Do prior online course outcomes provide more information than G.P.A. alone in predicting subsequent online course grades and retention? An observational study at an urban community college

In this study, prior online course outcomes and pre-course enrollment G.P.A. were used as predictors of subsequent online course outcomes, and the interaction between these two factors was assessed in order to determine the extent to which students with similar G.P.A.'s but with different prior online course outcomes may differ in their likelihood of successfully completing a subsequent online course. This study used a sample of 962 students who took an online course at a large urban community college from 2004 to 2010. Results indicate that prior online course experience is a very significant predictor of successful completion of subsequent online courses, even more so than G.P.A. For students with no prior online course experience, G.P.A. was a good predictor of future online course outcomes; but for students with previous online course experience prior online course outcomes was a more significant predictor of future online course grades and retention than G.P.A. We explore how prior online outcomes and GPA predict future online outcomes.Prior online course outcomes predict future online outcomes better than GPA.For a first-time online student, success online was strongly correlated with GPA.Students with prior online success, regardless of GPA, continued to succeed online.Unsuccessful online students continued to struggle online, regardless of GPA.

[1]  Doreen Gosmire,et al.  Perceptions of Interactions in Online Courses , 2009 .

[2]  Amaury Nora,et al.  Technology and Higher Education: The Impact of E-Learning Approaches on Student Academic Achievement, Perceptions and Persistence , 2008 .

[3]  Basmat Parsad,et al.  Distance Education at Postsecondary Institutions: 2006-07. First Look. NCES 2009-044. , 2008 .

[4]  Michael C. Rodriguez,et al.  Students' Perceptions of Online-Learning Quality Given Comfort, Motivation, Satisfaction, and Experience. , 2008 .

[5]  Sarah Carr.  As Distance Education Comes of Age, the Challenge Is Keeping the Students. , 2000 .

[6]  Nathan K. Lindsay,et al.  Thirty-two Trends Affecting Distance Education: An Informed Foundation for Strategic Planning , 2003 .

[7]  Badrul H. Khan,et al.  Toward a Learner-Oriented Community College Online Course Dropout Framework , 2007 .

[8]  Michael D. Summers.  ERIC Review: Attrition Research at Community Colleges , 2003 .

[9]  Joanna C. Dunlap,et al.  Learner Support Services for Online Students: Scaffolding for Success. , 2003 .

[10]  M. Cowles.  Modelling Survival Data in Medical Research (2nd ed.) (Book) , 2004 .

[11]  Eboni M. Zamani-Gallaher.  The Confluence of Race, Gender, and Class Among Community College Students: Assessing Attitudes Toward Affirmative Action in College Admissions , 2007 .

[12]  Sean G. Ryan.  Is online learning right for you , 2001 .

[13]  Jacob Cohen.  Statistical Power Analysis for the Behavioral Sciences , 1969, The SAGE Encyclopedia of Research Design.

[14]  Catherine L. Finnegan,et al.  Best Practices in Predicting and Encouraging Student Persistence and Achievement Online , 2008 .

[15]  Amaury Nora,et al.  An Exploration of College Persistence for Students Enrolled in Web-Enhanced Courses: A Multivariate Analytic Approach , 2008 .

[16]  A. Cabrera,et al.  The Role of Perceptions of Prejudice and Discrimination on the Adjustment of Minority Students to College , 1996 .

[17]  Cherng-Jyh Yen,et al.  Learner Autonomy as a Predictor of Course Success and Final Grades in Community College Online Courses , 2009 .

[18]  Thomas Mazzurana.  eLearning 2.0 , 2008 .

[19]  P. Lachenbruch.  Statistical Power Analysis for the Behavioral Sciences (2nd ed.) , 1989 .

[20]  Shanna Smith Jaggars,et al.  What We Know about Online Course Outcomes. Research Overview. , 2013 .

[21]  Mitchell H. Gail,et al.  A Reminder of the Fallibility of the Wald Statistic , 1996 .

[22]  Herbert E. Muse.  The Web-based community college student: An examination of factors that lead to success and risk , 2003, Internet and Higher Education.

[23]  Wallace E. Boston,et al.  Assessing Student Retention in Online Learning Environments: A Longitudinal Study , 2012 .

[24]  Johnette Moody.  Distance Education: Why Are the Attrition Rates so High? , 2004 .

[25]  Y. Pawitan.  In all likelihood , 2001 .

[26]  Z. Berge,et al.  Student barriers to online learning: A factor analytic study , 2005 .

[27]  Sunil J Rao,et al.  Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis , 2003 .

[28]  G. Leinhardt,et al.  Going the Distance With Online Education , 2006 .

[29]  Hannah D. Street,et al.  Factors Influencing a Learner's Decision to Drop-Out or Persist in Higher Education Distance Learning , 2010 .

[30]  Claire Wladis,et al.  Balancing Retention and Access in Online Courses: Restricting Enrollment … is it Worth the Cost? , 2013 .

[31]  I. E. Allen,et al.  Changing Course: Ten Years of Tracking Online Education in the United States. , 2013 .

[32]  Clifton Bob Clark,et al.  The University of North Carolina at Greensboro , 1980 .

[33]  David N. Figlio,et al.  Is It Live or Is It Internet? Experimental Estimates of the Effects of Online Instruction on Student Learning , 2010, Journal of Labor Economics.

[34]  Marcy F. Reisetter,et al.  Belonging Online: Students' Perceptions of the Value and Efficacy of an Online Learning Community , 2008 .

[35]  Susan G. Broyles.  Fall enrollment in colleges and universities 1983 , 2011 .

[36]  A. P. Rovai.  In search of higher persistence rates in distance education online programs , 2003, Internet High. Educ..

[37]  B. Patterson,et al.  Attrition in Online and Campus Degree Programs. , 2009 .

[38]  Claire Wladis,et al.  Is the Second Time the Charm? Investigating Trends in Online Re-Enrollment, Retention and Success , 2012 .

[39]  I. E. Allen,et al.  Class Differences Online Education in the United States, 2010 , 2010 .

[40]  Matti J. Haverila.  Prior e-Learning experience and perceived learning outcomes in an undergraduate e-learning course. , 2011 .

[41]  D. Collet.  Modelling Survival Data in Medical Research , 2004 .

[42]  D. Kember.  A Longitudinal-Process Model of Drop-Out from Distance Education , 1989 .

[43]  Roger Sauter,et al.  In All Likelihood , 2002, Technometrics.

[44]  I. E. Allen,et al.  Staying the course: online education in the United States, 2008 , 2008 .

[45]  Stephen Downes.  E-learning 2.0 , 2005, ELERN.

[46]  J. Fox.  Applied Regression Analysis, Linear Models, and Related Methods , 1997 .

[47]  Dc Washington,et al.  Distance education at degree-granting postsecondary institutions: (NCES -044). U.S. Department of Education, Institute of Education for Education Statistics. , 2009 .

[48]  Keith Tyler-Smith.  Early Attrition among First Time eLearners: A Review of Factors that Contribute to Drop-out, Withdrawal and Non-completion Rates of Adult Learners undertaking eLearning Programmes , 2006 .

[49]  Wallace E. Boston,et al.  Assessing Retention in Online Learning: An Administrative Perspective , 2011 .