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Longitudinal analysis of the direct and indirect influence of academic self-concept and academic support of teachers and parents on academic achievement in mathematics

학업적 자아개념 및 교사와 부모의 학업적 지원이 수학 학업성취도에 미치는 직·간접적인 영향력에 대한 종단적 분석

  • Received : 2022.02.10
  • Accepted : 2022.02.16
  • Published : 2022.02.28

Abstract

This study used the data of students from the 6th grade to the 3rd grade of middle schoolin the Korean Educational Longitudinal Study 2013 and classified them into subgroups with similar longitudinal changes in math academic achievement. In addition, the influence of longitudinal changes in the group's academic self-concept and teachers and parents academic support on the longitudinal changes in math academic achievement were analyzed, either directly or indirectly. As a result of the analysis, it was found that the academic self-concept of each group had a positive influence on the academic achievement in mathematics. In addition, the academic support of teachers and parents was found to have a positive influence on the academic achievement in mathematics through the mediating of the academic self-concept. In terms of direct and indirect influence on academic self-concept and math vertical scale scores, it was found that teachers' academic support had more influence than parents' academic support. The educational implications of these points were discussed.

본 연구는 한국교육종단연구2013의 초등학교 6학년부터 중학교 3학년까지의 학생 데이터들을 활용하여 수학 학업성취도의 종단적인 변화양상에 따른 학업적 자아개념 및 교사와 부모의 학업적 지원이 수학 학업성취도에 미치는 직·간접적인 영향력을 종단적으로 살펴보았다. 분석결과, 그룹별 학업적 자아개념은 수학 학업성취도에 긍정적인 영향력을 미치는 것으로 나타났으며, 교사와 부모의 학업적 지원은 학업적 자아개념을 매개로 하여 수학 학업성취도에 긍정적인 영향력을 미치는 것으로 나타났다. 또한, 학업적 자아개념과 수학 수직척도점수에 미치는 직·간접적인 영향력은 부모의 학업적 지원 보다 교사의 학업적 지원이 더 많은 영향력을 미치는 것으로 나타났다. 이러한 점에 따른 교육적인 함의점을 논의하였다.

Keywords

References

  1. An, H. J. & Chung, M. K. (2014). The effects of adolescents'academic self concept, intrinsic motivation, parental support on university adjustment mediated by future goal. The Korea educational review, 20(2), 277-298.
  2. Bae, B. R. (2016). Mplus 7.0 structural equation modeling. Cheongnam publishing.
  3. Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long(Eds), Testing structural equation models(pp. 136-162). Newbury Park, ca: SAGE.
  4. Byrne, B. M. (1984). The general academic self-concept monological network: A review of construct validation research. Review of Educational Research, 5, 427-256. https://doi.org/10.3102/00346543054003427
  5. Celeux, G., & Soromenho, G. (1996) An entropy criterion for assessing the number of cluster in a mixture model. Journal of Classification, 13, 195-212. https://doi.org/10.1007/BF01246098
  6. Chapman, J. M., Lambourne, R., & Silva, P. A. (1990). Some antecedents of academic self-concept: A Longitudinal study. British Journal Educational Psychology, 60, 142-152. https://doi.org/10.1111/j.2044-8279.1990.tb00931.x
  7. Chen, J. J. L. (2008). Grade-level differences: Relations of parental, teacher and peer support to academic engagement and achievement among Hong Kong students. School psychology international, 29(2), 183-198. https://doi.org/10.1177/0143034308090059
  8. Choi, C. K. (1997). The Self-Concept, Stress, and Delinquency of Adolescents. Master's thesis, Hanyang University Graduate School of Education.
  9. Choi, H. J., & Cho, M. H. (2014). Identifying Latent Classes in Adolescent's Self-Determination Motivation and Testing Determinants of Classes. The Korean Journal of School Psychology, 11(1), 253-274. https://doi.org/10.16983/KJSP.2014.11.1.253
  10. Choi, M. S. (2011). The Relationships of Parential Involvement of Learning, Academic Self-concept of Adolescence and Self-Determination of Adolescence. Master's thesis, Catholic University Graduate School of Counseling Psychology.
  11. Colarossi, L. G., & Eccles, J. S. (2003). Differential effects of support providers on adolescents' mental health. Social Work Research, 27, 19-30. https://doi.org/10.1093/swr/27.1.19
  12. Curran, P. J., West, S. G., & Finch, J. F. (1996). The robustness of test statistics to nonnormality and specification error in confirmatory factory analysis. Psychological Methods, 1(1), 16-29. https://doi.org/10.1037/1082-989X.1.1.16
  13. Duncan, T. E., & Duncan, S. C. (2004). An introduction to latent growth curve modeling. Behavior Therapy, 35(2), 333-363. https://doi.org/10.1016/S0005-7894(04)80042-X
  14. Duncan, T. E., Duncan, S. C., & Strycker, L. A. (2006). An introduction to latent variable growth curve modeling: concepts, issues, and applications. Mahwah, N.J. : Lawrence Erlbaum Associates.
  15. Go, Y. J. (2018). A study on analysis of actual state of mathmatics renouncers and treatment at the renouncer's level, Master's thesis, Ulsan University Graduate School of Education.
  16. Gonzalez-Pienda, J. A., Nunez, J. C., Gonzalez-Pumariega, S., Alvarez, L., Roces, C., & Garcia, M. (2002). A structural equation model of parental involvement, motivational and aptitudinal characteristics, and academic achievement. Journal of Experimental Education, 70,257-287. https://doi.org/10.1080/00220970209599509
  17. Gottfried, A. E., Fleming, J. S., & Gottfried, A. W. (1994). Role of Parental Motivational Practices in Children's Academic Intrinsic Motivation and Achievement. Journal of Educational Psychology 86, 104-113. https://doi.org/10.1037/0022-0663.86.1.104
  18. Guay, F., Larose, S., & Boivin, M. (2004). Academic self-concept and educational attainment level: A ten year longitudinal study. Self and Identity, 3(1), 56-68.
  19. Harter, S. (1983). Developmental perspectives on the self-esteem. In E. H. Hetherington (Ed.), Hand-book of child psychology: Vol. 4. Socialization, personality, and social development (pp. 275-385). New York: Wiley.
  20. Hattie, J. (2003). Teachers make a difference. What is the research evidence?. Paper presented at the Australian Council for Educational Research. Melbourne, Victoria.
  21. Hong, S. U. (2009). Analysis of large-scale academic achievement evaluation data using growth model. Collection of the 3rd KICE Curriculum Evaluation Policy Forum.
  22. Hu, L., & Bentler, P. (1999). Cutoff criteria for fit indices in covariance structure analysis: conventional criteria versus new alternatives. Structural Equation Modeling, 6,1-55. https://doi.org/10.1080/10705519909540118
  23. James, W. (1980). Principles of psychology. New York: Holt.
  24. Jeon, H. O. (2007). The Relationship among Perceived Parental Academic Achievement Pressure, Academic Self-Concept and Academic Achievement of Secondary School Students. Master's thesis, Kangwon National University Graduate School of Education.
  25. Jo, H. I. & Son, S. K. (2011). The Path Analysis among Parents' forced Social Comparison of Studies, Academic Stress, Academic Self-concept, and Academic Achievement. Journal of Future Oriented Youth Society, 8(2), 1-21.
  26. Kim, H. M., Kim, Y. S., & Han, S. Y. (2018). A Longitudinal Analysis on the Relationships Among Mathematics Academic Achievement, Affective Factors, and Shadow Education Participation, School Mathematics, 20(2), 287-306. https://doi.org/10.29275/sm.2018.06.20.2.287
  27. Kim, I. T., & Heo, N. J. (2004). An Examination of the Relationship Among Learners' Nonacademic Self-Concept, Learning Motivation and School-Related Adjustment. The Journal of Yeolin Education, 12(1), 75-96.
  28. Kim, J. H., & Seo, S. B. (2020). A Study on the Longitudinal Effect of Middle School Students' Self-Recognition, Academic Self-Efficacy, School Adjustment, and Academic Achievement. Journal of Learner-Centered Curriculum and Instruction, 20(10),365-383.
  29. Kim, J. H., Hong, S. H., & Kim, M. G. (2009).Writing a thesis with structural equations. Communication Books.
  30. Kim, J. W., & Kim, B. S. (2004). A Study on Relationship Between the Perceived Teacher's Characteristic and Academic Self-concept and Their Learning Attitude. The Journal of Child Education, 13(2), 253-262.
  31. Kim, J. W., Yang., J. Y., Lee, C. A., & Hong, S. H. (2019). Changes in Retiree's Depression after Retirement: Applying Growth Mixture Model, survey research, 20(1), 45-72. https://doi.org/10.20997/SR.20.1.3
  32. Kim, K. J. (1984). Effect of academic achievement and perceived parenting attitude on self-concept. Doctoral thesis, Chung-ang University.
  33. Kim, N. H. (2011). The Relationship between Student-Teacher Attachment Relationships and Academic Achievement mediated by Basic Psychological Needs and Academic Engagement: Differences in the Meaning and Functions of Teacher Support and Student-Teacher Attachment Relationships. Doctoral thesis, Hongik University.
  34. Kim, S. A. (2013). Effect of Support and Accomplishing Pressure of Parents and Teachers on Student' Self-Determination Motivation: Focusing on the Differences between Academic Achievement Groups. Master's thesis, Ewha Womans University.
  35. Kim, Y. B., Im, H. J., & Kim, N. O. (2012). An Analysis on Class- and Teacher-Level Variables Affecting Academic Achievement. Journal of Korean Education, 34(2), 27-49. https://doi.org/10.22804/JKE.2007.34.2.002
  36. Kim, Y. S. (2020). A longitudinal study on the effect of learner's internal and external factors on mathematics academic achievement: For middle and high school students. Doctoral thesis, Sungkyunkwan University.
  37. Kim, Y. S. (2021). A Longitudinal Study on the Influence of Learning Effort, Attitude, and Achievement Goal on Mathematics Academic Achievement: For elementary and secondary school students. Education of Primary School Mathematics, 24(1), 1-20. https://doi.org/10.7468/JKSMEC.2021.24.1.1
  38. Kline, R. B. (2005). Principles and Practice of Structural Equation Modeling. NY: The Guilford Press.
  39. Kline, R. B. (2010). Principles and Practice of Structural Equation Modeling. (Third ed.). NY: The Guilford Press.
  40. Korea Educational Development Institute [KEDI]. (2020). Data collection of the 14th Korean Educational Longitudinal Research Conference. Korea Educational Development Institute.
  41. Lee, J. H. (2016). Mediating Effedts of Self-Regulated Learning Ability in the Relation between Parent-child Relationships and Teacher-Student Relationships and Academic Self-Concept. Master's thesis, Kookmin University Graduate School of Education.
  42. Lee, K. S. (2021). The Influence of Instructor's Involvement and Achievement on Learning Continuation Intention in Programming Learning A Case Study of Programming Classes for Non-Majors. Culture and Convergence, 43(5), 129-147.
  43. Lee, M. A. (2006). The study of the effect of self-concept on academic achievement for college students. Journal of Education Evaluation, 19(1), 161-181.
  44. Lee, Y. M. (2018). The Effects of Grade 9 Students' Study Habits and School Adjustment on Academic Achievement. The Journal of Welfare and Counselling Education, 7(2), 217-238.
  45. MacCallum, R. C., & Kim, C. (2000). Modeling multi variate change. InT. D. Little, K. U. Schnabel, & U. Lindenberg (Eds.), Modeling Longitudinaland Multiple-Group Data: Practical Issues, Applied Approaches, and Specific Examples. Mahwah, NJ: Lawrence Erlbaum.
  46. MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling.Psychological Methods, 1(2), 130-149. https://doi.org/10.1037/1082-989X.1.2.130
  47. McLachlan, G., & Peel, D. (2000). Finite mixture models.New York: Wiley.
  48. Muijs, R. D. (1997). Symposium self-perception and performance: Predictors of academic achievement and academic self-concept: A longitudinal perspective. British Journal of Educational Psychology, 67, 263-277. https://doi.org/10.1111/j.2044-8279.1997.tb01243.x
  49. Mullis, I. V. S., Martin, M. O., Ruddock, G. J., O'Sullivin, C. Y., Arora, A., & Erberber, E. (2005). TIMSS 2007 Assessment Framework. TIMSS & PIRLS International Study Center, Lynch School of Education. Boston College.
  50. Muthen, B. (2004). Latent variable analysis: Growth mixture modeling and related techniques for longitudinal data. In D. Kaplan (Ed.), Handbook of quantitative methodology for the social sciences. 346-368. Newbury Park, CA: Sage Publications.
  51. Muthen, B. O., & Asparouhov, T. (2009). Growth mixture modeling: Analysis with non-Gaussian random effects. In Fitzmaurice, G., Davidian, M., Verbeke, G. & Molenberghs, G.(eds.), Longitudinal Data Analysis, pp.143-165. Boca Raton: Chapman & Hall/CRC Press.
  52. Muthen, B., & Muthen, L. K. (2000). Integrating person-centered and variable-centered analyses: Growth mixture modeling with latent trajectory classes. Alcoholism: Clinical and experimental research, 24(6), 882-891. https://doi.org/10.1111/j.1530-0277.2000.tb02070.x
  53. NCTM. (2000). Principles and Standards for School Mathmatics. Reston. VA: NCTM.
  54. No, G. S. (2014). Well-informed Thesis Statistical analysis. Han Bit Academy.
  55. Okada, H., Hirano, D., & Taniguchi, T. (2020). Negative symptoms in schizophrenia: modeling the role of experience factor and expression factor. Asian Journal of Psychiatry, 53, 102182. https://doi.org/10.1016/j.ajp.2020.102182
  56. Park, C. R. (2003). A study on the descent of the function-chapter in the middle school. Master's thesis, Mokpo University Graduate School of Education.
  57. Park, K. H. (2020). Korean Education Longitudinal Study 2013 (VIII): Survey Overview Report. Korea Educational Development Institute.
  58. Park, M. J. (2002). (The) relation of academic self-concept, self-efficacy and school-related adjustment. Master's thesis, Hongik University Graduate School of Education.
  59. Pascarella, E. T., & Terenzini, P. T. (2005). How College Affects Students: A Third Decade of Research. Volume 2. Jossey-Bass, An Imprint of Wiley. 10475 Crosspoint Blvd, Indianapolis, IN 46256.
  60. Pastor, D. A., Barron, K. E., Miller, B. J., & Davis, S. L. (2007). A latent profile analysis of college students' achievement goal orientation. Contemporary educational psychology, 32(1), 8-47. https://doi.org/10.1016/j.cedpsych.2006.10.003
  61. Purkey, W. W. (1970). Self-concept and school achievement .New Jersey: PrenticeHall, Inc.
  62. Purkey, W. W. (1974). Building self-concept in students and teachers. Unpublished paper, Univer. of Florida, Gainesville, FL.
  63. Shavelson, R. J., Hubner, J. J., & Stanton, G. C. (1976). self-concept: Validation of construct interpretation. Review of Educational Research, 46, 407-441. https://doi.org/10.3102/00346543046003407
  64. Sin, S. W. (2013). Predictors of Career Maturity in College Students. International Journal of Adult & Continuing Education, 16(1), 21-44.
  65. So, H. J., & Kim, B. (2009). Learning about problem based learning: Student teachers integrating technology, pedagogy and content knowledge. Australasia Journal of Educational Technology, 25(1), 101-116. https://doi.org/10.17232/KSET.25.4.101
  66. Son, Y. H. (2016). The Longitudinal Effects of student's Private Tutoring Time and Self-Studying Time on Longitudinal Change of Academic Achievement. Master's thesis, Seoul National University.
  67. Song, I. S. (1982). The dimensionality and relationship between home enviroment, self-concept and academic achievement. Doctrial dissertation, University of New England.
  68. Song, I. S. (2004). The Identification and Measurement of Self-Concept. Journal of Education Evaluation, 17(2), 1-26.
  69. Song, I. S. (2013). Self-Concept. Seoul: Hakjisa.
  70. Song, J. S. (2015). SPSS/AMOS statistical analysis method required for thesis writing. 21st century history.
  71. Song, S. J., Kim, J. M. & Nam, K. J. Y. (2012). The Effects of Adolescents'Experience of Student-Council Activities on Their Self-Concept. The Journal of Yeolin Education, 20(1), 117-139.
  72. Sternberg, R. J., & Wiliams, W. M. (2013). Educational Psychology (Translated by Kim, J. S., Shin, K. S., & Yoo, S. H). Sternberg's Psychology of Education. Seoul: Sigma Press. (publication 2009).
  73. Wentzel, K. R. (1998). Social Relationships and Motivation in Middle School: The Role of Parents, Teachers, and Peers'. Journal of Educational Psychology, 90, 202-09. https://doi.org/10.1037/0022-0663.90.2.202
  74. Yang, A. K., & Cho, H. J. (2009). An Analysis on the Influence of Self-Regulated Learning upon Academic Achievement. The Journal of korean educational forum, 8(3), 61-82.
  75. Yu, C. Y. (2002). Evaluating cutoff criteria of model fit indices for latent variable models with binary and continuous outcomes. Doctoral dissertation, University of California, Los Angeles.