Author Archives: jsprangers

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.


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

 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:

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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Coming to Terms with the Online Instructional Revolution: A Success Story Revealed through Action Research.

Lunsford, E., & Bolton, K. (2006). Coming to Terms with the Online Instructional Revolution: A Success Story Revealed through Action Research. Bioscene: Journal Of College Biology Teaching, 32(4), 12-16.

Lunsford and Bolton undertook an action research project involving the development of an online introductory biology course for non-science majors at a community college.  The framework of their action research included four steps:  1. Realize the problem,  2. Develop a plan of action,  3. Reflect on results and  4. Integrate results. 

Administration at  the college requested that these instructors consider teaching an online biology course.  The goal of the faculty designers was to keep the online course as “equitable in content as possible to traditional, seat-based courses as the school.”  It was also important to the instructors to provide students with as many authentic lab experiences as possible utilizing hands-on materials and living organisms.    The course that was chosen to be developed was the introductory, non-majors biology course.  Unfortunately, the non-science major course had not been taught at the college in recent years, so the basis for comparison was limited.  The authors elected to compare students in the non-majors course to students enrolled in the science majors course who had declared themselves to be non-science majors.    The investigators felt that focusing study on non-majors from both courses would offer the best method available to them for evaluating the new online course.

To further minimize potential sources of error in their comparison, the instructors compiled a list of content knowledge objectives that were common to both courses.  A third party researcher authored a 50 item multiple choice test that sampled most of the objectives.  The author of the test was blinded to the purpose of the study.  The test was given to students at the end of the term.  This test in no way affected their grade for the course in which they had enrolled.  Participation in the study was voluntary and anonymous.  Students had only to identify the course in which they were enrolled and whether they were a science major or non-major.

Results of this study indicated that the mean test scores of the seat-based and web-based non-majors groups were essentially identical.  Due to the small sample size ( nine members in each group), no statistical comparisons were made.  However, the results did alleviate the fears of the instructors with respect to offering an online biology course.  They said. “we can state that our concerns about content knowledge in online versus traditional instructional formats have been allayed.”  With the information obtained from this small study, an informed decision was made to continue teaching non-majors introductory biology in an online format.

It is important to note that both authors indicate further research is necessary to fully validate their results.  They acknowledge the limitations of their study, specifically with respect to sample size.  The care that was taken to preserve the essential hands-on, authentic  nature of the laboratory exercises provided in the online course is laudable.  This paper provides a “starting point” for biology and other science instructors to evaluate the effectiveness of online course delivery

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The History of Distance Education

Casey, D. (2008)  A Journey to Legitimacy: The Historical Development of Distance Education through Technology.   TechTrends: Linking Research & Practice to Improve Learning, 52(2), 45-51.

This article by Denise M. Casey clearly articulates the history of distance education in the United States.  Beginning in the 1850’s, the United States postal system was instrumental in the first distance education courses.  These were the correspondence courses, primarily vocational-type courses designed to teach skill sets for employment.  Course offerings included shorthand and mine safety.  In the late 1800’s, the University of Chicago created the first post-secondary distance learning program. 

 It was in the 1920’s that technology became associated with distance education.  The catalyst for this event was the invention of the radio.  Radio technology allowed for the expansion of the classroom beyond the boundaries of an institution.  Students could hear their instructors from a distance!  At this time, distance education evolved to include both radio and the traditional exchange of assignments and lessons between students and instructor through the postal service.

 The next step in the sequence involved use of the television as an instructional tool.  In 1934, the University of Iowa became the first institution to broadcast courses by television.  In the 1960’s, the FCC created the Instructional Television Fixed Service, some twenty television stations available to educational institutions to support distance learning courses.  The late 1960’s saw the advent of the Public Broadcasting System (PBS) to promote non-commercial, vis-a-vis educational, programming.

The radical changes in distance education that are seen currently began in 1971 with the development of the microprocessor by Intel.  Although it would be another 20 years before the World Wide Web came into being, the microprocessor and the computer provided the starting point.  The technological revolution gained momentum when satellite relay of information became affordable in the 1980’s.

 Today, technological changes occur at an astonishing rate.  The internet has become the superhighway of information dissemination.  “Podcasts”, “wikis”, “blogs”, “apps” are terms infused into the everyday language of our time.  Distance education, with its origins in vocational courses, has evolved into a multi-headed giant that serves all areas of academia and career training.

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