Big Data

As IDEL progressed we seem to have moved away from perhaps some of the more theoretical and human topics, towards a more technical focus. Week 9 was focused on digital badges and blockchaining, and week 10 looks at the concept of ‘big data’ and its implications for education.

Like blockchaining, I’m aware of the concept of big data, but have not got to grips on what this means, or what it can do for us. I think there’s a danger some of these initiatives can be seen as simply buzzwords or part of the zeitgeist, without any longevity to them. But it’s apparent by digging into both blockchaining and big data that these are unlikely to be fleeting developments and are likely to underpin many technical changes over the next few years.

Unsurprisingly, and in line with the rest of the course so far, the focus on the readings has been to contrast the opportunities big data provides with some of the pitfalls. There’s also been a focus on some of the blind spots in this area.

So starting with the positive aspects, with Selwyn (2015) highlighting three areas:

  • Increased ability to use data to measure goals, targets, benchmarks, performance indicators etc
  • An ability to harmonise and standardise across borders, whether these be institutional or geographic
  • To provide a basis for an infrastructure for education to be understood and organised

But naturally, there are some challenges. Eynon (2013) puts the spotlight on three aspects for concern:

  • The ethics behind the sourcing, mining, interpretation and ultimately use of the data
  • The scope of the data, what can be measured as a results, and the questions it can (and can’t) help us answer
  • Inequalities linked to the sourcing and accessing of any data.

The area of ethics is one discussed in detail across several of the recommended readings, as it seems to be a grave cause for concern. A wonderful example is given by Williamson (2015) on use of data provided by Facebook, and the criticism afterward about the permission (or lack thereof) around the use of the data (the defence being that it was already in the ‘public realm’).

To provide an example related to university admissions, at present applications are (largely) based on Academic results at an undergraduate level. However ‘big data’ could provide the ability to forecast degree completion, and perhaps future earning potential, and even link this to social backgrounds and family history. Naturally, on the one hand, this could be empowering – providing institutes with more insight into how to support their students to succeed. The rather dystopian view is that this could prejudice entry requirements, and given some of the metrics being forced upon universities (e.g. ‘satisfaction ratings) and the subsequent ‘slap on the wrists’ as a result of this, it doesn’t seem impossible that big data will be used in this way at some point.

Selwyn (2015) extrapolates these issues further to explore what they may mean for institutes and their students. He argues that this increase in performance metrics may create an “intensification of managerialism within education”, which suggests a move towards a workplace more typical of a commercial organisation.

This commercial influence is unsurprising, given the history of big data. It seems to me that using the processes and themes of big data in education comes with it with ‘baggage’, because of its very design. Because of the commercial background too, it’s important to critique the strength and role of the educational or academic voice within technical developments such as this. This harks back to one of IDEL’s earliest topics, about the role of technology in education, and who is at the table when it comes to the discussions and implementation of this. This seems to be another example of where education could be perceived as a recipient of this technology, rather than helping to shape it.

This is of particular concern when you read about Pearson’s developments in Williamson (2015). Some of the criticism of Pearson could be seen as a reaction against their developments, but when Williamson argues that Pearson could be using big data to create new “models of cognitive development and learner progression”, then this would be a major red flag. Pearson’s main responsibility is to their shareholders, to their students, so it’s important that the progression of technical initiatives like big data is not left to commercial educational companies to drive.

A common issue picked up by Eynon (2013), Selwyn (2015) and WIlliamson (2015), is that of an institution’s capability, or more specifically the personnel within it, to use big data. ‘Use’ in this context, is quite a broad term, from sourcing and mining the data, through to combining with different sources and interpreting it. Williamson argues that there are “several competencies for education data science”, and that there is a significant deficit in the numbers of those equipped with the necessary skills. The skills are a blend of the technical (computational and statistical skills), the educational and an understanding of the ethical and social concerns in this area. As such, Williamson argues that educational data science is very much a field in its own right, rather than an appendage to statistical analysis. Naturally, if this is an area that is significantly under-resourced, then this reduces the impact education can have in shaping big data.

This may also be more difficult to fix than Eynon envisages. The demand for talent – given the nature of the role – is spread across both commercial and educational organisations, meaning commercial companies may be able to outbid educational institutes for their services. It may be one thing to recognise the issue, but fixing it may be increasingly difficult.

I picked up on several themes across the papers that have been discussed earlier in IDEL.

Given the rise of commercial influence in this area (in particular), there seemed to be a ‘call to action’ to the wider educational crowd to become more vocal, and come more centre-stage in these discussions. Selwyn (2013) argues that “the opportunity now exists for educational research to develop nuanced approaches to understanding, and then offering alternatives to, the dominant data conditions that are being established across educational contexts”. This reminded me of Biesta (2013), in his call for teachers to teach, and Bayne (2015) to ensure academia has a role to play in wider technological developments.

Biesta’s references to a neo-liberalistic agenda also pop up in Selwyn – “expanded access to data allows institutions and individuals to operate more efficiently, effectively and equitably”, and Eynon also references themes of efficiency and cost-effectiveness in big data.

Selwyn (2013) also uses the metaphor of water in his discussions around big data. ‘Deluge’, ‘flow’, and ‘flood’ are terms used, and I think this possibly inevitable. The comparisons between data and water are natural – is it aplenty, can travel at speed (rivers) or not (lakes), comes from many different sources and directions, and requires real skill to manage. It’s also a fundamental of life, and you can argue data is the bedrock of economies now (it’s even been termed as more valuable than oil). The dystopian view is that it can also be a dangerous force of huge power, and like recent devastating floods all over the planet, can pose an immediate danger to us through years of mismanagement.

I thought it was interesting that Selwyn (2015) points out that the sociological approach to data is to assume that there are already some inherent issues with it. This admission of lack of neutrality is quite refreshing, and makes a lot of sense. It’s a battle that’s difficult to fight – it’s probably a better use of time to acknowledge this and work out how to deal with it than try and fix at source. The rhizomatic metaphor is also apparent here, in that Selwyn argues that “this approach is careful to acknowledge that data are profoundly shaping of, as well as shaped by, social interests”.

As a final thought, I liked this quote from Eynon (2013) – “We must not get seduced by Big Data”. I think if you were to replace ‘Big Data’ with ‘technology’, you’ve probably got the core theme of IDEL in a nutshell.

References:

Bayne, S., Gallagher, M. S., & Lamb, J. (2014) Reflections

Being back ‘at’ university over the last seven weeks, after so long outside of more formal education has been a challenging, but invigorating experience. This week we’ve been building on previous themes around online environments, community and spaces to think about our experiences as distance education students, and what it means for us to be ‘at’ university.

Bayne, Gallagher and Lamb’s paper is a great resource as it dissects the views of previous MSc students on this very course – so fantastic material for IDEL and this topic!

Some key points I took from the paper:

  • Distance education is often theorised through the lens of on-campus education. There are inherent issues and limitations with this. “The distancing of education makes possible new spatial practices, new patterns of movement and ‘new proximities’.”
  • Traditional perspectives from social science on spaces are not adequate to look at the ‘hosts, guests, buildings, objects, and machines’ at play in the topology of courses such as this – the ‘new mobilities paradigm’.
  • The authors used 4 kinds of proposed social spaces to consider social and mobility aspects of distance learning – regional, network, fluid and fire. These are intertwined and occur simultaneously, they are not mutually exclusive.
  • The physical campus is important to distance students, but in varying ways to different students.
  • Some students have an emotional/sentimental/nostalgic connection with the physical location  – others very little.
  • Absence is as important as presence in looking at the relationship between university and student (and can be overlooked if just viewing through ‘on-campus’ perspective).
  • The campus can be fluid and transient – a “cognitive (piece of)… real estate”.
  • There may need to be ongoing calibration of what it means to study ‘at’ a university in light of this, for all stakeholders including tutors, administrators, academic leads and students themselves.

This paper came at a good time – I’d already been wrestling in my head what it meant to be studying at the University of Edinburgh. I certainly share similar thoughts to some of the students who were interviewed as part of the research, in particular, Matthew Gillon’s quote that:

“In a strange way, I didn’t feel that I wasn’t in Edinburgh.”

This double negative is important. I don’t feel like I’m in Edinburgh (as I’m not), but I don’t feel as if I’m not in Edinburgh – there’s an important distinction here.

Erik Credle’s perspectives also strike a chord:

“I feel a sense of belonging to the University, but at the same time I dont feel that I am actually part of the University.”

I certainly feel a sense of belonging to the course and the team behind it, my fellow students, but perhaps differently to Erik I don’t feel a real connection with the university. At present, I feel more of an affinity and connection with the city than the university, which feels like a contradiction in terms. I think this may be the way I am viewing the university, as a physical place.

Having strong interactions with the course and its various participants creates the bond with the course. I think having visited Edinburgh before, and being able to visualise/feel/experience the environment, this is an important contributor.

I can’t help but feel having never visited the university campus this has a detrimental impact on my relationship with the university, but in any case, I don’t think this an important factor for me. The university is almost more important pre-course, when gauging the likely rigour and quality gone into creating and curating the learning experience. I think I’ll need more time to let this percolate and consider fully!

Reviewing this paper in light of recent readings, I again spotted some recurring themes:

  • The course repeatedly questions the approaches used in current discourse within digital education. Like Friesen questions the instrumentalist and essentialist approaches to technology (and the blind spots this causes), in this paper this is echoed in the approach taken to viewing ‘non-campus education’. These critical approaches can only be a good thing, and is at the very core of good scientific practice!
  • Rather than seeing things as separate strands (e.g. Friesen’s view on essentialism and instrumentalism), there is an ongoing challenge to view things as symbiotic and intertwined (with good reasons why!). In here we see this approach taken to the spatial topologies discussed.
  • Again there are issues with terminology and the implications of the choices made on this. Like Bayne argued the weaknesses with the phrase ‘Technology-Enhanced Learning’, here we see a similar argument around ‘Distance Learning’. These could be seen as ‘growing pains’ with the increasing introduction and usage of technology, but important to be discussed and addressed.

Before reading the paper, and the comments from alumni as part of this, it was useful to consider the questions posed.

My own personal view of arriving at the University of Edinburgh was the rather overwhelming contact points and breadth of information sent to me by email! It didn’t feel like a smooth experience, but in retrospect, I think this was a key aspect of realising that I’m studying at university again. With all the different departments and administrative functions in contact, you get a sense of the size and scale of studying at an institution, and I think this was an important realisation. And I’m not sure of the importance of this yet, but receiving the invoice and paying the course fees also had an effect, I’m still trying to distill what this was! All these different touch-points contribute to processing and establishing the experience, and without this, I may have taken a different approach (or level of focus?) to the course. As a contrast, you don’t get this with a MOOC for example (emails on matriculation, information on freshers week), and this inevitably adds to the unconscious feeling of uni ‘-lite’. As someone who is involved in positioning and marketing of products, this really stood out.

On reflection, I think twitter has been an essential tool for me to get a wider understanding of the University of Edinburgh. Although I’ve not actively engaged with them, it’s interesting that I feel I have a connection with two of the writers of the paper, Sian Bayne and Michael Gallacher. I see what they are discussing, what peaks their interest, who they, in turn, engage with. It helps position them as thought leaders who are in active debate and makes the course feel even more ‘alive’ and ever-evolving. I think it’s interesting that Twitter’s not been a central part of the course, yet without this, I feel the wider experience would have been poorer.

Finally, I absolutely loved the concept of a ‘digital postcard’. Wow, what a fantastic idea. Naturally, the first thought is “why not just use a video, that’d capture audio?”, but video forces you to go along with the pre-set pace and narrative, rather than allowing the viewer to explore and digest at their own speed. When tool we use heavily in my business is H5P. It’s a WordPress plug-in, used to add interactivity to media using HTML5 (think of it as being a poor person’s Thinglink). Continuing the experimentation, here’s my own digital postcard from my place of study.

(Caveat – my desk isn’t usually this untidy. It’s been a crazy week, but all the junk adds to the experience!).

References:

Metaphorical concepts

So it seems that how we think, act and speak is influenced by the metaphorical choices we use to conceptualise ideas. Another eye-opener in week 6, this time from Lakoff, G. and Johnson, M. (1980). As someone who resorts to metaphors quite often in language (in my on-going battle to articulate myself with clarity), it was interesting to read that this is more than just language – indeed the very metaphors we choose can influence how we think.

Continuing the spirit of experimentation, I pulled together a video of some of themes in biteable:

In traditional form though, here are some bullets for my own reference:

  • Metaphorical concepts are more than ‘skin deep’. We are able to articulate concepts metaphorically because we conceive of things metaphorically, then act metaphorically.
  • Structural metaphors – where one concept is metaphorically structured in terms of another. E.g. Time is money.
  • Metaphorical concepts may be only relevant to certain cultures
  • Metaphorical concepts may be interrelated, to create a metaphorical system
  • Metaphorical concepts are only partially structured. Time (the target domain) is analogous with money (the source domain), but time isn’t money. Therefore this can hide and limit the understanding of the target domain.
  • Orientational metaphors – organises a whole system of concepts with respect to one another. Spatial in that refer to our being in a physical environment. E.g. I’m feeling down.
  • Metaphorical systems provide an overarching theme to capture many metaphorical concepts, e.g. Happy is ‘up’.

I see the links in this paper with Bayne (2015), in terms of how choice of language, as innocuous as it may seem, can have wider repercussions if not chosen well, or at least without a critique of why the choices have been made.

Having done some further reading around this, I’ve come across Whorf’s theory of language, which perhaps looks at this from a different angle – that the choice of language itself shape how their speakers perceive and conceptualize the world.

In a forum thread earlier in the course, Clara O’Shea talks about mycorrhiza, and the symbiotic association this represents. This seems to be a pervading theme across the course, whether it be related to technology and teacher, metaphor and language, learning and education, teacher and student, instrumentalism and essentialism. There is a rich and intertwined dynamic going on throughout these topics, and it seems clarity is lost when the factors are treated as distinct individuals, rather than acknowledging the interplay between the two.

In terms of how metaphorical concepts apply to the digital environments, this is going to be interesting to explore on the forums with the rest of the guys. With regards to the idea of learning I can already see concepts such as nature, or growth coming through e.g. “it gave me the seed of an idea that grew”, and perhaps this is lost at times with digital, where the viewpoint (in some circles) may be to revolutionise, rather than evolve?

References:

  • Bayne, S. (2015). What’s the matter with ‘technology-enhanced learning’? Learning, Media and Technology, 40(1), 5-20, DOI: 10.1080/17439884.2014.915851
  • Lakoff, G. and Johnson, M.(1980) Metaphors We Live By. (London, University of Chicago Press). Chapters 1-4. pp3-21

Cousin, G. (2005) musings

Week 6 of IDEL and I think we’re moving into more familiar territory. Although digital environments is a very broad term, and Minecraft is still very much an unknown, we’ve begun to start using terms such as VLE, which is a bit closer to home.

Cousin, G. (2005) has been a really interesting read, and a great way to kick things off. I’m quite surprised how relevant many of themes still are, given its relative age (12 years) and all that has changed since.

It seems the author had a remarkable amount of foresight too, for example:

“technologies are constitutive of our identities”.

Given it was 2005 at time of writing – when it could be argued social media was very much a novelty – little could she have known how our identities these days are as much online as offline.

There were some key themes that I picked out:

  • She argues that the instrumentalist viewpoint is widespread at the time that this was written. This concurs with Friesen’s observations (Friesen, N. (2013) that use of technology is been viewed as plugging into the existing pedagogy.
  • Cousin argues that pedagogy has always been intertwined with technology, and that the two are “mutually determining”.
  • Technology should not be viewed as inert or separate from technology. Terms like ‘toolbox’ add to this. She argues that “different media demand different levels and forms of engagement or our senses and social relations”.
  • Power or control is a contributor to the positioning of technology as an enhancement. Again this keeps on coming up in the readings, the most relevant here being Selwyn, N. (2011).
  • She argues that VLEs tend to be skewed towards the simulation of the classroom, again this is referring to the instrumentalist approach.

The paper echoes previous readings in parts on the debate around the approach to technology within education. The resistance to the adoption of technology in education also seems to be still relevant.

It was Interesting to read the author’s observations that to avoid protestations within the teaching community, technology was being positioned as enhancing what is already good about education. This reminded me of a twitter thread recently, about how the notion ‘practice makes perfect’ is flawed should actually be repurposed as ‘practice makes permanent’. The sentiment being here that practice only reinforces something, it doesn’t change its nature. In the same way, technology could also be used to enhance bad teaching practice if the underlying pedagogy isn’t sound.

I can’t help but think that the argument that VLEs mirror a classroom approach still tends to hold true. But I’m not sure if this is entirely unexpected, particularly given some of the VLEs I’ve experienced and the story of their development. Again this refers back to earlier conversations we’ve had on the forums concerning the educational community’s influence in technology.

From my professional experience, many of the VLEs in the workplace have been brought over from more educational or academic backgrounds. We’re starting to see this change, with the advent of more resource-orientated frameworks (such as Fuse), and the development of tools such as xAPI which aim to acknowledge the learning that happens outside of formal training experiences. Perhaps these will feed back into the more academic VLEs, and improve them for the better.

(On a side note, given Biesta’s criticism of the ‘learnification’ of education, should in some cases the VLE be re-titled as the Virtual Education Environment 😉 ?)

I’d argue that with regards to terminology, work environments are more orientated towards ‘learning’ than ‘being educated’. Simple reason being that at work people want to access information and guidance to support them in doing something, usually right then and then. Given that, it’s less about a separate educator or teacher, the learner themselves are taking on aspects of the teaching role themselves by sourcing and validating (to some degree – this could be as little as being top of a search query) a piece of content. A slide on Nick Shackleton’s recent presentation at World of Learning summarises this quite nicely:

I suspect when we look at digital environments and spaces over next couple of weeks this is going to be particularly useful in the ‘day job’, and am looking forward to finding out more!

References:

  • Cousin, G. (2005). Learning from cyberspace. In R. Land & S. Bayne (Eds.), Education in Cyberspace. Abingdon: RoutledgeFalmer.
  • Hamilton, E., and Friesen, N. (2013). Online education: a science and technology studies perspective. Canadian Journal of Learning and Technology, 39(2), 1-21.
  • Selwyn, N. (2011), Education and Technology: key issues and debates. London: Continuum.
  • Biesta, G. (2012) Giving teaching back to education: responding to the disappearance of the teacher. Phenomenology & Practice. 6(2), 35-49. journal article]

A critical analysis of Hamilton, E., and Friesen, N. (2013)

One of the key aspects Hamilton and Friesen (2013) argue is that studies into the potential of technologies, and the pedagogical value of these, are limited by the approach often used in the conduct of the research. This echoes studies by McDougall & Jones, 2006 and Roblyer, 2005, that research into this area has “struggled to find its theoretical roots” (Graham, 2011, p. 1).

Hamilton and Friesen’s rationale is that a significant amount of research to date has been conducted through the viewpoints of essentialism and instrumentalism. These orientations, while providing useful insight, are hindered as “they fail to grasp the social and historical dimensions of technology”.

Indeed, Hamilton and Friesen are not lone voices in this area. Selwyn (2012) stresses that “education and digital technology should strive to analyse the exchanges between everyday practices and the encompassing cultural and societal structures” (p. 91), adding backing to the importance of social considerations. This echoes Savin-Baden, Tombs, Bhakta (2015), in that “research has tended to neglect the social context within which students interact with pedagogical agents” (p. 297).

Hamilton and Friesen make a persuasive case of their argument through detailed reasoning and strong evidence. By providing a thorough dissection of the essentialist and instrumentalist approaches on a theoretical basis, this allows the reader to pick apart the theoretical considerations, and in turn view the deficiencies in the two approaches. This also provides the reader with an insight into the depth of examination that has been conducted.

Investigations such as this are important, as any weaknesses in the research (of any subject area) have to be a cause for concern. Ultimately if the conclusions of any research work are to be used to provide a ‘sure footing’ to guide future development and influence direction, it needs to avoid any limitations. As the authors put it, the limitation “hampers understanding of the educational value of new technologies”.

While the critique of recent research appears strong, nonetheless there are areas in the paper that warrant scrutiny.

The assertion in the introduction that “technologies… (are)… of beneficial value in education.” is rather broad, and could be argued glosses over some of the intricacies and practicalities around the use of technology in education, and also don’t consider the  negative perspectives (for example Selwyn (2011) and Wood, Mueller, Willoughby, Specht & Deyoung (2005)) around this topic.

Whilst the authors make a compelling case on the limitations of current research, they would be mindful to be wary of any of their own blind spots, such as an unconscious positivity towards the opportunities with technology. Indeed considering the negative arguments around technology and education could further influence the choice and variety of viewpoints to consider in this field.

The authors also present a strong case for a constructivist approach in researching this field. Given the flaws in an essentialist and instrumentalist approach, they argue that a constructivist approach would allow social and historical aspects to be brought into the framework, and therefore provide a more rounded view.

Although a compelling argument is made, again driven by examples and case studies throughout, by only providing an insight into a constructivist approach (that one could argue they seem to favour), it could be contended that they have fallen into the same trap they are actively arguing against. There is a limited critique of the constructivist viewpoint, and given the purpose of the paper, some explicit scrutiny of this could have demonstrated stronger objectivity.

Contrast this with Selwyn’s (2012) paper. Although similarly strong arguments are made by Selwyn in his critique of current research in this area, he understands the inherent self-sabotage in simply changing tact towards a single, alternate approach. In his view“there is no one ‘correct’ theoretical stance to adopt when looking at… education and digital technology”.  Hamilton and Friesen allude to this in their own conclusion, but by providing a detailed breakdown of how a constructivist framework can address the issues with current research (without other alternatives or further an outline of potential flaws in this approach), one could argue they are demonstrating an inherent preference themselves.

Overall Hamilton and Friesen’s paper provides a compelling argument that the realm of education and technology should be considered through alternative philosophical standpoints in order to “provide fruitful new directions for online education research”. However further opinion should be sought to turn this into a tangible practice and minimise the risk of an incomplete view.

References:

The automated teaching assistant aka ‘teacherbot’

The developing potential in it was clear to see in Sian Bayne’s paper (Bayne S. (2015) Teacherbot: interventions in automated teaching. Teaching in Higher Education. 20(4):455-467) on the ‘teacherbot’ developed by a team at the University of Edinburgh, and used in an earlier MOOC.

The twitterbot examples we’d found as a collective were by their very nature designed for consumption by large audiences, and in most cases offered little interaction. They use the power of algorithms to source, rework and mix up varieties of content.

Given Twitter’s primary use as a platform for interaction, it was really intriguing to find how the teacherbot had been designed for use for a particular set of people (namely the MOOC participants) but also provided value in several ways.

It seemed like the bot offered some immediate efficiency gains, for example, automated reminders of assessment deadlines, based on keywords. But it seemed to me in the paper that one of Sian’s key arguments was that automation should not just be viewed as simply a way of gaining efficiencies. Indeed exploration in this field should be framed differently, to provide a wider field to test its potential.

So the real excitement comes from the examples of interaction between the teacherbot and MOOC student, even if it was “slightly ‘clunky’ and often rather wide-of-the-mark”. It seems in some cases it provoked useful reflection and discussion, which would add value to the student’s experience.

The paper did make me ponder on a few things: It’d be fascinating to see

  • It’d be fascinating to see teacherbot v2. Given its first iteration was understandably clunky at times, and that an algorithm/bot improves when it is receptive to feedback, it’d be useful to view how much interaction happens the second time around, and the value it brings to the student experience. Given subsequent ‘polishing’ of the teacherbot interactions, I wonder if it would become increasingly difficult to spot it as a bot. (Obviously, there are the ethical discussions to be had here about not raising awareness of this with students, but putting this to one side for now…).
  • Taking this further, and should bots become more commonplace with these environments, would students increase or decrease their interaction with the bot as a result, and ultimately would they even care if it was human or non-human? Is that relevant to the experience, and is this just a personal choice?
  • In some of the forum postings, there has been some discussion about the procurement of technology within education, and how this has in several instances been sold into the institution or organisation gain as an efficiency gain (primarily). The pedagogical advantages have been at times been a secondary consideration. Given the speed of development or development of any technology is often tied in with the adoption rate (more usage brings more development), should we think more pragmatically about this, and ensure that any technology we wish to bring into education has an efficiency element to appeal to certain stakeholders within the decision-making process?

Feeling swamped – MOOC perspectives

We’ve been posed some very interesting scenarios this week on the topic of ‘constructing community’, and it’s been fascinating to read the different takes from fellow students on these on the forums.

I was particularly intrigued by some of the points raised about the sense of feeling ‘swamped’ in a MOOC (Massive Open Online Course) environment, and thought it would be worthwhile diving into this a little deeper.

In the example provided, there seemed to a variety of factors contributing to this feeling:

  • the sheer volume of students on the course
  • the volume of content created by the students on the course
  • engaging with content outside of the main environment (e.g. additional reading)

It got me thinking about the nature of MOOCs, and strategies that could be put in place to help manage these challenges.

(Before looking at this, I think it’s important to note from the outset that this could be seen as a ‘nice’ problem to have! The fact that the MOOC has attracted successfully attracted thousands of students obviously taps into a subject that people are keen to develop their understanding in!).

Assessment

Although the example doesn’t give details, I’ve found several MOOCs I’ve participated in to use ‘engagement’ as a metric, or contributor of success.

The majority of MOOCs I’ve come across have primarily been a) free of charge and b) require no prior knowledge or experience. While this is one of the fantastic aspects of MOOCs – being able to provide a learning experience for anyone, anywhere. But this could be a double-edged sword, with a bigger and more diverse audience, perhaps that sense of community and connection is more difficult to bring together, simply because there may be more that makes people different, than similar.

Therefore it’s difficult to base success of a MOOC simply based on an end assessment. Given a person could potentially complete an assessment without actually touching the course content or interacting with other users, how to do you evaluate success this way?

(And given many MOOCs are used as a brand awareness activity by universities, and could be considered a ‘marketing’ activity, engagement (however this is defined) is probably a better metric internally within an institution).

Given engagement is a key driver then, perhaps it creates an onus on students to contribute, even if it offers little value (to themselves, or the other students). As the example itself states:

“What was the point of adding another blog post when there were so many floating around already?”

Perhaps then a strategy for the course designers is to think carefully about the metrics related to the course, both from an academic, student and institutional perspective. As ultimately what may be quite subtle measurements could extrapolate to fairly profound impact on the overall course experience. (I think of Ken Robinson’s quote here, “If you design a system to do something specific, don’t be surprised if it does it”.)

Group size

I wonder if there was a way the course tutors on the MOOC in the example could have split the group size into smaller cohorts. It seems there has been plenty of discussion over ideal group sizes within MOOCs elsewhere, with understandably little agreement (given the nature of MOOCs are quite diverse).

One interesting question to pose is how to create cohorts, and what to base the cohort decision on. Registration date is the obvious one, simply batching them based on chronological enrolment. But could geographic location but one option, and perhaps levels of engagement itself? Ultimately this would need some consideration and piloting to make the MOOC experience for students more enjoyable, without losing any of the diversity and breadth of opinion that could occur outside of the student’s specific cohort.

Managing expectations

On further reflection, I wonder if the feelings expressed by the MOOC student were representative of the wider group. It strikes me that this student could be trying to view everything created by the course and its students, which in this scenario seems unrealistic.

Hajira Khan, a fellow student on this IDEL course, suggested moderators have a key part to play in this process too:

“The tutor for the course should be an active moderator so that discussions are moderated and are kept relevant and concise.”

That role of tutor could be key to keeping the discussion on track, but also managed what is expected.

The feelings are obviously genuine and not to be dismissed, but changes should be considered for future MOOCs in line with wider feedback too, this student’s experience could be an outlier.

One consideration for tutors is to ensure there is the facility to capture feedback like this early on, and where possible have the flexibility to adapt the MOOC where possible to get it back on track.

Slightly off-piste I know, but I also wondered if that feeling of being swamped had been cited as one of the reasons for the notorious MOOC drop-off rates that occur. After looking at several sources, it isn’t named explicity (although it could contribute to the wider tag of ‘bad experience’).

Daniel Onah, of Warwick University, discusses the following contributors to MOOC drop-off rates here:

  • No real intention to complete
  • Lack of time
  • Course difficulty and lack of support
  • Lack of digital skills or learning skills
  • Bad experiences
  • Expectations
  • Starting late
  • Peer review

So while feeling swamped could be a contributor, it seems the reasons for drop-off could be quite wide-ranging!

A step into the unknown

Well some 13 years after graduating from an undergraduate degree in Economics, here I am back in the realm of formal education! Yet the motivations for doing so could hardly be more different.

It’s a real maelstrom of feelings, particularly in the last week when it’s moved from being just an exciting project in the future to a sense of ‘wow what have I taken on!’. I’m slowly working my way through all the introductory information and it’s a lot to take in – but as with all these things once you have a bit of momentum it all starts to fall into place (or so I hope).

So what am I looking forward to in the next few weeks? There’s quite a lot to be excited about:

  • I think there is so much yet untapped in the area of digital education and learning, we’re still just exploring the potential. I’m looking forward to learning about where we’re at, where things are headed, and ultimately what I can help shape.
  • Connecting with others to share, discuss, argue, disagree (!) in an online setting is something I can’t wait to get stuck into. As a father of three young kids, working from home, life can be quite isolated at times so extending my network, both professionally and personally is a real motivator for me.
  • Having worked in a commercial environment for the entirety of my working life, I think it’s going to be quite a culture shift to get back into ‘education’ and learning alongside people of different, and perhaps more academic, perspectives.
  • Having dipped my toe into other online offerings in the past few years, the only real experience that stood out as ‘breaking the mould’ was the University of Edinburgh MOOC on digital cultures. Given the format and thought that’d gone into this, I can only be enthusiastic about what lies ahead. In my opinion ‘elearning’ has quite a negative reputation, and that’s largely down to some of ‘click next’ compliance courses we’ve all experienced in the past at some point. I’m looking forward to being challenged about what a digital learning experience could be, and how this can be facilitated.

So what about the fears?

  • I’m sure every student has the same doubts, but the anticipated time commitment is on my mind. I want to contribute, and ultimately gain full value from the course but am a tad nervous about baking this into my week. But I’m sure once I’ve got into a rhythm it’ll be fine – once the conversations start flowing they’ll be fuel for my learning fire!
  • It seems the real framework of the IDEL course is the personal blog. Having always battled to articulate my thoughts from many words into few, I think this’ll be a big challenge at the start. But I see the opportunity to practice, and ultimately work on this soft skill as a real fringe benefit of taking the course.

So what lies ahead over the next few days? Well, I’m travelling back to the UK tomorrow (I’ve left the family in Holland with the in-laws for another week), and am downloading what I can now to get up to speed on ‘Week 0’ while in transit. Then come week 1, it’s all systems go!