Research Article
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Identifying the Factors Affecting Science and Mathematics Achievement Using Data Mining Methods

Year 2015, Volume: 1 Issue: 1, 28 - 48, 21.01.2015
https://doi.org/10.21891/jeseh.41216

Abstract

The purpose of this article is to identify the order of significance of the variables that affect science and mathematics achievement in middle school students. For this aim, the study deals with the relationship between science and math in terms of different angles using the perspectives of multiple causes-single effect and of multiple causes-multiple effects. Furthermore, the study examines and reveals how the reading skills, problem solving skills, cognitive and affective variables influence the math and science achievement. The data was collected from the results of Turkish students who participated in three international examinations; TIMSS 1999, PISA 2003 and PISA 2006. We analyzed the data using two data-mining methods (decision trees and clustering). The findings show that science or mathematics achievement is not influenced by the course-specific variable alone but also by other related variables. The following variables are the most important; the students’ reading and problem-solving skills affected both mathematics and science achievement; the mathematics achievement affected the science achievement; and the science achievement affected the mathematics achievement. It is also found that the affective variables have almost equally significant effects on the science and mathematics achievement.

References

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Year 2015, Volume: 1 Issue: 1, 28 - 48, 21.01.2015
https://doi.org/10.21891/jeseh.41216

Abstract

References

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  • Barkatsas, A, Kasimatis, K., & Gialamas, V. (2009). Learning secondary mathematics with technology: Exploring the complex interrelationship between students’ attitudes, engagement, gender and achievement. Computers and Education, 52, 562–570.
  • Basista, B., & Mathews, S. (2002). Integrated science and mathematics professional development programs. School Science and Mathematics, 102(7), 359–370.
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  • Bekdemir, M. (2007). The causes of mathematics anxiety in elementary preservice teachers and proposals for decreasing mathematics anxiety. The example of faculty of Erzincan education. Erzincan Eğitim Fakültesi Dergisi, 9(2), 131–144.
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  • Blanchette, I., & Dunbar, K. (2002). Representational change and analogy: How analogical inferences alter target representations. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28, 672–685.
  • Brookover, W. B., Thomas, S. & Peterson, A. (1964). Self-concept of ability and school performance. Sociology of Education, 37, 271–278.
  • Bursal, M. (2008). Changes in Turkish pre-service elementary teachers’ personal science teaching efficacy beliefs and science anxieties during a science method course. Journal of Turkish Science Education, 5 (1).
  • Bursal, M., & Paznokas, L. (2006). Mathematics anxiety and preservice elementary teachers’ confidence to teach mathematics and science. School Science and Mathematics, 106(4), 173–180.
  • Byrne, B. M. (1996). Measuring self-concept across the life span. Issues and instrumentation. Washington, DC: American Psychological Association.
  • Cahan, D. (2003). From natural philosophy to the sciences: Writing the history of nineteenth- century science. London: University of Chicago Press.
  • Caston, M. (1986). Parent and student attitudes toward mathematics as they relate to third grade mathematics achievement. Research report. (Eric Document Reproduction No. ED334078).
  • Chien, C., & Chen, L. (2008). Data mining to improve personnel selection and enhance human capital: A case study in high-technology industry. Expert Systems with Applications, 34, 280–290.
  • Chui, C., Chen, Y., Kou, I., & Ku, H. C. (2009). An intelligent market segmentation system using k-means and particle swarm optimization. Expert Systems with Applications, 36(1), 4558–4565.
  • Davison, D. M., Miller, K. W., & Metheny, D. L. (1995). What does integration of science and mathematics really mean? School Science and Mathematics, 95(5), 226–230.
  • Dede, Y., & Yaman, S. (2008). A questionnaire for motivation toward science learning: A validity and reliability study. Necatibey Faculty of Education Electronic Journal of Science and Mathematics Education, 2(1), 19–37.
  • Delen, D., Walker, G., & Kadam, A. (2005). Predicting breast cancer survivability: A comparison of three data mining methods. Artificial Intelligence in Medicine, 34, 113–127.
  • Demir, İ., & Kılıç, S. (2009). Matematikte başarı üzerine öğrencilerin kendileriyle ilgili görüşleri (Students’ self efficacy about themselves on the math achievement). Paper peresented at the 6th Statistics Congress, Antalya.
  • Dewey, J. (1969). Interest and effort in education. New York: Augustus M. Kelley Publishers.
  • Dewey, J. (1933). How we think. Boston, MA: Heath and Company.
  • Dotterer, A. M., McHale, S. M., & Crouter, A. C. (2009). The development and correlates of academic interests from childhood through adolescence. Journal of Educational Psychology, 101(2), 509–519.
  • EARGED. (2005). Öğrenci başarısını belirleme programı (PISA–2003), ulusal ön rapor (Student achievement determining program (PISA-2003), national preliminary report). Ankara: MEB-Eğitimi Araştırma ve Geliştirme Dairesi Başkanlığı.
  • EARGED. (2003). TIMSS-R: Third international mathematics and science study-repeat/ üçüncü uluslararası matematik ve fen araştırmasının tekrarı-uluslararası ölçme ve değerlendirme çalışmaları (international measurement and assessment studies). Ankara: MEB Eğitimi Araştırma ve Geliştirme Dairesi (EARGED) Yay. (http://earged.meb.gov.tr)
  • Eggen, P., & Kauchak, D. (2001). Educational psychology: Windows on classrooms. New Jersey: Prentice Hall.
  • Erten, S. (2008). Interests of 5th through 10th grade students toward human biology. Hacettepe University, Journal of Education, 35, 135–147.
  • Friend, H. (1985). The effect of science and mathematics integration on selected seventh- grade students’ attitudes toward and achievement in science. School Science and Mathematics, 85(6), 453–461.
  • Gardner, P. L., & Tamir, P. (1989). Interest in biology. Part I: A multidimensional construct. Journal of Research in Science Teaching, 26(5), 409–423.
  • Girasoli, A. J., & Hannafin, R. D. (2008). Using asynchronous AV communication tools to increase academic self-efficacy. Computers and Education, 51, 1676–1682.
  • Gleick, J. (1987). Chaos: Making a new science. New York: Viking Press.
  • Gonzalez, E. J., & Miles, J. A. (Eds.) (2001). TIMSS 1999 user guide for the international database: IEA’s repeat of the third ınternational mathematics and science study at the eighth grade. Lynch School of Education, Boston, MA: International Study Center, Boston College.
  • Gömleksiz, M. N. (2003). Validity and reliability of an attitude scale on affective domain in English course. Fırat University Journal of Social Science, 13(1), 215-226.
  • Guay, F., Marsh, H. W., & Boivin, M. (2003). Academic self-concept and academic achievement: Developmental perspectives and their causal ordering. Journal of Educational Psychology, 95, 124–136.
  • Güleç, S., & Alkış, S. (2003). Relations among primary school students’ course performances. İlköğretim-Online, 2 (2), 19–27.
  • Güngör, A., Eryılmaz, A., & Fakıoğlu, T. (2007). The relationship of freshmen’s physics achievement and their related affective characteristics. Journal of Research in Science Teachıng, 44(8), 1036–1056.
  • Harper, N. W., & Daane, C. J. (1998). Causes and reduction of math anxiety in preservice elementary teachers. Action in Teacher Education, 19(4), 29–38.
  • Hembree, R. (1990). The nature, effects and relief of mathematics anxiety. Journal for Research in Mathematics Education, 21(1), 33–46.
  • Hendrickson, A. B. (1997). Predicting student success with the learning and study strategies 14. inventory (LASSI). Unpublished Master’s thesis. Iowa State University, Ames, IA.
  • Hizarcı, T., Atılboz, N. G., & Salman, S. (2005). A study on the attitudes of elementary school students from two different socio-economic regions towards living organisms. Journal of Gazi Educational Faculty, 25(2), 55–69.
  • House, J. D. (2004). Cognitive-motivational characteristics and science achievement of adolescent students: results from the tımss 1995 and tımss 1999 assesments. International Journal of Instructional Media, 31(4), 411-424.
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Details

Primary Language English
Journal Section Articles
Authors

S. Ahmet Kiray

Bilge Gok This is me

A. Selman Bozkir This is me

Publication Date January 21, 2015
Published in Issue Year 2015 Volume: 1 Issue: 1

Cite

APA Kiray, S. A., Gok, B., & Bozkir, A. S. (2015). Identifying the Factors Affecting Science and Mathematics Achievement Using Data Mining Methods. Journal of Education in Science Environment and Health, 1(1), 28-48. https://doi.org/10.21891/jeseh.41216

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