Does this “massive” scale really attest to “Massive”, one of the conspicuous characteristics of MOOC? A pergent voice appears to argue against its massive enrollment of participants. And the prosecution against it usually starts by highlighting the huge attrition rates of MOOC. For instance, Duke University Fall 2012 offering of Bioelectricity had 12,175 students registered. However, only 7,761 students ever watched a video, 3,658 students took at least one quiz, 345 students attempted the final exam, and finally only 313 passed with a certificate (Jordan, K., 2013; Catropa, Dayna, 2013). Based on another survey undertaken by The Chronicle of Higher Education in February 2013, the average MOOC enrolment is 33,000 students, with an average of 7.5% completing the course (Kolowich, 2013). 

We cannot deny the fact that there do exist a great number of inpiduals dropping out along the way of the courses. Since high attrition rate of MOOC has already become a hurdle in the way of the development of MOOC, increasingly more concerns have been given to deal with this problem. Though institutions implementing MOOCs like Harvard, MIT release annual reports of the courses, displaying descriptive statistics of registration, certification and information of participants’ demographics, activity and geography, trying to find a connection between these two aspects, they admit and “place considerable emphasis on the limitations of these data” (Ho, A. D. et al, 2014). It is not easy to well interpret these numbers and arrive at a unified conclusion considering their obscurity and the fact that rates vary widely between courses. 

    Besides, in the context of MOOCs, students have substantially more freedom to determine what, when, where, and how they will learn. The materials are freely available, which creates the opportunity for students to brow, pick and choose, and follow their own agenda in ways that were not feasible in earlier models of online education. The barrier to entry is low, and there is no penalty for dropout (Yang, D., 2013). These characteristics of the behaviors of students whose intentions and expectations are unknown to us to some degree add more difficulties to the further study of attrition rate of MOOCs. Despite the current limitations and the fact that it’s a long-standing issue for distance educators (Anderson, T. 2012), this paper tries to explain the dropout rate from a perspective of motivation theory as well as put forward some corresponding suggestions to increase low levels of retention often experienced in the MOOC format.

2. Literary Review

In this section, this paper at first outlines the perspectives on attrition rate that have been explored so far in the emerging literature e on MOOCs.

The high rate of attrition of MOOC has garnered a good deal of attention from academia, so there are plenty of research articles focusing on it. Katy Jordan (2014) seeks to draw together the data that has found its way into the public domain in order to explore factors affecting enrolment and completion. Though this study provides a more detailed view of trends in enrolment and completion than was available previously and studies a small number of general factors, the author points out that “various other factors would be worthwhile to explore to better understand the reasons behind and how courses could be improved for both students and course leaders”.

In addition, Clow, Doug (2013) introduces the metaphor of a ‘funnel of participation’ to reconceptualise the steep drop-off inactivity, and the pattern of steeply unequal participation, which appear to be characteristic of MOOCs and similar learning environments. He holds the view that “the funnel of participation is a real, significant phenomenon in MOOCs and related courses. Compared to formal learning, there tends to be much higher rates of drop-out and steeply unequal patterns of participation”.来~自^优尔论+文.网www.youerw.com/