Understanding the massive open online course (MOOC) student experience: An examination of attitudes, motivations, and barriers

Abstract

a b s t r a c tDuring the widespread development of open access online course materials in the last two decades, advances have been made in understanding the impact of instructional design on quantitative outcomes. Much less is known about the experiences of learners that affect their engagement with the course content. Through a case study employing text analysis of interview transcripts, we revealed the authentic voices of participants and gained a deeper understanding of motivations for and barriers to course engagements experienced by students participating in Massive Open Online Courses (MOOCs). We sought to understand why learners take the courses, specifically Introduction to Chemistry or Data Analysis and Statistical Inference, and to identify factors both inside and outside of the course setting that impacted engagement and learning. Thirty-six participants in the courses were interviewed, and these students varied in age, experience with the subject matter, and worldwide geographical location. Most of the interviewee statements were neutral in attitude; sentiment analysis of the interview transcripts revealed that 80 percent of the statements that were either extremely positive or negative were found to be positive rather than negative, and this is important because an overall positive climate is known to correlate with higher academic achievement in traditional education settings. When demographic data was added to the sentiment analysis, students who have already earned bachelor's degrees were found to be more positive about the courses than students with either more or less formal education, and this was a highly statistically significant result. In general, students from America were more critical than students from Africa and Asia, and the sentiments of female participants' comments were generally less positive than those of male participants. An examination of student statements related to motivations revealed that knowledge, work, convenience, and personal interest were the most frequently coded nodes (more generally referred to as "codes"). On the other hand, lack of time was the most prevalently coded barrier for students. Other barriers and challenges cited by the interviewed learners included previous bad classroom experiences with the subject matter, inadequate background, and lack of resources such as money, infrastructure, and internet access. These results are enriched by illustrative quotes from interview transcripts and

A Classification of Barriers that Influence Intention Achievement in MOOCs

“…Also, a very recent study by Shapiro, Lee, Roth, Li, Çetinkaya-Rundel and Canelas [17] on barriers to retention in MOOCs, sought to identify which antecedents, both inside and outside the course setting, had an impact on MOOC-learning. Their qualitative approach of conducting 36 online interviews identified, in order of severity, lack of time, bad previous experiences, online format and inadequate background as barriers to MOOC-learning.…”

“…Still, a shortcoming of prior studies is that they merely examine several specific potential barriers to MOOC-learning and are limited in their empirical analysis. As it is important to continue to explore potential barriers to MOOC-learning to gain a richer understanding of these issues [17,21], a next step is to generate a composite overview of potential MOOC-specific barriers or groupings of barriers based on literature and related studies as already available in online learning or distance education context [9,10].…”

“…While there are related studies dealing with the empirical analysis of the effects of barriers to online learning and distance education using various statistical techniques [8][9][10][11][12][13], for the context of massive open online learning such analyses are limited. Current studies on barriers in MOOCs mainly focus on a restricted number of barriers in case studies, qualitative research setups, literature reviews and descriptive studies [14][15][16][17]. There are some studies which empirically investigate barriers to student retention, however these studies merely focus on the effect of specifically selected barriers [18,19].…”

The Demand for Massive Open Online Courses (MOOC): Evidence from Russian Education

“…The following motivations for online learning have been observed in MOOC participants: fun and enjoyment; interest in the topic; relevance of subject to academic field of study; obtaining new in-depth knowledge in subject; trying online education; curiosity, entertainment; eager to explore a new topic; personal challenge; getting a credential; career advancement, opportunity for professional growth; resume enhancement; free access; interest in the field of study; substitute for an offline course which is inaccessible; interest in how these courses are taught; extending current knowledge of the topic; professional conversion / changing a major; obtaining knowledge to improve academic performance; new acquaintances and friends [Belanger, Thornton 2013;Hew, Cheung 2014;Kizilcec, Piech, Schneider 2013;Breslow et al 2013;Shapiro et al 2017]. "Non-pragmatic" motives like curiosity, enjoyment from learning, etc.…”

Co-Training Semi-Supervised Deep Learning for Sentiment Classification of MOOC Forum Posts

“…Generally, learners generate a large volume of forum posts, even tens of thousands of forum posts for one course. Due to the very high learner-to-instructor ratios in online learning environment, it is unrealistic to expect instructors to fully track the forum posts to identify learners' sentiment orientations and provide feedback in a timely manner [8]. Thus, it is necessary to use machine learning techniques to complete sentiment classification.…”