MERLOT Journal of Online Learning and Teaching
Vol. 6, No. 1, March 2010
because it is the only way they can access higher education.
If they rush in unprepared to this
environment and do not experience educational goals. One suggestion is students to take OSS if needed.
success, to create
they may turn an assessment
away from this method for meeting their tool that will encourage prospective online
Finally, if the OSS class should be targeted at those students who need help learning online, it would benefit from concentrating on developing the skills that make a student successful online. This classroom implication points to the first research implication, and that is to study what makes online students successful. Given the large number of online classes at the college, this project would require the involvement of many students and instructors.
Other implications for future research will help refine the classroom suggestions mentioned.
historical data will be more complete if academic records from other online colleges are included. students reported they had taken online classes at other colleges, but their performance in those was not included in historical data. It may be difficult to incorporate data from all online colleges,
Several classes but in a
multi-campus to expand the
district that uses historical data to
one database for its enrollment and academic data it include records from the other colleges in the district.
More historical and academic data about students from all four groups will allow additional analysis. For example, the number of units attempted online and in non-online classes would suggest how much of the students’ academic effort was engaged in online learning. (This assumes that a unit of academic credit
of the course.)
This could be
preparation. It also implications for how to
would show how many online provide student services to online
combined with their skills and academic classes, which has
This additional enrollment data would help analyze an unexpected result from the demographic data: OSS students in all three groups are more likely to live near campus. If OSS students are also more likely to take classes on campus, this would beg asking how these students found out about OSS and would have potential implications for marketing OSS to the online students who do not live near campus.
Research implications for the survey include finding a way to get additional responses.
participants were more likely to be recent enrollees in OSS. Asking them to contribute responses after their OSS enrollment might increase participation, as their e-mail addresses are more likely
soon to be
current. In addition, they might the online learning modality.
A final set of research implications comes from this project’s successes and should be repeated in similar efforts. What worked well was giving students a place for open-ended responses on the survey. It provided material to corroborate results of historical data analysis and humanized the presentation of results. Using Microsoft Excel to analyze the historical data also worked well. The pivot table allowed easy compilation of relevant data, and the statistical functions made quick work of counting and calculating project numbers. Finally, the process for conducing the survey should be repeated. Survey data were collected using the same tool (a Blackboard course account) that was used to teach OSS, so there was no technical learning curve for respondents.
The author would like to acknowledge the support offered by the @ONE Carnegie Scholar Program during the 2005-2006 academic year. The program encourages the effective use of technology in the classroom by helping faculty conduct research using the classroom action research methodology. Particularly helpful were the suggestions and comments made by the college researchers that took part in the project: Michelle Barton, director of institutional research and planning at Palomar College, and Darla Cooper, institutional research director at Oxnard College.
Artino, Anthony, Jr. 2009. Online learning: Are subjective perceptions of instructional context related to academic success? Internet and Higher Education 12, nos. 3-4:117-25.
Berenson, Robin, Gary Boyles, and Ann Weaver. 2008. Emotional intelligence as a predictor for success in online learning. International Review of Research in Open and Distance Learning 9, no. 2:1-17.