This is the second post of four capturing my paper presented at the ALT Conference, 3-5 September 2019, Edinburgh (abstract, annotated slides, video recording). This section looks at the contradictions prevalent in designing MOOCs (massive open online courses) and expands upon the presentation with exploration of personalised learning.
The first post explored learning design perspectives that influence online professional development for teachers. This section considers how the professional development needs of teachers, or indeed any open course for professionals, has to balance many different design decisions.
Contradictions of open online course design
Personal needs vs. sequence of activity
In previous work, I have touched upon the difficulties inherent in developing a course that, through its open access brings learners with diverse learning goals (DeBoer, et al., 2014), and the design contradiction of a predetermined sequence of activity. Even the navigation through a course in a non-linear pattern is implicitly constrained by how a course is presented on a platform with clear structure. For the courses I lead, the platform is FutureLearn which adopts a weekly layout and numerically numbered course pages (steps).
That is not to say that having a structure itself is at a detriment to learning, as a logical progression through content, with content grouped by theme, headed up and placed within a manageable weekly schedule provides a learning structure. More exploratory forms of presentation, such as mindmaps, many interconnected pages, even Padlet-like boards of content nuggets would struggle to support linking of specific concepts to a bigger picture or conceptual narrative that would better propel learners through sequential content.
However, there is a question as to how learners who have a specific learning goal in mind locate the activities and content to help them meet that goal, without proceeding linearly through a course. Part of this is due to the perception of linearity, with the expectation learners may have that course completion requires a linear progression. In my view, this comes from trained behaviours of formal education, where it is expected to complete a course by undertaking every task and viewing content in a linear sequence.
This is in complete contrast with informal learning which tends to meet more immediate development needs. Consider the example of functional needs, such as knowing how to use a formula in Excel. This can be met in a non-linear way, by experimenting, searching online, watching a video or reading a help file. It may be that the content first accessed is too detailed, or not sufficient to resolve the development need, therefore there is a more iterative process which gradually refines the choice of learning content and task in tandem with experimentation. Such an approach is perhaps more akin to problem-based learning in formal settings. In open online courses, further exploration is needed to understand whether learners adopt such iterative approaches to addressing development goals over longer periods of time.
Individual timelines vs. socialisation
If discussion and collaborative activity are key aspects to the learning design, then there must be some form of synchronicity of activity (even within ‘asynchronous discussions’). Learners need to be present within the same space, and whilst not at the exact same time. There needs to be consideration then, what the window of opportunity for collaboration may be.
FutureLearn learners can join courses up to 11 weeks after the course start date. Most learners will join within the first week of the course starting, and therefore most discussion, interaction and collaboration happens in sync. However, with an increasing proportion joining after, it is difficult for course designs to still enable the benefits of social learning.
Similarly, the weekly structure of the online course can be sidestepped, where a learner takes a week off and then returns where they left off. They are now out of sync with the majority of learners, and indeed out of sync with any weekly-timed emails.
Finally, where there are calendar-based activities, such as recorded Q&A sessions with educators, there are learners who have kept pace with the course from the start date and are in the best position to contribute as well as learners fresh to the course. Both should be welcomed to participate, and in some cases the Q&A acts as a personal signpost from the educator to the learner to indicate which parts of the course would be most relevant. Therefore, activities, whether ‘asynchronous’ or ‘synchronous’ have to be designed for a wide range of individualised learner timelines and pace.
“It is not only the magnitude of data, but also the diversity of user intentions and backgrounds and the unconstrained asynchronicity of their activities that distinguish the MOOC context from conventional classrooms.”
DeBoer, et al. (2014:82)
DeBoer, et al. (2014) talked about the way learners use open online courses differently, to meet their individual needs. The idea of ‘unconstrained asynchronicity’ wonderfully encapsulates the idea that learners will be engaging with a course when and where it works for them, doing activities flexibly and even joining the course out of sync with other learners and facilitation periods. This presents us with learning design challenges, how to ensure our learners can still undertake professional development both in terms of social and instructional pedagogies, with and without support.
Openness of access vs. self-efficacy of learners
The third contradiction I am considering is based on the supposition that open education is open to all. In order to access open online courses, there are various technical hurdles to overcome, arguably less so than in previous decades. There are also issues of awareness and how many individuals know that this form of learning exists.
The issue of self-efficacy of learners to learn online is the biggest challenge I view for the effectiveness of open online learning. Within an open online course there may be experienced online learners, those who have the collaboration and communication skills to further their learning through interaction with others, or those who are new and consider the course as an online textbook, passively consuming, but limited in self-motivating cognitive effort. A learning design has to bridge these two extremes, catering for those who both want to learn, but are not sure how to maximise their learning, and those who can steer their own path.
“Ultimately, if people are to become effective learners, they need to be able to learn on their own. They need to be able to find the resources they need, assemble their own curriculum, and forge their own learning path. They will not be able to rely on education providers, because their needs are too many and too varied.”
Downes (2016)
I would argue that there is a tension where open online courses require a form of learning that is simply not trained to learners through traditional educational systems. In schooling, and some respects modular-based higher education, there is a linear path to follow and a curriculum laid out by the educator. As Downes (2016) described, to meet personal learning needs, a learner really has to hold the skills required to draw upon what is most relevant to them. This way of thinking about learning, as alluded to by Downes, requires a shift of direction from the deliverer of education to the learner themselves. A learner needs to be confident in making decisions about which content and activities they will and will not undertake. This is efficiency of learning, as much as effectiveness.
Implications of these contradictions
The variation of learner goals on open access courses and the diversity of learning self-efficacy does provide learning design challenges. In a MOOC purposed for educators (a skewed audience already), Salmon, et al. (2017), noted:
“Those participants who were able to be flexible and move quickly and easily around the MOOC (we called them “agile learners”) had a greater capacity to adjust to the MOOC experiences and adjust their original expectations if necessary.”
Salmon, et al. (2017:1290)
Considering their learners were educationalists, it is surprising that this ‘capacity’ to be an ‘agile learner’ was not ubiquitous. Though the demographic Salmon, et al. (2017) indicated had a significant proportion with previous experience of MOOCs specifically, not just online learning, it perhaps could be suggested that even having prior learning through open courses still does not lead to an understanding of how to best learn online. Milligan and Littlejohn (2016:117) suggested otherwise, where “experienced MOOC-takers often talked… about how they had settled on an approach to MOOC learning.” Their MOOC for health care professionals identified, in the majority, learners had confidence and learning skills to complete activities and sustain engagement. In the minority, learners would acknowledge time is required to have a deep understanding but fail to allocate appropriate time to complete the course (Milligan and Littlejohn, 2016).
Whether a learner succeeds by their own definition or by the course designer’s, may be due to how many open online courses do not scaffold or facilitate the reflection of the learning experience itself. Both Milligan and Littlejohn (2016) and Salmon, et al. (2017) suggested strongly the role of scaffolding learning approaches and enabling self-motivation to meet development needs. Both studies also concluded with recommendations for developing pathways through the content, “routes through content that suit their specific goals and motivations” (Milligan and Littlejohn, 2016:120). Yet, this appears to reiterate the complexity of the design contractions above. At one end of a continuum of self-motivation and learning skill, learners require support to sustain their engagement and purpose the content in their own contexts. This is probably best supported through facilitation. At the other end, the learning design itself, for facilitator support is not always available, must enable learners to realise they can self-direct, be flexible and find their own path.
“Identify typical participant cohorts and their likely desired expectations of the process of the MOOC, especially the behaviours of other participants and offer alternatives pathways, if deemed necessary;
Identify typical participant cohorts and their likely range of motivations, and, if in a large MOOC, offer different pathways through the materials to account for different motivations and expectations;
Encourage participants’ reflections and articulation of unexpected and emergent benefits of their continuing commitment to the MOOC…”
Salmon, et al. (2017:1291)
Some of the practices that support learners to identify their pathway have been embedded in the online courses on the programme I lead. This includes tasks to elicit development needs, reflection steps and importantly discussions to contextualise course content. These ‘self-audits’ currently only focus on the subject knowledge of the course and not on the capacity of the learner to undertake professional development. In a proposed design model to address some of the issues raised above, Gynther (2016) described an adaptive design framework.
“The design must be able to: identify the participants current skills – visualized in a competency profile; visualize a competence-gap in terms of a personalized curriculum; recommend a learning path which adaptively matches the learner’s personalized curriculum; identify the student’s ability to learn in and with a MOOC; establish an adaptive scaffolding of the student’s learning process in the MOOC.”
Gynther (2016:20)
The impression is a very complex platform that delivers a fully tailored curriculum for the individual learner, though mediated with blended learning to involve some degree of interaction between learner and educator in the choice of the learning pathway. However, Gynther (2016) regularly refers to difficulties in delivering certain learning activities, particularly in the face-to-face environment of the blended approach, where learners have highly personalised course pathways.
For fully online professional development, the limitations are more likely to come from the lack of personalisation or guidance to personalise learning. The offline aspects, such as implementation of course concepts in a professional practice, are instead highly personalised by context. There appears then to be significant value in the type of learning activities that allow a learner to find their own route through course content, by taking that course content, or not, back into their professional practice space.
Facilitation does play a significant role, and as Bonk, et al. (2018) suggested, online facilitators and course designers can use a range of educator-led personalisation approaches, such as “feedback techniques, pedagogical activities, resources, interactions, and assessments to address learner needs” (Bonk, et al., 2018:106). Lack of facilitation is not necessarily the issue, and is not the underlying issue from which the contradictions above emerge. The design challenges are more to do with enable learners to realise their learning goals through the bridging of the highly structured and linear course design and the highly personalised offline learning space.
Further, each of the design recommendations, perhaps more implicitly than explicitly, still focus on the completion of a course. Note ‘continuing commitment’ is the purpose of ongoing reflection as much as discovery of unintended learning outcomes. The course design still resides very much within a formal linear narrative, though the intended engagement may be non-linear or selective. In professional learning, as Milligan and Littlejohn (2016) explained, some learners will be motivated to complete from the outset, others complete to receive certification, but there was little exploration of the value of more selective learning engagement. Achievements in online courses, such as certification, only come from completion. Partial completion that has still met the individual learners’ needs, may be presented, wrongly perhaps, as a non-achievement.
In the next post, I will draw upon data from several open online courses to explore learner engagement patterns. I will argue the case to look beyond course completion and instead look to outcomes of a learning experience.
References
- Bonk, C. J., Zhu, M., Kim, M., Xu, S., Sabir, N. (2018). ‘Pushing Toward a More Personalized MOOC: Exploring Instructor Selected Activities, Resources, and Technologies for MOOC Design and Implementation’, International Review of Research in Open and Distributed Learning, 19(4), 92-115.
- DeBoer, J., Ho, A.D., Stump, G.S., Breslow, L. (2014). ‘Reconceptualizing Educational Variables for Massive Open Online Courses’, Educational Researcher, 43(2), 74-84.
- Downes, S. (2016). ‘Personal and personalized learning‘, European Multiple MOOCs Aggregator Newsletter.
- Gynther, K. (2016). ‘Design Framework for an Adaptive MOOC Enhanced by Blended Learning: Supplementary Training and Personalized Learning for Teacher Professional Development’, The Electronic Journal of e-Learning, 14(1), 15-30.
- Milligan, C. and Littlejohn, A. (2016). ‘How health professionals regulate their learning in massive open online courses’, Internet and Higher Education, 31, 113-121.
- Salmon, G., Pechenkina, E., Chase, A. and Ross, B. (2017). ‘Designing Massive Open Online Courses to take account of participant motivations and expectations’, British Journal of Educational Technology, 48(6), 1284–1294.
Next: Part 3 – Data
Leave a Reply