Increasing Success of Online Students: Evaluating Student Readiness

A major movement in education in the United States is the growth of online learning.  In the most recent Sloan Consortium’s report, the number of students taking online courses in 2008 grew by 17% when compared to the previous year, while traditional face-to-face course enrollment only increased by 1.2% (Allen, 2010).  As enrollment in online courses continues to expand, the issue of student retention takes on significance.  Efforts to improve success of college students enrolled in online classes either through improved Grade Point Averages or by program/degree completion are becoming widespread. 

Student success in online course has been linked to three factors: 
1. Student readiness
2. Student orientation
3. Student support (Harrell, 2008) 

This report focuses on some of the strategies institutions are utilizing to predict student readiness for and success in the online environment.

A large body of research involves the development of assessment surveys.  These surveys may be administered by the institution or may be self-assessments. One such survey, the LASSI for Online Learning (LLO) was investigated by Carson (2011).  His findings indicated that the LASSI Motivation subscale provided the most efficient predictor of student success with time management being the second most important predictor.  His report is noteworthy as the sample size was quite large, including 8112 students. 

On a smaller scale, Robyler and Marshall (2002) developed an Educational Success Prediction Instrument (ESPRI) for use with high school students.  After completing a literature review and compiling a list of qualities of successful online students, the 70-item instrument was designed.  This instrument predicted student success, defined as a grade of “C” or better, with 100% confidence. 

The authors identified three factors as being the strongest predictors of student success: 
1. Study environment
2. Motivation
3. Computer confidence 

They conclude with the recommendation that this instrument be used in a larger study to determine if it is an effective predictor in the widespread population.

A more targeted study was completed by Fisher and Tague (2001).  These authors undertook to develop a readiness scale for self-directed learning for nursing students.  The final scale included 40 items that reflected three components: self-management, desire for learning (motivation) and self-control. 

Self-assessments are also widely used.  When investigating the institutions within the Minnesota Colleges and Universities system (MnSCU), it was found that 15 of 30 two-year community and technical colleges offered students the opportunity to self-assess their readiness for online learning while 4 of 7 four-year institutions linked students to a similar survey (compiled by Sprangers, 2012)

Another strategy used by some institutions is the development of a course specifically designed to augment student success in the online environment.  One course, “Online Student Success (OSS)” is offered by Consomes River College in Sacramento, California.  After implementation of this course, it was found that 78% of students achieved a grade of “C” or better in their online courses if they had been successful in OSS.  This compares to only 38% of students achieving a passing grade in an online course prior to taking OSS (Beyrer, 2010).

An important finding of this review is the key role of motivation in online student success.  Yet, these investigations lead to additional questions.  For example, is it possible to develop a single, standarized tool that would accurately predict student success across a wide variety of disciplines?  Are population demographics important in assessing the validity of these tools?  How well do these tools correlate with the “success” characteristics that have been identified in the literature?  With the rapid rise in enrollment for online courses, it is clear that there is much work to be done if we, as educators, wish to promote student success in online classrooms.

References:

Allen, I. S. (2010).  Learning on Demand: Online Education in the United States, 2009. Retrieved July 5, 2012 from

http://sloanconsortium.org/publications/survey/learning_on_demand_sr2010

 Beyrer, G. (2010).  Online Student Success: Making a Difference.  Journal of Online Teaching and Learning, 6(1), 89-108.

 Carson, A. D. (2011). Predicting Student Success from the LASSI for Learning Online (LLO). Journal Of Educational Computing Research, 45(4), 399-414.

 Fisher, M., King, J., and Tague, G. (2001).  Development of a self-directed learning readiness scale for nursing education. Nurse Education Today, 21, 516-525.

Harrell, I.L. (2008). Increasing the Success of Online Students.  Retrieved July 5, 2012 from Virginia Community College System: http://www.vccaedu.org/inquiry/inquiry-spring-2008/1-13-Harrell.html

Roblyer, M. D., & Marshall, J. C. (2002). Predicting Success of Virtual High School Students: Preliminary Results from an Educational Success Prediction Instrument. Journal Of Research On Technology In Education, 35(2), 241.

Information on MnSCU institutions compiled by J. Sprangers (2012)

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