The Learning Analytics and Knowledge conference (LAK16) is happening this week in Edinburgh. I unfortunately, due to existing travel and other commitments, am not in attendance.
I have great hope for the learning analytics field as one that will provide significant research for learning and help us move past naive quantitative and qualitative assessments of research and knowledge. I see LA as a bricolage of skills, techniques, and academic/practitioner domains. It is a multi-faceted approach of learning exploration and one where anyone with a stake in the future of learning can find an amenable conversation and place to research.
Since I am missing LAK16, and feeling nostalgic, I want to share my reflections of how LAK and the Society for Learning Analytics Research (SoLAR) became the influential agencies that they now are in learning research. Any movement has multiple voices and narratives so my account here is narrow at best. I am candid in some of my comments below, detailing a few failed relationships and initiatives. If anyone reading this feels I have not been fair, please comment. Alternatively, if you have views to share that broaden my attempt to capture this particular history, please add them below.
How we got started
On March 14, 2010, I sent the following email to a few folks in my network (Alec Couros, Stephen Downes, Dave Cormier, Grainne Conole, David Wiley, Phil Long, Clarence Fisher, Tony Hirst, and Martin Weller. A few didn’t respond and those that joined didn’t stay involved, with the exception of Phil):
As more learning activities occur online, learners produce growing amounts of data. All that data cries out to be parsed, analyzed, interrogated, tortured, and visualized. The data being generated could provide valuable insight into teaching and learning practices. Over the last few years, I’ve been promoting data visualization as an important trend in understanding learners, the learning process, and as an indicator of possible interventions.
Would you be interested in participating in a discussion on educational analytics (process, methods, technologies)? I imagine we could start this online with a few elluminate meetings, but I think a f2f gathering later this year (Edmonton is lovely, you know) would be useful. (Clarence, Alec, and I tackled this topic about three years ago, but we didn’t manage to push it much beyond a concept and a blog ).
At the same time, I sent an email to colleagues in TEKRI (Rory McGreal, Kinshuk, and Dragan Gasevic) asking if this could be supported by Athabasca University. Dragan promptly replied stating that “I can say that most of the things we are doing with semantic technologies are pretty much related to analytics and I would be quite interest in such an event”. Then he told me that my plan for a conference in fall 2010 were completely unrealistic asking “[who] would be a potential participant? How we can get any audience in December?”.
Dragan and Shane Dawson, who I connected with through a comment on this blog, are two critical connections and eventually friends. Except Shane. He is mean and has relationship issues. SoLAR would not exist without their involvement. Another important connect was Ryan Baker. Ryan started the International Educational Datamining Society a few years earlier. The fact that Ryan was willing to assist in the formation of a possibly competing organization speaks volumes about his desire to have rich scientific discourse. We ended up publishing an article in LAK12 about collaboration and engagement between our fields.
Organization was slow plodding for the first LAK conference. We built out our steering committee (defined by anyone who agreed to join) to include Erik Duval, Simon Buckingham Shum, and Caroline Haythornthwaite). We set up a Google group at the end of March on Education Analytics. The bulk of the planning for the first conference happened in that Google Group. By the end of June, I had seen the light of Dragan’s wisdom and agreed to move the conference to 2011. The LAK11 conference was held in Banff, Alberta in March. Important to note that we paid $500 for that logo. It should have come with a hit of acid.
The financials of any first event are critical. There is always risk. I’ve had events fail that cost a fair bit of money – a social media conference that I ran in Edmonton was a pleasant financial failure. For LAK11, we received financial support from Athabasca University, CEIT (University of Queensland), Kaplan, D2L, and the Gates Foundation. We generated a profit of ~$10k and that was forwarded to the organizers of LAK12 (Shane Dawson) to help seed the next conference. We didn’t have a formal organization to share in the expenses so each organizer for the first several years had to bear the financial risk. Paying past success forward made things easier for the next event. Leading up to LAK14, we were legally organized as SoLAR and took on the financial risk for local organizers.
Finding a publisher
In order to improve the scholarly profile of the conference, we pursued formal affiliation with a publisher. For many academics in Europe and Latin America, this was important in order to receive funding for travel. Dragan made numerous attempts to get Springer’s LNCS volume affiliation for the conference. The LNAI affiliation ended up being the avenue that we were suggested to pursue. Dragan put in the application on September 11, 2010. Springer stonewalled us at great length. We finally received confirmation that they would publish on July 17, 2011. Needless to say, as a professional organization, we did not want to work with a partner where that type of delay was considered acceptable. We were fortunate to connect with ACM and our first proceedings were published with them. Simon Buckingham Shum and Dragan were critical in securing this relationship, and in many ways for the academic rigour now found in LAK. I have been appropriately criticized by top researchers like Ryan Baker that the conference proceedings aren’t open. It was a decision that we made to broaden, oddly enough, access to travel funds to researchers from other countries.
My momma don’t like you
Not everyone was a fan of the idea of learning analytics. As this discussion thread on Martin Weller’s blog post reveals, there were voices of doubt around the idea of learning analytics:
Wish you luck in pursuing this Next Greatest Thing. Maybe next year’s can include the words “Mobile” “Emergent” and “Open” to broaden its hipness even further…really, really, really have been trying very hard not to make any comments since I first saw this announced early in 2010. I mean REALLY hard, because that comment above doesn’t even start to capture the amount of bullshit this smells like to me. But I am sure it will be a smashing success, a new field will have been invented, and my suspicions that there is no ‘there there’ even more unfounded. History will surely side with you George, of that I have little doubt.
Some of these doubts have become reality due to a techno-centric view of analytics, as is often captured by Audrey Watters. Interestingly, one of my first interviews on LA was with Audrey when she was writing for O’Reilly. The field has sometimes moved distressingly close to solutionism and Audrey has rightly turned toward criticism. We need more criticism of the field – both from researchers and practitioners and I find people like Audrey who are bluntly honest are essential to progressing as a research domain.
Leading up to LAK11, I organized a LA MOOC (haha, MOOCs were so cool back then). This served as an opportunity to get people onto the same page regarding LA and to broaden possible attendance to the conference. LAK11 was fairly small with about 100+ people in attendance.
About two days before LAK11, I sent out an email stating:
We are expecting a week of nice weather – beautiful for strolling around Banff and enjoying the amazing scenery. Weather in the Canadian Rockies can be a bit temperamental, so it’s advised to pack clothing for the possibility of some chilly days.
Well, I lied. We were expecting -2C. We got -35C. Freaking cold for those of you that haven’t experienced it before. Also, it generated exceptionally high attendance rates as few people wanted to be outside.
The conference agenda (here) reveals the significant contributions of early attendees. While my first email to colleagues included my blogging network (Stephen, Alec, Dave, Martin) the LAK conference itself resulted in me engaging with a largely new social network disconnected from much of what I had been doing with connectivism and MOOCs, though there were points of overlap. In many ways, I see both MOOCs and LA as an extension of my thinking on connectivism as my more recent focus on the social, affective, and whole person aspects of learning.
Expanding and Growing
Following LAK, we spent some time organizing and getting our act together about what we had created. Over time it became clear that we needed an umbrella organization – one that was research centric – to guide and develop the field. On Oct 2, I sent the following email to our education analytics Google Group. I include the bulk of it as it reflects our transition to SoLAR – the Society for Learning Analytics Research.
With interest continuing to grow in learning analytics – at institutional, government, and now entrepreneurial levels – some type of organization of our shared activities might be helpful.
Based on the sentiment expressed at the post-LAK11 meeting on developing a group or governing body for learning analytics, a few of us have been working on forming such an organization. In the process, I’ve had the opportunity to meet and chat with several SC members (Erik Duval, Dragan Gasevic, Simon Buckingham-Shum) on different organizational structures that might serve as a model. We’ve done enough organizing work, we think, to open the discussion to a broader audience…namely the LAK SC (that’s you).
We’ve decided on Society for Learning Analytics Research (SoLAR) as a name for our organization. The term was coined by Simon Buckingham-Shum (program co-chair, LAK12). Obviously, we would like to invite existing LAK conference steering committee members to be a part of it. Are you interested in transferring your SC role to SoLAR? If so, please provide an image of your lovely head as well as a preferred link to your site/blog/work and a few sentences about how awesome you are.
We have also reserved the domain name: solaresearch.org for our society.
We envision SoLAR as an umbrella group that runs the LAK conference, engages in collaborative research, work with research students, scholar exchange, applies for grants, provides access for researchers to broader skill sets than they might have on their team, produces publications, etc. SoLAR is expected to be an international society/network where learning analytics researchers can connect, collaborate, and amplify their work. It is possible that SoLAR may occasionally provide feedback on policy details as states and provinces adopt LA. Maybe that’s a bit too blue sky…
Over the next few months, various documents will be drafted, including a charter, mission, and decision making process for SoLAR. For example, how do we elect officials? How do we decide where the conference will be held next year? etc. We (currently: Shane, Simon, Dragan, Caroline, John (Campbell), and myself) recommend that an interim SoLAR leadership board – the group just listed – be tasked with developing those documents and sharing with the SoLAR steering committee for comment and approval. Once this interim leadership has completed its organizing work, we will then open the process to democratic elections based on SC and society membership. We haven’t yet determined the criteria for being a SoLAR member (fees? attend a conference? invite only?) or how long SC members serve. Currently we are a self-organized group. Everyone is here either by an invite or expressing interest. Laying a clear, democratic, foundation now will help to position SoLAR as a strong advocate for learning analytics in education.
LAK12 was a tremendous success. Shane was a spectacular host. It became clear to us that interest was high in LA as a research activity and practice space. We arranged a meeting following the conference where we brought in ~50 representatives from funding agencies, corporations, and government officials. The intent was to discuss how LA might evolve as a field, what was needed to broaden impact, and how grant and foundation funding might assist in improving the impact of work.
Following LAK12, SoLAR engaged in a series of initiatives to improve the sharing of research and increase support for faculty entering the field. We had spent time in late 2011 discussing a journal, but didn’t get much traction on this until 2012. In early April, Dragan and Simon had put together an overview of the journal theme and it was approved by SoLAR executive and announced at LAK12. Dragan, Simon, and Phil were the first editors. Simon stepped down shortly after it started and Shane stepped in. Shane and Dragan have been the main drivers of the Journal of Learning Analytics.
A mess of other activities were started during this time including workshops at HICCS (organized by Dan Suthers, Caroline Haythornthwaite, and Alyssa Wise), Storms – local workshops, Flares – regional conferences, events affiliated with other academic organizations such as learning sciences. Basically, we were putting out many shoots to connect with as many academics and practitioners as possible.
One activity that continues to be highly successful is the Learning Analytics Summer Institute (LASI). In August of 2012, I sent Roy Pea from Stanford an email asking if he’d be interested in joining SoLAR in organizing a summer institute. We felt the Stanford affiliation signalled a good opportunity for SoLAR. Roy agreed and we started organizing the first event.
Roy and I didn’t connect well. Roy felt I was too impatient. I was pushing too hard to get things organized. Academic timelines always give me a rash. We managed to secure significant funding from the Gates Foundation and the first LASI was a success, in no small part do to Roy’s organizing efforts. After LASI, we decided to move the institute to different locations annually – a perspective that I strongly pushed as I didn’t want LASI to be affiliated with only one school. Due to my head bumping with Roy and suggestions to host the next LASI elsewhere (Harvard it turned out), I was written out of the final learning analytics report that he produced for the Gates Foundation on LASI. Academics are complex people!
A list of LASI, Flare, and LAK events can be found here.
Getting the finances right
Follow LAK11, we started exploring university subscriptions to SoLAR. This was informed by Shane’s thinking on paying an annual fee to be involved in groups such as NMC or EDUCAUSE. We set up a series of “Founding Universities”, each committing about $10k to be founding members. This served to be a prudent decision as it gave us a base of funds to use for growing our membership and hosting outreach events. Our doctoral seminars, for example, are funded and supported by these subscriptions.
We had strong corporate support as well with organizations like D2L, Oracle, Intel, Instructure, McGraw-Hill, and others providing support for the conferences and summer institutes. Corporate support has proven to be valuable in running successful conferences and enabling student opportunities. We decided to stay away from sponsored keynotes so as to ensure academic integrity of our conferences. I continue to be disappointed that we have been largely unable to get support from pure LA companies such as Civitas and education research arms of companies such as SAS. The students that we graduate grow the field. LA companies benefit from field growth. Or at least that’s my logic.
The founding members and current institutional partners are listed here. Each one has been central to our success.
Grace Lynch joined SoLAR work in 2012. During LASI at Stanford, she pitched the idea of hiring someone to do administrative and organizing work with SoLAR. Up to that point, we were run by academics devoting their time. The work load was increasing. And those who know me also know my attention for detail is somewhat, um, varied. Hiring Grace was the best decision that I made in SoLAR. She was able to get us organized, financially and administratively. The success of SoLAR and LAK and LASI events is due to her effort. I frequently hear from others who first attend a SoLAR event about how impressed they are with the professionalism and organization. That’s Grace’s doing.
Engaging with with big ideas
During LAK11, we expressed our goals as an association:
Advances in knowledge modeling and representation, the semantic web, data mining, analytics, and open data form a foundation for new models of knowledge development and analysis. The technical complexity of this nascent field is paralleled by a transition within the full spectrum of learning (education, work place learning, informal learning) to social, networked learning. These technical, pedagogical, and social domains must be brought into dialogue with each other to ensure that interventions and organizational systems serve the needs of all stakeholders.
In order to serve multiple stakeholders, beyond LAK/LASI/Journal, we also held leadership summits and produced reports such as Improving the Quality and Productivity of the Higher Education Sector: Policy and Strategy for Systems-Level Deployment of Learning Analytics.
We have also been active in helping to shape the direction of the field by advocating for open learning analytics – a project that is still ongoing.
Losing Erik Duval
When one’s personal and professional worlds come together, as they often due in long term deep collaborative relationships, individual pain becomes community pain. Erik Duval, a keynote speaker at our first LAK conference, passed away earlier this year. He shared his courageous struggle on his blog. Reading the Twitter stream from LAK16, I am encouraged to see that SoLAR leadership has set up a scholarship in his honour. His contributions to LA as a discipline are tremendous. But as a friend and human being, his contributions to people and students are even more substantive. You are missed Erik. Thank you for modelling what it means to be an academic and a person of passion and integrity.
What I am most proud of
LAK is a unique conference and SoLAR is a special organization. I have never worked with such open, non-ego, “we’re in it because we care”, people in my life. I wish that future leadership also has the pleasure of experiencing this collegial and collaborative spirit. Our strengths as a community are in the diversity of our membership. This diversity is reflected in global representation and academic disciplines. As a society, we have better gender diversity than what is found in many technical fields. It is not where it should be yet. And the progress that we have made is due to the advocacy of Caroline Haythornthwaite and Stephanie Teasley. The current executive is a reflection of that diversity.
At LAK15, I stepped down as founding president of SoLAR. I felt like it was time to go – I’ve seen too many fields where a personality becomes too large for the health of the field. We’ve always emphasized that SoLAR should be a welcoming space where individuals from different disciplines and research interests can find a place to play, to work, to connect. In order for this to happen, fluid processes for getting opinionated people out and new ideas in is important!
My attention is now primarily focused on two areas: developing LA as a field in China and increasing the sophistication of data collection. Recent visits to China, Tsinghua University and Beijing Normal University as well as an Intel LA event in Hangzhou in fall, have made it clear to me that LA is robust, active, and sophisticated in China. In many of the projects and products that I’ve seen, they’re well ahead of where the current state of publishing in English suggests that we are. In conversations with colleagues at Tsinghua, we have agreed to make the development of a research network and academic community in China a key priority.
Secondly, at LINK Research Lab, we have turned our research attention to wearables and ambient computing. As I stated in my keynote at LAK12, increasing and improving the scope and quality of data collection is needed in order to improve the sophistication of our work as a field. Physiological and contextual data will assist in advancing the field, as will a greater focus on social and affective aspects of learning. Cognition is only one aspect of learning. As a consequence, focus on affective, social, meta-cognitive, and process and strategy is required. To get there, we need better, broader data.
Well, that’s my reflection how we got here with LA and SoLAR. What have I missed?
Damn it, I didn't bring my big camera. The camera in my phone does not do this justice...
There is something genuinely awesome - in the original sense of the word - about being out on the water in a boat that is smaller than the creature swimming next to you. The humpback whale swam around us for about 40 minutes before moving on. Somewhere between 10 and 20 seals hung around nearby hoping for some left-overs, as did a small flock of seagulls. We tried to keep our distance (unlike a couple of boats) but the whale was quite happy to swim around us.
As I am preparing for a talk next week on the future of online learning and writing a bit in a paper about the same kind of thing, I am pleased to see another timely publication in a long line of excellent Pew reports on American life, this time focusing on lifelong learning, which is hugely relevant to what I will be speaking and writing about about. As I need to think a bit more on this topic anyway, this seems like a good opportunity for reflection.
Findings of the report
Before moving on to my reflections, there are a few things that particularly stand out for me. For instance:
- 74% of Americans have engaged in some deliberate personal learning (as measured by the researchers) over the past year, though only 16% have taken an online course.
- 73% consider themselves to be lifelong learners.
This makes me worry greatly about over a quarter of Americans that have done no such thing and that do not consider themselves to be lifelong learners. It is hard to understand how one could be human and not consider oneself a learner but the study's design likely shaped the kind of answers it received. I will have more to say on that. It is also interesting that courses play such a small role. More on that later too.
I am fascinated by the motivations of the subjects of the study:
- 80% of personal learners say they pursued knowledge in an area of personal interest because they wanted to learn something that would help them make their life more interesting and full.
- 64% say they wanted to learn something that would allow them to help others more effectively.
- 60% say they had some extra time on their hands to pursue their interests.
- 36% say they wanted to turn a hobby into something that generates income.
- 33% say they wanted to learn things that would help them keep up with the schoolwork of their children, grandchildren or other kids in their lives.
This accords better with my understanding of human beings. People love to learn, and learning has huge social value in both process and product. It is notable that far fewer of the study's subjects have extrinsic than intrinsic motivation, and it appears that, for the vast majority, the extrinsic driver is at most a catalyst for them to do something that is intrinsically fulfilling. This is reinforced in the following graphs, that are a terrific confirmation of the predictions of self-determination theory (SDT):
As we already know from SDT, the value of learning is fundamentally about achieving competence as a good thing in itself, deeply social in purpose and value, and highly concerned with being in (or gaining) control: in brief, competence, relatedness and autonomy support. This is exactly what we see here. It is noteworthy that, though advancement in occupations matters to professional learners, there is no mention of money nor of qualifications in any of this. This accords with the fact that only 16% of those in the study took courses, given that courses tend to lead to formal or less formal credentials. It is very unfortunate that institutional learning has become so much concerned with courses and credentialing that all of these very good reasons for learning are incredibly crowded out. Much of the time, people in institutions learn in order to get the qualification, not for the pleasure that is so profoundly obvious in these findings. The luckiest ones get both. Most are not so lucky. More than a few get neither fulfillment nor credentials.
Matthew Effects: the rich get richer
The survey finds very strong links between existing education, prosperity and culture, and lifelong learning. Furthermore, the digital divide is, at least by some measures, widening:
As a rule, those adults with more education, household incomes and internet-connecting technologies are more likely to be participants in today’s educational ecosystem and to use information technology to navigate the world.
This is not too surprising - it's pretty much there in the definition - but the Matthew Effect is in full swing here:
For personal learning, 87% of those with college degrees or more (throughout this report adults with college degrees or more refers to anyone who has at least a bachelor’s degree) have done such an activity in the past year, compared with 60% for among those with high school degrees or less. For professional learning, about three quarters (72%) of employed adults with at least college degrees have engaged in some sort of job-related training in the past year, while half (49%) of employed adults with high school degrees or less have done this.
Those that have learned to learn, and to see the value in it, learn more. They probably have more time and resources for it:
Among those with a smartphone and a home broadband connection (just over half the population), 82% have done some personal learning activity in the past year. For the remaining adults (those with just one of these connection devices or neither of them), 64% have done personal learning in the past year.
It is interesting that technology appears to have quite a large effect on learning. This is causal, not just a correlation. It's not the tools, per se, but the adjacent possible that the tools bring. Basically, the tools can support learning or not but, if you don't have the tools, the opportunity never arises. Those that claim technology has no effect on learning are simply wrong, but what is significant here is that it is not the teachers, but the learners, that make this so. There may be some very faint and equivocal glimmer of truth in the belief that technology does not normally do much to improve teaching, but it sure does a lot to improve learning.
Being America, a land of conspicuous inequality, the report shows that there are also strong divisions along ethnic lines, with African Americans and Hispanics considerably less likely to have engaged in personal learning, and somewhat less likely to have engaged in professional learning. The report is less clear whether this is a socio-economic issue or a more broadly cultural concern. I'm guessing a bit of both. When a social system separates particular groups, for whatever reason (and ethnicity is a deeply stupid reason), then patterns of behaviour are likely to cluster. As always, diversity (and the celebration of diversity) is much to be wished for here. We are wisest when we are exposed to and open to diverse views, values and opinions.
Finally, an opportunity for distance institutions like Athabasca University. Some of the notable preference for face to face learning (81% to 54%) is almost certainly down to lack of awareness of digital learning methods:
Noteworthy majorities of Americans say they are “not too” or “not at all” aware of these things:
- Distance learning – 61% of adults have little or no awareness of this concept.
- The Khan Academy, which provides video lessons for students on key concepts in things such as math, science, the humanities and languages – 79% of adults do not have much awareness of it
- Massive open online courses (MOOCs) that are now being offered by universities and companies – 80% of adults do not have much awareness of these.
- Digital badges that can certify if someone has mastered an idea or a skill – 83% of adults do not have much awareness of these.
It seems we have not been particularly smart about getting the message out! That's a huge and untapped population of people who do not even know our methods of teaching exist, let alone of our own existence. At least some of those appear to be educated people with a thirst for knowledge.
Learning and the Kardashians
A lot of the inequalities demonstrated in the Pew report are deeply worrying and endemic. It seems to me that, as well as trying to address that imbalance directly, we in education should give a bit more thought to how we might embed productive learning more deeply into all our interactions, rather than just concentrating on making courses and tutorials in educational systems. While some of this embedding can be addressed with deliberate intent - popular channels, celebrity scientists and artists, accessible and appealing museums and galleries, subsidies for Internet access, libraries, etc - a lot of this is about system design. It's about building tools and environments where critical and reflective engagement is part of the fabric of the system.
With that in mind, I think it is important to note a strong methodological bias in these findings. Significantly, they rely on self-reporting of deliberate learning activities that are largely defined by the researchers. There's a strong bias towards things like courses, tutorials, guides, workshops, conferences and clubs that are explicitly designed to support learning. It is worth observing that most learning is not designed and not intentional (including in formal education). Almost every act of communication involves at least a hint of learning and, especially for interactive media such as Internet or Mobile technologies, the percentage of time spent learning in the process is normally significant. Almost all reading, watching and dialogue involves learning. We might not recognize it as such, but every time we learn of Bieber's latest exploits, or Trump's latest vileness, or our friend's new puppy, we are deeply engaged in acts of learning. It is not just (and rarely most importantly) about the content of what is learned, but the ways of being that such learning engenders. Our values, beliefs and attitudes are deeply dependent on our interactions with others, mediated or not, and what we perceive of the world around us (especially the people and their creations within it). What we choose to observe or communicate changes us. Often, we engage critically with what we read or watch or talk about. Even simple learning from observation is not just about copying but about interpreting and constructing. Internet technologies, in particular, have massively increased the quantity and breadth of such observation and communication. Most of what we know is not learned deliberately but emerges through our interactions with other people and the world around us. Most of what even traditional teachers teach is not the content of what they teach but the ways of being and thinking that go along with it.
To suggest or imply, therefore, that lack of deliberate learning through conventional channels means that no learning is happening is deeply mistaken, and somewhat dangerous, because it ignores all but the visible tip of the iceberg. By far the biggest opportunities for education lie not in the stuff that we educators currently do for a job, but in embedding learning in the everyday; in designing pedagogies that are not pedagogies; in creating architectures where learning can thrive rather than in deliberately leading people in directions we think they should go. It is possibly sad but definitely true that the Kardashians are far better teachers with far greater reach than most professional teachers, apart from (maybe) celebrities like David Attenborough, Randall Munroe, David Suzuki or Neil Degrasse Tyson. What the Kardashians teach might seem to have little value and, arguably, might have negative value, but it should not be discounted as irrelevant learning. Nor, for that matter, should what we learn (directly and indirectly) from politicians, musicians and sports stars. The shapers of our emerging global society are many and varied, and I would be hesitant to suggest, snobbishly, that the reflective, critical, synthetic, analytic and creative skills that professional teachers try to support should have a monopoly over the emotional, social, value-forming ways of thinking that other contributors to society provide in greater measure.
Boundaries and education
Personally, I think the things we try to formally teach (not so much the content as the reflective, critical, synthetic, analytic and creative skills) matter a great deal. Taught well, they directly and demonstrably lead to better, healthier, richer, more creative, more caring, more productive societies, where people can look more critically on the likes of Trump and the Kardashians, with greater perspicacity, with greater creativity, and with more kindness to and understanding of those that think differently. But they also lead to a lot of things that are not so healthy, especially in their institutionalized control-freakery and cataleptic attitudes to change. Educational institutions have done and continue to do a lot of good but, if we really want to bring about a better, more educated world, there is a very good chance that they are no longer the ideal platform for it, and definitely far from the only one.
In my talk next week I will be exploring the ways that physical boundaries, notably of time and place, have deeply influenced how we go about the process of education. Almost all of our pedagogies are predicated on the assumption that a number of people need to gather in a particular place at a particular time, with associated structures, rules and processes to support that. Teachers are a scarce resource, classrooms are rival goods, and schedules matter. So we invented classes, courses, timetables, and methods of managing them. This in turn inevitably demands that people learn things they don't need to learn, that they may be unable or unwilling to learn, at times that may not suit them, under conditions that greatly restrict their autonomy. All in all, despite good support for relatedness, this is terrible for motivation, and it crowds out almost all the great benefits that are reported on in the Pew study. One-to-one learning works much better because it largely avoids those constraints but is, for all but a few, economically unviable. Voluntary attendance to learning activities when needed (much of what is reported on in the study) is also good, but not well catered for in our educational systems that need to adopt tight schedules and lack much flexibility. Thus, much of our pedagogical practice and almost all of our educational system is designed to overcome or reduce the demotivating side-effects of simple physics. All too often, and all too often institutionalized, the solution is to fall back on primitive behaviourist models of motivation that do a great deal more harm than good. Such physics seldom if ever applies online, where boundaries are inherently fuzzy, metaphorical, fluid and malleable. However, most of us still adopt substantially the same pedagogies and we pointlessly (or worse) attempt to fit our teaching into systems that were designed for and with different boundaries. We even build tools like learning management systems that embody them, saving them from exinction and perhaps even magnifying them (it's often easier to see what is going on in a live classroom than within the confines of an LMS). And, having done so, we cement the demotivational effects by controlling learners through grades and certificates, rewarding and punishing with Skinnerian efficiency. It's no surprise that, when you take such things away, MOOC completion rates, though improving thanks mainly to better self-selection and increasing use of real reward and punishment through more recognized credentials (often becoming significantly less open in the process), average no more than 15%
Shifting boundaries and open spaces
Though online boundaries are different, there are lessons to be drawn from the built environment. I am incredibly lucky to live in Vancouver, where public art, information and hey-wow architecture and design is everywhere to be seen. It is hard to look anywhere without being informed, delighted or provoked in useful ways, from the shapes of leaves immortalized on the sidewalks to street art and poetry on the walls. Our cognition is fundamentally distributed, and the richness of the spaces around us, virtual or physical, contributes considerably to how and what we know, as well as our values and behaviours. Even simple separation of space can make a huge difference. It took a while after coming here to realize what was the main difference between schools here and in the UK: fences. In the UK, a school is normally enclosed by tall fences that both keep people out and keep children in. Around the school along the sea wall from me there are no such barriers, and children play at break-time in the parks and playgrounds outside. It's still very safe - many eyes see to that, as well as a culture of trust - but it makes all the difference in the world to the meaning of the space, especially to the children but also to the community around them. Such little things make big differences. Part of the value of that is, again, diversity: being exposed to different stimuli and people is always a good thing, and another of Vancouver's immense strengths. The area around the school is a wonderful mix of expensive luxury waterfront property and cheap but attractive and well cared-for community housing: unless you happen to know that red roofs signify community housing, you would be very unlikely to spot the difference. Messing with boundaries and celebrating diversity is, of course, a big part of the thinking behind the Landing. It's a space where boundaries are deliberately softened, where learning can be visible and shared, but which is still safe and where everyone is accountable. Simply opening up the space is enough to bring about greater and different learning, and a different attitude towards it.
Openness alone is not enough, though. Far too many public forums and comment areas (e.g. most newspaper sites) that are quite open are filled with vitriol, inanity and stupidity. Sure, a lot of learning happens, but mostly not in a productive or useful way, at least from my biased perspective and that of a lot of people that are turned off by it. I am guessing that this might well be what would happen if fences around UK schools were torn down without considering the surrounding community and environment. Community makes a huge difference: though I am sure they have to indulge in a bit of judicious pruning and moderation, when I read blogs by people like, say, Stephen Downes, George Siemens , Terry Anderson, or David Wiley, I see almost nothing but intelligent dialogue from those that comment, because those with an interest in the area have shared concerns and contested but concordant values. Well, perhaps the dialogue is not always intelligent, but at least it is always a learning dialogue. The downside of that is, of course, a relative lack of diversity in the communities that read their work.
So, environment matters too, and often helps to shape the community. For instance, I am still much smitten, after nearly two decades, by the model of SlashDot, which shapes learning dialogues through a combination of smart algorithms and, most importantly, the actions and interactions of people using the system. The best of these dialogues is more than a match for any textbook or classroom, and the worst are not too bad: anything else evolves away. The algorithms are complex and it takes skill to get the most out of them, so it is way too geeky to be of general use, but it shows the general methods and principles that might underlie a system that makes knowledge grow and learning happen simply by shaping the space of interaction, giving individuals the tools to filter and form the space, and providing a space to gather. Less sophisticated/effective but more generally usable tools of this nature include Reddit and StackExchange, which combine ratings and karma information to allow the community to shape what the community sees. While both are flawed and neither is infallible, the combination of human organization and machine filtering generally makes both quite useful for a wide range of topics. I am also much encouraged by how Wikipedia has evolved: its more deliberate structuring and guidance of the flow means it involves higher maintenance than more obviously collectively guided tools but it is incredibly successful at supporting and spreading useful knowledge (including about the Kardashians). The approach of each of these systems to diversity is a little like that of the Vancouver City planners: to design for it. There are places where communities meet and interact but there is also parcellation, with signals of their boundaries but no significant barriers, that supports the growth of a supportive culture (at least in places - there are, of course, some areas that thrive on dischord), and that makes trust visible.
There are potential opportunities for analytics tools, collaborative filters, and similar forms of data-driven algorithmic approaches here too. Such methods come with enormous risks, mostly due to the insatiable desire of programmers to control what other people do: to erect new boundaries. Even when done with good intentions, they can have harmful effects. Almost the last thing we need in such spaces is filter bubbles and echo chambers, but such approaches can embed and reinforce patterns and attitudes simply by doing their job, building boundaries that are all the more dangerous because they are invisible and unmentioned. The absolute last thing we need is machines to make decisions for us based on what a programmer has decided is best for us or, just as bad, using criteria over which we have no say. There are huge risks of designing new boundaries that are just as controlling and just as demotivating as the ones they replace. I don't resent Amazon's recommendations of what I might like to read next at all, for example, especially when it tells me why it is making those recommendations, because it does nothing to enforce those recommendations and learns when I disagree. I do resent Netflix limiting what it shows me that I might want to watch, though: this reduces my autonomy. I greatly dislike learning analytics tools that tell me how well I am meeting someone else's goals, but I approve of those that help me to define and reach my own. I am happy for Google Search to suggest relevant sites I might want to visit, as long as it continues to show me those it is less impressed with, but I am deeply unhappy that Facebook shows me a tiny percentage of posts I might like to see. I love that clicking a word or phrase in an e-book will give me a definition and a link to Wikipedia or Google Search. I hate that clicking a help link will tell me what someone else thinks I need to know (especially when the nugget I need is hidden in a lengthy video that gives me no clues about where to find it). What all of this boils down to is support for the fundamental drivers found in the Pew report: autonomy, relatedness and competence. Take away any one of those, and you take away the love of learning. But, with care, scrutability, and attention to supporting human needs, such systems can be expansive and liberating.
For now, most of the new systems we use to replace the formal process of teaching show promise but most have numerous weaknesses, most of which formal teaching overcomes: concerns about reliability, trust, safety, efficiency, and the effects of deliberate malice are well founded, and there are big issues of control and autonomy to overcome. But it seems to me that, as we start to dismantle the boundaries of traditional educational practice, the opportunities to extend and improve learning through reinvention of our learning spaces online are (virtually!) limitless, while we reached a state of near stasis in physically located learning many hundreds of years ago. Sure, there have been incremental improvements here and there but they have been uneven at best, and it is possible to see examples of great pedagogies being used thousands of years ago that are barely, if at all, improved today. It's all down to physics.Footnote
I wouldn't know a Kardashian if one kicked me in the face and, until just now, I had little idea about what they were apart from being a family that is known across the Internet for nothing more substantial than their own celebrity. For quite a long time I actually thought the headlines and post titles about them were about a fictitious race from Star Trek. What's quite interesting about that is that I had learned what little I knew on the subject without, until just now, any intention of doing so. I found out a bit more just now by way of fact checking, through Wikipedia, but it seems that what I already knew was pretty much accurate. Education happens whether we seek it or not. It would be good if that education were more valuable more of the time.
An article from The Atlantic describing a study that reveals autonomy is, almost entirely, the reason people like to have power. This accords very well with the predictions of self-determination theory.
Power (in the most meaningful sense of the word) is pretty much the same thing as autonomy, I think: it's about feeling that you are in control of your life, regardless of whether that feeling is justified. This suggests that some forms of what we generally recognize as power (ie. positions of authority, with control over what others do) might not be so great, inasmuch as the accompanying responsibilities can considerably reduce autonomy. Those in middle management, myself incuded, are in a great many ways less autonomous than those over whom they have purported power, in part because of their responsibility to those they lead, and in part due to their accountability to those with greater power. I'm guessing that the same is true right up to leaders of institutions, who are accountable to governments and other funding bodies in much the same way as those lower in the pecking order are accountable to them.
For optimal happiness, organizational hierarchies (not those that occur in natural systems but that are designed by humans) are an inherently weak idea, most notably because they must always be antagonistic to autonomy. They survive as a reasonably effective compromise made to make organizations and societies function like machines: indeed, they are one of our most fundamental enabling technologies. They are the main way that large groups of people can efficiently live in peace and prosperity together. Hierarchies are responsible for many good things, a foundational technology on which much of human society, culture and technology is based, without which we would likely still be in the trees. But it is important to remember that they are just technologies: they are inventions that can be improved upon and that could easily be superceded by better inventions. Democratic governance was likely the last major successful innovation in the technology, but it doesn't solve many of the inherent weaknesses. For the most part, the inevitable inefficiencies, filtering of information and, above all, diminution of intrinsic motivation make organizational hierarchies a deeply flawed solution to the problems of large scale human coordination that they are designed to solve.
With modern technologies, especially those involved in and emerging from ubiquitous communication and availability of knowledge, we can and should do better than hierarchies. I am increasingly intrigued by and drawn to the model of The Morning Star Company, that thrives without hierarchies, where everyone, from temporary tomato pickers to the CEO, is a manager, and where power is not given but taken as a natural right. What's remarkable about it is not so much the pattern (which is not unlike that of traditional academia and many other organizations and social forms) but the fact that the pattern works really well.
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We have reached that point in the course where you will be creating an artefact. More on the details of that below. Both to support the process and as field trips, I would like to arrange a couple of sessions where we can meet and discuss it and other things relating to the course. There will also be a final session where we share our discoveries.
Sorry for the delay, by the way: I was already late with it last night when my Internet connection yet again died and did not come back before I needed to sleep. My connection has been getting worse for weeks, cutting out every 2-10 minutes, usually just for seconds but sometimes for many minutes. Telus have tried to help, sending out an engineer to replace and check all they could think of. I still blame Telus, Telus blames my wiring but, as I have tried connecting my router directly to the entry point with fresh cable and still get the same problems, I think I am right! A bit of an impasse. I am getting a new provider over new cable, hopefully Friday morning, so this should not happen again. My 3G bill is high, and I'm spending some of each day working on my little sailboat, which has very cramped conditions and terrible public wifi but at least it only dies once an hour.
I'd like to run at least two field trips using different and contrasting technologies. The first of these will, I hope, be this week, using our own OpenSIM instance, at http://opensim.athabascau.ca:9000/ (more details to follow, but check out last year's instructions at https://landing.athabascau.ca/blog/view/1082373/virtual-field-trip-to-an-immersive-world-tonight-at-6pm-mdt for an overview: since then it appears that something quite odd has happened to the world, that is now a peaceful and hardly developed island, but hopefully that will be enough). I propose that we should meet there Friday, 6pm Mountain Time. If that is not suitable, please suggest an alternative in the comments. My whole Friday is 'free' (technically a vacation day, but I've given up on such things!) or early next week is an option.
The next virtual field trip, next week or the week after, will likely make use of a gaming environment - this is Craig's suggestion. Craig suggested we might use World of Warcraft (free for the first 20 levels) but I am concerned about the steep learning curve, unless you are all familiar with it or similar games. I have looked into a couple of alternatives. My son suggested Minecraft, that appeals to me because it can be played collaboratively as well as competitively, it has a slightly shallower learning curve, would be a great contrast with general purpose VR thanks to the clear shared endeavour, and there is a 5-day demo available. However, it does cost about $30 for the real thing so we would only have a small window of opportunity to coordinate our demo versions. If anyone has any better ideas, do pass them on.
We might also spend some time using Adobe Connect, if there's sufficient interest.
Arranging the final session: showcasing and celebrating...
During the final week (March 29 - April 1 - a short week due to Easter Monday) you will be sharing what you have done via Adobe Connect - our last virtual fieldtrip. I'd like everyone to be there and I am expecting it to last for a couple of hours so we need to arrange a time that suits all. Here is a list of options (all times Mountain Time):
Tuesday, March 29th, 6pm OR
Wednesday, March 20th, 5pm OR
Thursday, August 6th, March 21st, 5pm OR
Friday, April 1st, 6pm
If any or all of these are impossible for you, please tell me. We will default to the Friday if no one objects or has any strong preferences for another day. Final portfolios are due by midnight Mountain Time on Sunday, April 3rd.
And so to the artefact (or artifact - either spelling will do!) -
More about the artefact and project process
An outline of the tasks and expectations is available at http://scis.lms.athabascau.ca/mod/ouwiki/view.php?id=22236&page=Development+of+Artefact
In brief, the idea is to produce some kind of social artefact - such as a website, a mashup, a customization of an existing tool, a plugin, a Landing group, or a program written from scratch - that puts some of the learning you have been doing on this course into action. I will not be marking this from a perspective that considers coding ability or the artefact's technical sophistication (from a digital tools perspective). This is about analyzing a problem relating to social media/computing, designing a solution to support two or more people (maybe lots more!), implementing it, and thinking about what you have done. While it would be good to produce something that works and I do expect something that people can at least use, the thinking behind it matters far more.
It is possible to do this effectively using nothing more sophisticated than a Landing group, though you are welcomed and encouraged to explore and use different systems and technologies. In previous iterations of the course we have had a wide range of artefacts ranging from a highly customized Drupal installation, a community support site written in ASP, a couple of mashups including those pulling together tags from different sites and those incorporating external polls into a purpose-built site, a couple of Landing groups to support specific communities, a mobile social app, a collaborative filter using information from different sites, a social navigation tagging tool, a content management tool for a camping community, and more. There are infinite possibilities - a Second Life artefact, a location-aware social app, a Facegroup or Google group, a bulletin board, a social widget, a feed aggregator for a topic area, etc. As long as it is a social computing artefact, it's fine. Choose something that interests you and that you can do within a little under four weeks.
What I will look for
What I will be looking for will include (non-exclusively) careful consideration of individual needs, very careful consideration of the communities involved and what they contribute/get out of it, a well-documented design process that includes theoretical thinking as well as pragmatic concerns, a carefully considered design, and a thorough critical review of what you have achieved and how you have achieved it. In all cases, I will be looking for appropriate approaches. By this I mean that your design and artefact should be well chosen and fit the needs of its users as well as your technical skills. Try to avoid taking on too much from a technical perspective if that means taking time out from thinking about why you are doing it and who you are doing it for. At the same time, make sure that it is not too small that you will be unable to say much of interest about it. If you are using a fairly limited toolset but you don't take good advantage of it, things will not go well. If you're not sure whether your idea makes sense, that's why I am here! The instructions suggest contributing to a discussion forum to share your idea but, given the size of the group, it is probably easier just to add it as a comment to this post. I will provide feedback, mainly to approve it or to suggest extending it or cutting back on the effort.
It is absolutely fine to specify a bigger and more functional system than you actually create and you are very strongly encouraged to document what you would do to improve it if you had more time or expertise - the documentation is usually the largest part of the submitted work and it should normally talk about things beyond the implemented artefact itself. An artefact that works well enough to demonstrate your thinking but that has many incomplete placeholders is absolutely fine, as long as you discuss what would happen in those placeholders. Even a (working) model without a backend is OK.
Why we are doing this
There are numerous pedagogical reasons for asking you to actually build something but one of the big ones is to viscerally experience the role of constraints in the development process and the vital role of the artefacts that we build in helping to understand what it is we are trying to build. When designing this course I originally considered simply allowing designs, with no working artefacts, but that would not be anything like as effective in encouraging a thinking process about real-world users and real-world problems. Remember the mantra 'we shape our dwellings and afterwards our dwellings shape our lives' - this is as much about contstraints and affordances as it is about the order that you try to impose. Though programmers are very welcome indeed to write programs, this is not a programming exercise. This is an exercise in social system design. In many cases, if you don't have time to program or configure things as you would wish, you can consider using softer tools like conditions, terms of service, rules of engagement or scripts to encourage people to behave in ways that you think may be valuable. You should almost certainly think about such issues and approaches even if you are building something like a widget to be used as a tool within a different system.
A few questions and things to think about
To a large extent, the relevance of these questions and suggestions will depend upon what kind of system you are building and not all will apply to everyone. The needs and issues for an Elgg plugin that enhances a generalized social site, say, are very different from those of a support system for a community, and different again from a collaborative filter or search system. These bullet points are intended to spark ideas and help to fill in gaps, not to be a definitive list of issues that must be addressed:
- In a social system, thinking about the processes, motivations, fears and expectations of people using it, is crucial. The first thing you need to think about is why people will be using your system in the first place. It is often a good idea to think about personas and scenarios to help think about this and empathize with users (and it all contributes to good documentation so it helps with marks too!) but, as always, this should be appropriate to the artefact.
- You will probably need to think about the effects of scaling and the change process. A social system used by two people is usually very different from one used by two million. Size matters. You might want to give some consideration of the technical issues here too - big sites can get slow, especially if you fill them with features (the Landing is a case in point!)
- Think carefully about how your system will mediate or collect interactions, what it will inhibit, what it will promote and, vitally, how and why it will do so.
- Will it needs rules and terms of service?
- Are there other systems out there that you can use or incorporate that would add value?
- Will social structures be flat or hierarchical?
- How will it map onto existing communities and networks? What kinds of relationship will people have with one another on the site? Are there specific demographics?
- What pacing will be expected and how will you cope with it (fast pacing can make it hard to track back and see patterns, slow pacing can reduce motivation and momentum)?
- How will you cope with the problem of evil - deliberate spammers, people who break social mores, hackers, abusers, insensitivity?
- How will you build trust? Do you need it? Why? Why not?
- How will your system relate to identity and how (if at all) will identity be portrayed? Will users have avatars? Login IDs? Profiles? Why? Why not?
- Is reputation an issue?
- How will your system add value to its community?
- Would rewards (e.g. likes, thumbs-up, plus-one, karma points) help? Would they hinder?
- Would anonymity be helpful?
- What about access control? Who will you let in, and how?
- What levels of privacy will you allow? Who can share with whom? Why?
- How about connecting with others? Will there be any kind of social networking? If so, who sees what? How do you promote connections? Will you allow blocking?
- What might cause resistance to using your system? How will you overcome it?
- Will the system involve sharing social objects? What other glue will help to attract and keep people?
- How open will it be? Will it play nicely with other systems?
- Will you have a means of separating communities? e.g. the Landing's use of groups.
- Does something similar already exist? Could you make use of it?
- What are your own constraints? How much can you do in the time available?
As importantly as the artefact and its documentation will be your reflections, both on your own creation and that of your fellow students. Do not forget to keep your learning diary update throughout this whole process, a minimum of once a week!
For your own system, your reflections can help to explain decisions as well as to show your thinking about what might have been, had you had more time, or started differently, or known what you knew now at the start.
The requirements say that you should evaluate and participate in the sites of at least two colleagues. I am hoping this will still be possible even in this small group. It is, therefore, very important that whatever system you create should be usable by other members of the course, so do remember to ensure that they have some way of doing that. If it is web-accessible, share the link. If not, share the files or means of access.
As well as this post, we will be discussing such things in the real-time virtual field trips and I will be posting hints and tips as we go through - you might want to look back over previous iterations of the course to find what I have said before as much of it will be duplicated here!
That's all for now. As always, please ask questions if anything is unclear, as comments on this post, in the discussion forum, or as a personal message to me (email firstname.lastname@example.org or use the Landing's internal messaging system).
And, as always, have fun!
This is an article about how and why The Morning Star Company works. It's a company where
"• No one has a boss.
• Employees negotiate responsibilities with their peers.
• Everyone can spend the company’s money.
• Each individual is responsible for acquiring the tools needed to do his or her work.
• There are no titles and no promotions.
• Compensation decisions are peer-based."
Moreover, it is:
" a large, capital-intensive corporation whose sprawling plants devour hundreds of tons of raw materials every hour, where dozens of processes have to be kept within tight tolerances, and where 400 full-time employees produce over $700 million a year in revenues. And by the way, this unique company is a global market leader".
I believe that this could serve as a superb model for academia. In fact, I strongly suspect it would work even better in academia, that has a natural leaning towards autonomy. It would increase motivation, ownership, engagement, efficiency and creativity across the board.
The title of the article is not altogether accurate because the central mechanism through which Morning Star Co achieves its remarkable success is to treat everyone - from the temporary pickers of tomatoes to the president of the company - as a manager. It's not about getting rid of managers at all but creating a process in which everyone has power and agency, without structural hierarchies (or, at least, with very lightweight, flexible and shifting hierarchies). This is clearly very motivating:
“If people are free, they will be drawn to what they really like as opposed to being pushed toward what they have been told to like,” says Rufer. “So they will personally do better; they’ll be more enthused to do things.” Morning Star’s employees echo this sentiment. “When people tell you what to do, you’re a machine,” says one operator."
One thing I particularly like is that it is hugely empowering, but it's not about empowerment:
"the notion of empowerment assumes that authority trickles down—that power gets bestowed from above, as and when the powerful see fit. In an organization built on the principles of self-management, individuals aren’t given power by the higher-ups; they simply have it."
The benefits - more initiative, more expertise, more flexibility, more collegiality, better judgement and more loyalty - are well explained in the article. This is a highly successful company, not just in its market but for its workers.
The article goes into some detail on how it works without centralized control and power hierarchies. It explains how those who don't pull their weight are treated, how processes are coordinated, how success is measured and what makes it both efficient and creative at the same time. The mechanisms of control are almost entirely social and the production process is almost entirely self-organizing. The company is designed to create the conditions needed for people to work together effectively: not so much a machine as an ecosystem. Inspiring stuff. Not only would it be a great way to run a university, it would not be a bad way to run a program or even an individual course.
Address of the bookmark: https://hbr.org/2011/12/first-lets-fire-all-the-managers
Several years ago, a group of us wrote a concept paper on Open Learning Analytics (.pdf). Our goal was to create openness as a foundation for the use of data and analytics in education. We have, it appears, largely failed to have our vision take root.
Few things are more important in education today than the development of an open platform for analytics of learning data. It’s a data-centric world. Data, and the analysis of those data, are a rapidly emerging economic value layer. Most educators and students are unaware of how much algorithmic sorting happens in the educational process. Even before students apply to a university, the sorting has started (postal/ZIP codes can indicate chances of success). Recommender systems suggest next courses. Engagement with course content produces predictive models. Suggested help resources are generated for students identified to be at risk. And this all happens behind the scenes as the Wizard of Algorithms spins dials and outputs intimidating results (often with more smoke and noise than actual usefulness) that are starting to drive learning practices that cover the full range of a student’s engagement with higher education.
We are, as a field, facing an interesting time. The decisions that we make now will cast a long shadow into the future. And the best decision, in uncertain times, is the one that allows the greatest range of decisions in the future. It is here, in analytics and data use in education, that far more attention and awareness is needed than is currently evident. Algorithms will subsume most of our educational practices as they will embody certain pedagogies, support roles, and even faculty practices. Quite simply, the shape of tomorrow’s university is now actively being coded into analytics models. I’m generally fine with this as a concept, but quite nervous about this as an action. The future needs to be open. And yet, the exact opposite is happening.
The article in the Chronicle today on Big Data and Education is timely reminder of the importance of the work and the challenges of a closed learning analytics future. The work is rather urgent. And we as academics have been sleeping.
Whenever I visit a new country, region or city I visit McDonald's as soon as I can to have a Bic Mac and an orange juice. Actually, in Delhi that turns into a Big Raj (no beef on the menu) and in some places I substitute a wine or a beer for the orange juice, but the food is not really important. There are local differences but it's pretty much as horrible wherever you go.
I inflict this on myself because The McDonald's Experience should, on the whole, be a pretty consistent thing the world over: that's how it is designed. Except that it isn't the same. The differences, however, compared with the differences between one whole country or city and another, are relatively slight and that's precisely the point. The small differences make it much easier to spot them, and to focus on them, to understand their context and meaning. Differences in attitudes to cleaning, attitudes to serving, washroom etiquette, behaviour of customers, decor, menu, ambiance, care taken preparing or keeping the food etc are much easier to absorb and reflect upon than out on the street or in more culturally diverse cafes because they are more firmly anchored in what I already know. Tatty decor in McDonald's restaurants in otherwise shiny cities speak worlds about expectations and attitudes, open smiles or polite nods help to clarify social expectations and communication norms. Whether people clear their own tables, whether the dominant clientele are fat, or families, or writers, whether it's a proletarian crowd or full of intelligentsia or a place that youth hang out. Whether people smoke, whether they drink. How loud the music (if any) is playing. The layout of the seating. How people greet their friends, how customers are greeted, how staff interact. How parents treat their children. There's a wide range of different more or less subtle clues that tell me more about the culture in 20 minutes than days spent engaging more directly with the culture of a new place. Like the use of the Big Mac Index to compare economies, the research McDonald's puts into making sure it fits in also provides a useful barometer to compare cultures.
McDonald's thus serves as a tool to make it easier to learn. This is about distributed cognition. McDonald's channels my learning, organises an otherwise disorganised world for me. It provides me with learning that is within my zone of proximal development. It helps me to make connections and comparisons that would otherwise be far more complex. It provides an abstract, simplified model of a complex subject.
It's a learning technology.
Of course, if it were the only technology I used then there would be huge risks of drawing biased conclusions based on an outlier, or of misconstruing something as a cultural feature when it is simply the result of a policy that is misguidedly handed down from a different culture. However, it's a good start, a bit of scaffolding that lets me begin to make sense of confusion, that makes it easier to approach the maelstrom outside more easily, with a framework to understand it.
There are many lessons to be drawn from this when we turn our attention to intentionally designed learning technologies like schools, classrooms, playgrounds, university websites, learning management systems, or this site, the Landing. Viewed as a learning technology about foreign culture, McDonald's is extraordinarily fit for purpose. It naturally simplifies and abstracts salient features of a culture, letting me connect my own conceptions and beliefs with something new, allowing me to concentrate on the unfamiliar in the context of the familiar. Something similar happens when we move from one familiar learning setting to the next. When we create a course space in, say, Moodle or Blackboard, we are using the same building blocks (in Blackboard's case, quite literally) as others using the same system, but we are infusing it with our own differences, our own beliefs, our own expectations. Done right, these can channel learners to think and behave differently, providing cues, expectations, implied beliefs, implied norms, to ease them from one familiar way of thinking into another. It can encourage ways of thinking that are useful, metacognitive strategies that are embedded in the space. Unfortunately, like McDonald's, the cognitive embodiment of the designed space is seldom what learning designers think about. Their focus tends to be on content and activities or, for more enlightened designers, on bending the tools to fit a predetermined pedagogy. Like McDonald's, the end result can be rather different from the intended message. I don't think that McDonald's is trying to teach me the wealth of lessons that I gain from visiting their outlets and, likewise, I don't think most learning designers are trying to tell me:
- that learning discussions should be done in private places between consenting adults;
- that it is such a social norm to cheat that it's worth highlighting on the first page of the study guide;
- that teachers are not important enough to warrant an image or even an email link on the front page;
- that students are expected to have so little control that, instead of informative links to study guide sections, they are simply provided with a unit number to guide their progress;
- that the prescribed learning outcomes are more important than how they will be learned, the growth, and the change in understanding that will occur along the way.
And yet, too many times, that's what the environment is saying: in fact, it is often a result of the implied pedagogies of the technology itself that many such messages are sent and reinforced. The segregation of discussion into a separate space from content is among the worst offenders in this respect as that blocks one of the few escape routes for careful designers. Unless multi-way communication is embedded deeply into everything, as it is here on the Landing, then there is not even the saving grace of being able to see emergent cultural behaviours to soften and refine the hegemonies of a teacher-dominated system.
Like McDonald's, all of this makes it far more likely that you'll get a bland salty burger than haute cuisine or healthy food.
Terry Anderson and I have written a fair bit about the different social forms that apply in (at least) an educational context. We reckon that they fall fairly neatly into physically overlapping but conceptually distinct categories of groups, nets and sets. In the past, we used the term 'collectives' instead of 'sets' but we have come to realise that collectives are something else entirely.This post starts with an overview of the distinctions and then drifts into vaguer territory in an attempt to uncover what it might be like for something to have meaning for a social entity. That's a rather bizarre concept at first glance: is there any sense at all in which a collection of people, not the people within that collection but the collection itself, can feel or think anything and, if not, how can anything be said to have meaning to it? And yet, oddly, we do ascribe human attributes to collections of people all the time in our everyday speech - 'Apple is a creative company', 'Canada got another gold medal', 'We came top of the league', 'the crowd is angry', 'this is the most enthusiastic class I've ever taught', 'Google beat Oracle in the court case', 'Athabasca University is committed to open learning' and so on. While this is often just a shorthand notation for something else or a poetic metaphor, the ubiquity of such language makes it worth examining further.
Groups, nets, sets and collectives
Groups are the stuff of conventional teaching and learning: they are distinct and intentional entities that people join and know that they are members. You are in a group or out of it: you might be more or less engaged, but there is no real in-between state. Groups are generally characterised by things like purposes, collaboration, hierarchies, roles, exclusion. We know a lot about groups and their effects on learning, and the whole field of social constructivist models of teaching and learning is based on them.
Networks are more tenuous entities. To join a network you connect with one or more of its nodes. You might intentionally wish to make connections with particular people or kinds of people, but a network has no formal constitution, no innate roles and hierarchies, no innate exclusion: it's about individuals and their connections with one another. It is composed of nothing but connections and ties and has no formal boundaries. Networks are traversable and offer ways of linking and connecting to others and their knowledge. Learning in networks tends to be informal, connected and undirected by any individual. Networks are great for on-demand and serendipitous learning, combining social ties with unbounded knowledge.
Sets are about categories and topics. Set-based learning is about finding people and knowledge based on shared characteristics, typically a topic about one wishes to learn. Wikipedia, YouTube, and Google Search epitomise the nature and value of sets in learning, with ascending social interest sites like Pinterest or Quora beginning to enter the fray. However, libraries and bookshops are also primarily set-oriented, so this is nothing new. Unlike networks, there may be no direct connection with others and certainly no expectation of sustained interaction (though it may occur and develop into other social forms). Unlike groups, there is no formal constitution of a collection of individuals. It is just a bunch of people joined (in a set-theory sense) by a shared interest.
When social forms act together as a single entity, they become collectives - not a social form, as such, but the result of social forms and the interactions of individuals within them. A collective may be the result of direct or indirect interactions of individual autonomous agents, such as may be found in natural social forms like ant or termite nests, herds, flocks or shoals or, in human systems, in the operations of money markets, mobs, stock exchanges, group-think and forest path formation. The 'invisible hand' is a collective in action, the result of myriad local interactions rather than a deliberate global plan. The environment plays a strong role in this: things like the availability of resources, sight-lines, weather patterns, topology and more play a role in determining how such dynamics play out.
In computer-based systems, the combination that leads to a collective is not just a result of the emergent results of individual agents but may be effected and consequently notably affected by a machine: Amazon recommendations, Google Search, PayPal reputations and so on are all combining intelligent and independent actions of humans using algorithms in a machine in order to affect human action. The computer system extends what is possible through direct/indirect interaction alone, but it is still powered by individual intelligent beings making intelligent choices. It leads to a cyborg entity where collective emergence is part-human, part-machine. This makes such systems very powerful and flexible as a means to create collective intelligence that is directed to some end, rather than being simply an emergent feature of a complex system that happens to have value. Not only does the environment itself play a role in shaping behaviour, as in 'natural' systems, but it actually creates some of the rules of interaction. In effect, it bends and sometimes creates the rules of social physics.
Values in collections of people
In some sense, groups, sets, nets are all identifiable entities in the world that achieve some kind of action or purpose that is distinct from the individual actions or purposes of the people of which they are comprised. Clay Shirky talked of them as first class objects - things in themselves. But are these entities, these first class objects, anything like people? Are there values we can ascribe to them? Do they have intentions and purposes that are analogous to those of individuals? Do they have attitudes that are separable or different from the attitudes of those that comprise them? This is a problem that my student Eric Von Stackelberg has been exploring in his masters thesis and he has made some very interesting progress on this by using categories, that are used in psychology to describe individual values, as a means of describing group values ('group' used here in the generic sense of a collection of people of some identifiable sort). I've been challenging him to clarify what it would mean for that to be true. Can a bunch of people (not the individuals, the bunch itself) be kind, or hedonistic, or happy, or avaricious, or whatever in a manner that is meaningfully different from saying that the individuals themselves, or even a majority of them, have those attitudes? It seems that a corollary of that implies we might ascribe to them something akin to emotion. Could a bunch of people (the bunch, not the people in the bunch) feel happiness, amusement, tiredness, anger, pain, hate or love? I find this a difficult concept to get my head around. And yet...
It seems intuitively obvious that there is something organism-like in a social cluster. It is certainly normal to speak of organizational values, national values, group beliefs, group norms and so on. Athabasca University, for example treats itself as a unified entity in its mission statement that talks of values, purposes and intentions as though it were (almost) a human being. Corporations are treated in the law of some countries almost exactly like people (albeit odd ones, given that all would be diagnosed as having, on analysis, serious psychopathic disorders). Nations are very similar - we can talk of America invading Afghanistan without batting an eyelid, even though it is very clearly not something that is literally or physically the case in the way it would be were, say, a bully to pick on someone in a playground. A similar but far more worrisome phrase like 'the French have always despised the English' sounds like it plays on a similar notion but suggests something rather different. When we say that a country has invaded another we are talking about a group activity, something organized and intentional, whereas when we suggest that a whole population of people thinks in a certain way we are talking about a set: people with the shared attribute of nationality (the same applies to race, or gender, or physical attribute, etc - that way bigotry lies). There are interesting hybrids: it is normal to say 'we won' when a hockey team wins even though 'we' had negligible input or nothing to do with it at all. We identify at a set level (we, the supporters of the team) in a manner that encompasses the team (a distinct group). It is harder to find examples of networks being treated in quite the same way, though the flow of memes that is so easily facilitated through social networking sites may be an example of values of a sort being a feature of networks. However, the innately diffuse nature of a network means it is significantly less likely to have values of its own. It may be predicated on individuals' values (e.g a network of religious believers) but a network itself does not seem to have any, at least at first glance. Networks are primarily about individuals and their connections to other individuals, each seeing their part of the network from their own unique perspective. This is not promising territory to find anything apart from emergent patterns of value.
There are natural parallels though, that suggest an alternative view. It makes no sense to think of an ant colony as just a load of autonomous ants - the colony itself is undoubtedly a super-organism and an ant from such a colony is, on its own, not a meaningful entity: it is constituted only in its relation to others, as part of a single network. We can use telological language about the colony, and even ascribe to it wants, desires and intentions. It is also absolutely reasonable to think of an organism like a human being as a group/network/set of tightly coupled cells that are behaving, together, as a single unified entity that is not dissimilar to an ant colony in its complexity and interdependence. An individual cell may live on its own, but its meaning only becomes apparent in the presence of others. Even at a cellular level, our cells are a community of different symbiotic organisms. The vast majority of the cells in our bodies don't even have human DNA (that still staggers me - what are we?) but we still cannot think of ourselves as anything other than individuals that have values, intentions, meaning and - well - an autonomous life of their own. Are social forms so very different? It seems that at least one contained network that constitutes an entity may well have values because, well, we have values and we can be viewed as networks. In fact, we can also be thought of as sets and, in some senses, as groups.
While chatting about this kind of thing, a friend recently remarked that perhaps the most crucial value that we can ascribe to an individual is the value of survival: the will to survive. An arbitrary collection of entities does not have this. If we are thinking in terms of organisms, then I guess we might more properly think of it in evolutionary terms as a bunch of genes seeking to survive, but that's a layer of abstraction higher than needed here.
At the individual organism level it is the organism that tries to survive. This is one obvious reason that it is logical to think of an ant, termite or bee colony as a single organism: individuals will readily sacrifice themselves for the colony exactly as the cells in our own bodies continuously sacrifice themselves in order to protect and sustain the entity that we recognise as a person. We can easily see this survival imperative in intentionally created groups, from small departments to sewing circles, from gangs and teams to companies to countries (groups). If a group exists, it will typically try to preserve itself, and individual members may often be seen as expendable in meeting that need: thing of countries at war, political parties, hockey teams and so on. We can also see it in less rigidly defined entities such as cultures (sets/nets) and institutions (sets/groups). Even though individuals may have no formal connections with one another with, at most, tenuous networks and no unifying constitution, the simple fact of observable similarities and shared features leads to a self-reinforcing crowd effect that leads to survival. Often, intentional groups will be formed to support these but the interesting thing is that they are not groups defending their own 'lives' but a kind of collective antibody formed to protect the broader, sometimes barely tangible, set. People who form organizations to defend society against some challenge to what they see as being its central cultural, aesthetic, ethical or social values are doing just that. The set of which they feel a part is somehow greater than the group that they form to protect it.
It is harder to see this in human networks. Although there do appear to be emergent and dynamically stable features in many networks, that's just it: they are emergent features like a solonic wave in a river, the rhythmic dripping of a tap, or a whorl of clouds in a storm. It makes far less sense to talk of a cloud formation as trying to survive than it does of an ant colony. We do, however, see moods and trends spread through networks - if you know people who are getting fatter then you are far more likely to become fat yourself, for instance, and depression is contagious. It is reasonable to surmise that values spread in much the same way: indeed, if we look at extremes such as the spread of Naziism or the growth of fundamental religions, there is a very strong sense in which networks act as conduits for value. But I think that's it: they are conduits, not containers of value. Whatever has values may consist of networks that facilitate the spread or even the formation of those values, but it is the thing, not the network, that is what we care about here.
All of this leads me to suspect that the social forms that Terry and I identified as different in their pedagogical uses and affordances have some fundamental characteristics that go quite a way beyond that and relate to and intersect with one another in quite distinctively different ways. When we picture them as a Venn diagram it homogenizes these differences and makes it seem as though there are simply overlaps between vaguely similar entities, but there is more to it. Networks provide conduits for the spread of value between and within sets and groups. They are not the only conduits by any means: for example, if the human race were attacked by an alien civilization then I think it unlikely that a network would be needed to spread a range of values that would surface fairly ubiquitously (as a set characteristic), though it might help spread attitudes to how we should respond to such a threat. The same is true of many things in the more mundane realms of broadcast media, city planning and publication, not to mention the effects of natural features of the environment. Part of the reason for the distinctive culture and values in Canada, for example, is surely related to its dangerously cold climate that makes assistance to and from others a very strong necessity, plus a million other things like the opportunities afforded by its abundant natural resources and its proximity to other places. Prairie people are not quite the same as mountain people for reasons that go beyond historical happenstance and path dependencies. This is all about sets: shared characteristics and features. Sets can help to generate values: the fact that shorter-than-average people have to interact differently with the environment than taller-than-average people in many different ways leads to (at least) greater tendencies to share some values. The fact that people are collocated in a region, quite apart from network and group facets that emerge, means they are likely to share some attitudes and tendencies. It's simple evolutionary theory. It's why the finches in the Galapagos Islands have evolved differently: they have to interact with their different environments, and those environments have varied constraints and affordances. Other factors like path dependencies play an enormous role. Networks have a crucial part here too as co-evolution occurs not only in response to the environment but in response to the interconnections between agents in the system. In human systems, groups are both containers of networks and are themselves nodes in networks, so there are layers of scale that make this quite a complex thing.
The complexity becomes much more manageable if, instead of focusing on the social forms of aggregation, we think of values as being attached not to the aggregations themselves but to the collectives that emerge from them. Collectives are, by definition, behaviours that emerge from multiple interactions and are different from those interactions. A human can be viewed as a net, a set or even a group (there are hierarchies of organisation in which the brain might be seen as a controller) but it is the collective, the emergent entity that arises out of sets, nets and groups that is recognisably an individual, that has values. In the development of nationalist or religious values, it is the operation of algorithms that makes the set, net or group of which it is comprised into something distinct and potentially able to embody values, typically resulting from a mix of interactions combined with intentional categorisation by individuals - a collective.
I don't see any of this as suggesting even a glimmer of consciousness but it does seem at least possible that collectives can, at least sometimes, be described as having tropisms and to talk, perhaps loosely, in terms of intentionality. Whether this is enough to ascribe values to them is another matter, but it is not entirely absurd. We sometimes talk of plants as 'liking the sun' or 'liking the shade' in ways that probably have more to do with metaphor than beliefs about plant feelings, but there is a sense that it is true. It is even more obviously true in animals: even single-celled organisms are slightly more than just billiard balls bouncing round in reaction to their surroundings. They have purposes, aversions, likes and dislikes. Some exhibit fascinatingly complex behaviours - slime moulds, for example. It is not a great stretch from there to talking about human collectives in similar terms. Financial markets, for instance, are archetypal examples of human collectives that in principle need little or no machine mediation, yet move in complex ways that are not simply the sum of their parts. And, interestingly, we talk blithely of bull and bear markets as though they were in some way alive and, in some sense, imbued with feelings and even emotions. And maybe, in some sense, they are.
TEKRI researcher blogs etc
- Reflecting on Learning Analytics and SoLAR
- Humpback whale in English Bay
- Learning and the Kardashians
- Study: People Want Power Because They Want Autonomy
- Hello world!
- W16: week 9 - beginning the artefact
- First, Let’s Fire All the Managers
- Open Learning Analytics. Again
- McDonald's as a learning technology
- Collective values