Journal of Science Education (과학교육연구지)

Science Education Research Institute Kyungpook National University (경북대학교 과학교육연구소)
권호 표지
DOI QR코드

DOI QR Code

The Effects of the Number, Ratio of Advanced Courses, and Variety in Science Elective Subjects on the Growth of High School Science Course Students' Attitude Towards Science

고등학교에서 과학 선택 과목의 수, 심화(II) 과목 비율, 교과 다양성이 이과 학생의 과학에 대한 태도 성장에 미치는 효과

  • Received : 2022.02.21
  • Accepted : 2022.04.30
  • Published : 2022.04.30
Download PDF
⟨ Previous Next ⟩

Abstract

We fitted latent growth models of attitude towards science using the Korea Education & Employment Panel 2004-2007 data with 343 high school students. The growth model show better fit indices compared to the no growth model. The intercept and slope showed significant variances, and thus, we added control variables of the number, ratio of advanced courses, and variety in science elective subjects, and the achievement percentile for middle school. In the conditional growth model, the previous achievement has significant positive effects on the intercept and the ratio of the advanced courses and variety of science subjects show significantly positive effects on the slope. Based on the results, it supports the 2022 Revised Science Curricular that high school credit system should provide students with basic 'Physics,' 'Chemistry,' 'Biology,' and 'Earth Science,' credits in 'general electives', various integrated subjects in 'converged electives', and highly advanced subjects in 'career electives.'

한국교육고용패널 2004-2007년 자료 중 343명의 이과 고등학생 조사 데이터를 활용하여 과학에 대한 태도에 대한 잠재 성장 모형을 적합하였다. 모형 적합 결과, 과학에 대한 태도의 무성장 모형보다 성장 모형이 더 나은 것으로 나타났다. 통제 변수가 없는 무조건 성장모형에서 과학에 대한 태도의 초기치와 변화량의 분산이 유의미하였으므로, 여기에 학생 개인 수준에서 이수한 과학 선택 과목의 수, 심화(II) 과목의 비율, 교과 다양성, 그리고 중학교 3학년 때의 성적 백분위를 통제 변수로 투입하였다. 이러한 조건 성장모형에서 중학교 3학년 때의 성적 백분위는 과학에 대한 태도 초기치에 정적으로(+) 유의미한 직접 효과가 있었고, 과학 심화 과목의 비율과 교과 다양성이 과학에 대한 태도 변화량에 정적으로(+) 유의미한 직접 효과가 있었다. 연구 결과에 기반하여, 2022 개정 과학과 교육과정이 고교학점제를 대비하여 '일반선택' 계열에서는 교과 지식의 구조를 견지한 물리, 화학, 생물, 지구과학 교과를 제시하고, '융합선택' 계열에서는 해당 교과들의 구조가 어느 정도 유지된 통합형 교과를 개발하며, '진로선택' 계열에서는 차별화된 심화성과 엄격성을 지닌 교과를 제공하는 방향을 제안하고 지지하였다.

Keywords

References

  1. Burnham, K. P., & Anderson, D. R. (2004). Multimodel inference: Understanding AIC and BIC in model selection. Sociological Methods & Research, 33(2), 261-304. https://doi.org/10.1177/0049124104268644
  2. Chon, K. H., & Kim, J. Y. (2017). An analysis on the academic achievement trends based on the college admission types using latent growth models. CNU Journal of Educational Studies, 38(1), 243-263. https://doi.org/10.18612/cnujes.2017.38.1.243
  3. Gardner, P. L. (1975). Attitudes to science: A review. Studies in Science Education, 2(1), 1-41. https://doi.org/10.1080/03057267508559818
  4. Geroge, R. (2000). Measuring change in students' attitudes toward science over time: an application of latent variable growth modeling. Journal of Science Education and Technology, 9(3), 213-225. https://doi.org/10.1023/A:1009491500456
  5. Hu, L. T., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3(4), 424-453. https://doi.org/10.1037/1082-989X.3.4.424
  6. Jo, K. -h., Choi, J., & Cho, H. S. (2012). High school students' opinions on choosing their academic track and elective courses for science and mathematics. Journal of Research in Curriculum Instruction, 16(3), 839-857. https://doi.org/10.24231/rici.2012.16.3.839
  7. Kim, H., Bae, S., & Park, J. (2017). Analysis of the causes of decrease in the number of students taking Chemistry I in the CSAT by analyzing Chemistry I question in the CSAT and the recognition survey of students and teachers. Journal of the Korean Chemical Society, 61(6), 378-387. https://doi.org/10.5012/JKCS.2017.61.6.378
  8. Kim, S. (2014). An analysis of general education high school students' English achievement. Journal of Research in Curriculum Instruction, 18(4), 1261-1280. https://doi.org/10.24231/rici.2014.18.4.1261
  9. Kim, Y., & Kwak, Y. (2021). Research on resconstruction of Earth Science elective courses. Journal of Korean Society of Earth Science Education, 13(1), 40-52. https://doi.org/10.15523/JKSESE.2020.13.1.40
  10. Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling (4th ed.). New York, NY: Guilford publications.
  11. Ministry of Education [MOE]. (1997). Science curricular. Seoul: Author.
  12. Ministry of Education, Science, and Technology [MEST]. (2010). Press release for the grading result of College Scholastic Ability Test for 2011. Seoul: Author.
  13. Ministry of Education [MOE]. (2015). Science curricular. Sejong: Author.
  14. Ministry of Education [MOE]. (2018a). Press release for 「The college entrance policy forum for discussing subject structure and coverage of the College Scholastic Ability Test for 2022」. Sejong: Author.
  15. Ministry of Education [MOE]. (2018b). Press release for 「The announcement of plans for revising college entrance policy for 2022 and directions for reforming high school education」. Sejong: Author.
  16. Ministry of Education [MOE]. (2020). Press release for the grading result of College Scholastic Ability Test for 2021. Sejong: Author.
  17. Ministry of Education [MOE]. (2021). Plans for proceeding future curriculum with peoples. Sejong: Author.
  18. Kwak, Y. (2021). Ways to restructure science convergence elective courses in preparation for the high school credit system and the 2022 Revised Curriculum. Journal of Korean Society of Earth Science Education, 14(2), 112-122. https://doi.org/10.15523/JKSESE.2021.14.2.112
  19. Lee, G.-G., & Hong, H.-G. (2018). Educational data mining regarding selection of advanced science subject in CSAT: Using the KEEP 2005-2009 data. Journal of Vocational Education & Training, 21(3), 191-224. https://doi.org/10.36907/KRIVET.2018.21.3.191
  20. Lee, H. (2010). The longitudinal study on academic achievement of mathematic and scientific subject. Journal of Science Education, 34(1), 1-11. https://doi.org/10.21796/jse.2010.34.1.1
  21. Lee, H., & Chung, H. (2020). The longitudinal relationship among reading activity, career maturity, and self-directed learning in adolescents using multivariate latent growth modeling. Secondary Education Research, 68(2), 389-412.
  22. Lee, H., & Noh, S. (2013). Advanced Statistical Analysis (2nd ed.). Goyang: Moonwoo.
  23. Lee, I., Kwak, Y. (2021). Ways to restructure science elective courses in preparation for the high school credit system and the 2022 Revised Curriculum. Journal of the Korean Association for Science Education, 41(2), 145-154. https://doi.org/10.14697/JKASE.2021.41.2.145
  24. Lee, I., Kwak, Y., & Cho, H. (2019). A survey research on science and engineering college students' perception on completing prerequisite science courses in high school. Journal of Science Education, 43(2), 195-206. https://doi.org/10.21796/jse.2019.43.2.195
  25. Lee, S. H., & Choi, H. (2013). What makes students select Physics I on the College Scholastic Ability Test? The Journal of Curriculum and Evaluation, 16(1), 231-251. https://doi.org/10.29221/jce.2013.16.1.231
  26. Leem, Y. W., & Kim, Y.-S. (2013). A historical study on the Korean science curriculum for the elementary and secondary schools. Biology Education, 41(3), 483-503. https://doi.org/10.15717/bioedu.2013.41.3.483
  27. Meredith, W., & Tisak, J. (1990). Latent curve analysis. Psychometrika, 55(1), 107-122. https://doi.org/10.1007/BF02294746
  28. Oh, P. S., & Han, M. (2021). A review of the history of and recent trends on emotion research in science education. Journal of the Korean Association for Science Education, 41(2), 103-114. https://doi.org/10.14697/JKASE.2021.41.2.103
  29. Organisation for Economic Co-operation and Development [OECD]. (2019). OECD future of education and skills 2030: OECD learning compass 2030. Paris, France: Author.
  30. Shin, M.-J., & Song, B.-H. (2008). Different perceptions of students and teachers to the elective subject-oriented science education system. Secondary Education Research, 56(2), 465-490. https://doi.org/10.25152/ser.2008.56.2.465
  31. Shin, S., Rachmatullah, A., Ha, M., & Lee, J.-K. (2018). A longitudinal trajectory of science learning motivation in Korean high school students. Journal of Baltic Science Education, 17(4), 674-687. https://doi.org/10.33225/jbse/18.17.674
  32. Shin, Y. (2021). The process of competence-fostering science curricular restructuring and ways of elementary-secondary science curricular content. in Proceedings of the Public Hearing for Competence-fostering Science Curricular Restructuring Research.
  33. So, K. (2017). Understanding Curriculum. Paju: Kyoyookbook.
  34. White, J. (2011). The invention of the secondary curriculum. New York, NY: Palgrave Macmillan.
  35. Woo, J. (2012). The concept and understanding of structural equation model. Seoul: Hannarae.
  36. Yeo, S., & Park, S. (2012). An application of latent growth modeling: Use of curriculum-based measurement as longitudinal data. Asian Journal of Education, 13(4), 247-273. https://doi.org/10.15753/aje.2012.13.4.011
  37. Yoo, M., & Shin, D. (2013). Trends in high school students' selection of science subjects: Focusing on Earth Science. Journal of Research in Curriculum Instruction, 17(2), 595-618. https://doi.org/10.24231/rici.2013.17.2.595