As part of my doctoral process, I have to review a lot of literature. A LOT. To motivate me to keep track of the resources as I read them, I am going to try to post summaries of the pertinent articles here. My hope is that I will get in the habit of writing and summarizing so that the literature review portion of my dissertation is easier to write. We’ll see if that works, and if I can keep up with the summaries!
Koutropoulos, A., Gallagher, M. S., Abajian, S. C., De Waard, I., Hogue, R. J., Keskin, N. O., & Rodriguez, C. O. (2012). Emotive Vocabulary in MOOCs: Context & Participant Retention. European Journal of Open, Distance and E-Learning. Retrieved from http://www.eric.ed.gov/ERICWebPortal/detail?accno=EJ979609
In this paper, the researchers examine the high enrollments and low completion common to MOOCs by analyzing the content on the discussion forums of MobiMOOC. Specifically, they investigated whether the vocabulary used when communicating about the MOOC gave clues about how they felt about the MOOC, if language and key words could be used to predict participation and retention.
The authors used a narrative inquiry approach with an analysis of emotive language frequency, participation frequency, and participant interactions. They assumed that increase in engagement or disengagement could be inferred from emotive language in the first three weeks of the course or by a change in participation pattern in the second half of the course (weeks 4-6).
The researchers conducted four examinations of the data. First, they read the transcripts to develop a detailed picture of the week-by-week discussions. In the second pass, they used Linguistic Inquiry and Word Count Analysis software to determine the degree of positive or negative emotive language use. Positive emotive vocabulary use substantially outweighed negative vocabulary. Word clouds allowed the most commonly used words to be compared from week to week.
In the third pass, the researchers looked at discussion analytics to determine participation frequency (number of posts, number of participants, category of participants). Number of posts increased during weeks 1 and 2 then decreased, reaching a plateau in weeks 5 and 6. The number of participants was highest in week 1 then decreased until again reaching a plateau in weeks 5 and 6. This is expected based on enrollments trends in MOOCs. However, the post-per-participant ratio was higher during the final weeks than it was during the initial weeks, indicating that the remaining participants were more active and engaged as a core participant group emerged. The researchers also noted that the initial weeks included more Novices and Lurkers, while later weeks had higher concentrations of Elders, Leaders, and Regulars (terminology from membership life cycle of Kim, 2000). Emotive language was not found to correspond to retention or disengagement.
The final pass through the data was a narrative analysis of select passages from the first week of MobiMOOC. Three themes were apparent from the coding:
- Possible professional mismatch between course objectives and participant expectations
- Trepidation, uncertainty, unfamiliarity, some indication of a lack of confidence in ability
- Professional expertise, experience, confidence, self-assuredness
This paper demonstrates a qualitative analysis of participation. While the findings were non-significant, it does suggest ways that a future course and study could be designed to increase the accuracy of the data to identify other predictors of retention.