Higher education and performance: examining at-risk populations in an online environment

• Authors: Dooley T. Price , Wang Junfeng
• Languages of publication: EN

Abstracts

EN

Using data from a Master's of Public Administration (MPA) program at a Mid-western regional university in the United States, this paper studies whether Learning Management Systems (LMS) have equivalent outputs relative to more traditional educational delivery systems. In essence, are current generation LMS, used for online only instruction, equivalent to traditional teaching models when examining race and gender? This study examined certain output criteria using regression analysis and found no statistically significant difference between online and on-ground students in terms of their MPA degree GPA. However, African American student performance was relatively weaker than non-African American students in terms of GPA regardless of whether they were admitted into the online or on-ground program. This finding is consistent with other studies examining on-ground only performance. We posit that this difference was caused by their lower grades before they entered into this master's program. To combat the gap, fair grading is a good but not sufficient practice, and additional resources and remedial approaches should be in place in order to better prepare African American students as competitive as other racial groups.

Keywords

EN

higher education; online environment

• Publisher: Szkoła Główna Handlowa w Warszawie
• Journal: e-mentor
• Year: 2015
• Issue: 5 (62)
• Pages: 84-90

Contributors

author

Dooley T. Price

• University of Illinois at Springfield

author

Wang Junfeng

• University of Illinois at Springfield

References

• Alexander K.L., Entwisle D.R., Thompson M.S., School performance, status relations, and the structure of sentiment: Bringing the teacher back in, „American Sociological Review” 1987, pp. 665-682.
• Allen W.R., The Color of Success: African-American College Student Outcomes at Predominantly While and Historically Black Public Colleges and Universities, „Harvard Educational Review” 1992, Vol. 62, No. 1, pp. 26-45, http://dx.doi.org/10.17763/haer.62.1.wv5627665007v701.
• Bandura A., Self-efficacy: Toward a unifying theory of behavioral change, „Psychological Review” 1997, Vol. 84, No. 2, pp. 191-215, http://dx.doi.org/10.1037/0033-295X.84.2.191.
• Bandura A., Social foundations of thought and action: A social cognitive theory, Prentice Hall, Englewood Cliffs 1986.
• Bandura A., Social cognitive theory, [in:] R. Vasta (ed.), Annals of Child Development. Vol. 6. Six theories of child development, JAI Press, Greenwich 1989.
• Brown J.L.M., Online Learning: A Comparison of Web-Based and Land-Based Courses, „Quarterly Review of Distance Education” 2012, Vol. 13, No. 1, pp. 39-42.
• Carter D.F., Key issues in the persistence of underrepresented minority students, „New Directions for Institutional Research” 2006, No. 130, pp. 33-46, http://dx.doi.org/10.1002/ir.178.
• Cook B.J., Córdova D.I., Minorities in higher education twenty-second annual status report: 2007 supplement, http://minority-health.pitt.edu/996/.
• Desjardins S.L., Ahlburg D.A., McCall B.P., A Temporal Investigation of Factors Related to Timely Degree Completion, „Journal of Higher Education” 2002, Vol. 73, No. 5, pp. 555-581, http://dx.doi.org/10.1353/jhe.2002.0042.
• Dooley T.P., Schreckhise W.D., Evaluating Social Cognitive Theory in Action: An Assessment of the Youth Development Program's Impact on Secondary Student Retention in Selected Mississippi Delta Communities, „Youth & Society” 2013, http://dx.doi.org/10.1353/jhe.2002.0042.
• Endo J.J., Harpel R.L., The effect of student-faculty interaction on students' educational outcomes, „Research in Higher Education” 1982, Vol. 16, No. 2, pp. 115-138, http://dx.doi.org/10.1007/BF00973505.
• Ferguson R.F., Teachers' perceptions and expectations and the black-white test score gap, „Urban Education” 2003, Vol. 38, No. 4, pp. 460-507, http://dx.doi.org/10.1177/0042085903038004006.
• Gilhooly K., Making e-learning effective, „Computerworld” 2001, Vol. 35, No. 29, pp. 52-53.
• Hatch L.R., Mommsen K., The Widening Gap in American Higher Education, „Journal of Black Studies” 1984, Vol. 14, No. 4, pp. 457-476, http://dx.doi.org/10.1177/002193478401400404.
• Hu S., St. John E.P., Student persistence in a public higher education system: Understanding racial and ethnic differences, „Journal of Higher Education” 2001, Vol. 72, No. 3, pp. 265-286, http://dx.doi.org/10.2307/2649332.
• Lim C.K., Computer self-efficacy, academic self-concept, and other predictors of satisfaction and future participation of adult distance learners, „American Journal of Distance Education” 2001, Vol. 15, No. 2, pp. 41-51, http://dx.doi.org/10.1080/08923640109527083.
• Lou Y., Bernard R.M., Abrami P.C., Media and pedagogy in undergraduate distance education: A theory-based meta-analysis of empirical literature, „Educational Technology Research and Development” 2006, Vol. 54, No. 2, pp. 141-176, http://dx.doi.org/10.1007/s11423-006-8252-x.
• McCall H., When successful alternative students “disengage” from regular school, „Reclaiming Children and Youth” 2003, Vol. 12, No. 2, pp. 113-117.
• McGrady P.B., Reynolds J.R., Racial Mismatch in the Classroom Beyond Black-white Differences, „Sociology of Education” 2013, Vol. 86, No. 1, pp. 3-17, http://dx.doi.org/10.1177/0038040712444857.
• McKown C., Weinstein R., Teacher expectations, classroom context, and the achievement gap, „Journal of School Psychology” 2008, Vol. 46, No. 3, pp. 235-261, http://dx.doi.org/10.1016/j.jsp.2007.05.001.
• Means B., Toyama Y., Murphy R., Bakia M., Jones K., Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies, US Department of Education, Washington DC 2009.
• Miller L.S., An American imperative: Accelerating minority educational advancement, Yale University Press, 1995.
• Minor E.C., Racial Differences in Teacher Perception of Student Ability, „Teachers College Record” 2014, Vol. 116, No. 10, s. 1-22.
• Moore H.A., Keith B., Human capital, social integration, and tournaments: A test of graduate student success models, „The American Sociologist” 1992, Vol. 23, No. 2, pp. 52-71, http://dx.doi.org/10.1007/BF02691908.
• Oates G.L.S.C., Teacher-Student Racial Congruence, Teacher Perceptions, and Test Performance, „Social Science Quarterly” 2003, Vol. 84, No. 3, pp. 508-525, http://dx.doi.org/10.1111/1540-6237.8403002.
• Pajares F., Self-Efficacy Beliefs in Academic Settings, „Review of Educational Research” 1996, Vol. 66, pp. 543-578, http://dx.doi.org/10.3102/00346543066004543.
• Pigott R.L., Cowen E.L., Teacher race, child race, racial congruence, and teacher ratings of children's school adjustment. „Journal of School Psychology” 2000, Vol. 38, No. 2, pp. 177-195, http://dx.doi.org/10.1016/S0022-4405(99)00041-2.
• Scheer T.J., Exploring the impact of distance learning on MPA students, „Journal of Public Affairs Education” 2001, Vol. 7, No. 2, pp. 101-115.
• Schunk D.H., Social-self interaction and achievement behavior, „Educational Psychologist” 1999, Vol. 34, No. 4, pp. 219-227, http://dx.doi.org/10.1207/s15326985ep3404_3.
• Seidman A., Minority student retention: Resources for practitioners, „New Directions for Institutional Research” 2005, No. 125, pp. 7-24, http://dx.doi.org/10.1002/ir.136.
• Shea P., Li C.S., Swan K., Pickett A., Developing learning community in online asynchronous college courses: The role of teaching presence, „Journal of Asynchronous Learning Networks” 2005, Vol. 9, No. 4, pp. 59-82.
• Swan K., Building learning communities in online courses: The importance of interaction. „Education, Communication & Information” 2002, Vol. 2, No. 1, pp. 23-49, http://dx.doi.org/10.1080/1463631022000005016.
• Tinto V., Dropouts from Higher Education: A Theoretical Synthesis of the Recent Literature, „A Review of Educational Research” 1975, Vol. 45, No. 1, pp. 89-125, http://dx.doi.org/10.1080/1463631022000005016.
• U.S. Department of Education, National Center for Education Statistics, Digest of Education Statistics (2009 ed.), http://nces.ed.gov/programs/digest/d09/tables/dt09_275.asp.
• U.S. Department of Education, National Center for Education Statistics, Digest of Education Statistics (2010 ed.), http://nces.ed.gov/programs/digest/d10/tables/dt10_286.asp.
• U.S. Department of Education, National Center for Education Statistics, Digest of Education Statistics (2011 ed.), http://nces.ed.gov/programs/digest/d11/tables/dt11_290.asp.
• U.S. Department of Education, National Center for Education Statistics, Digest of Education Statistics (2012 ed.), http://nces.ed.gov/programs/digest/d12/tables/dt12_317.asp.
• U.S. Department of Education, National Center for Education Statistics, Digest of Education Statistics (2013 ed.), http://nces.ed.gov/programs/digest/d13/tables/dt13_318.30.asp.
• Watson W.R., Watson S.L., What are Learning Management Systems, What are They Not, and What should they Become? „TechTrends” 2007, Vol. 51, No. 2.