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Dokuzuncu Sınıf Öğrencilerinin Biyoloji ve Fizik Derslerindeki Kaynak Yönetimi Stratejilerin İncelenmesi

Year 2017, Volume: 11 Issue: 2, 197 - 211, 18.12.2017
https://doi.org/10.17522/balikesirnef.373342

Abstract









Bu araştırmanın amacı dokuzuncu sınıf öğrencilerinin biyoloji ve fizik
derslerinde kullandıkları kaynak yönetimi stratejileri arasındaki farklılıkları
ve ilişkileri incelemektir. Araştırmaya Muğla İli Menteşe İlçesindeki üç lisede
öğrenim gören toplam 603 öğrenci katılmıştır. Araştırmanın verileri zaman ve
çalışma ortamı yönetimi, emek yönetimi, akran iş birliği ve yardım isteme alt
faktörlerini içeren Güdülenme ve Öğrenme Stratejileri Ölçeğinin kısa versiyonu ile
toplanmıştır. Araştırma sorularına cevap vermek için tekrarlı- çoklu varyans
analizi (MANOVA) ve doğrulayıcı faktör analizi kullanılmıştır. Araştırma
sonucunda, öğrencilerin fizikte daha yüksek bir emek yönetimi stratejisini kullandıkları,
biyoloji dersinde ağırlıklı olarak zaman ve çalışma ortamı, akran iş birliği ve
yardım isteme stratejilerini kullandıkları bulunmuştur. Ayrıca, her iki derste
de öğrencilerinin kaynak yönetimi stratejilerinin birbiriyle ilişkili olduğu
bulunmuştur.

References

  • Açışlı, S. (2015). Öğretmen adaylarının öğrenme stilleri ve eleştirel düşünme eğilimlerinin incelenmesi, Necatibey Eğitim Fakültesi Elektronik Fen ve Matematik Eğitimi Dergisi, 9, 23-48.
  • Alexander, P. A., & Buehl, M. M. (2009). Beliefs about learning in academic domains. In K. Wentzel & A. Wigfield (Eds.), Handbook on motivation at school (pp. 697-726). New York: Routledge.
  • Alexander, P. A., Dinsmore, D. L., Parkinson, M. M. & Winters, F. I. (2011). Self-regulated learning in academic domains. In B. J. Zimmerman and D. H. Schunk (Ed.), Handbook of Self-Regulation of Learning and Performance (pp. 393-407) Abingdon: Routledge.
  • Alpaslan, M. M., Yalvac, B., Loving, C. C. & Willson, V. (2016). Exploring the relationship between high school students’ physics-related personal epistemologies and self-regulated learning in Turkey. International Journal of Science and Mathematics Education, 14(2), 297–317.
  • Arıkan, S. (2014). A regression model with a new tool: IDB analyzer for identifying factors predicting mathematics performance using pisa 2012 indices, US-China Education Review A, 4(10), 716-727.
  • Britner, S.L. (2008). Motivation in high school science students: A comparison of gender differences in life, physical, and earth science classes. Journal of Research in Science Teaching, 45, 955-970.
  • Büyüköztürk, Ş., Akgün, Ö. E., Demirel, F., & Özkahveci, Ö. (2004). Güdülenme ve Öğrenme Stratejileri Ölçeği’nin Türkçe formunun geçerlik ve güvenirlik çalışması. Kuram ve Uygulamada Eğitim Bilimleri Dergisi, 4(2), 207-239.
  • Cebesoy, Ü. B. (2013). Pre-Service science teachers’ perceptions of self-regulated learning in physics. Turkish Journal of Education, 2(1), 4-18.
  • Creswell, J.W. (2007). Qualitative inquiry and research design: Choosing among five approaches. Thousand Oaks, CA: Sage.
  • Erdogan, N., & Stuessy, C. L. (2015). Examining inclusive STEM schools’ role in the college and career readiness of students in the United States: A multi-group analysis of students’ achievement outcomes. Educational Sciences: Theory & Practice, 15(6), 1517-1529.
  • Fraenkel, J. R., & Wallen, N. E. (2006). How to design and evaluate research in education. Boston: McGraw-Hill.
  • Greene, J. A., Bolick, C. M., Caprino, A. M., Deekens, V. M., McVea, M., Yu, S. & Jackson, W. P. (2015). Fostering high-school students’ self-regulated learning online and across academic domains. The High School Journal, 99(1), 88-106.
  • Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55.
  • McCardle, L., & Hadwin, A. F. (2015). Using multiple, contextualized data sources to measure learners’ perceptions of their self-regulated learning. Metacognition and Learning, 10, 43-75.
  • Muis, K. R. (2007). The role of epistemic beliefs in self-regulated learning. Educational Psychologist, 42, 173–190.
  • Muis, K. R., Bendixen, L. D., & Haerle, F. (2006). Domain-generality and domain-specificity in personal epistemology research: Philosophical and empirical reflections in the development of a theoretical framework. Educational Psychology Review, 18, 3–54.
  • National Research Council. (2007). Taking science to school: Learning and teaching science in grades K–8 (R. A. Duschl, H. A. Schweingruber, & A. W. Shouse, Eds.). Washington, DC: National Academies Press.
  • Özek, N., Gönen, S., Maskan, A.K., Kavak, M.T. & Aşkın, M. (2003). Fizik lisans öğrencilerinin fizik öğrenmeye ilişkin görüşleri üzerine bir çalışma. Eğitim ve Bilim, 28, 35- 41.
  • Pintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regulated learning in college students. Educational Psychology Review, 16, 385–407.
  • Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ). Ann Arbor, MI: National Center for Research to Improve Postsecondary Teaching and Learning.
  • Redish, E. F., & Steinberg, R. N. (1999). Teaching physics: Figuring out what works. Physics Today, 52(1), 24–30.
  • Sadler, P. M., Sonnert, G., Hazari, Z., & Tai, R. (2012). Stability and volatility of STEM career interest in high school: A gender study. Science Education, 96(3), 411–427.
  • Spall, K., Stanisstreet, M., Dickson, D. & Boyes, E. (2004). Development of school students' constructions of biology and physics. International Journal Of Science Education, 26, 787-803.
  • Topçu, M. S. (2013). Preservice teachers’ epistemological beliefs in physics, chemistry, and biology: A mixed study. International Journal of Science and Mathematics Education, 11(2), 433-458.
  • Vermunt, J.D. (2005). Relations between student learning patterns and personal and contextual factors and academic performance. Higher Education, 49, 205–234
  • Winne, P. H., & Hadwin, A. F. (1998). Studying as self-regulated learning. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), Metacognition in educational theory and practice (pp. 277–304). Mahwah, NJ: Lawrence Erlbaum.
  • Wolters, C. A. & Pintrich, P. R. (1998). Contextual differences in student motivation and self-regulated learning in mathematics, English, and social studies classrooms. Instructional Science, 26, 27-47.
  • Yumusak, N., Sungur, S., & Cakiroglu, J. (2007). Turkish high school students' biology achievement in relation to academic self-regulation. Educational Research and Evaluation, 13, 53–69
  • Yıldızlar, M. (2012). Öğretmen adaylarının öğrenme stratejileri üzerine bir çalışma. Hacettepe Üniversitesi Eğitim Fakültesi Dergisi, 42, 430-440.
  • Zimmerman, B. J. (2011). Motivational sources and outcomes of self-regulated learning and performance. In B. J. Zimmerman and D. H. Schunk (Ed.), Handbook of Self-Regulation of Learning and Performance (pp. 49-65) Abingdon: Routledge

Examining The Disciplinary Differences of Ninth Graders’ Resource Management Strategies in Biology and Physics

Year 2017, Volume: 11 Issue: 2, 197 - 211, 18.12.2017
https://doi.org/10.17522/balikesirnef.373342

Abstract









The purpose of this study is to examine the differences and the
relations between ninth grade students’ resource management strategies in
biology and physics. A total of 603 ninth graders from three high schools in
Muğla in Turkey participated in the study. A short version of the Motivated
Strategies for Learning Questionnaire including managing time and study
environment, effort management, peer learning and help-seeking was
administrated. Repeated multivariate analysis of variance (MANOVA)s and confirmatory
factor analysis were utilized. Results showed that students reported a higher
usage of managing time and study environment, peer learning and help-seeking
biology than in physics, whereas a higher usage of effort management in physics
than in biology. Also it was found that students’ resource management
strategies in both courses were correlated to each other. The implications and
future directions were discussed.

References

  • Açışlı, S. (2015). Öğretmen adaylarının öğrenme stilleri ve eleştirel düşünme eğilimlerinin incelenmesi, Necatibey Eğitim Fakültesi Elektronik Fen ve Matematik Eğitimi Dergisi, 9, 23-48.
  • Alexander, P. A., & Buehl, M. M. (2009). Beliefs about learning in academic domains. In K. Wentzel & A. Wigfield (Eds.), Handbook on motivation at school (pp. 697-726). New York: Routledge.
  • Alexander, P. A., Dinsmore, D. L., Parkinson, M. M. & Winters, F. I. (2011). Self-regulated learning in academic domains. In B. J. Zimmerman and D. H. Schunk (Ed.), Handbook of Self-Regulation of Learning and Performance (pp. 393-407) Abingdon: Routledge.
  • Alpaslan, M. M., Yalvac, B., Loving, C. C. & Willson, V. (2016). Exploring the relationship between high school students’ physics-related personal epistemologies and self-regulated learning in Turkey. International Journal of Science and Mathematics Education, 14(2), 297–317.
  • Arıkan, S. (2014). A regression model with a new tool: IDB analyzer for identifying factors predicting mathematics performance using pisa 2012 indices, US-China Education Review A, 4(10), 716-727.
  • Britner, S.L. (2008). Motivation in high school science students: A comparison of gender differences in life, physical, and earth science classes. Journal of Research in Science Teaching, 45, 955-970.
  • Büyüköztürk, Ş., Akgün, Ö. E., Demirel, F., & Özkahveci, Ö. (2004). Güdülenme ve Öğrenme Stratejileri Ölçeği’nin Türkçe formunun geçerlik ve güvenirlik çalışması. Kuram ve Uygulamada Eğitim Bilimleri Dergisi, 4(2), 207-239.
  • Cebesoy, Ü. B. (2013). Pre-Service science teachers’ perceptions of self-regulated learning in physics. Turkish Journal of Education, 2(1), 4-18.
  • Creswell, J.W. (2007). Qualitative inquiry and research design: Choosing among five approaches. Thousand Oaks, CA: Sage.
  • Erdogan, N., & Stuessy, C. L. (2015). Examining inclusive STEM schools’ role in the college and career readiness of students in the United States: A multi-group analysis of students’ achievement outcomes. Educational Sciences: Theory & Practice, 15(6), 1517-1529.
  • Fraenkel, J. R., & Wallen, N. E. (2006). How to design and evaluate research in education. Boston: McGraw-Hill.
  • Greene, J. A., Bolick, C. M., Caprino, A. M., Deekens, V. M., McVea, M., Yu, S. & Jackson, W. P. (2015). Fostering high-school students’ self-regulated learning online and across academic domains. The High School Journal, 99(1), 88-106.
  • Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55.
  • McCardle, L., & Hadwin, A. F. (2015). Using multiple, contextualized data sources to measure learners’ perceptions of their self-regulated learning. Metacognition and Learning, 10, 43-75.
  • Muis, K. R. (2007). The role of epistemic beliefs in self-regulated learning. Educational Psychologist, 42, 173–190.
  • Muis, K. R., Bendixen, L. D., & Haerle, F. (2006). Domain-generality and domain-specificity in personal epistemology research: Philosophical and empirical reflections in the development of a theoretical framework. Educational Psychology Review, 18, 3–54.
  • National Research Council. (2007). Taking science to school: Learning and teaching science in grades K–8 (R. A. Duschl, H. A. Schweingruber, & A. W. Shouse, Eds.). Washington, DC: National Academies Press.
  • Özek, N., Gönen, S., Maskan, A.K., Kavak, M.T. & Aşkın, M. (2003). Fizik lisans öğrencilerinin fizik öğrenmeye ilişkin görüşleri üzerine bir çalışma. Eğitim ve Bilim, 28, 35- 41.
  • Pintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regulated learning in college students. Educational Psychology Review, 16, 385–407.
  • Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ). Ann Arbor, MI: National Center for Research to Improve Postsecondary Teaching and Learning.
  • Redish, E. F., & Steinberg, R. N. (1999). Teaching physics: Figuring out what works. Physics Today, 52(1), 24–30.
  • Sadler, P. M., Sonnert, G., Hazari, Z., & Tai, R. (2012). Stability and volatility of STEM career interest in high school: A gender study. Science Education, 96(3), 411–427.
  • Spall, K., Stanisstreet, M., Dickson, D. & Boyes, E. (2004). Development of school students' constructions of biology and physics. International Journal Of Science Education, 26, 787-803.
  • Topçu, M. S. (2013). Preservice teachers’ epistemological beliefs in physics, chemistry, and biology: A mixed study. International Journal of Science and Mathematics Education, 11(2), 433-458.
  • Vermunt, J.D. (2005). Relations between student learning patterns and personal and contextual factors and academic performance. Higher Education, 49, 205–234
  • Winne, P. H., & Hadwin, A. F. (1998). Studying as self-regulated learning. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), Metacognition in educational theory and practice (pp. 277–304). Mahwah, NJ: Lawrence Erlbaum.
  • Wolters, C. A. & Pintrich, P. R. (1998). Contextual differences in student motivation and self-regulated learning in mathematics, English, and social studies classrooms. Instructional Science, 26, 27-47.
  • Yumusak, N., Sungur, S., & Cakiroglu, J. (2007). Turkish high school students' biology achievement in relation to academic self-regulation. Educational Research and Evaluation, 13, 53–69
  • Yıldızlar, M. (2012). Öğretmen adaylarının öğrenme stratejileri üzerine bir çalışma. Hacettepe Üniversitesi Eğitim Fakültesi Dergisi, 42, 430-440.
  • Zimmerman, B. J. (2011). Motivational sources and outcomes of self-regulated learning and performance. In B. J. Zimmerman and D. H. Schunk (Ed.), Handbook of Self-Regulation of Learning and Performance (pp. 49-65) Abingdon: Routledge
There are 30 citations in total.

Details

Journal Section Makaleler
Authors

Muhammet Mustafa Alpaslan

Publication Date December 18, 2017
Submission Date November 25, 2016
Published in Issue Year 2017 Volume: 11 Issue: 2

Cite

APA Alpaslan, M. M. (2017). Examining The Disciplinary Differences of Ninth Graders’ Resource Management Strategies in Biology and Physics. Necatibey Faculty of Education Electronic Journal of Science and Mathematics Education, 11(2), 197-211. https://doi.org/10.17522/balikesirnef.373342