Modelling IS Student Retention in Taiwan: Extending Tinto and Bean’s Model with Self-Efficacy

References

• AksenovaS. S., ZhangD., & LuM. (2006). Enrollment prediction through data mining. Paper presented at the IEEE conference on Information reuse and integration.
   Google Scholar
• AstinA. W., & OsegueraL. (2002). Degree attainment rates at American colleges and universities. Los Angeles, CA: UCLA graduate school of education higher education research Inst.
   Google Scholar
• BanduraA. (1989). Human agency in social cognitive theory. American psychologist, 9, 1175-1183.
   Google Scholar
• BanduraA. (1997). Self-efficacy: the exercise of control. New York: Freeman.
   Google Scholar
• BankB. J., BiddleB. J., & SlavingsR. L. (1990). Effects of peer, faculty, and parental influences on student persistence. Sociology of education, 63, 209-225.
   Google Scholar
• BeanJ. P. (1980). Dropouts and turnover: The synthesis and test of a causal model of student attrition. Research in higher education, 12(2), 155-187.
   Web of Science ®Google Scholar
• BeanJ. P. (1983). The application of a model of turnover in work organizations to the student attrition process. The Review of Higher Education, 6(2), 129-148.
   Google Scholar
• BeanJ. P., & EatonS. B. (2001). The psychology underlying successful retention practices. Journal of college student retention, 3(1), 73.
   Google Scholar
• BeanJ. P., & MetznerB. S. (1985). A conceptual model of nontraditional undergraduate student attrition. Review of educational research, 55, 485-540.
   Web of Science ®Google Scholar
• BelchH. A., GebelM., & MaasG. M. (2001). Relationship between student recreation complex use, academic performance, and persistence of first-time freshmen. NASPA Journal, 38(2), 254-268.
   Google Scholar
• BergerJ. B., & BraxtonJ. M. (1998). Revising Tinto’s interactionalist theory of student departure through theory elaboration: examining the role of organizational attributes in the persistence process. Research in higher education, 39(2), 103-119.
   Web of Science ®Google Scholar
• BiggersM., BrauerA., & YilmazT. (2008, March 12-15). Student perceptions of computer science: a retention study comparing graduating seniors vs. CS leavers. Paper presented at the SIGCSE, Portland, Oregon, USA.
   Google Scholar
• BraunsteinA., McGrathM., & PescatriceD. (2001). Measuring the impact of financial factors on college persistence. Journal of college student retention, 2(3), 191-203.
   Google Scholar
• BraxtonJ. M. (2000). Reworking the student departure puzzle. Nashville: Vanderbilt University Press.
   Google Scholar
• BraxtonJ. M., HirschyA. S., & McClendonS. A. (2004). Understanding and reducing college student departure. San Francisco: Jossey-Bass.
   Google Scholar
• BraxtonJ. M., MilemJ. F., & SullivanA. S. (2000). The influence of active learning on the college student departure process. Journal of higher education, 71(5), 569-590.
   Web of Science ®Google Scholar
• BraxtonJ. M., SullivanA. S., & JohnsonR. (1997). Higher education: handbook of theory of research (Vol. 12). New York: Agathon press.
   Google Scholar
• CabreraA. F., CastanedaM. B., NoraA., & HengstlerD. (1992). The convergence between two theories of college persistence. The journal of higher education, 63(2), 143-167.
   Web of Science ®Google Scholar
• CabreraA. F., NoraA., & CastanedaM. B. (1993). Structural equations modeling test of an integrated model of student retention. The journal of higher education, 64(2), 123-139.
   Web of Science ®Google Scholar
• ChinW. W. (1998). Issues and option on structural equation modeling. MIS quarterly, 22(1), 7-16.
   Web of Science ®Google Scholar
• CloseW., & SolbergS. (2008). Predicting achievement, distress, and retention among lower-income Latino youth. Journal of vocational behavior, 72, 31-41.
   Web of Science ®Google Scholar
• CorkR. D., DetmerW. M., & FriedmanC. P. (1998). Development and initial validation of an instrument to measure physicians’ use of, knowledge about, and attitudes toward computers. Journal of the American medical informatics association, 5(2), 164-176.
   PubMed Web of Science ®Google Scholar
• DenzinN. (2009). The research act: A theoretical introduction to sociological methods: Aldine De Gruyter.
   Google Scholar
• Department of Education, T. a. Y. A. (2000). Students 1999: selected higher education statistics. Canberra: Commonwealth government.
   Google Scholar
• DeShieldsO. W., KaraA., & KaynakE. (2005). Determinants of business student satisfaction and retention in higher education: applying Herzberg’s two-factor theory. International journal of educational management, 19(2), 128-139.
   Google Scholar
• DiamantopoulosA., & SiguawJ. A. (2000). Introducing LISREL:a guide for the uninitiated. Thousand Oaks, CA: Sage.
   Google Scholar
• EthingtonC. (1990). A psychological model of student persistence. Research in higher education, 31(3), 279-293.
   Web of Science ®Google Scholar
• GeorgeJ., ValacichJ., & ValorJ. (2005). Does information systems still matter? Lessons for a maturing discipline. Paper presented at the Communications of the association for information systems.
   Google Scholar
• GrangerM. J., DickG., JacobsonC. M., & SlykeC. V. (2007). Information systems enrollments: challenges and strategies. Journal of Information systems education, 18(3), 303.
   Google Scholar
• HairJ. F., AndersonR. E., TathamR. L., & BlackW. C. (2006). Multivariate data analysis. Upper saddle river, NJ: Prentice Hall.
   Google Scholar
• JohnsonJ. L. (2000-1). Learning communities and special efforts in the retention of University students: what works, what doesn’t and is the return worth the investment? Journal of college student retention, 2(3), 219-238.
   Google Scholar
• JoreskogK. G., & SorbomD. (1989). LISREL7: users’ reference guide. Chicago, IL: Scientific software international.
   Google Scholar
• KraemerB. A. (1997). The academic and social integration of Hispanic students into college. The review of higher education, 20(2), 163-178.
   Web of Science ®Google Scholar
• KumerN., ScheerL. K., & SteenkampJ. (1995). The effects of supplier fairness on vulnerable resellers. Journal of marketing research, 32(1), 54-65.
   Web of Science ®Google Scholar
• LentR. W., BrownS. D., & LarkinK. C. (1984). Relation of self-efficacy expectations to academic achievement and persistence. Journal of counseling psychology, 31, 356-363.
   Web of Science ®Google Scholar
• LentR. W., BrownS. D., & LarkinK. C. (1986). Self-efficacy in the prediction of academic performance and perceived career options. Journal of counseling psychology, 33, 265-269.
   Web of Science ®Google Scholar
• MannanM. A. (2007). Student attrition and academic and social integration: application of Tinto’s model at the university of Papua New Guinea. Higher education, 53, 147-165.
   Web of Science ®Google Scholar
• McConnellE. S., Lekan-RutledgeD., NevidjonB., & AndersonR. (2004). Complexity theory: a long term care specialty practice exemplar for the education of advanced practice nurses. Journal of nursing education, 43(2), 84-87.
   PubMed Web of Science ®Google Scholar
• McKenzieK., & SchweitzerR. (2001). Who succeeds at university? Factors predicting academic performance in first year Australian university students. Higher education research & development, 20(1), 21-33.
   Google Scholar
• Ministry of Education. (2010). The statistics of education. Retrieved from http://www.edu.tw/files/site_content/B0013/98_all_level.doc.
   Google Scholar
• MortensonT. G. (1997). Actual versus predicted institutional graduation rates for 1100 colleges and universities. Postsecondary education opportunity, 58, 1-24.
   Google Scholar
• MortensonT. G. (1998). Institutional graduation rates by control, academic selectivity and degree level 1983 to 1998. Postsecondary education opportunity, 73, 1-10.
   Google Scholar
• MoultonK. D., BrownS. D., & LentR. W. (1991). Relation of self-efficacy beliefs to academic outcomes: a meta-analytic investigation. Journal of counseling psychology, 38(1), 30-38.
   Web of Science ®Google Scholar
• MukherjeeA. (2000). Effective use of in-class mini case analysis for discovery learning in an undergraduate MIS course. The journal of computer information systems, 40(3), 15-23.
   Web of Science ®Google Scholar
• MunroB. H. (1981). Dropouts from higher education: Path analysis of a national sample. American Educational Research Journal, 133-141.
   Web of Science ®Google Scholar
• Mussat-WhitlowB. J. (2004). Understanding retention at a historically black college and university: a logistic regression and path analytic approach. PhD, University of North Carolina, Greensboro.
   Google Scholar
• NettlesM. T., GosmanE. J., ThoenyA. R., & DandridgeB. A. (1985). The causes and consequences of college students’ performance: a focus on black and white students’ attrition rate, progression rates and grade point averages: Tennessee higher education commission.
   Google Scholar
• NoraA. (1987). Determinants of retention among Chicano college students: A structural model Research in higher education, 26(1), 31-58.
   Web of Science ®Google Scholar
• NoraA., & RendonL. I. (1990). Determinants of predisposition to transfer among community college students: A structural model. Research in higher education, 31(3), 235-255.
   Web of Science ®Google Scholar
• PajaresF. (1996). Self-efficacy beliefs in academic settings. Review of educational research, 66(4), 543-578.
   Web of Science ®Google Scholar
• PascarellaE. T. (1980). Student-faculty informal contact and college outcomes. Review of educational research, 50(4), 545-595.
   Web of Science ®Google Scholar
• PascarellaE. T., & ChapmanD. W. (1983). Validation of a theoretical model of college withdrawal: Interaction effects in a multi-institutional sample. Research in Higher Education, 19(1), 25-48.
   Web of Science ®Google Scholar
• PascarellaE. T., SmartJ., & EthingtonC. (1986). Long-term persistence of two-year college students. Research in higher education, 24(1), 4-71.
   Google Scholar
• PascarellaE. T., & TerenziniP. T. (1980). Predicting freshmen persistence & voluntary dropout decision from a theoretical model. Journal of higher education, 51(1), 60-75.
   Web of Science ®Google Scholar
• SchreiberJ. B., NoraA., StageF. K., BarlowE. A., & KingJ. (2006). Reporting structural equation modeling and confirmatory factor analysis results: a review Journal of educational research & policy studies, 99(6), 323-337.
   Google Scholar
• SchunkD. H., & PajaresF. (2001). Development of Academic Self-Efficacy 2.
   Google Scholar
• SchwattzS. H. (1994). Beyond individualism/collectivism: new cultural dimensions of values. Thousand Oaks, CA: Sage.
   Google Scholar
• ScottC., BurnsA., & CooneyG. (1996). Reasons for discontinuing study: the case of mature age female students with children. Higher education, 31, 233-253.
   Web of Science ®Google Scholar
• ScottM., BaileyT., & KienzlG. (2006). Relative success? determinants of college graduation rates in public and private colleges in the U.S. Research in higher education, 47(3), 249-279.
   Web of Science ®Google Scholar
• SeijtsG. H., LathamG. P., TasaK., & LathamB. W. (2004). Goal setting and goal orientation: an integration of two different yet related literatures. Academy of management journal, 47(2), 227-240.
   Web of Science ®Google Scholar
• St. JohnE. P. (2000). The impact of student aid on recruitment and retention: what the research indicates. New directions for student services, 89(Spring), 61-76.
   Google Scholar
• St. JohnE. P., HuS., SimmonsA., CarterD. F., & WeberJ. (2004). What difference does a major make? Research in higher education, 45(3), 209-252.
   Web of Science ®Google Scholar
• The Education and Employment Committee, U. K., Parliament. (2001). Select committee on Education and Employment. 6. Retrieved from http://www.parliament.the-stationery-office.co.uk/pa/cm200001/cmselect/cmeduemp/124/12403.htm
   Google Scholar
• TintoV. (1975). Dropout from higher education: A theoretical synthesis of recent research. Review of Educational Research, 45(1), 89-125.
   Web of Science ®Google Scholar
• TintoV. (1982). Limits of theory and practice in student attrition. The journal of higher education, 53(6), 687-700.
   Web of Science ®Google Scholar
• TitusM. A. (2004). An examination of the influence of institutional context on student persistence at 4-year colleges and universities: A multilevel approach. Research in higher education, 45(7), 673-699.
   Web of Science ®Google Scholar
• TorresJ., & SolbergV. (2001). Role of self-efficacy, stress, social integration and family support in Latino college student persistence and health. Journal of vocational behavior, 23, 53 -63.
   Google Scholar
• WatsonG., JohnsonG. C., & AustinH. (2004). Exploring relatedness to field of study as an indicator of student retention. Higher education research & development, 23(1), 57-73.
   Google Scholar
• WilliamsJ. E., & CoombsW. T. (1996). An analysis of the reliability and validity of Bandura’s multidimensional scales of perceived self-efficacy.
   Google Scholar
• WoodardD. B., AlloryS. L., & De LucaA. M. (2001). Retention and institutional effects: a self-study framework. NASPA Journal, 39(1), 53-83.
   Google Scholar
• YamaguchiS. (1994). Collectivism among the Japanese: a perspective from the self. Newbury Park, CA: Sage.
   Google Scholar
• ZajacovaA., LynchS., & EspenshadeT. (2005). Self-Efficacy, Stress, and Academic Success in College. Research in higher education, 46(6), 677-706.
   Web of Science ®Google Scholar