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:
- Does the technology foster creativity and personal expression?
- Does the technology develop the learner and contribute to her formation as a person?
- Is the technology fun and engaging?
- Does the technology have the human teacher and/or peer learners at the centre?
- 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.