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
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.
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.