The Relationship between the Amount of Learning and Time(The Example of Equations)

Year 2016, Volume: 5 Issue: 3, 125 - 135, 15.07.2016

Cenk Kesan , Deniz Kaya , Gokce Ok , Yusuf Erkus

https://doi.org/10.12973/eu-jer.5.3.125

Abstract

The main purpose of this study is to determine the amount of time-dependent learning of "solving problems that require establishing of single variable equations of the first order" of the seventh grade students. The study, adopting the screening model, consisted of a total of 84 students, including 42 female and 42 male students at the seventh grade. Data was collected using an assessment tool consisting of 10 open-ended questions. The findings show that the learning group of 84 students were behind the value closest to the full learning level by a score of 0.013. While the female students reached the lower limit of 0.987 specified for the full learning level in a period of 3.2 course hours, the male students reached this limit in 4.0 course hours. The learning amount of 0.999, which is the closest value to the full learning level, was reached by the learning group in a period of 9.7 course hours, the female students in 8.5 course hours, and the male students in 11.3 course hours. In addition to this, the data obtained showed that learning difficulties among to the learning groups decreased as the space below the curve of time and learning amount decreased. As a result of the study, it was recommended that it is possible to determine the closest course periods for the full learning level for each of the gains found in all levels of education and all teaching programmes, which define certain learning outcomes within a certain time.

Keywords

Amount of learning, time, equations, seventh grade

References

• Akkaya, R., & Durmus, S. (2006). Misconceptions of elementary school students in grades 6-8 on learning algebra. Hacettepe University Journal of Education, 31(2), 1-12.
• Arici, O. (2013). A scaling study for the factors affect the attitudes of students towards maths lesson according to the views of teachers. Journal of Aegean Education, 14(2), 25-40.
• Bal, P. (2008). The evaluation of new mathematic curriculum in term of teachers’ perspectives. Journal of Cukurova University Institute of Social Sciences, 17(1), 53-68.
• Bagci, O. (2015). Secondary mathematics 7 lesson book. Ankara: Tutku Publications.
• Bayar, H. (2007). Error analysis in equations. Unpublished Master’s Thesis, Balikesir University, Institute of Educational Sciences, Balikesir, Turkey.
• Bayindir, N. (2006). The learning strategies instruction and effects on cognitive processes. Unpublished Doctoral Dissertation, Marmara University, Institute of Educational Sciences, Istanbul, Turkey.
• Booth, J., & Koedinger, K. (2008, March 16). Key misconceptions in algebraic problem solving. Retrieved from http://pact.cs.cmu.edu/pubs/BoothKoedingerCogSci2008.pdf
• Cedefop (2010, March 14). Modernizing vocational education and training. Retrieved from www.cedefop.europa-.eu
• Dede, Y., & Peker, M. (2007). Students’ errors and misunderstanding towards algebra: Pre-service mathematics teachers’ prediction skills of error and misunderstanding and solution suggestions. Elementary Education Online, 6(1), 35-49.
• Dursun, S., & Dede, Y. (2004). The factors affecting students’ success in mathematics: Mathematics teachers’ perspectives. Gazi Journal of the Faculty of Education, 24(2), 217-230.
• Erdem, Z. C. (2013). Determination of students’ mistakes and misconceptions about equations and teacher views on reasons and solutions of these mistakes and misconceptions. Unpublished Master’s Thesis, Adiyaman University, Institute of Science, Adiyaman, Turkey.
• Eurydice (2011, March 16). Mathematics education in Europe: Common challenges and national policies. Retrieved from http://eacea.ec.europa.eu/
• Hannula, M. S. (2002). Attitude towards mathematics: emotions, expectations and values. Educational Studies in Mathematics, 49(1), 25-46.
• Heppner, P. P., & Lee, D. (2009). Problem-solving appraisal and psychological adjustment. Oxford Handbook of Positive Psychology. Edited by C. R. Snyder & Shane L. Lopez. Oxford Library of Psychology.
• Hoffman, B., & Spatariu, A. (2008). The influence of self-efficacy and metacognitive prompting on math problem-solving efficiency. Contemporary Educational Psychology, 33(4), 875-893.
• Karasar, N. (2009). Methods of scientific research (20. Press). Ankara: Nobel Publication Distribution.
• Kardash, C. M., & Howell, K. L. (2000). Effects of epistemological beliefs and topic-specific beliefs on undergraduates’ cognitive and strategic of dual-positional text. Journal of Educational Psychology, 92(3), 524-35.
• Kuru, Y. (2014). Mathematics learning difficulties at the 8th grade of elementary. Unpublished Master’s Thesis, Duzce University, Institute of Social Sciences, Duzce, Turkey.
• Marzano, R. J. (2000). Transforming classroom grading. Alexandria, VA: Association for Supervision and Curriculum Development.
• Ministry of National Education (MNE) (2013). Secondary mathematics book (5, 6, 7 and 8. class) programme of teaching. Ankara: Board of Education.
• Nagle, R. K., Saff, E. B., & Snider, A. D. (2013). Fundamentals of differential equations. (Trans. O. Dogru) Ankara: Nobel Academic Publication.
• Namlu, A. G. (2004). Metacognitive learning strategies scale: A study of reliability and validity. Anadolu University Journal of Social Sciences, 2, 123-136.
• Official Gazette (2014). T. C. Official Gazette, 13 September, (29118). Retrieved from http://www.resmigazete.gov.tr/default.aspx
• OECD (Organization for Economic Co-operation and Development) (2003). Mathematics teaching and learning strategies in PISA. Paris: OECD Publishing. Retrieved from http://www.oecd.-org/dataoecd/1/60/3400-2216.pdf
• Ozer, Y., & Anil, D. (2011). Examining the factors affecting students’ science and mathematics achievement with structural equation modeling. Hacettepe University Journal of Education, 41, 313-324.
• Psifidou, I. (2009). Innovation in school curriculum: The shift to learning outcomes. Procedia Social and Behavioral Sciences, 1, 2436-2440.
• Riding, R. J., & Stephen, R. G. (1998). Cognitive styles and learning strategies: Understanding style differences in learning and behavior. London: David Fulton Publisher.
• Savas, E., Tas, S. & Duru, A. (2010). Factors affecting students’ achievement in mathematics. Inonu University Journal of the Faculty of Education, 11(1), 113-132.
• Soylu, Y. (2008). 7th grade students’ interpretation of algebraic expression and symbol of letters while doing these interpretations. Selcuk University Journal of the Faculty of Education, 25, 237-248.
• Stacey, K., & MacGregor, M. (2000). Learning the algebraic method of solving problems. Journal of Mathematical Behavior, 18(2), 149-167.
• Thomson, S., Lokan, J., Lamb S., & Ainley, J. (2003). Lessons from the third international mathematics and science study. TIMSS Australia Monograph Series. Australian Council for Educational Research.