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  1. The Pony in the Pile Vince Kellen, Ph.D. CIO, University of Kentucky 10/4/2012
  2. A tale of two learners Abraham Lincoln • Autodidactic • Books, books, books • Became a skilled military strategist • Penchant for poetry, Shakespeare, politics and history My nephew • Not an autodidact • Good worker, smart kid, but… • It takes a village • After a few low-security colleges and much money borrowed • He has found an intellectual home 2
  3. Can you explain how the heart works? n Four chambers n Four valves n It beats, pumping to/from lungs, to/from body 3
  4. Can you explain how the brain learns? 4
  5. What compels the water to leap down the horse’s throat? n Individual attributes • Motivation, effort, repetition • Cognitive abilities (verbal, visual, reasoning, working memory, long-term memory, attention, pre-existing knowledge…) • Confidence, self-efficacy, reflective ability, need for sensation/cognition • Processing strategy • Social identity, social capability n External representation attributes • Cultural relevancy, dialect, personalization • Use of words and pictures, types of visuals elements, arrangement • Complexity, duration, animation, sequencing, interactivity • Social interaction; constructivist and active learning approaches n Among many other things • Ultimately, the learners individual and social identity, desire and motivation, and integration with a community matters greatly • Serendipity plays a role! What environments foster serendipity? 5
  6. Questions, questions, questions Is traditional higher education doomed? Will the free MOOCs change everything? Will VC Edutech take off? Or will Harvard/MIT EdX rule? Will online replace face to face? Will badges replace degrees? Will top faculty become itinerant millionaire e-faculty? What will employers and society really value? Will any of this big data stuff work? 6
  7. Everyone wants to distort the competitive field 7
  8. “Excuse me. I just wanted to ask a question. What does God need with a starship?” - Captain Kirk 8
  9. Competitive factors n Players are trying to figure out the value of MOOCs. The MOOC fight may be about data which in time would be a critical component of a future business model n Wireless continues to grow. Smart phones are overtaking all other phones. Tablets are growing now. Mobile technology has a role to play n The number of technical options for delivery of learning are expanding n The market is ‘novel.’ A decade ago, investors avoided higher education like the plague. Now they want in. Why is this? n There is no agreed ‘theory of mind’ to guide creation of standard approaches. Nearly all entrepreneurs, decision and policy makers are not schooled in how the human brain actually learns n We have a continuum of learners with the back half of the bell curve of special interest. The invisible hand has a hard time with the ‘last mile’ 9
  10. What has happened in the past century All the ‘low hanging fruit’ has been picked. (The Great Stagnation, Tyler Cowan) Those that have the cognitive In 1900, 0.25% went to college (1 in 400). In 2009, 40% of 18-24 year-olds were enrolled in college, capabilities are in the higher 70% of all high school graduates were enrolled in college education system (Tyler Cowan & NY Times) 10
  11. What may happen? Higher costs, diminishing government support may affect access, potentially reducing the audience Those than have the cognitive and financial capability are in the higher education system 11
  12. First target for MOOCs? If badges gain credibility, MOOCs let autodidacts learn more and get hired. Abraham Lincoln would be ecstatic! 12
  13. What is our mission? Who is our audience? But what about those who may be capable but need help? How do we lower costs while improving learning? 13
  14. Another consideration n Middle skill jobs have received little wage growth and job growth since 1980 n High skilled jobs, especially those with advanced degrees, have experienced the best wage and job growth n The work force middle is getting ‘hollowed out’ n The recession may have accelerated the trend The Growth of Low Skill Service Jobs and the Polarization of the U.S. Labor Market. David Autor and David Dorn. NBER Working Paper 15150. 14
  15. In times of chaos, return to strategy fundamentals n Will the technology help solve a critical problem? • For whom? How many? Exactly how? n How valuable is the thing in question? What is it worth? • Badges, data about the learner, learner eyeballs, transferred credit (Colorado State & Udacity), recruiting for other programs n Does the provider have a scarce resource that can’t be gotten elsewhere? • Patented algorithm, a network of partners or potential customers, superior efficiency, brand equity n How does the technology enhance institution competiveness? • What causes students to choose the institution? What makes the institution unique in achieving its mission? How does the technology enhance the uniqueness? n How can the institution defend a new approach? • Can the solution integrate with unique, non-replicable institutional characteristics? How easily can other institutions copy? 15
  16. Disruptive technology versus disruptive practices n If the technology is easily replicated, differentiation will lie in the practices adopted in combination with the technology. Free access won’t differentiate institutions. Technology by itself may not matter n Institutions still need to improve their ability to transform learners, especially those at the margins. MOOCs, as currently conceived, will help the Abraham Lincolns, but not my nephew n Learners, families and employers must perceive the value in the transformation, however it occurs. Some interaction between institutions, families, alumni and employers will need to take place to reinforce a new model. These cultural shifts take time n Current large-scale online models replicate 20th century mass approaches: build once, deploy thousands to millions. Can this model develop superior results? Or is something more needed? n How can universities achieve superior results (students with superior abilities) at lower costs? Some combination of distinctive practices and appropriate combinations of technology may be in order. This is our challenge! 16
  17. A suggestion: deep personalization n Social aspects • We naturally adjust what we communicate in social settings. Face-to-face communication lets us interpret cues consciously and non-consciously • Something as difficult and complex as transformational education usually requires HIGH socialization (Abraham Lincoln aside) • Authentic, small group interaction, digital or face-to-face, enhances learning • When digital interactions let us suspend disbelief, they will have parity with molecular interactions! Until then, face-to-face has a unique position • A flipped classroom provides more time to foster active, group learning n Individual aspects • Visual and verbal concepts, terms, text, tone and style can be altered based on individual differences in – Cognition (working memory, visual/verbal, reasoning, prior knowledge…) – Affect/personality (need for sensation/cognition, optimism, confidence, effort, self efficacy, identity, persistence…) • We do this automatically in F2F interactions. How can the computer do this? 17
  18. I was attending a distance learning conference in Orlando, Florida, when it struck me… 18
  19. What happens when we have suspension of disbelief? And why was I attending a distance learning conference in Florida? 19
  20. Future possibilities with personalization and IT n Our current course capture system could be an adaptive MOOC in a box! • Add quizzes, an adaptive learning engine, leverage current LMS technology and integrate with student data warehouses • If learning objects are delivered online, can we measure student mastery of concepts via both bottom-up and top-down metadata approaches? n Can audio and video be automatically appended with metadata? • Statistically improbable phrases (e.g. Microsoft MAVIS) for superior way-finding? This would enable automated capture of concept engagement and difficulty • Can something like Kinect be used to detect and categorize motion in a class? n Can we collect individual attributes and personalize content? • Verbalizer/visualizer, need for sensation, working memory limits, prior experience • Collect this information via drip irrigation survey techniques • Augment with adaptive learning techniques that identify concept mastery n How inexpensively can we make create digital content and make it available in ways that help learners? • An ecosystem approach, adroitly done, might be a way 20
  21. What can universities do? n From vertical dissemination to active collaboration • Breakdown of the monolithic faculty model • Redesign of the classroom furniture and layout • Breaking free from seat-time requirements, promote flexible paths to degree completion • Reserve face-to-face for high value-add interactions (flipped class, etc.) n Personalize online education based on sound educational, psychological concepts • Content personalization based on psychographics, concept mastery • Vary pedagogy and tools based on the curriculum and learning task analysis • Design for and manage “micro-segments” (small class sizes, small market niches, small collections of students that share common attributes) • Master the long-tail of digital course creation and distribution! n Increase efficiency • Use a range of content fidelity (high to low) to match the opportunity • Automate as much as possible low-fidelity content creation and metadata augmentation • Find ways of producing high quality content at lower costs (insourced and outsourced) 21
  22. What can universities do? n Take advantage of facilities • Colleges provide an immersive experience that is not going away • Weave together technology, facilities and culture, e.g., living-learning communities n Use technology to encourage interaction • It’s an mobile, attention economy • Let students access their materials and interactions 7x24. Family portal? • Have the system ‘poke’ the students into action via personalized reminders, surveys, assistance, recommendations, reminders. Group ‘poking?’ Poke me and my friend? • Quickly predict and detect current and future engagement and progression issues • Escalate issues via automated workflows that can involve, track and remind all parties n Anticipate needs • Use data to understand progression and other ‘logistic’ log jams • Use data to identify proactive advice that can help students plan (readiness, over- optimism in career planning, program options, skill matching). Is there an e-harmony for academic career matching? n Data from the various learning technologies can inform the process • Do all these technologies have standard, real-time integration capabilities? 22
  23. New core competencies n Higher education is being forced to develop two new core competencies, previously thought incompatible but now required • Cost effectiveness • A superior learner experience n At the center of both of these competencies lies data and analytics • We are awash in all sorts of data • Universal data impedance theorem: those who could use it, don’t have it. Those who have it, don’t use it • Not all of this (if any) is big, but all of it is fast. New tools are available n The VC-funded ed tech market is looking like a fight over data • Data analytics to deliver relevant content to learners • Data assets to be used later to develop a viable profit model • Unsurprisingly, elite institutions moved first on MOOCs. Do they have more to lose? 23
  24. Predictions over the next three to five years n A new model is about to be invented • We are learning from past forays into large-scale online degrees, learning management systems, mobility and now what MOOC-related technology can offer • The new model embraces – Weaving together of place, facilities, F2F, online and mobility – Data to tailor, personalize, automate and enhance learning, advising and self-service – A range of fidelity (high to low) and content creation approaches (inexpensive to expensive) – Use of data and IT to increase faculty and staff productivity while maintaining effectiveness n Clever combinations of technologies and practice will surprise us! • Technologies – A plethora of options. Increased diversification of tools, technologies and approaches – No dominant supplier/vendor; open source, outsourced and DIY solutions could thrive • Practice – More universities will successfully apply a range of technologies – Most universities will have difficulties with organizational elements (Leadership, faculty & staff readiness, governance, incentive models, infrastructure, data integration and innovation capability) n How can you combine technologies and practices in unique ways? • Which traditional universities will be the first to overcome organizational and technical difficulties? Which ones would you argue already have? 24
  25. Questions?