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Proje Tabanlı Öğrenmenin Öğrencilerin Merkezi Eğilim Ve Yayılım Ölçülerine Yönelik İstatistiksel Okuryazarlık Seviyelerine Etkisi

Year 2015, Volume: 23 Issue: 2, 773 - 796, 15.05.2015

Abstract

Bu çalışma ile proje tabanlı öğrenme yaklaşımının öğrencilerin merkezi eğilim ve yayılım ölçülerine yönelik istatistiksel okuryazarlık seviyelerine etkisinin ortaya çıkarılması amaçlanmıştır. Yarı deneysel çalışma yönteminin benimsendiği çalışmada, deney grubunda proje tabanlı öğrenme, kontrol grubunda ise geleneksel yaklaşım etkinlikleri yürütülmüştür. Geliştirilen veri toplama aracı gruplara uygulama öncesi ve uygulama sonrası uygulanmıştır. Elde edilen ham puanlar Rasch analizi yapan bir program ile lineer puanlara dönüştürülmüştür. Bu lineer puanlar ile ANCOVA analizi yapılmıştır. Uygulama öncesi ve sonrası istatistiksel okuryazarlık seviyeleri kişi madde haritaları ile ortaya konmuştur. Ayrıca deney grubunda yapılan mülakatlar nitel olarak değerlendirilmiştir. Elde edilen bulgulara göre proje tabanlı öğrenme yaklaşımının öğrencilerin merkezi eğilim ve yayılım ölçülerine yönelik istatistiksel okuryazarlık seviyelerini arttırdığı sonucuna varılmıştır.

References

  • Australian Education Council (1991). A national statement on mathematics for Australian schools. Melbourne: Author.
  • Australian Education Council., (1994). Mathematics: A curriculum profile for Australian schools. Carlton, Victoria: Curriculum Corporation.
  • Biggs, J., Collis, K. (1982). Evaluating the quality of learning: The SOLO taxonomy. New York, NY: Academic Press.
  • Bond, T. G., Fox, C. M. (2007). Applying the Rasch model: Fundamental measurement in the human sciences (2nd ed.). Mahwah, NJ: Lawrence Erlbaum.
  • Bryce, G. R. (2005). Developing tomorrow’s statistician. Journal of Statistics Education, 13(1). http://www.amstat.org/publications/jse/v13n1/bryce.html
  • Callingham, R. & Watson, J. M. (2005). Measuring statistical literacy. Journal of Applied Measurement, 6 (1), 29, 19–47.
  • Capel, A.D. (1885). Catch guestions in aritmetic mensuretion and how to solve them. London: Joseph Hughes.
  • Carnell, L.J. (2008). The effect of a student-designed data collection project on attitudes to- wards statistics. Journal of Statistics Education, 16(1).
  • Cook, C.M.A. (1998). Designing a first experiment: A project for design of experiment cour- ses. The American Statistician, 52(4), 338–342.
  • Elhan A. H, Atakurt Y. (2005). Ölçeklerin değerlendirilmesinde niçin Rasch analizi kullanıl- malıdır? Ankara Üniversitesi Tıp Fakültesi Mecmuası 2005; 58, 47–50
  • Gal, I. (2004). Adult’s statistical literacy: Meaning, components, responsibilities In D. Ben- Zvi & J. Garfield (Eds ), The challenge of developing statistical literacy, reasoning, and thinking, 47–78. Dordrecht: Kluwer
  • Gal, I. (2002). Adult statistical literacy: Meanings, components, responsibilities. International Statistical Review, 70(1), 1–25.
  • GAISE (2005). Guidelines for assessment and instruction in statistics education (GAISE) re- port: A curriculum framework for PreK–12 statistics education. The American Statistical Association (ASA). http://www.amstat.org/education/gaise/
  • Garfield, J. (1995). How students learn statistics. International Statistical Review, 63(1). 25–34.
  • Garfield, J. ve Gal, I. (1999). Assessment and statistics education: Current challenges and directions. International Statistical Review, 67(1), 1–12.
  • Garfield, J., Ben-Zvi, D. (2007). Developing Students’ Statistical Reasoning: Connecting Re- search and Teaching Practice. Emeryville, CA: Key College Publishing.
  • Izard, J., Haines, C., Crouch, R., Houston, S., Neill, N. (2003). Assessing the impact of the teaching of modelling: Some implications. In S. Lamon, W. Parker, K. Houston (Eds.), Mathematical Modelling: A Way of
  • Kaynar Y., Halat, E. (2012). İlköğretim II.. Kademe Matematik Öğretim Programının “Ola- sılık ve İstatistik” Alt
  • Öğrenme Alanının “İstatitik” Boyutunun İncelenmesi X. Fen Bilimleri ve Matematik Eğitimi Kongresi, Niğde
  • Konold, C., Pollatsek, A. (2002). Data analysis as the search for signals in noisy processes Journal for Research in Mathematics Education. 33(4), 259-289.
  • Koparan, T., Güven, B. (2013). Proje Tabanlı Öğrenme Yaklaşımının Öğrencilerinin Örnek- lem Kavramına Yönelik İstatistiksel Okuryazarlık Seviyelerine Etkisi. Eğitim Araştırma- ları Dergisi, 2(1), 185–196.
  • Lehohla, P. (2002). Promoting Statistical literacy: a South African perspective. In B. Phil- lips (Ed.). Proceedings of the sixth International Conference on Teaching Statistics, Cape Town, South Africa. International Statistical Institute and International Association for statistics Education
  • Linacre, J.M. (2011). A user’s guide to WINSTEPS: Rasch model computer programs. MESA Pres: Chicago. http://www.winsteps.com/
  • Misailidou, C., Williams, J. (2003). Diagnostic assessment of children’s proportional reaso- ning. Journal of Mathematical Behaviour, 22, 335–368.
  • Mokros, J., Russell, S. (1995). Children’s Concepts of Average and Representativeness, Jour- nal for Research in Mathematics Education, 26, 20-39.
  • Moore, D. S. and McCabe, G. P. (1993).Introduction to the Practice of Statistics, Second Edition. Freeman, 794–795.
  • National Council of Teachers of Mathematics (2000). Principles and standards for school mathematics. http://standards.nctm.org.
  • Randall, G. (2006). An Exploration of Students’ Statistical Thinking. Teaching Statistics, 28(1), 17-21.
  • Roberts, H. V. (1992), “Student-Conducted Projects in Introductory Statistics Courses,” in Statistics for the Twenty-First Century, eds. Florence Gordon and Sheldon Gordon, MAA Notes No. 26, Washington, DC: Mathematical Association of America, 109–121.
  • Uçar, T. Z. ve Akdoğan, N. E. (2009). İlköğretim 6-8. Sınıf Öğrencilerinin Ortalama Kavra- mına Yüklediği Anlamlar, İlköğretim Online, 8(2), 391-400, Erişim: 5 Mayıs 2012, http:// ilkogretim-online.org.tr
  • Wallman, K.K. (1993). Enhancing statistical literacy: Enriching our society. Journal of the American Statistical Association, 88(421), 1–8.
  • Watson, J. M. (1997). Assessing statistical literacy using the media. In I. Gal & J. B. Garfield (Eds.), The assessment challenge in statistics education. 107–121. Amsterdam, The Net- herlands: IOS Press & The International Statistical Institute.
  • Watson, J.M., Callingham, R. (2003) Statistical literacy: A complex hierarchical construct Statistics Education Research Journal, 2, 3-46
  • Watson, J., Kelly, B., Izard, J. (2004). Student change in understanding of statistical variation after instruction and after two years: An application of Rasch analysis. Refereed paper presented at the AARE Conference, Melbourne, Vic http://www.aare.edu.au (search code WAT04867)
  • Watson J.M. (2006). Statistical Literacy at School, Growth and Goal. Lawrence Erlbaum Assocıates, Publishers. Londan. 27–53.
  • Yıldırım, H. H. (2006). The Differential Item Functioning (DIF) Analysis of Mathematics Items in the International assessment Programs. YayLmlanmamLK Doktora Tezi, Orta Do u Teknik Üniversitesi, Ankara.

The Effect Of Project Based Learning On The Statistical Literacy Levels: Central Tendency And Dispersion Measures

Year 2015, Volume: 23 Issue: 2, 773 - 796, 15.05.2015

Abstract

This study investigates the effect of project based learning approach on students’ statistical literacy levels towards central tendency and dispersion measures. Quasi-experimental research model was used. A test was developed and applied as pre and post-tests. The data were analysed using Rasch (1980) model. All raw scores transformed lineer scores by Winsteps 3.72 and ANCOVA analysis is used. Person item maps were produced and study supplemented with qualitative data. The results of the study revealed that the project based learning increased students’ statistical literacy levels towards central tendency and dispersion measures in the intervention group.

References

  • Australian Education Council (1991). A national statement on mathematics for Australian schools. Melbourne: Author.
  • Australian Education Council., (1994). Mathematics: A curriculum profile for Australian schools. Carlton, Victoria: Curriculum Corporation.
  • Biggs, J., Collis, K. (1982). Evaluating the quality of learning: The SOLO taxonomy. New York, NY: Academic Press.
  • Bond, T. G., Fox, C. M. (2007). Applying the Rasch model: Fundamental measurement in the human sciences (2nd ed.). Mahwah, NJ: Lawrence Erlbaum.
  • Bryce, G. R. (2005). Developing tomorrow’s statistician. Journal of Statistics Education, 13(1). http://www.amstat.org/publications/jse/v13n1/bryce.html
  • Callingham, R. & Watson, J. M. (2005). Measuring statistical literacy. Journal of Applied Measurement, 6 (1), 29, 19–47.
  • Capel, A.D. (1885). Catch guestions in aritmetic mensuretion and how to solve them. London: Joseph Hughes.
  • Carnell, L.J. (2008). The effect of a student-designed data collection project on attitudes to- wards statistics. Journal of Statistics Education, 16(1).
  • Cook, C.M.A. (1998). Designing a first experiment: A project for design of experiment cour- ses. The American Statistician, 52(4), 338–342.
  • Elhan A. H, Atakurt Y. (2005). Ölçeklerin değerlendirilmesinde niçin Rasch analizi kullanıl- malıdır? Ankara Üniversitesi Tıp Fakültesi Mecmuası 2005; 58, 47–50
  • Gal, I. (2004). Adult’s statistical literacy: Meaning, components, responsibilities In D. Ben- Zvi & J. Garfield (Eds ), The challenge of developing statistical literacy, reasoning, and thinking, 47–78. Dordrecht: Kluwer
  • Gal, I. (2002). Adult statistical literacy: Meanings, components, responsibilities. International Statistical Review, 70(1), 1–25.
  • GAISE (2005). Guidelines for assessment and instruction in statistics education (GAISE) re- port: A curriculum framework for PreK–12 statistics education. The American Statistical Association (ASA). http://www.amstat.org/education/gaise/
  • Garfield, J. (1995). How students learn statistics. International Statistical Review, 63(1). 25–34.
  • Garfield, J. ve Gal, I. (1999). Assessment and statistics education: Current challenges and directions. International Statistical Review, 67(1), 1–12.
  • Garfield, J., Ben-Zvi, D. (2007). Developing Students’ Statistical Reasoning: Connecting Re- search and Teaching Practice. Emeryville, CA: Key College Publishing.
  • Izard, J., Haines, C., Crouch, R., Houston, S., Neill, N. (2003). Assessing the impact of the teaching of modelling: Some implications. In S. Lamon, W. Parker, K. Houston (Eds.), Mathematical Modelling: A Way of
  • Kaynar Y., Halat, E. (2012). İlköğretim II.. Kademe Matematik Öğretim Programının “Ola- sılık ve İstatistik” Alt
  • Öğrenme Alanının “İstatitik” Boyutunun İncelenmesi X. Fen Bilimleri ve Matematik Eğitimi Kongresi, Niğde
  • Konold, C., Pollatsek, A. (2002). Data analysis as the search for signals in noisy processes Journal for Research in Mathematics Education. 33(4), 259-289.
  • Koparan, T., Güven, B. (2013). Proje Tabanlı Öğrenme Yaklaşımının Öğrencilerinin Örnek- lem Kavramına Yönelik İstatistiksel Okuryazarlık Seviyelerine Etkisi. Eğitim Araştırma- ları Dergisi, 2(1), 185–196.
  • Lehohla, P. (2002). Promoting Statistical literacy: a South African perspective. In B. Phil- lips (Ed.). Proceedings of the sixth International Conference on Teaching Statistics, Cape Town, South Africa. International Statistical Institute and International Association for statistics Education
  • Linacre, J.M. (2011). A user’s guide to WINSTEPS: Rasch model computer programs. MESA Pres: Chicago. http://www.winsteps.com/
  • Misailidou, C., Williams, J. (2003). Diagnostic assessment of children’s proportional reaso- ning. Journal of Mathematical Behaviour, 22, 335–368.
  • Mokros, J., Russell, S. (1995). Children’s Concepts of Average and Representativeness, Jour- nal for Research in Mathematics Education, 26, 20-39.
  • Moore, D. S. and McCabe, G. P. (1993).Introduction to the Practice of Statistics, Second Edition. Freeman, 794–795.
  • National Council of Teachers of Mathematics (2000). Principles and standards for school mathematics. http://standards.nctm.org.
  • Randall, G. (2006). An Exploration of Students’ Statistical Thinking. Teaching Statistics, 28(1), 17-21.
  • Roberts, H. V. (1992), “Student-Conducted Projects in Introductory Statistics Courses,” in Statistics for the Twenty-First Century, eds. Florence Gordon and Sheldon Gordon, MAA Notes No. 26, Washington, DC: Mathematical Association of America, 109–121.
  • Uçar, T. Z. ve Akdoğan, N. E. (2009). İlköğretim 6-8. Sınıf Öğrencilerinin Ortalama Kavra- mına Yüklediği Anlamlar, İlköğretim Online, 8(2), 391-400, Erişim: 5 Mayıs 2012, http:// ilkogretim-online.org.tr
  • Wallman, K.K. (1993). Enhancing statistical literacy: Enriching our society. Journal of the American Statistical Association, 88(421), 1–8.
  • Watson, J. M. (1997). Assessing statistical literacy using the media. In I. Gal & J. B. Garfield (Eds.), The assessment challenge in statistics education. 107–121. Amsterdam, The Net- herlands: IOS Press & The International Statistical Institute.
  • Watson, J.M., Callingham, R. (2003) Statistical literacy: A complex hierarchical construct Statistics Education Research Journal, 2, 3-46
  • Watson, J., Kelly, B., Izard, J. (2004). Student change in understanding of statistical variation after instruction and after two years: An application of Rasch analysis. Refereed paper presented at the AARE Conference, Melbourne, Vic http://www.aare.edu.au (search code WAT04867)
  • Watson J.M. (2006). Statistical Literacy at School, Growth and Goal. Lawrence Erlbaum Assocıates, Publishers. Londan. 27–53.
  • Yıldırım, H. H. (2006). The Differential Item Functioning (DIF) Analysis of Mathematics Items in the International assessment Programs. YayLmlanmamLK Doktora Tezi, Orta Do u Teknik Üniversitesi, Ankara.
There are 36 citations in total.

Details

Other ID JA43DY73PY
Journal Section Review Article
Authors

Timur Koparan This is me

Bülent Güven This is me

Publication Date May 15, 2015
Published in Issue Year 2015 Volume: 23 Issue: 2

Cite

APA Koparan, T., & Güven, B. (2015). The Effect Of Project Based Learning On The Statistical Literacy Levels: Central Tendency And Dispersion Measures. Kastamonu Education Journal, 23(2), 773-796.

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