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Investigating the Effect of Online Learning Tools on the 9th Grade Students Attitudes Towards Statistics

Year 2021, Volume: 10 Issue: 4, 1625 - 1667, 30.12.2021

Nur Esra Sevimli , Eyüp Sevimli , Emin Aydın

https://doi.org/10.30703/cije.892802

Abstract

It has been stated that it is important for students to have statistical thinking competence in mathematics curricula, and it has been suggested that current technologies be widely used in the teaching of statistics subjects by emphasizing technology literacy. It is important to determine the difference between online platforms developed for statistics education from current technologies for understanding classroom learning practices. In this study, the effect of using online learning tools in teaching statistics subjects was examined on students' attitudes towards statistics, by comparing current teaching contents. Participants of the study are 56 students studying in the ninth grade. The study was designed according to the quasi-experimental design, and the teaching of the "data" subject was carried out in the experimental group through activities prepared with the online learning tool, and in the control group, based on the current curriculum and the teaching activities included in the textbook. The Statistical Attitude Scale was applied to the experimental and control groups as a pre-post-retention test. In addition, student diaries were used to examine the teaching process in more detail. The Scale and diary data were analyzed using predictive and descriptive statistics. The results of the study showed that there was a statistically significant difference in favor of the experimental group between the attitude scale post-test mean scores of the experimental and control groups. As a result of the intergroup comparison, it was determined that there were statistically significant differences between the pre-post test scores of the students in both the experimental and control groups, but retention was achieved in the experimental group. The findings obtained from the student diaries showed that the students had a positive opinion about the use of online learning tools in teaching statistics subjects. As a result of the study, content development and training of tutors’ studies have been suggested so that current technologies can be used in statistics education.

Keywords

Statistics attitude online learning tool activity high school mathematics

References

  • Anastasiadou, S. D. (2011). Reliability and validity testing of a new scale for measuring attitudes toward learning statistics with technology. Acta Didactica Napocensia, 4(1), 1-10.
  • Avcı, E. and Coşkuntuncel, O. (2019). Middle school teachers’ opinions about using Vustat and Tinkerplots in the data processing in middle school mathematics. Pegem Eğitim ve Öğretim Dergisi, 9(1), 01-36. http://dx.doi.org/10.14527/pegegog.2019.00
  • Azmy, C. (2019). Secondary mathematics preservice teacher development of statistics teaching self-efficacy. Unpublished PhD dissertation, North Carolina State University, USA.
  • Ben-Zvi, D., Bakker, A. and Makar, K. (2015). Learning to reason from samples. Educational Studies in Mathematic, 88(3), 291-312. https://doi.org/10.1007/s10649-015-9593-3
  • Biehler, R., Ben-Zvi, D., Bakker, A. and Makar, K. (2013). Technological advances in developing statistical reasoning at the school level. In Bishop, A., Clement, K., Keitel, C., Kilpatrick, J., veLeung, A. Y. L. (Eds.). Third international handbook on mathematics education (pp. 643–689). New York: Springer.
  • Bond, M. E., Perkins, S. N. and Ramirez, C. (2012). Students' perceptions of statistics: an exploration of attitudes, conceptualizations, and content knowledge of statistics. Statistics Education Research Journal, 11(2), 6–25. https://doi.org/10.52041/serj.v11i2.325
  • Chance B., Ben-Zvi D., Garfield, J. and Medina E. (2007). The role of technology in improving student learning of statistics. Technology Innovations in Statistics Education, 1(1), 1-26.
  • Chiesi, F. and Primi, C. (2010). Cognitive and non-cognitive factors related to students’ statistics achievement. Statistics Education Research Journal, 9(1), 6-26. https://doi.org/10.52041/serj.v9i1.385
  • Eagly, A. H. and Chaiken, S. (1995). Attitude strength, attitude structure and resistance to change. In Richard E. Petty and Jon A. Krosnick (eds.). Attitude Strength: Antecedents and Consequences. Hillsdale, NJ: Erlbaum.
  • Fabian, K., Topping, K. J. and Barron, I. G. (2018). Using mobile technologies for mathematics: effects on student attitudes and achievement. Educational Technology Research and Development, 66(5), 1119-1139. https://doi.org/10.1007/s11423-018-9580-3
  • Francis, G. (2010). Online learning materials: Are they put to different uses by online and on campus students? In C. Reading (Ed.), Data and context in statistics education: Towards an evidence-based society. Proceedings of the eighth International Conference on Teaching Statistics (ICOTS8), Ljubljana, Slovenia. Voorburg, The Netherlands: International Statistical Institute.
  • Franklin, C. and Garfield, J. (2006). The GAISE (Guidelines for Assessment and Instruction in Statistics Education) project: Developing statistics education guidelines for pre K-12 and college courses. In G. Burrill (Ed.), Thinking and Reasoning with Data and Chance (pp. 345-376). National Council of Teachers of Mathematics.
  • Gal. I. and Garfield. J. (1997). The assessment challenge in statistics education. The Netherlands: IOS Press.
  • Gal, I., Ginsburg, L. and Schau, C. (1997). Monitoring attitude and beliefs in statistics education. In Gal, I. ve Garfield, J. B. (Eds.) The Assessment Challenge in Statistics Education (pp. 37-51). The Netherlands: IOS Press.
  • GAISE (2016). Guidelines for assessment and instruction in statistical education. College report 2016. Alexandria, VA: American Statistical Association. [Online: www.amstat.org/asa/files/pdfs/GAISE/GaiseCollege_Full.pdf
  • Groth, R. E. (2013). Characterizing key developmental understandings and pedagogically powerful ideas within a statistical knowledge for teaching framework. Statistical Education of Teachers Mathematical Thinking and Learning, 15, 121–145. https://doi.org/10.1080/10986065.2013.770718
  • Hannigan, A., Hegarty, A. C. and McGrath, D. (2014). Attitudes towards statistics of graduate entry medical students: the role of prior learning experiences. BMC Medical Education, 14(1), https://doi.org/1-7. 10.1186/1472-6920-14-70
  • 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:1016048823497
  • Hassad, R. A. (2013). Faculty attitude towards technology-assisted instruction for introductory statistics in the context of educational reform. Technology Innovations in Statistics Education, 7(2). Retrieved from https://escholarship.org/uc/item/9k19k2f7
  • Kennedy, R. L. and McCallister, C. J. (2001). Attitudes toward advanced and multivariate statistics when using computers. Retrieved from https://www.learntechlib.org/p/93456/.
  • Koparan, T. (2015). İstatistiğe yönelik tutum ölçeği geliştirilmesi: geçerlik ve güvenirlik çalışması. Karaelmas Eğitim Bilimleri Dergisi, 3(1), 76-86.
  • Lalonde, R. N. and Gardner, R. C. (1993). Statistics as a second language? A model for predicting performance in psychology students. Canadian Journal of Behavioural Science, 25(1), 108-119. https://doi.org/10.1037/h0078792
  • Lee, H. S., Mojica, G. F. and Lovett, J. N. (2020). Examining how online professional development impacts teachers' beliefs about teaching statistics. Online Learning, 24(1), 5-27. https://doi.org/10.24059/olj.v24i1.1992
  • Millar, A. M. and White, B. J. (2014). How do attitudes change from one stats course to the next. In Sustainability in Statistics Education. Proceedings of the Ninth International Conference on Teaching Statistics (ICOTS9), Flagstaff, Arizona, USA. Voorburg: International Association of Statistics Education.
  • Milli Eğitim Bakanlığı (MEB, 2018). Ortaöğretim matematik dersi (9, 10, 11, 12. Sınıflar) öğretim programı. Ankara.
  • Mills, J. D. (2004). Students' attitudes toward statistics: Implications for the future. College Student Journal, 38(3), 349-362.
  • Mojica, G. F., Barker, H. and Azmy, C. N. (2019). Instrumented learning in a CODAP-enabled learning environment. Retrieved from https://www.ugr.es/~fqm126/civeest/mojica.pdf.
  • Pratt, D., Davies, N. and Connor, D. (2011). The role of technology in teaching and learning statistics. In Teaching statistics in school mathematics-challenges for teaching and teacher education (pp. 97-107). Springer, Dordrecht.
  • Ramirez, C., Schau, C. and Emmioglu, E. (2012). The importance of attitudes in statistics education. Statistics Education Research Journal, 11(2), 57-71. https://doi.org/10.52041/serj.v11i2.329
  • Rossman, A. J. and Chance, B. L. (2014). Using simulation‐based inference for learning introductory statistics. Computational Statistics, 6(4), 211-221. https://doi.org/10.1002/wics.1302
  • Schau, C., Millar, M. and Petocz, P. (2012). Research on attitudes towards statistics. Statistics Education Research Journal, 11(2), 2-5.
  • Schau, C., Stevens, J., Dauphinee, T. L. and Vecchio, A. D. (1995). The development and validation of the survey of antitudes toward statistics. Educational and Psychological Measurement, 55(5), 868-875. https://doi.org/10.1177/0013164495055005022
  • Sevimli, N. E. (2010). Matematik öğretmen adaylarının istatistik dersi konularındaki kavram yanılgıları; istatistik dersine yönelik öz yeterlilik inançları ve tutumlarının incelenmesi, (Yayınlanmamış yüksek lisans tezi), Marmara Üniversitesi, Eğitim Bilimleri Enstitüsü, İstanbul.
  • Sevimli, N. E. (2020). İstatistiksel kavramların teknoloji kullanımıyla öğretimine yönelik tasarlanan bir öğretim modülünün etkililiğinin incelenmesi, (Yayınlanmamış doktora tezi), Marmara Üniversitesi, Eğitim Bilimleri Enstitüsü, İstanbul.
  • Vanhoof, S., Kuppens, S., Castro Sotos, A. E., Verschaffel, L. and Onghena, P. (2011). Measuring statistics attitudes: structure of the survey of attitudes toward statistics. Statistics Education Research Journal, 10(1), 35-51. https://doi.org/10.52041/serj.v10i1.354
  • Zysberg, L. (2012). Student attitudes. New York: Nova Science Publishers.

Çevrim içi Öğrenme Araçlarıyla İstatistik Eğitiminin 9. Sınıf Öğrencilerinin İstatistiğe Yönelik Tutumlarına Etkisinin İncelenmesi

Year 2021, Volume: 10 Issue: 4, 1625 - 1667, 30.12.2021

Nur Esra Sevimli , Eyüp Sevimli , Emin Aydın

https://doi.org/10.30703/cije.892802

Abstract

Matematik öğretim programlarında, öğrencilerin istatistiksel düşünme yetkinliğine sahip olmalarının önemine dikkat çekilmesi ve teknoloji okuryazarlığına vurgu yapılması, istatistik konularının öğretiminde güncel teknolojiklerin yaygın olarak kullanılması ihtiyacını doğurmuştur. İstatistik eğitimi için geliştirilen çevrim içi veri analizi platformlarının mevcut teknolojilerden farkının belirlenmesi, sınıf içi öğrenme pratiklerinin anlaşılması için önemlidir. Bu çalışmada, lise matematiğindeki istatistik konularının öğretiminde çevrim içi öğrenme araçları kullanımının öğrencilerin istatistiğe yönelik tutumlarına etkisi, mevcut öğretim pratikleri ile kıyaslanarak incelenmiştir. Araştırmanın katılımcılarını, dokuzuncu sınıfta öğrenim gören 56 öğrenci oluşturmaktadır. Yarı deneysel desen ile tasarımı yapılan çalışmada, "Veri" konu alanının öğretimi, deney grubunda, çevrim içi öğrenme aracı ile hazırlanmış CODAP etkinlikleri üzerinde, kontrol grubunda ise mevcut uygulamadaki öğretim programı ve ders kitabının içerdiği öğretim etkinlikleri esas alınarak gerçekleştirilmiştir. İstatistiğe Yönelik Tutum Ölçeği, ön-son-kalıcılık testi şeklinde, deney ve kontrol gruplarına uygulanmıştır. Çalışma sonuçları, deney ve kontrol gruplarının tutum ölçeği son-test puan ortalamaları arasında, deney grubu lehine istatistiksel olarak anlamlı farklılık olduğunu göstermiştir. Grup içi karşılaştırma sonucunda, hem deney, hem de kontrol grubundaki öğrencilerin ön-son test puanları arasında istatistiksel olarak anlamlı farklılıklar olduğu, ancak kalıcılığın, deney grubunda sağlandığı tespit edilmiştir. Öğrenci günlüklerinden elde edilen bulgular, öğrencilerin istatistik konularının öğretiminde çevrim içi öğrenme aracı kullanımına dair olumlu görüşe sahip olduğunu göstermiştir. Araştırma sonucunda, güncel teknolojilerin istatistik eğitiminde kullanılabilmesi için içerik geliştirme ve eğiticilerin eğitimi çalışmalarına önem verilmesi önerisinde bulunulmuştur.

Keywords

İstatistik tutum çevrimiçi öğrenme aracı etkinlik lise matematiği

References

  • Anastasiadou, S. D. (2011). Reliability and validity testing of a new scale for measuring attitudes toward learning statistics with technology. Acta Didactica Napocensia, 4(1), 1-10.
  • Avcı, E. and Coşkuntuncel, O. (2019). Middle school teachers’ opinions about using Vustat and Tinkerplots in the data processing in middle school mathematics. Pegem Eğitim ve Öğretim Dergisi, 9(1), 01-36. http://dx.doi.org/10.14527/pegegog.2019.00
  • Azmy, C. (2019). Secondary mathematics preservice teacher development of statistics teaching self-efficacy. Unpublished PhD dissertation, North Carolina State University, USA.
  • Ben-Zvi, D., Bakker, A. and Makar, K. (2015). Learning to reason from samples. Educational Studies in Mathematic, 88(3), 291-312. https://doi.org/10.1007/s10649-015-9593-3
  • Biehler, R., Ben-Zvi, D., Bakker, A. and Makar, K. (2013). Technological advances in developing statistical reasoning at the school level. In Bishop, A., Clement, K., Keitel, C., Kilpatrick, J., veLeung, A. Y. L. (Eds.). Third international handbook on mathematics education (pp. 643–689). New York: Springer.
  • Bond, M. E., Perkins, S. N. and Ramirez, C. (2012). Students' perceptions of statistics: an exploration of attitudes, conceptualizations, and content knowledge of statistics. Statistics Education Research Journal, 11(2), 6–25. https://doi.org/10.52041/serj.v11i2.325
  • Chance B., Ben-Zvi D., Garfield, J. and Medina E. (2007). The role of technology in improving student learning of statistics. Technology Innovations in Statistics Education, 1(1), 1-26.
  • Chiesi, F. and Primi, C. (2010). Cognitive and non-cognitive factors related to students’ statistics achievement. Statistics Education Research Journal, 9(1), 6-26. https://doi.org/10.52041/serj.v9i1.385
  • Eagly, A. H. and Chaiken, S. (1995). Attitude strength, attitude structure and resistance to change. In Richard E. Petty and Jon A. Krosnick (eds.). Attitude Strength: Antecedents and Consequences. Hillsdale, NJ: Erlbaum.
  • Fabian, K., Topping, K. J. and Barron, I. G. (2018). Using mobile technologies for mathematics: effects on student attitudes and achievement. Educational Technology Research and Development, 66(5), 1119-1139. https://doi.org/10.1007/s11423-018-9580-3
  • Francis, G. (2010). Online learning materials: Are they put to different uses by online and on campus students? In C. Reading (Ed.), Data and context in statistics education: Towards an evidence-based society. Proceedings of the eighth International Conference on Teaching Statistics (ICOTS8), Ljubljana, Slovenia. Voorburg, The Netherlands: International Statistical Institute.
  • Franklin, C. and Garfield, J. (2006). The GAISE (Guidelines for Assessment and Instruction in Statistics Education) project: Developing statistics education guidelines for pre K-12 and college courses. In G. Burrill (Ed.), Thinking and Reasoning with Data and Chance (pp. 345-376). National Council of Teachers of Mathematics.
  • Gal. I. and Garfield. J. (1997). The assessment challenge in statistics education. The Netherlands: IOS Press.
  • Gal, I., Ginsburg, L. and Schau, C. (1997). Monitoring attitude and beliefs in statistics education. In Gal, I. ve Garfield, J. B. (Eds.) The Assessment Challenge in Statistics Education (pp. 37-51). The Netherlands: IOS Press.
  • GAISE (2016). Guidelines for assessment and instruction in statistical education. College report 2016. Alexandria, VA: American Statistical Association. [Online: www.amstat.org/asa/files/pdfs/GAISE/GaiseCollege_Full.pdf
  • Groth, R. E. (2013). Characterizing key developmental understandings and pedagogically powerful ideas within a statistical knowledge for teaching framework. Statistical Education of Teachers Mathematical Thinking and Learning, 15, 121–145. https://doi.org/10.1080/10986065.2013.770718
  • Hannigan, A., Hegarty, A. C. and McGrath, D. (2014). Attitudes towards statistics of graduate entry medical students: the role of prior learning experiences. BMC Medical Education, 14(1), https://doi.org/1-7. 10.1186/1472-6920-14-70
  • 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:1016048823497
  • Hassad, R. A. (2013). Faculty attitude towards technology-assisted instruction for introductory statistics in the context of educational reform. Technology Innovations in Statistics Education, 7(2). Retrieved from https://escholarship.org/uc/item/9k19k2f7
  • Kennedy, R. L. and McCallister, C. J. (2001). Attitudes toward advanced and multivariate statistics when using computers. Retrieved from https://www.learntechlib.org/p/93456/.
  • Koparan, T. (2015). İstatistiğe yönelik tutum ölçeği geliştirilmesi: geçerlik ve güvenirlik çalışması. Karaelmas Eğitim Bilimleri Dergisi, 3(1), 76-86.
  • Lalonde, R. N. and Gardner, R. C. (1993). Statistics as a second language? A model for predicting performance in psychology students. Canadian Journal of Behavioural Science, 25(1), 108-119. https://doi.org/10.1037/h0078792
  • Lee, H. S., Mojica, G. F. and Lovett, J. N. (2020). Examining how online professional development impacts teachers' beliefs about teaching statistics. Online Learning, 24(1), 5-27. https://doi.org/10.24059/olj.v24i1.1992
  • Millar, A. M. and White, B. J. (2014). How do attitudes change from one stats course to the next. In Sustainability in Statistics Education. Proceedings of the Ninth International Conference on Teaching Statistics (ICOTS9), Flagstaff, Arizona, USA. Voorburg: International Association of Statistics Education.
  • Milli Eğitim Bakanlığı (MEB, 2018). Ortaöğretim matematik dersi (9, 10, 11, 12. Sınıflar) öğretim programı. Ankara.
  • Mills, J. D. (2004). Students' attitudes toward statistics: Implications for the future. College Student Journal, 38(3), 349-362.
  • Mojica, G. F., Barker, H. and Azmy, C. N. (2019). Instrumented learning in a CODAP-enabled learning environment. Retrieved from https://www.ugr.es/~fqm126/civeest/mojica.pdf.
  • Pratt, D., Davies, N. and Connor, D. (2011). The role of technology in teaching and learning statistics. In Teaching statistics in school mathematics-challenges for teaching and teacher education (pp. 97-107). Springer, Dordrecht.
  • Ramirez, C., Schau, C. and Emmioglu, E. (2012). The importance of attitudes in statistics education. Statistics Education Research Journal, 11(2), 57-71. https://doi.org/10.52041/serj.v11i2.329
  • Rossman, A. J. and Chance, B. L. (2014). Using simulation‐based inference for learning introductory statistics. Computational Statistics, 6(4), 211-221. https://doi.org/10.1002/wics.1302
  • Schau, C., Millar, M. and Petocz, P. (2012). Research on attitudes towards statistics. Statistics Education Research Journal, 11(2), 2-5.
  • Schau, C., Stevens, J., Dauphinee, T. L. and Vecchio, A. D. (1995). The development and validation of the survey of antitudes toward statistics. Educational and Psychological Measurement, 55(5), 868-875. https://doi.org/10.1177/0013164495055005022
  • Sevimli, N. E. (2010). Matematik öğretmen adaylarının istatistik dersi konularındaki kavram yanılgıları; istatistik dersine yönelik öz yeterlilik inançları ve tutumlarının incelenmesi, (Yayınlanmamış yüksek lisans tezi), Marmara Üniversitesi, Eğitim Bilimleri Enstitüsü, İstanbul.
  • Sevimli, N. E. (2020). İstatistiksel kavramların teknoloji kullanımıyla öğretimine yönelik tasarlanan bir öğretim modülünün etkililiğinin incelenmesi, (Yayınlanmamış doktora tezi), Marmara Üniversitesi, Eğitim Bilimleri Enstitüsü, İstanbul.
  • Vanhoof, S., Kuppens, S., Castro Sotos, A. E., Verschaffel, L. and Onghena, P. (2011). Measuring statistics attitudes: structure of the survey of attitudes toward statistics. Statistics Education Research Journal, 10(1), 35-51. https://doi.org/10.52041/serj.v10i1.354
  • Zysberg, L. (2012). Student attitudes. New York: Nova Science Publishers.
There are 36 citations in total.

Details

Primary Language Turkish
Journal Section Research Article
Authors

Nur Esra Sevimli 0000-0003-4533-9684

Eyüp Sevimli 0000-0002-2083-688X

Emin Aydın 0000-0003-4298-2623

Publication Date December 30, 2021
Published in Issue Year 2021Volume: 10 Issue: 4

Cite

APA Sevimli, N. E., Sevimli, E., & Aydın, E. (2021). Çevrim içi Öğrenme Araçlarıyla İstatistik Eğitiminin 9. Sınıf Öğrencilerinin İstatistiğe Yönelik Tutumlarına Etkisinin İncelenmesi. Cumhuriyet Uluslararası Eğitim Dergisi, 10(4), 1625-1667. https://doi.org/10.30703/cije.892802
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