What Can You Learn in a 7-Week Course?: Outcomes and Perceptions of Time-Intensive Online Courses Who Benefits
Concurrent Session 8
While time-intensive (7-week) courses are becoming more common in online learning, there is not a strong evidence base regarding their outcomes and student perceptions. In this session, we will share findings from our large-scale study that utilizes both survey data and hierarchical mixed-effects logistic regression from learning analytics.
With the need for online learning to meet the demands of busy non-traditional students who want flexible educational options, many institutions have opted to offer online courses in a time-intensive format -- meaning that the amount of content that is taught in a traditional semester-length course is compressed into a shorter period of time (e.g. 7 weeks). While there have been a few research studies that have shown initial evidence that time-intensive courses can have similar or better outcomes as traditional length courses (Ewer et al, 2002; Austin & Gustafson, 2006; Sheldon & Durdella, 2009; Ferguson & DeFelice, 2010), only a few studies have focused specifically on course length in the online environment (Ferguson and DeFelice, 2010; Mensch, 2013). Additionally, there are questions from the literature regarding some potentially negative aspects of time-intensive online courses such as lack of communication time (Wolfe, 1998), lack of preparation time (Ho and Polonskly, 2009), and degradation of faculty grading standards (Scott, 1994).
This research project was borne out of the need at our institution to increase the evidence-base of the practice of teaching online courses in time-intensive formats. We have many programs that currently use 7-week courses and frequently receive questions from faculty about the overall effectiveness of this length. Therefore, we sought to conduct a systematic investigation of the impact of online course length on student outcomes. This investigation included large scale data analysis from our learning analytics system as well as a student survey to better understand their experience in taking 7-week online courses.
To perform the analysis, we gathered enrollment data from fully online courses for 10 semesters (Summer 2016 - Summer 2019). After data was cleaned and anonymized, we built a hierarchical mixed-effects logistic regression using course length as the predictor and whether or not the student passed the course (with a C- or above, with Ws excluded) as the outcome variable. CourseID was used as the level to account for the variance in grade distributions and activity across courses. To determine whether there was a significant difference between the overall activity that students were spending in a 7-week course versus a traditional length course, we conducted a multi-level linear regression, with course length as the predictor variable and course activity (as measured by several learning analytics measures) as the outcome variable.
In addition to performing quantitative analysis on the outcomes of the online courses, we also sought to better understand the experience of students who were participating in these 7-week courses. We distributed a survey to online students who had taken a course in both a 7-week and a 15-week format. Students were asked to compare the formats in terms of a) level of challenge; b) overall performance; c) ability to focus; d) time management; e) likelihood to cram or procrastinate; and f) likelihood to get bored.
Results from pilot analysis and surveys indicate that students, on average, have a higher odds of passing given a 7-week course compared to a 15-week course, but full and updated results will be shared during the session. We will also discuss how this project has acted as a model for making evidence-based decisions utilizing data. In setting up the project, we created a reproducible data analysis pipeline to allow ourselves to perform the analysis across all online students (as we did in this portion of the research study) or for individual online programs. This additional analysis for one of our online programs led them to convert all of their courses to a 7-week format.
Once the results have been shared, we want to engage in a conversation with the audience regarding their reaction to the results of the analysis. Possible questions include:
- What experiences have other institutions gathered with their students in time-intensive online courses?
- What factors most strongly influence the outcomes in a time-intensive course?
- How do students' backgrounds interact with their performance in a time-intensive course?
- How do we ensure equitable outcomes in time-intensive online courses?