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Major issues associated with MOOCs (redirected from Major issues associated with MOOCs and their limitations)

Page history last edited by Xuan Nguyen 11 years, 7 months ago


Social issues


MOOCs have contributed to eliminate one of the great advantages the rich have always enjoyed over the poor by open online education provision (Downes, 2012a), which in turn, helps narrow the knowledge gap, promoting equity in education (Conole, 2012b). Likewise, Siemens (2012c) also shares his acclaim of xMOOCs that learners from different parts of the world who find xMOOCs extremely beneficial as they do not have access to learning materials of that quality at their institutions. “The strangest thing about this MOOC obsession is the idea that something that very wealthy private institutions offer for free, at a loss, as a service to humanity, must somehow represent the magic numbers in the higher-education lottery”, as Vaidhyanathan (2012) comments.


Nevertheless, it is unrealistic expectation of MOOCs that they will bridge all the gaps and bring social justice to the education as they still give more privilege a certain kind of learning and learner, in this case, those having technology access and digital literacy (Cormier, 2012). In fact, what inhibits this mission of MOOCs appears to be the prevailing unresolved problem of digital divide, conventionally known as the gap in equity between those who have already get access to such technology as computer and the Internet and those who have not (Bernard, 2011). Digital divide, once seen as an issue of wealth, is now seen as a matter of education and that those with digital literacy are likely to have more opportunities in evolving multiple learning opportunities in the digitally-networked society (Johnson, Adams, & Haywood, 2011). Besides, researchers point to a ‘participation gap’ which signals unequal access and accessibility to the opportunities, skills and experiences that will prepare students for life in the 21st century (Payton & Hague, 2010). Whilst some organizations are working to ensure that all people, regardless of income, age, or race, are not left without access or training to use and benefit from digital technology (Vega, 2011) and overall access to ICT has significantly grown in recent years, the digital divide still exists between and within countries (O'Brien, 2012).  


Cultural issues


Through their research into OER, including MOOCs, in different countries, Richter and McPherson (2012) find out that culture-related issues including the historical effects of colonization, language issues, contextual gaps, a lack of cultural diversity, educational privilege and illiterate adults, and the need for basic education are the main barriers to its adoption and development. Take language for example. It is clear that the worldwide web is written in most popular languages, especially those of Western colonialism. Conventionally seen as international language, English, as Kickbusch (2001) notes, is the language used in four four out of five websites while only one in 10 people speaks it. This implies that knowing such elite language as English is a privilege to have access to a wider learning community and that the possibility to do so remains limited. Even translation function is available; communication is still restricted due to delayed interpretation or mis-interpretation.


Trolling issues


A prominent problem related to the Internet culture is trolling, most of the time involving negative effects, which is one of the high risks that organization might probably face when running a MOOC. This kind of malicious behavior is also evident in MOOCs as it openness, unexpectedly welcomes massive chances for trollers to do so. The irrelevant and even misleading deceiving information has caused not only annoyance, confusion, but also posed challenges to the quality as well as security of MOOC experience. 


Copy right & IP issues


The question of who owns the content generated by teachers and students in a MOOC is not often asked nowadays as it is common knowledge that these intellectual properties are protected under creative commons, for instance, in MOOC MOOC course:

     Screenshot of MOOC MOOC Copyright


Nevertheless, as content is shared widely and openly in a confusing environment of the Internet, controlling the use of IP generated throughout a MOOC and ensuring it is not for commercial purposes is unfeasible.  This results in the critical problem of plagiarism. Being a prevailing issue in conventional education, plagiarism, in the increasing likelihood of academic dishonesty, particularly in online platforms, due to the insufficiency of regulation and supervision, seems to be unavoidable (Mak, 2012; Young, 2012). MOOCs, described by Patterson (2012) as “a cheating rich environment”, relying on auto-grading system and peer review, often without support of personal identification system, are much more susceptible to this problem. An interesting example is a participant’s story about plagiarizing in a fantasy and science fiction course offered by Coursera, as Young (2012) and Wukman (2012) report. Even though the plagiarism incident has been claimed, and openly debated in the forum, no influential action has been taken except for a professor’s call for students’ double checking and reviewing the essay. This is among many other cases of cheating, some are identified or other are not, which have not been thoroughly addressed. The software in used seems to be not very effective especially in “creative remixing” and that MITx have personal identification system software does not guarantee cheating elimination. 


N.B.: See also Butler (2012) for useful information about  legal and policy issues in relation to MOOCs. 


Assessment issues


Scalable automated assessment and (mostly summative) feeback are what set cMOOCs and xMOOCs apart. It has been seen as “the innovation driving the xMOOC phenomenon” (Carson, 2012). The ability to provide feedback to thousands of students at once benefits providers more than learners. Yet, these insufficient support and rigorous assessment of MOOCs account for their inappropriateness to many learning styles and contexts (Left, 2012).


So far, as observed by Carson (2012), there have been three main types of automated assessment. The most popular one involves quiz questions. A more sophisticated form is simulation, for example the circuitry sandbox used for 6.002x, enabling open-ended manipulation of variables, and hence, requiring more development effort. At a higher level of complication are the true adaptive learning environments in such courses as Carnegie Mellon’s Open Learning Initiative.


Significant efforts have been made in improving assessment in xMOOCs. Lugton (2012a) notes that one-sided broadcast that constitutes most lectures are now replaced by a sum of smaller units of consumption and comprehension testing, which are believed to make the lessons more engaging and easier for learners’ uptake. Coursera also attempt to implement a creative system for crowdsourcing peer assessment. For example, in the Human Computer Interaction course, students are to mark each other’s work based on a clear rubric, being themselves evaluated to be an adequately accurate assessor (Lugton, 2012a). However, again, this method of assessment is still restricted with just numbers, in order to keep the consistent standard of marking. In the end, this does not make much sense even though students may probably learn from peer evaluating.


Concerning cMOOCs, their approach to and participants’ perception of the importance of assessment are markedly different from those of xMOOCs (Quinn, 2012). Despite having no particular kind of assessment, cMOOCs exploits a robust peer learning community as valuable crowdsourcing means of evaluation in major form of formative feedback. One piece of opinion could be shared and discussed from a wide spectrum of diverse perspectives, many of which are of highly knowledgeable, experienced, and talented people around the world (Watters, 2012c). In Quinn’s (2012, para. 3) words, “assessment comes from participation and reflection, without explicit contextualized practice”. This is obviously of far greater value than being assessed or receiving feedback by a machine automatically or even by a lone instructor. Furthermore, this goes beyond assessment solution but heightens the significance of a meaningful learning community where great ideas potentially meet or are generated, which is vividly illustrated in Johnson’s (2010) video below:



Above all, open and massive nature of MOOCs demands certain flexibility (Mak, 2012d; Friend, 2012). There is no point in trying to do the impractical task of tracking and assessing performance of an enormous number of students for no credits since students obviously outnumber instructors. It also adds unexpected and unnecessary extra burden to teachers. Mak (2012d) pinpoints that research in MOOCs tend to put assessment last as it is not easy to assess learning emerged out of MOOCs as it inevitably involves a lot of conversation, interaction, and development of personal learning experiences. He further explains that the assessment of learning in an open distributed space can merely be based on a subjective measure as formal objective and collective assessment is out of question. Needless to say, it is impossible to evaluate a MOOC learner’s achievement based on the course outcomes as each of them has his or her own learning goals that may be different from those of others and those of the course (Mak, 2012d). Hence, it might be a better idea to empower students with that authority and to stop worrying about the assignments and assessment so that real learning can happen for learning’s sake in MOOCs (Friend, 2012)


--> Strategies for implementing MOOCs


Comments (2)

Hnin Pwint Soe said

at 8:17 pm on Oct 31, 2012

Issues are well-discussed!! =)

Xuan Nguyen said

at 8:18 pm on Oct 31, 2012

Thanks, Pwint :D

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