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Looking to the future with Lev Gonick, Part 4 - Video instruction + artificial intelligence for student success

BY LSGONICK – FEBRUARY 24, 2021

Editor’s note: This is the fourth installment of a five-part series from ASU CIO Lev Gonick, featuring two key trends: real-time video instruction and artificial intelligence. Read the previous installments now and check back soon for the final installment for more from Lev on the ten trends leading higher education in 2021.

6. The real-time video instruction paradigm shifts

Robust video instruction delivered over the internet saved education in 2020. Institutions and organizations, big and small, pivoted (many overnight) to support hundreds, thousands, even tens of thousands of courses to 80 million K-20 students in the United States alone. Some executives in this product space were remarkably generous and made their video meeting platforms available at little or no cost for education.

Creative teachers made use of basic functionality designed to support business users in the service of the learning needs of their students. In the adrenaline-driven experience that was education for much of 2020, business-focused video meeting technologies were more than good enough for last year. Not so much going forward. 

Software development teams follow user journeys as they develop their products and platforms. The need of a business may appear to the casual observer to be approximately the same as to the learning environment. While there are some basic comparisons, many of the most effective learning methodologies are not well suited to be "crammed" into a platform built to facilitate business development and workflows. In short, last year’s experience with video delivery for learning has proven to be necessary, but I observe broad consensus in education circles that it is insufficient for our needs going forward.

While some have called for a video platform designed for education purposes, the more scalable and pragmatic approach for 2021 is to encourage teams to leverage APIs and even SDKs (software pieces of code or glue that allows you to assemble or integrate code) from companies like BlueJeans, WebEx, Teams and Zoom to redesign existing user experiences to enable an authentic learner-centered experience. 

To be sure, there are raging debates about whether real-time interactive video-based learning is here to stay. I believe real-time interactive video learning will engender a whole new category of hybrid offerings to address dynamic market conditions and is likely to represent the largest growth opportunity for traditional campuses to grow new markets with their faculty and brands.

Campus-based teams, collaborations within and between education segments and a growing number of entrepreneurs are poised to take video-based instruction to the next level in 2021. And if first-mover advantage does not appeal to you, and the baseline offering from your favorite video meeting vendor works in your education setting, you can watch and join the next wave of innovation in video-based real-time learning at a future date.

The ASU Example - Zooming forward

Zoom is coming to the Greater Phoenix in a big way, with a new Research & Development center planned for the area around the ASU Tempe campus. ASU President Michael Crow said, “Zoom’s expansion into the Phoenix market reflects the success of our efforts to grow and support a new economy for Arizona that is based on technology and innovation.”

7. Artificial intelligence & machine learning for student success

Competing visions of machine intelligence, as either augmentation of human intelligence or the supplanting of human intelligence goes back at least 75 years. Issac Asimov’s short story, "Runaround," published in a 1942 issue of Astounding Science Fiction, imagined the need to establish what Asimov called the Three Laws of Robotics. 

Several years later, in 1950, Alan Turing offered what became known as the Turing Test, a framework for attempting to delineate when a machine begins to think for itself. While theoretical and science fiction work advanced over the decades, with DARPA and Google in the early 2000s, technological know-how, computational capacity and real-time machine learning had advanced sufficiently to propose the audacious idea of a real, commercially viable autonomous automobile. 

The arms race and hype cycle on artificial intelligence and augmented intelligence took off thereafter. Narrative science demonstrated the ability of a machine to produce sophisticated reports in 2010. IBM Watson was able to recall and parse massive amounts of data in fractions of a second and beat the Jeopardy champion in 2011. In the same year, personal attendants were born, enabling a robust voice-driven, if sometimes humorous, error-filled services marketplace, answering and recommending questions in an ever more nuanced fashion over time through interacting with humans. 

By the time Google’s DeepMind AlphaGo beat the world champion in Go in 2016, a growing chorus of education futurists saw cognitive computing as the next frontier for augmenting the prospect of learner success at scale.

Thus far, beyond vendor pitches and canned demonstrations, the near term promise of learning transformation through machines and AI have generally been more incremental and less earth-shattering than most enthusiasts would have expected. The most impressive offerings have been the growing number of knowledge bots as well as meaningful insight engines. In the next stage of adaptive learning engines, personalized, contextualized and just-in-time pathways for learning must be able to ingest and provide.

It’s been well over a decade since the early euphoria and predictions of mind-reading robo-tutors in the sky. Many of the early ventures have been unable to develop viable business options as expanding market adoption has been difficult to come by. However, much has been learned along the way.

The underlying technologies continue to mature. And while there is critical design work to be done to advance digital trust, the broader social acceptance of machine learning in so many other facets of our lives makes it highly probable that AI is just beginning to mature as a relevant technology set to advance learning outcomes and student success.  More than half of the students who start college in the United States do not finish. This comes at a terrible personal cost and massive social consequences. There is a socio-technical imperative to apply technical insights and pedagogical creativity to support the student journey especially around logic, reasoning, and critical thinking.

In the year ahead, the conditions are set for multiple new ventures to develop true learning software that are both adaptive and capable of personalization. There is ample opportunity to integrate what we know about active and social contexts of learning into these routines. New solutions are poised to make learning not just efficient but also provide compelling and adaptive narratives that incentivize and motivate diverse learners to discover deeper forms of learning. In short, 2021 is the year of the reset and relaunch of the next wave of AI and ML products and projects in education. 

The ASU Example - Artificial intelligence, genuine innovation

Two of UTO’s Humble Heroes of 2020, Paul Alvarado and Mike Sharkey, dedicated a lot of their time to leverage AI in giving data-driven resources to Student Success Coaches across the entire University.

Stay tuned for the final installment, "Going digital with trust, wallets and transformation" coming March 3.

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