Nina Hood

The Many Guises of MOOCs

Massive open online courses (MOOCs) often are viewed as synonymous with innovation and openness. In this chapter, we trace their origins and varied manifestations and the ways they are understood. We interrogate the wide-ranging uses and interpretations of the terms massive, open and course, and how these terms are represented in different types of MOOCs. We then identify contradictions associated with MOOC excitement. Despite the initial agenda of MOOCs to open up access to education, it is seen that they tend to attract people with university education. Rather than offering scaffolds that support people who are not able to act as autonomous learners, MOOCs often are designed to be used by people who are already able to learn. Like traditional education systems, MOOCs usually require learners to conform to expected norms, rather than freeing learners to chart their own pathways. These norms sustain the traditional hierarchy between the expert teacher and novice learner (Ross et al. 2014). A particularly troubling feature of MOOCs is that, as supports are becoming automated and technology-based, this power structure is becoming less visible, since it is embedded within the algorithms and analytics that underpin MOOCs.

Re-imagining the nature of (student-focused) learning through digital technology:

Digital technology is frequently positioned as being central to the establishment of a ‘future focused’ education system that provides high quality student-focused learning opportunities and re-envisioned educational outcomes. While recognising the potential of technology, this paper explores some of the questions about its role in education and learning – in particular, how technology addresses issues of equity and social justice; what it means to design educational and learning experiences that are truly student-focused; and the potential for technology to dehumanise the learning process. The paper concludes with some considerations of how to integrate digital technology effectively into an education system.

Designing for Quality

There are significant complexities in interpreting and measuring quality in MOOCs. In this chapter, we examine experts’ perceptions of how to measure quality in MOOCs, using empirical data we gathered through conversations with MOOC specialists. In their experience, while data can be helpful in understanding quality, the metrics measured are shaped by underpinning assumptions and biases. In conventional education, it is assumed that the learner wants to follow a course pathway and complete a course. However, this assumption may not be valid in a MOOC. Quality data might not capture the underlying goals and intentions of MOOC learners. Therefore, it is difficult to measure whether or not a learner has achieved his or her goals. We stress the need to explore quality metrics from the learner’s point of view and to encompass the variability in motivations, needs and backgrounds, which shape conceptions of quality for individuals.

Massive Numbers, Diverse Learning

MOOCs provide education for millions of people worldwide. Though it is not clear whether everyone can learn in a MOOC. Building on the typology of MOOC participants introduced is in Chap. 3, and we explore the claim that MOOCs are for everyone. We trace the different reasons people participate in MOOCs and the ways they learn. MOOCs tend to be designed for people who are already able to learn as active, autonomous learners. Those with low confidence may be inactive. However, even learners who are confident and able to regulate their learning experience difficulties if they don’t comply with the expectations of the course designers or their peers. For example, if a learner chooses to learn by observing others, rather than contributing, this behaviour can be perceived negatively by tutors and by peers. This indicates that MOOCs sustain the traditional hierarchy between the educators (those that create MOOCs and technology systems) and the learners (those who use these courses and systems). Although this hierarchy is not always visible, since it is embedded within the algorithms and analytics that power MOOC tools and platforms.

The Emancipated Learner? The Tensions Facing Learners in Massive, Open Learning

MOOCs have the potential to challenge existing educational models. Paradoxically, they frequently reinforce educational conventions by requiring the learners to conform to expected norms of current educational models. Recent research has produced data on how learners engage in MOOCs. And yet, despite the extensive data, rather than freeing learners to chart their own pathways, MOOCs still require the learners to conform to expected norms. The very act of learning autonomously often causes tensions, most noticeably when learners choose to drop out, rather than complete a course as expected, or when they engage in MOOCs as mere observers, rather than active contributors. In this chapter, we explore how the emphasis on the individual as active and autonomous learner sometimes conflicts with the expectation that learners conform to accepted norms. This expectation that learners conform to accepted ‘ways of being’ in a MOOC isolates those who plan their own pathway. The chapter concludes with a typology of different learners, arguing that, rather than adhering to a ‘type’, each MOOC participant moves across these learner types, depending on their motivations, and may span different types, rather than falling into one single category.

The [Un]Democratisation of Education and Learning

MOOCs have engendered excitement around their potential to democratise education. They appear to act as a leveller and offer equal opportunity to millions of learners worldwide. Yet, this alluring promise is not wholly achieved by MOOCs. The courses are designed to be used by people who are already able to learn, thereby excluding learners who are unable to learn without direct tutor support. The solutions to this problem tend to focus on the course, as ‘learning design’ or ‘learning analytics’. We argue that effort needs to be focused on the learner directly, supporting him or her to become an autonomous learner. Supporting millions of people to become autonomous learners is complex and costly. This is a problem where education is shaped principally by economic and neoliberal forces, rather than social factors. However, ‘automated’ solutions may result in attempts to quantify learners’ behaviours to fit an ‘ideal’. There is a danger that overly simplified solutions aggravate and intensify inequalities of participation.

A Crisis of Identity? Contradictions and New Opportunities

Drawing on the previous chapters, this chapter explores four tensions that characterise MOOCs. Although MOOCs are seen as an attempt to democratise education, they often privilege the elite, rather than acting as an equaliser. MOOCS are also considered a way to radically open access to education, yet they tend to offer education to people who are already able to learn rather than providing opportunities for everyone. While MOOCs are positioned as a disrupting force, often they replicate the customs and values associated with formal education, rather than unsettling educational norms. MOOCs are conceived as social networks that allow learners to learn through dialogue with others, yet many learners have limited interactions with others. Even when learners have the ability to learn autonomously, they often are expected to conform to course rules, rather than deciding their own learning strategies. These problems may be accentuated where MOOCs are viewed as a set of products (content and credentials) on sale to student consumers, rather than as a transformational educational experience for learners. The view of MOOCs as a product for the consumer learner may overly simplify the complex, transformational processes that underscore learning. Particularly where underlying automated systems try to improve progression by quantifying learners’ behaviours and ‘correcting’ these to fit an ‘ideal’ learner profile or where algorithms and metrics are based on convectional education, rather than on future-facing forms of learning. This chapter examines these problems with MOOCs, offering promising future directions.

Conceptualising online knowledge sharing: What teachers’ perceptions can tell us

Abstract This study questions the current dependence on theories of social learning and communities of practice in research on teachers’ online learning and online knowledge-sharing behaviour. It employs the interpretative approach to examine how teachers conceptualise their engagement with two USA-based online knowledge-sharing platforms within the context of their broader teaching practice. The findings suggest that the platforms, together with teachers’ engagement with them, are intimately connected with, and must be understood in reference to, both the online and offline contexts in which they operate, with each setting providing unique affordances that shape engagement and outcomes. Teachers’ engagement was largely motivated by their individual knowledge requirements and practice-based needs, resulting in learning primarily being individually rather than socially mediated and constructed.