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

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Journal of Educational Innovation Research 2019, Vol. 29, No. 1, pp.377-397 DOI: http://dx.doi.org/10.21024/pnuedi.29.1.201903.377 - 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 * 2018. Corresponding Author: Yoon, Hae-Rim. Kosin University, Center for Educational Quality Enhancement, 194 Wachi-ro, Yeongdo-Gu, Busan, Korea. e-mail: 214040@kosin.ac.kr

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,,, (,, ).,, (2005),,,,,, (2016),,., (,,, 2016).. Astin(1993),,, (2014),. (2018),,. (2005), (2014) -,, (2010) -, -.,, (2011),,,. Anaya Cole(2001),,, Kuh Hu(2001) - (,, ).,, -. Chickering Gamson(1987),,,,,, (, 2014 )., (2016),. (2014)

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. 4 K. K 2018 8 31 9 2 600, 2018 2 K 4,962 12.1%. 1 2, 3, 4., 182 (30.3%), 418 (69.7%) K, 306 (51.0%), 294 (49.0%). < -1>.

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. SPSS 21.0 AMOS 21.0... 5,,,, 3, 2.,,. (skewness) (kurtosis), 2, 4 (Curran, West, & Finch, 1996),. ** p<.01 1.559 ** 1.540 **.467 ** 1.508 **.543 **.553 ** 1.207 **.217 **.038.124 ** 1.443 **.570 **.249 **.362 **.222 ** 1 3.29 3.75 3.76 3.81 2.12 3.33.662.742.816.949.944.753.545.016 -.194 -.476.690.034.281 -.481 -.335 -.345 -.260.262

,,,,, 2 (two step approach)., X =329.736, df=120, p=.000, TLI=.956, CFI=.965, NFI=.947, IFI=.965 RMSEA=.054. (, 2013). 1, p.001.. < -2>. 1 1.125 *** (.055) 1.114 *** (.057) 1.078 *** (.056) 1.978 *** (.029).985 *** (.034) 1 1.108 *** (.084).434 *** (.050) 1.823 *** (.063) 1,.966 *** (.036).978 *** (.038) 1 1.115 *** (.092).733 *** (.066) Note:, *** p<.001, X =336.564, df=122, p=.000, TLI=.955, CFI=.964,

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

b(s.e.) β.268 *** (.073).276.157 *** (.034).188.283 *** (.054).365.611 *** (.072).530.120 * (.047).125.147 * (.071).164 -.034(.094) -.030.151 ** (.042).185.150 *** (.042).212 -.036(.047) -.057.064 * (.027).095.402 *** (.073).510.509 *** (.042).750 Note:, * p<.05, ** p<.01, *** p<.001 (,,,, 2017;,,, 2016;,, 2009;, 2018;,, 2009),,,, K ( vs ) (multi-group SEM).,,. χ =490.979, df=244, p=.000, CFI=.959, TLI=.949, RMSEA=.041, χ =502.089, df=256, p=.000, CFI=.959, TLI=.951, RMSEA=.040. χ =514.516, df=268, p=.000, CFI=.959, TLI=.953, RMSEA=.039.,.,,. K

.,,. K.,,..,,..,,. K., (.504,.464)., (.472), (.553)., (.441). < -4>. b(s.e.) β b(s.e.) β.166.421 **.169 (.085) (.133).441.133 **.181 ***.162 (.046) (.048).220.382 ***.151.472 (.068) (.093).203.631 ***.619 ***.553 (.089) (.114).536.138 *.094.147 (.059) (.074).099

( ) Note:, * p<.05, ** p<.01, *** p<.001 b(s.e.) β b(s.e.) β.103.220.111 (.090) (.074).257.072 -.217.064 (.105) (.182) -.197.140 *.192 *.173 (.064) (.081).229.191 **.106.269 (.060) (.064).146 -.033 -.037 -.050 (.060) (.079) -.060.027.107 *.040 (.035) (.042).155.398 ***.371 **.501 (.082) (.128).464.504 ***.505 ***.710 (.057) (.056).790.,,,,..,,.,,.,, (,,, 2011;, 2014;, 2016;, 2013), (, 2005;, 2014;, 2018).,

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(3), 41-65., (2011). : 5. (2), 199-213., (2016).,. 187-213., (2009).. (1), 59-80.,, (2007).,,. 1-18. (2008).. (1). 49-62.,,, (2013).. 275-296. (2011).. (3), 27-50. (2016).. 899-918., (2014).,,. (7), 167-185., (2016).,. 383-402. (2005).,..,, (2008).. (1), 287-313. (2017). L. (6), 303-332., (2012). :. (2), 175-195., (2010).. (3), 61-82.,, (2011). :. (4), 23-42. (2012). PLS SES,,,. 203-243.,, (2011).

. (4), 319-337., (2015).. (1), 105-127. (2014). ( ). 83-107., (2006). e-learning. (1), 1-21. (2013). -S. (1), 269-292. (2013).,,. 53-83.,,, (2016). :. (4), 89-107., (2017).. (4), 149-168. doi: 10.22327/kei.2017.35.4.149 (2018).. (4), 31-55., (2009). :. (1), 199-222., (2010). - :. (2), 131-154. (2007).. 355-374. 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, 9-15. doi: 10.1016/j.iheduc.2012.09.005 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

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), 1-55. Kuh, G, D., & Hu, S. (2001). The effects of student-faculty interaction in the 1990s. The Review of Higher Education, 24(3), 309-332. 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), 89-101. Tucker, L. R., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38(1), 1-10. 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, 1 37. 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), 1231-1239. Zhang, L. F. (2003). Does the big five predict learning approaches?. Personality and individual differences, 34(8), 1431-1446. : 2019.01.31. / : 2019.02.07. / : 2019.03.20.

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