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Announcing: aWEAR Conference: Wearables and Learning

Over the past year, I’ve been whining about how wearable technologies will have a bigger impact on how we learn, communicate, and function as a society than mobile devices have had to date. Fitness trackers, smart clothing, VR, heart rate monitors, and other devices hold promising potential in helping understand our learning and our health. They also hold potential for misuse (I don’t know the details behind this, but the connection between affective states with nudges for product purchases is troubling).

Over the past six months, we’ve been working on pulling together a conference to evaluate, highlight, explore, and engage with prominent trends in wearable technologies in the educational process. The aWEAR conference will be held Nov 14-15 at Stanford. The call for participation is now open. Short abstracts, 500 words, are due by July 31, 2016. We are soliciting conceptual, technological, research, and implementation papers. If you have questions or are interested in sponsoring or supporting the conference, please send me an email

From the site:

The rapid development of mobile phones has contributed to increasingly personal engagement with our technology. Building on the success of mobile, wearables (watches, smart clothing, clinical-grade bands, fitness trackers, VR) are the next generation of technologies offering not only new communication opportunities, but more importantly, new ways to understand ourselves, our health, our learning, and personal and organizational knowledge development.

Wearables hold promise to greatly improve personal learning and the performance of teams and collaborative knowledge building through advanced data collection. For example, predictive models and learner profiles currently use log and clickstream data. Wearables capture a range of physiological and contextual data that can increase the sophistication of those models and improve learner self-awareness, regulation, and performance.

When combined with existing data such as social media and learning management systems, sophisticated awareness of individual and collaborative activity can be obtained. Wearables are developing quickly, including hardware such as fitness trackers, clothing, earbuds, contact lens and software, notably for integration of data sets and analysis.

The 2016 aWEAR conference is the first international wearables in learning and education conference. It will be held at Stanford University and provide researchers and attendees with an overview of how these tools are being developed, deployed, and researched. Attendees will have opportunities to engage with different wearable technologies, explore various data collection practices, and evaluate case studies where wearables have been deployed.

What does it mean to be human in a digital age?

It has been about 30 months now since I took on the role to lead the LINK Research Lab at UTA. (I have retained a cross appointment with Athabasca University and continue to teach and supervise doctoral students there).

It has taken a few years to get fully up and running – hardly surprising. I’ve heard explanations that a lab takes at least three years to move from creation to research identification to data collection to analysis to publication. This post summarizes some of our current research and other activities in the lab.

We, as a lab, have had a busy few years in terms of events. We’ve hosted numerous conferences and workshops and engaged in (too) many research talks and conference presentations. We’ve also grown significantly – from an early staff base of four people to expected twenty three within a few months. Most of these are doctoral or post doctoral students and we have a terrific core of administrative and support staff.

Finding our Identity

In trying to find our identity and focus our efforts, we’ve engaged in numerous activities including book clubs, writing retreats, innovation planning meetings, long slack/email exchanges, and a few testy conversations. We’ve brought in well over 20 established academics and passionate advocates as speakers to help us shape our mission/vision/goals. Members of our team have attended conferences globally, on topics as far ranging as economics, psychology, neuroscience, data science, mindfulness, and education. We’ve engaged with state, national, and international agencies, corporations, as well as the leadership of grant funding agencies and major foundations. Overall, an incredible period of learning as well as deepening existing relationships and building new ones. I love the intersections of knowledge domains. It’s where all the fun stuff happens.

As with many things in life, the most important things aren’t taught. In the past, I’ve owned businesses that have had an employee base of 100+ personnel. There are some lessons that I learned as a business owner that translate well into running a research lab, but with numerous caveats. Running a lab is an entrepreneurial activity. It’s the equivalent of creating a startup. The intent is to identify a key opportunity and then, driven by personal values and passion, meaningfully enact that opportunity through publications, grants, research projects, and collaborative networks. Success, rather than being measured in profits and VC funds, is measured by impact with the proxies being research funds and artifacts (papers, presentations, conferences, workshops). I find it odd when I hear about the need for universities to be more entrepreneurial as the lab culture is essentially a startup environment.

Early stages of establishing a lab are chaotic. Who are we? What do we care about? How do we intersect with the university? With external partners? What are our values? What is the future that we are trying to create through research? Who can we partner with? It took us a long time to identify our key research areas and our over-arching research mandate. We settled on these four areas: new knowledge processes, success for all learners, the future of employment, and new knowledge institutions. While technologies are often touted as equalizers that change the existing power structure by giving everyone a voice, the reality is different. In our society today, a degree is needed to get a job. In the USA, degrees are prohibitively expensive to many learners and the result is a type of poverty lock-in that essentially guarantees growing inequality. While it’s painful to think about, I expect a future of greater racial violence, public protests, and radicalized politicians and religious leaders and institutions. Essentially the economic makeup of our society is one where higher education now prevents, rather than enables, improving one’s lot in life.

What does it mean to be human in a digital age?

Last year, we settled on a defining question: What does it mean to be human in a digital age? So much of the discussion in society today is founded in a fetish to talk about change. The narrative in media is one of “look what’s changing”. Rarely is the surface level assessment explored to begin looking at “what are we becoming?”. It’s clear that there is much that is changing today: technology, religious upheaval, radicalization, social/ethnic/gender tensions, climate, and emerging super powers. It is an exciting and a terrifying time. The greatest generation created the most selfish generation. Public debt, failing social and health systems, and an eroding social fabric suggest humanity is entering a conflicted era of both turmoil and promise.

We can better heal than any other generation. We can also better kill, now from the comfort of a console. Globally, less people live in poverty than ever before. But income inequality is also approaching historical levels. This inequality will explode as automated technologies provide the wealthiest with a means to use capital without needing to pay for human labour. Technology is becoming a destroyer, not enabler, of jobs. The consequences to society will be enormous, reflective of the “spine of the implicit social contract” being snapped due to economic upheaval. The effects of uncertainty, anxiety, and fear are now being felt politically as reasonably sane electorates turn to solutionism founded in desire rather than reality (Middle East, Austria, Trump in the US to highlight only a few).

In this milieu of social, technology, and economic transitions, I’m interested in understanding our humanity and what we are becoming. It is more than technology alone. While I often rant about this through the perspective of educational technology, the challenge has a scope that requires thinking integratively and across boundaries. It’s impossible to explore intractable problems meaningfully through many of the traditional research approaches where the emphasis is on reducing to variables and trying to identify interactions. Instead, a complex and connected view of both the problem space and the research space is required. Trying to explore phenomena through single variable relationships is not going to be effective in planning

Complex and connected explorations are often seen to be too grandiose. As a result, it takes time for individuals to see the value of integrative, connected, and complex answers to problems that also possess those attributes. Too many researchers are accustomed to working only within their lab or institutions. Coupled with the sound-bite narrative in media, sustained and nuanced exploration of complex social challenges seems almost unattainable. At LINK we’ve been actively trying to distribute research much like content and teaching has become distributed. For example, we have doctoral and post-doctoral students at Stanford, Columbia, and U of Edinburgh. Like teaching, learning, and living, knowledge is also networked and the walls of research need the same thinning that is happening to many classrooms. Learning to think in networks is critical and it takes time, especially for established academics and administrators. What I am most proud of with LINK is the progress we have made in modelling and enacting complex approaches to apprehending complex problems.

In the process of this work, we’ve had many successes, detailed below, but we’ve also encountered failures. I’m comfortable with that. Any attempt to innovate will produce failure. At LINK, we tried creating a grant writing network with faculty identified by deans. That bombed. We’ve put in hundreds of hours writing grants. Many of which were not funded. We were involved in a Texas state liberal arts consortium. That didn’t work so well. We’ve cancelled workshops because they didn’t find the resonance we were expecting. And hosted conferences that didn’t work out so well financially. Each failure though, produced valuable insight in sharpening our focus as a lab. While the first few years were primarily marked by exploration and expansion, we are now narrowing and focusing on those things that are most important to our central emphasis on understanding being human in a digital age.

Grants and Projects

It’s been hectic. And productive. And fun. It has required a growing team of exceptionally talented people – we’ll update bios and images on our site in the near future, but for now I want to emphasize the contributions of many members of LINK. It’s certainly not a solo task. Here’s what we’ve been doing:

1. Digital Learning Research Network. This $1.6m grant (Gates Foundation) best reflects my thinking on knowing at intersections and addressing complex problems through complex and nuanced solutions. Our goal here is to create research teams with R1 and state systems and to identify the most urgent research needs in helping under-represented students succeed.

2. Inspark Education. This $5.2m grant (Gates Foundation) involves multiple partners. LINK is researching the support system and adaptive feedback models required to help students become successful in studying science. The platform and model is the inspiration of the good people at Smart Sparrow (also the PIs) and the BEST Network (medical education) in Australia and the Habworlds project at ASU.

3. Intel Education. This grant ($120k annually) funds several post doctoral students and evaluates effectiveness of adaptive learning as well as the research evidence that supports algorithms that drive adaptive learning.

4. Language in conflict. This project is being conducted with several universities in Israel and looks at how legacy conflict is reflected in current discourse. The goal is to create a model for discourse that enables boundary crossing. Currently, the pilot involves dialogue in highly contentious settings (Israeli and Palestinian students) and builds dialogue models in order to reduce legacy dialogue on impacting current understanding. Sadly, I believe this work will have growing relevance in the US as race discourse continues to polarize rather than build shared spaces of understanding and respect.

5. Educational Discourse Research. This NSF grant ($254k) is conducted together with University of Michigan. The project is concerned with evaluating the current state of discourse research and to determine where this research is trending and what is needed to support this community.

6. Big Data: Collaborative Research. This NSF grant ($1.6m), together with CMU, evaluates the impact of how different architectures of knowledge spaces impacts how individuals interact with one another and build knowledge. We are looking at spaces like wikipedia, moocs, and stack overflow. Space drives knowledge production, even (or especially) when that space is digital.

7. aWEAR Project. This project will evaluate the use of wearables and technologies that collect physiological data as learners learn and live life. We’ll provide more information on this soon, in particular a conference that we are organizing at Stanford on this in November.

8. Predictive models for anticipating K-12 challenges. We are working with several school systems in Texas to share data and model challenges related to school violence, drop out, failure, and related emotional and social challenges. This project is still early stages, but holds promise in moving the mindset from one of addressing problems after they have occurred to one of creating positive, developmental, and supportive skillsets with learners and teachers.

9. A large initiative at University of Texas Arlington is the formation of a new department called University Analytics (UA). This department is lead by Prof Pete Smith and is a sister organization to LINK. UA will be the central data and learning analytics department at UTA. SIS, LMS, graduate attributes, employment, etc. will be analyzed by UA. The integration between UA and LINK is one of improving the practice-research-back to practice pipeline. Collaborations with SAS, Civitas, and other vendors are ongoing and will provide important research opportunities for LINK.

10. Personal Learning/Knowledge Graphs and Learner profiles. PLeG is about understanding learners and giving them control over their profiles and their learning history. We’ve made progress on this over the past year, but are still not at a point to release a “prototype” of PLeG for others to test/engage with.

11. Additional projects:
- InterLab – a distributed research lab, we’ll announce more about this in a few weeks.
- CIRTL – teaching in STEM disciplines
- Coh-Metrix – improving usability of the language analysis tool

Going forward

I know I’ve missed several projects, but at least the above list provides an overview of what we’ve been doing. Our focus going forward is very much on the social and affective attributes of being human in our technological age.

Human history is marked by periods of explosive growth in knowledge. Alexandria, the Academy, the printing press, the scientific method, industrial revolution, knowledge classification systems, and so on. The rumoured robotics era seems to be at our doorstep. We are the last generation that will be smarter than our technology. Work will be very different in the future. The prospect of mass unemployment due to automation is real. Technology is changing faster than we can evolve individually and faster than we can re-organize socially. Our future lies not in our intelligence but in our being.

But.

Sometimes when I let myself get a bit optimistic, I’m encouraged by the prospect of what can become of humanity when our lives aren’t defined by work. Perhaps this generation of technology will have the interesting effect of making us more human. Perhaps the next explosion of innovation will be a return to art, culture, music. Perhaps a more compassionate, kinder, and peaceful human being will emerge. At minimum, what it means to be human in a digital age has not been set in stone. The stunning scope of change before us provides a rare window to remake what it means to be human. The only approach that I can envision that will help us to understand our humanness in a technological age is one that recognizes nuance, complexity, and connectedness and that attempts to match solution to problem based on the intractability of the phenomena before us.

The Godfather: Gardner Campbell

Gardner Campbell looms large in educational technology. People who have met him in person know what I mean. He is brilliant. Compassionate. Passionate. And a rare visionary. He gives more than he takes in interactions with people. And he is years ahead of where technology deployment current exists in classrooms and universities.

He is also a quiet innovator. Typically, his ideas are adopted by other brash, attention seeking, or self-serving individuals. Go behind the bravado and you’ll clearly see the Godfather: Gardner Campbell.

Gardner was an originator of what eventually became the DIY/edupunk movement. Unfortunately, his influence is rarely acknowledged.

He is also the vision behind personal domains for learners. I recall a presentation that Gardner did about 6 or 7 years ago where he talked about the idea of a cpanel for each student. Again, his vision has been appropriated by others with greater self-promotion instincts. Behind the scenes, however, you’ll see him as the intellectual originator.

Several years ago, when Gardner took on a new role at VCU, he was rightly applauded in a press release:

Gardner’s exceptional background in innovative teaching and learning strategies will ensure that the critical work of University College in preparing VCU students to succeed in their academic endeavors will continue and advance…Gardner has also been an acknowledged leader in the theory and practice of online teaching and education innovation in the digital age

And small wonder that VCU holds him in such high regard. Have a look at this talk:

Recently I heard some unsettling news about position changes at VCU relating to Gardner’s work. In true higher education fashion, very little information is forthcoming. If anyone has updates to share, anonymous comments are accepted on this post.

There are not many true innovators in our field. There are many who adopt ideas of others and popularize them. But there are only a few genuinely original people doing important and critically consequential work: Ben Werdmuller, Audrey Watters, Stephen Downes, and Mike Caulfield. Gardner is part of this small group of true innovators. It is upsetting that the people who do the most important work – rather than those with the loudest and greatest self-promotional voice – are often not acknowledged. Does a system like VCU lack awareness of the depth and scope of change in the higher education sector? Is their appetite for change and innovation mainly a surface level media narrative?

Leadership in universities has a responsibility to research and explore innovation. If we don’t do it, we lose the narrative to consulting and VC firms. If we don’t treat the university as an object of research, an increasingly unknown phenomena that requires structured exploration, we essentially give up our ability to contribute to and control our fate. Instead of the best and brightest shaping our identity, the best marketers and most colourful personalities will shape it. We need to ensure that the true originators are recognized and promoted so that when narrow and short-sighted leaders make decisions, we can at least point them to those who are capable of lighting a path.

Thanks for your work and for being who you are Gardner.

The Future of Learning: Digital, Distributed, Data-Driven

Yesterday as I was traveling (with free wifi from the good folks at Norwegian Air, I might add), I caught this tweet from Jim Groom:

The comment was in response to my previous post where I detailed my interest in understanding how learning analytics were progressing in Chinese education. My first internal response was going to be something snarky and generally defensive. We all build in different ways and toward different visions. It was upsetting to have an area of research interest be ridiculed. Cause I’m a baby like that. But I am more interested in learning than in defending myself and my interests. And I’m always willing to listen to the critique and insight that smart people have to offer. This comment stayed with me as I finalized my talk in Trondheim.

What is our obligation as educators and as researchers to explore research interests and knowledge spaces? What is our obligation to pursue questions about unsavoury topics that we disagree with or even find unethical?

Years ago, I had a long chat with Gardner Campbell, one of the smartest people in the edtech space, about the role of data and analytics. We both felt that analytics has a significant downside, one that can strip human agency and mechanize the learning experience. Where we differed was in my willingness to engage with the dark side. I’ve had similar conversations with Stephen Downes about change in education.

My view is that change happens on multiple strands. Some change from the outside. Some change from the inside. Some try to redirect movement of a system, others try to create a new system altogether. My accommodating, Canadian, middle child sentiment drives my belief that I can contribute by being involved in and helping to direct change by being a researcher. As such, I feel learning analytics can play a role in education and that regardless of what the naysayers say, analytics will continue to grow in influence. I can contribute by not ignoring the data-centric aspects in education and engage them instead and then attempting to influence analytics use and adoption so that it reflects the values that are important for learners and society.

Then, during the conference today, I heard numerous mentions of people like Ken Robinson and the narrative of creativity. Other speaking-circuit voices like Sugata Mitra were frequently raised as well. This lead to reflection about how change happens and why many of the best ideas don’t gain traction and don’t make a systemic level impact. We know the names: Vygostky, Freire, Illich, Papert, and so on. We know the ideas. We know the vision of networks, of openness, of equity, and of a restructured system of learning that begins with learning and the learner rather than content and testing.

But why doesn’t the positive change happen?

The reason, I believe, is due to the lack of systems/network-level and integrative thinking that reflects the passion of advocates AND the reality of how systems and networks function. It’s not enough to stand and yell “creativity!” or “why don’t we have five hours of dance each week like we have five ours of math”. Ideas that change things require an integrative awareness of systems, of multiple players, and of the motivations of different agents. It is also required that we are involved in the power-shaping networks that influence how education systems are structured, even when we don’t like all of the players in the network.

I’m worried that those who have the greatest passion for an equitable world and a just society are not involved in the conversations that are shaping the future of learning. I continue to hear about the great unbundling of education. My fear is the re-bundling where new power brokers enter the education system with a mandate of profit, not quality of life.

We must be integrative thinkers, integrative doers. I’m interested in working and thinking with people who share my values, even when we have different visions of how to realize those values.

Slides from my talk today are below:

Reflecting on Learning Analytics and SoLAR

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.

LAK11
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.

LAK11

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.

Enter Grace
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.

What’s next
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?

Open Learning Analytics. Again

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.

Adios Ed Tech. Hola something else.

I’ve been involved in educational technology since the late 1990′s when I was at Red River College and involved in deploying the first laptop program in Canada. Since that time, I’ve been involved in many technology deployments in learning and in researching those deployments. Some have been systems-level – like a learning management system. Others have been more decentralized and unstructured – like blogs, wikis, and social media.

But there is something different in the ed tech space today than what I have experienced in the past. Most of my career has involved using technology to help people get better access to learning resources and materials, to better connect with each other, to better access formal education, and to improve their teaching practices and pedagogies. I’ve been fortunate to journey with talented folks: Grainne Conole, Stephen Downes, Dave Cormier, Martin Weller, Dragan Gasevic, Shane Dawson, Carolyn Rose, David Wiley, Ryan Baker, and many many others. At some level we all shared a goal that fairness, justice, and equity underpin the role of education in society and that by enabling access to learning and improving the the quality of learning, we were helping to improve the lives of learners and of society more broadly. Sometimes this meant helping people to develop digital skills to find new jobs or transition into new roles. Sometimes it meant connecting people eager to collaborate with others from around the world. Sometimes it was about righting a wrong or injustice. Regardless of whether the goal was finding a job or developing new mindsets, my focus was always on the learner, on the human.

Emerging technology today departs from my previous vision of improving the human condition. Through AI/Machine Learning, we are constantly hearing that technology is becoming more human and becoming more capable of judgements that we once thought were our domain. In education though, the opposite is happening: educational technology is not becoming more human; it is making the human a technology. Instead of improving teaching and learning, today’s technology re-writes teaching and learning to function according to a very narrow spectrum of single, de-contextualized skills.

Two articles this past week crystallized my thinking. First, Sebastian Thrun, in an Economist article, states: “BECAUSE of the increased efficiency of machines, it is getting harder and harder for a human to make a productive contribution to society”. If that is true, why is his startup trying to teach humans? Why not drop the human teaching thing altogether and just develop algorithms for making the stated productive contribution to society? He also details nanodegrees which are essentially what we in academia have to date called “certificates”. Perhaps we can call them nano-robo-certificates. Making up words is fun when media attention is petitioned. Most discouraging about this is that I’ve met Sebastian and he is a friendly, caring, deeply motivated person. The Thrun-of-media doesn’t align with the thoughtful Thrun-in-person.

The second article focused on Knewton. Jose Fereirra states “this robot tutor can essentially read your mind”. I’ve met Jose on numerous occasions. He’s bright, charismatic, and appears to genuinely care about improving learning. His rhetoric doesn’t align with the real challenges of education where cognitive capability alone is a small factor in learner success. Robot tutors will not make personalized learning easy. Learning is contextual, social, and involves whole person dynamics. In the past, I’ve stated that Knewton is the only edtech company with Google like potential. That is likely still the case, but I’m no longer convinced that this is a good thing.

Both Udacity and Knewton require the human, the learner, to become a technology, to become a component within their well-architected software system. Sit and click. Sit and click. So much of learning involves decision making, developing meta-cognitive skills, exploring, finding passion, taking peripheral paths. Automation treats the person as an object to which things are done. There is no reason to think, no reason to go through the valuable confusion process of learning, no need to be a human. Simply consume. Simply consume. Click and be knowledgeable.

My framework for technologies in the edtech space now, those that I find empowering for learners and reflective of a human and creative-oriented future, includes five elements:

  1. Does the technology foster creativity and personal expression?
  2. Does the technology develop the learner and contribute to her formation as a person?
  3. Is the technology fun and engaging?
  4. Does the technology have the human teacher and/or peer learners at the centre?
  5. Does the technology consider the whole learner?

I go through five year cycles. My early interest was in blogs and wikis in learning. Then my attention turned to connectivism and networked learning. Then to MOOCs. And then to learning analytics. These have all been terrific experiences and I’m proud to have been able to work with leading researchers and exceptional students. But it’s time for change. A curious disconnect has been emerging in my thinking, one that has been made clear with the hype-oriented buzzwords of today’s ed tech companies. I no longer want to be affiliated with the tool-fetish of edtech. It’s time to say adios to technosolutionism that recreates people as agents within a programmed infrastructure.

Over the last several years, my grants and research interests have turned to something…else. I’m not sure what the unifying thread is a this stage. Partly it’s a focus on the whole person. On empowered states of learning. On mindfulness, complexity, integrative learning, contemplative practices, formative learning, creativity, making. The dLRN grant focuses on connecting researchers with state systems to improve learning opportunities for under represented learners. (btw, you really should join us at our conference at Stanford in October). Our grant with Smart Sparrow focuses on multiple dimensions of learning success where the teacher remains central in the learning experience. Our project with Intel involves several post docs exploring how personalization can be improved in the learning process by developing a graph model of the learner that considers contextual, cognitive, social, and metacognitive factors. Two of our NSF grants are focused on language and discourse analysis and using big data to explore roles that learners adopt in variously configured knowledge spaces (Wikipedia, Stack Overflow, and MOOCs). Our MRI grant produced a report on digital learning – an evaluation of how technologies foster learning, rather than foster routine clicking. These are promising narratives to the de-humanizing edtech narratives. Others, such as Lumen Learning, Domain of One’s Own, and Candace Thille’s research on adaptive learning are similarly advancing humanizing technologies.

These transitions in research are part of a broader agenda that will help, at least in LINK lab, to create tools, technologies, and pedagogies that enable creation, personal formation, engagement, fun, and joy. I’m still fleshing out exactly what this will look like over the next several years. Obviously technology will be central in this process, but it will be one where mindful and appropriate learning practices are promoted. Where technology humanizes rather than reduces people to algorithmic and mechanical practices. Whatever this research agenda becomes, I’m more excited for the future of technology enabled learning than I have been in many years.

White House: Innovation in Higher Education

A few weeks ago, I received an invitation to the White House. The invitation was somewhat cryptic, but basically stated that the focus on the meeting was on quality and innovation. This invite was then followed a week later with a link to a post by Ted Mitchell, Undersecretary of Education, on Innovation and Quality in Higher Education, to help prepare for the conversation.

The event organizers made it clear that no media or social media was allowed during the event in order to have an open brainstorming session. My thoughts below are suitably vague so as to not identify who else was there and the specifics of the meeting. Instead, my comments are more about my personal reactions to the conversation without going into details about who said what specifically. (I was worried that the trip would have to be cancelled as I managed to get food poisoning a few days prior to the event, but fortunately, things worked out).

1. The White House is secure. As a “foreign national” it took me over two hours to clear three layers of security, was provided a special pink badge to identify me as a foreign national and was required to navigate only with an escort (including restroom visits and ultimately WH departure). I’m baffled how people manage to jump the White House fence. I felt watched over with lovingkindness.

2. Higher education generally has no clue about what’s brewing in the marketplace as a whole. The change pressures that exist now are not ones that the existing higher education model can ignore. The trends – competency-based learning, unbundling, startups & capital inflow, new pedagogical models, technology, etc – will change higher education dramatically.

3. No one knows what HE is becoming. Forget the think tanks and the consultants and the keynote speakers. No one knows how these trends will track or what the university will look like in the future. This unknowability stems from HE being a complex systems with many interacting elements. We can’t yet see how these will connect and inter-relate going forward. The best strategy in a time of uncertainty is not to seek or force the way forward, but to enter a cycle of experimentation. The Cynefin Framework provides the best guidance that I’ve seen on how to function in our current context.

4. I was struck by how antagonistic some for-profits are toward public higher education. I sat in one session where a startup spent much of the time expressing intense dislike for higher education in today’s form “my tax dollars are going to bad actors”, ironically to be followed up with “I loved my time in university. It shaped me and made me”. It reminds me of Peter Thiel’s drop out of school and start a company. But what does Thiel expect when his money and his life is at stake? He expects, for his hedge fund: “High GPA from top-tier university; preferably in computer science, mathematics, statistics, econometrics, physics, engineering or other highly quantitative”. I’m worried that the future will have an education system where the wealthy continue to receive high quality education on campuses, but the poor receive some second-tier alternative system that prepares them mainly to work but not to be change agents in the world. This gets at the heart of a challenge in higher education. HE is a system that is deeply embedded in societal realities, including equity and justice. It’s not an ROI equation. It’s a quality of life equation. A startup or corporate entity has a primary purpose of doing what makes sense economically. It’s their job. But it conflicts with the most dominant needs of our society today: how to educate individuals from low socio-economic status. The bottom income quartile of society has seen zero increase in degree completion over the past 50 years. Any meaningful redesign of higher education, for the benefit of individuals and society broadly, has to be primarily focused on helping to move this population toward success.

5. Title IV is the kingmaker. This is the alpha agent in change. Title IV drives federal student aid in the US. Systems that are included have access to students aid funding. Those that are not included (say a bootcamp startup) do not have access. As Title IV funding changes, so will US education. I heard several pushes for voucher systems (i.e. fund the student directly and they decide what to do with the dollars). This is the main space to watch in identifying which innovations will have legs and which ones will fail to get traction.

6. Expect a future of universities being more things to more people. A future of broadening scope regionally and of greater engagement in the lives of individuals. I addressed this toward the end of this presentation, starting slide 28. Higher Education is moving from a 4 year relationship to students to a 40 year relationship

7. Expect a future of far greater corporate involvement in HE. VC funds are flowing aggressively and these funders are also targeting policy change at local, state, and national levels. We aren’t used to this level of lobbying and faculty is unprepared to respond to this. Expect it. Your next faculty meeting will involve a new student success system, a personalized learning system, an analytics system, a new integrated bootcamp model, new competency software, new cloud-based computing systems, and so on. Expect it. It’s coming.

8. Expect M & A activities in higher education. I fully anticipate some combination of partnering with companies like General Assembly, creation of in-house bootcamps, or outright acquisitions by innovative universities.

9. The scope of change is starting to settle somewhat in HE. It’s a more comprehensible landscape than it was a few years ago. We’ve had our MOOC hype moment. The system of universities globally withstood the assault (remember when this was a legitimate conference topic??). Not only that, it was discovered that MOOCs are exceptional for those on campus. Similarly, some solidification of innovative teaching and learning practices is happening and it’s making it a bit easier for leaders to respond. As stated previously, this doesn’t mean that we know what HE will look like in the future, but it does provide a firmer foundation for planning for leaders. Any university that doesn’t yet have some department or committee focused on “responding systemically to innovations and change pressures” is missing an important opportunity.

10. Higher education is a great integrator and subsumer. I fully expect a future of more, not less universities globally. They play too significant a regional and local economic and identity role for regions to not expect a university in their backyard. Look how hard it has been to kill Sweet Briar. The clock is ticking on the nonsense of Drucker and Christensen’s statements about 50% campus closures. We are entering the golden age of learning. Why would we kill our universities?

11. I was stunned and disappointed at the lack of focus on data, analytics, and evidence. In spite of the data available, decision making is still happening on rhetoric. We don’t understand the higher education market analytically – i.e. scope, fund flows, student flows, policy directives, long term impact, – well nationally and internationally. I want to hold both universities and corporate sectors to accountability in their claims of impact. We can’t do that without a far better data infrastructure and greater analytics focus.

12. I’m getting exceptionally irritated with the narrative of higher education is broken and universities haven’t changed. This is one of the most inaccurate pieces of @#%$ floating around in the “disrupt and transform” learning crowd. Universities are exceptional at innovating and changing. Explore any campus today. It’s a new world on most campuses, never mind the online, competency, and related systems. And if your slide deck includes an image of desks and argues that nothing has changed, you’re being dishonest and disingenuous. Repent. Healing is possible for you, but first you must see the falseness of your words.

Employability and quality of life

The employability narrative for higher education is over powering. While I certainly agree that work is important, I think the framework of “getting a job” is too limiting for the role that higher education (can and should) play in society. I had the privilege recently to deliver a talk to a group of folks at HERDSA in Australia on this topic. My argument: employability is important, but quality of life is more critical as a long term focus. Slides are below.

Personal Learning Graphs (PLeG)

Personalized and adaptive learning has been described as the so-called holy grail of education. The idea is not new, though its technological instantiation is getting increased attention. In a well-funded education system, personalized instruction happens when guided by a teacher as each students strengths and weaknesses and knowledge gaps are known. However, when classrooms start to exceed 20+ students, some type of mediating agent is needed in order to address knowledge gaps as it becomes impossible for a teacher to be aware of what is happening with each learner. So, while the human educator is the original (and best) personalized learning system, the current funding constraints and other resource challenges have raised the need for alternative approaches to make sure that each learner is receiving support reflective of her needs.

Many of the personalized learning systems now available begin with an articulation of the knowledge space – i.e. what the learner needs to know. What the learner knows is somewhat peripheral and is only a focal point after the learner has started interacting with content. Additionally, the data that is built around learner profiles is owned by either the educational institution or the software company. This isn’t a good idea. Learners should own the representation of what they know.

Last year, I posted on personalized learner knowledge graphs. Since then, I’ve been working with several colleagues to refine and develop this idea. Embedded below is a summary of our recent thinking on what this would look like in practice. Personal Learning Graph (PLeG – pronounced ‘pledge’ (acronyms are hard)) is intended as a response to how work and life are changing due to technology and the importance of individuals owning their own learning representation.