (Eds), Innovative Approaches in Educatıonal Sciences, December, 2018, Ankara, Turkey, 63-76.
  • Çelik, A. & Özdemir, E.Y. (2011). The relationship between elementary school students’ proportional reasoning skills and problem posing skills ınvolving ratio and proportion. Pamukkale Üniversity Journal of Education Faculty, 30(30), 1-11.
  • Çelik, E.H. & Yılmaz, V. (2013). Structural equation modeling with Lisrel 9.1, Basic concepts- applications- programming (2th edition). Ankara: Anı Publishing.
  • Çetin, H. (2009). A study on the relation between proportional reasoning skills and the successes of solving equation of elementary school secondary stage students. Published Master's Thesis, Selçuk Üniversity, Institute of Natural and Applied Sciences, Konya.
  • Duran, M. (2011). Relationship between visual math literacy self efficacy perceptions with visual mathematic achievements of elementary 7th grade students. Published Master's Thesis, Erzincan Üniversity, Institute of Natural and Applied Sciences, Erzincan.
  • Duran, M. ve Bekdemir, M. (2013). Evaluation of visual math literacy self efficacy perception with wisual mathematics accomplishment. Pegem Journal of Education and Instructıon, 3(3), 27-40.
  • Durmus, S., Toluk, Z. and Olkun, S. (2002). Determining the geometry field knowledge levels of first year students of mathematics teaching, researches and results for the improvement of the levels. V. National Science and Mathematics Education Congress, 16-18 September, Ankara, 28-30.
  • Erdoğan, T. (2006). The Effect of Van hiele model based instruction process on primary candidate teachers' level of readiness towards new geometry subjects. Published Master's Thesis, Abant İzzet Baysal University, Institute of Social Sciences, Bolu.
  • Ev Çimen, E. ve Aygüner, E. (2018). An analysis of eight grade students’ self-efficacy perception of visual mathematics literacy and their actual performance. Elementary Education Online, 17(2), 675-696.
  • Gallant, D.J. (2009). Predictive validity evidence for an assessment program based on the work sampling system in mathematics and language and literacy. Early Childhood Research Quarterly, 24(1), 133–141.
  • Geer, E.A., Quinn, J.M., & Ganley, C.M. (2018). Relations between spatial skills and math performance in elementary school children: A longitudinal investigation. Developmental Psychology, 54(12), 1-22.
  • Güleş, H.K., Akgemci, T. and Türkmen, M. (2011). Strategic production-business performance relationship: an analysis of structural equation modeling. Istanbul University Journal of Econometrics and Statistics, 13(2011), 62-79.
  • Hair, J.F., Anderson, R., Tahtam, R.L., & Black W.C. (1998). Multivariate Data Analysis. Fifth Edition. New Jersey: Prentice-Hall International Inc.
  • Hohenwarter, M. & Preiner, J. (2007). Dynamic mathematics with geogebra. The Journal of Online Mathematics and its Applications, 7(1). 1-21.
  • Hu, L., & Bentler, P.M. (1999). Cut off criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1-55.
  • Authors. (2015). Development of visual mathematics literacy scale towards.
  • Authors. (2019). Investigation of the relationship between visual mathematics literacy perception level, reasoning skill on geometry and performance levels.
  • Authors. (2018). Examination of reasoning skills on geometric shapes.
  • Jadallah, M. (2009). Teacher scaffolding moves and children’s talk in collaborative reasoning discussions. Publishing Doctoral Thesis, University of Illinois, Available from ProQuest Dissertations and Theses database. (UMI Microform 3392077).
  • Jayaram, J., Kannan, V.R., & Tan, K.C. (2004). Influence of initiators on supply chain value creation. International Journal of Production Research, 42(20), 4377-4399.
  • Jöreskog, K.G. & Sörbom, D. (1993). Lisrel 8 user’s reference guide; PRELIS 2 user’s reference guide. Incorporat: Scientific software international.
  • Karadağ, E., Baloglu, N. and Küçük, E. (2010). The effect of perception of manager supervision on teachers' professional motivation level: A path analysis study. Turkish Journal of Educational Sciences, 8(2), 417-437.
  • Karasar, N. (1999). Scientific research methods. Ankara: Nobel Publication Distribution.
  • Keskin, S. (1998). Path coefficients and path analysis. Published Master's Thesis, Ankara University, Institute of Natural and Applied Sciences, Ankara.
  • Kılıç, S. (2015). Statistical Expression. Journal of Mood Disorders, 5(3), 142-150.
  • Kline, R.B. (2011). Principles and Practice of Structural Equation Modeling (3nd Edition ed.). New York: The Guilford Press.
  • Kocakaya, S. (2008). Investigation of relations among the factors that affect physics course achievement of high school students using path analysis technique. Published Doctoral Thesis, Dicle University, Institute of Natural and Applied Sciences, Diyarbakır.
  • Koğar, H. (2015). Investigation of the factors affecting PISA 2012 mathematics literacy with mediation model. Journal of Education and Science, 40(179), 45-55.
  • Konyalıoğlu, A.C. (2003). Investigation of effectiveness of visualization approach on understanding of concepts in vector spaces at the university level. Unpublished doctoral dissertation, Atatürk University, Institute of Natural and Applied Sciences, Erzurum.
  • Kukey, E. (2013). The effects of the mathematics literacy level of the secondary school 8th grade students to mathematics achievement. Published Master's Thesis, Fırat University, Institute of Educational Sciences, Elazığ.
  • Kurtz, K.J., Gentner, D., & Gunn, V. (1999). Reasoning. San Diego: Hanbook of perception and cognition.
  • Kyttälä, M., & Lehto, J.E. (2008). Some factors underlying mathematical performance: The role of visuospatial working memory and non-verbal intelligence. European Journal of Psychology of Education, 23(1), 77-94.
  • Kyttälä, M. & Björn, P.M. (2014). The role of literacy skills in adolescents’ mathematics word problem performance: Controlling for visuo-spatial ability and mathematics anxiety. Learning and Individual Differences, 29(1), 59–66.
  • Loehlin, J.C.(2004). Latent variable models: an introduction to factor, path, and structural analysis. Mahwah, NJ: Lawrence Erlbaum Associates.
  • Meaney, T. (2007). Weighing up the ınfluence of context on judgements of mathematical literacy. International Journal of Science and Mathematics Education, 5(1), 681-704.
  • Ministry of National Education [MoNE] (2005). Elementary mathematics lesson 1-8. classes curriculum. Ankara: Board of Education and Training.
  • Ministry of National Education [MoNE] (2009). Secondary mathematics lesson 5-8. classes curriculum. Ankara: Board of Education and Training.
  • Ministry of National Education [MoNE] (2011). Secondary mathematics lesson 5-8. classes curriculum. Ankara: Board of Education and Training.
  • Ministry of National Education [MoNE] (2013). Secondary mathematics lesson 5-8. classes curriculum. Ankara: Board of Education and Training.
  • Ministry of National Education [MoNE] (2017). Board of education and training, mathematics teacher special field competencies. Retrieved from http://otmg.meb.gov.tr/alanmatematik.html at 02.04.2017.
  • Ministry of National Education [MoNE] (2018). Primary and secondary school mathematics 1-8. classes curriculum. Ankara: Board of Education and Training.
  • Oaksford, M. (2005). Reasoning. In Nick Brais by & Angus Gellatly, Cognitive psychology. New York: Oxford University Press Inc.
  • Olkun, S. (2003). Making Connections: ımproving spatial abilities with engineering drawing activities. International Journal of Mathematics Teaching and Learning, Aprıl(1), 1-10.
  • Özdemir, F., Duran, M. ve Kaplan, A. (2015). Investigation of middle school students’ self-efficacy perceptions of visual mathematics literacy and perceptions of problem-solving skill. Journal of Theoretical Educational Science, 9(4), 532-554.
  • Özsoy, G. (2005). The relationship between problem solving skills and mathematical achievement. Journal of Gazi University Education Faculty, 25(3), 179-190.
  • Pajares, F. & Kranzler, J. (1995). Self-efficacy beliefs and general mental ability in mathematical problem-solving. Contemporary Educational Psychology, 20(1), 426-443.
  • Paksu, A.D. (2013). Investıgatıon of preservıce elementary teachers' abılıtıes on drawıng geometrıc constructıon. Kastamonu Education Journal, 21(3), 827-840.
  • Pellegrino, J.W., Alderton, D.L. & Shute, V.J. (1984). Understandings patialability. Educational Psychologist, 19(3), 239-253.
  • Rapp, W.H. (2009). Avoiding math taboos: effective math strategies for visual-spatial learners. Journal of Teachıng Exceptional Children Plus, 6(2), 2-12.
  • Schermelleh E.K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Test of significance and descriptive goodness of fit measures. Methods of Psychological Research Online, 8(2), 23-74.
  • Suhr, D. (2008). Step your way through path analysis. Western Users of SAS Software Conference Proceedings. 15.08.2017. Retrieved from, www.wuss.org/ proceedings 08/08WUSS%20Proceedings/papers/pos/pos04.pdf.
  • Şahin, Y. (2012). An investigation on geometric reasoning of pre-service elementary mathematics teachers in terms of some variables. Published Master's Thesis, Hacettepe University, Institute of Educational Sciences, Ankara.
  • Umay, A. Duatepe, A. and Akkus, Cıkla, O. (2005). Readiness levels for new mathematical content in the curriculum of primary teacher candidates. XIV. National Educational Sciences Congress Pamukkale University, Faculty of Education, 28-30 September, Denizli, 456-458.
  • Webb, N.L. (1993). Assesment for the mathematics clasroom. Reston, VA: NCTM.
  • Yore, L.D., Pimm, D., & Tuan, H.L. (2007). The literacy component of mathematical and scientific literacy. International Journal of Science and Mathematics Education, 5(1), 559-589.
Toplam 75 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Alan Eğitimleri
Bölüm Research Articles
Yazarlar

Aziz İlhan 0000-0001-7049-5756

Recep Aslaner 0000-0003-1037-6100

Yayımlanma Tarihi 1 Ocak 2021
Kabul Tarihi 15 Eylül 2020
Yayımlandığı Sayı Yıl 2021 Cilt: 8 Sayı: 1

Kaynak Göster

APA İlhan, A., & Aslaner, R. (2021). Analysis of the Correlations Between Visual Mathematics Literacy Perceptions, Reasoning Skills on Geometric Shapes and Geometry Performances of Pre-Service Mathematics Teachers. Participatory Educational Research, 8(1), 90-108. https://doi.org/10.17275/per.21.5.8.1