Journal of Educational Innovation Research 2019, Vol. 29, No. 1, pp DOI: - K * The Analysis

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1 Journal of Educational Innovation Research 2019, Vol. 29, No. 1, pp DOI: - K * The Analysis on the Casual Model between Higher Education Learning Outcomes and the factors - Focusing on a private, small-scale provincial university Purpose: This study aimed to examine the elements that universities should focus on to strengthen the quality of their high-level education and achieve growth as small-scale competitive universities. To this end, the study conducted an analysis of the factors that impact the learning outcomes of small-scale, provincial university. Method: With a pool of 600 students presently attending a small-scale, four-year university located in Busan, this study analyzed the factors that impact the learning outcomes using a structure equation model analysis and multi-group SEM. Results: First, the study found that the level of satisfaction toward the quality of lectures had a statistically significant impact on students self-directed learning ability and academic achievement, students interaction with professors and academic ability and class attitude. Their participation in non-curriculum programs significantly impacted their self-directed learning ability, their attitude toward classes and their learning outcomes. Second, self-directed learning ability significantly impacted their attitude toward classes and their learning outcomes, while their attitude toward classes significantly impacted their learning outcomes. Third, There was a significant difference between the humanities, social sciences and the science, nature sciences. Conclusion: Small provincial universities need to collaborate with community organizations, exchange with other universities, organically cooperate among members of the campus, and carefully designed policies and institutions. Key words : Learning outcomes, Self-directed learning ability, Interaction with Professors, Quality of Lectures * Corresponding Author: Yoon, Hae-Rim. Kosin University, Center for Educational Quality Enhancement, 194 Wachi-ro, Yeongdo-Gu, Busan, Korea @kosin.ac.kr

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10 ,,,,, 2 (two step approach)., X = , df=120, p=.000, TLI=.956, CFI=.965, NFI=.947, IFI=.965 RMSEA=.054. (, 2013). 1, p < -2> *** (.055) *** (.057) *** (.056) *** (.029).985 *** (.034) *** (.084).434 *** (.050) *** (.063) 1,.966 *** (.036).978 *** (.038) *** (.092).733 *** (.066) Note:, *** p<.001, X = , df=122, p=.000, TLI=.955, CFI=.964,

11 NFI=.945, IFI=.965, RMSEA=.054,.,,.,,,,,,,,,,..,. K.,.,.,,,.,,,,.,..,,.., (.510), (.212), (185), (.095). (.365), (.276), (.188). (.530), (.164), (.125). < -3>.

12 b(s.e.) β.268 *** (.073) *** (.034) *** (.054) *** (.072) * (.047) * (.071) (.094) ** (.042) *** (.042) (.047) * (.027) *** (.073) *** (.042).750 Note:, * p<.05, ** p<.01, *** p<.001 (,,,, 2017;,,, 2016;,, 2009;, 2018;,, 2009),,,, K ( vs ) (multi-group SEM).,,. χ = , df=244, p=.000, CFI=.959, TLI=.949, RMSEA=.041, χ = , df=256, p=.000, CFI=.959, TLI=.951, RMSEA=.040. χ = , df=268, p=.000, CFI=.959, TLI=.953, RMSEA=.039.,.,,. K

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14 ( ) Note:, * p<.05, ** p<.01, *** p<.001 b(s.e.) β b(s.e.) β (.090) (.074) (.105) (.182) *.192 *.173 (.064) (.081) ** (.060) (.064) (.060) (.079) *.040 (.035) (.042) ***.371 **.501 (.082) (.128) ***.505 ***.710 (.057) (.056).790.,,,,..,,.,,.,, (,,, 2011;, 2014;, 2016;, 2013), (, 2005;, 2014;, 2018).,

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18 (3), , (2011). : 5. (2), , (2016)., , (2009).. (1), ,, (2007).,, (2008).. (1) ,,, (2013) (2011).. (3), (2016) , (2014).,,. (7), , (2016)., (2005).,..,, (2008).. (1), (2017). L. (6), , (2012). :. (2), , (2010).. (3), ,, (2011). :. (4), (2012). PLS SES,,, ,, (2011).

19 . (4), , (2015).. (1), (2014). ( ) , (2006). e-learning. (1), (2013). -S. (1), (2013).,, ,,, (2016). :. (4), , (2017).. (4), doi: /kei (2018).. (4), , (2009). :. (1), , (2010). - :. (2), (2007) Anaya, G., & Cole, D. G. (2001). Latina/o student achievement: Exploring the influence of student-faculty interactions on college grades. Journal of College Student Development, 41(2), 3-14 Astin, A. W. (1993). What Matters in College? Four Critical Years. San Francisco: Jossey-Bass. Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238. Cheng, G., & Chau, J. (2013). Exploring the relationship between students' self-regulated learning ability and their e-portfolio achievement. Internet and Higher Education, 17, doi: /j.iheduc Chickering, A. W., & Gamson, Z. F. (1987). Seven principles for good practice in undergraduate education. AAHE Bulletin, 39(7), 3-7. Curran, P. J., West, S. G., & Finch, J. F. (1996). The robustness of test statistics to nonnormality and

20 specification error in confirmatory factor analysis. Psychological methods, 1(1), 16. Ewell, P. (2005). Applying learning outcomes concepts to higher education: Anoverview. Prepared for the University Grants Committee. Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: a multidisciplinary Journal, 6(1), Kuh, G, D., & Hu, S. (2001). The effects of student-faculty interaction in the 1990s. The Review of Higher Education, 24(3), Nusche, D. (2008). Assessment of learning outcomes in higher education: A comparative review of selected practices. OECD Education Working Paper 15. Paris, S. G., & Paris, A. H. (2001). Classroom applications of research on self-regulated learning. Educational Psychologist, 36(2), Tucker, L. R., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38(1), Zimmerman, B. J. (2001). Theories of self-regulated learning and academic achievement: An overview and analysis. In B. J. Zimmerman & D. H. Schunk (Eds.), Self-regulated learning and academic achievement: Theoretical Perspectives, 2, Lounsbury, J. W., Sundstrom, E., Loveland, J. M., & Gibson, L. W. (2003). Intelligence, Big Five personality traits, and work drive as predictors of course grade. Personality and individual differences, 35(6), Zhang, L. F. (2003). Does the big five predict learning approaches?. Personality and individual differences, 34(8), : / : / :

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Journal of Educational Innovation Research 2019, Vol. 29, No. 2, pp DOI: 3 * Effects of 9th

Journal of Educational Innovation Research 2019, Vol. 29, No. 2, pp.357-378 DOI: http://dx.doi.org/10.21024/pnuedi.29.2.201906.357 3 * Effects of 9th Grade Students Participation in Career Curriculum Cluster