Simon Buckingham Shum is Professor of Learning Informatics at Australia’s University of Technology Sydney (UTS) and Director of the Connected Intelligence Centre (CIC)—an innovation center where students and staff can explore education data science applications. Simon holds a Ph.D from the University of York, and is known for bringing a human-centered approach to analytics and development. He also co-founded the Society for Learning Analytics Research (SoLAR), which is committed to advancing learning through ethical, educationally sound data science.

In this episode, Simon and I discuss the state of education technology (edtech), privacy, human-centered design in the context of using AI in higher ed, and the numerous technological advancements that are re-shaping the higher level education landscape.

Our conversation covered:

• How the hype cycle around big data and analytics is starting to pervade education
• The differences between using BI and analytics to streamline operations, improve retention rates, vs. the ways AI and data are used to  increase learning and engagement
• Creating systems that teachers see as interesting and valuable, in order to drive user adoption and avoid friction.
• The more difficult-to-design-for, but more important skills and competencies researchers are working on to prepare students for a highly complex future workplace
• The data and privacy issues that must be factored into ethical solution designs
• Why “learning is not shopping,” meaning we the creators of the tech have to infer what goes on in the mind when studying humans, mostly by studying behavior.
• Why learning scientists and educational professionals play an important role in the edtech design process, in addition to technical workers
• How predictive modeling can be used to identify students who are struggling—and the ethical questions that such solutions raise.

Resources and Links

Designing for Analytics

simon.buckinghamshum.net

Simon on LinkedIn

#experiencingdata

Designing for Analytics Podcast

Quotes from Today’s Episode

“We are seeing AI products coming out. Some of them are great, and are making a huge difference for learning STEM type subjects— science, tech, engineering, and medicine. But some of them are not getting the balance right.” — Simon

“The trust break-down will come, and has already come in certain situations, when students feel they’re being tracked…” — Simon, on students perceiving BI solutions as surveillance tools instead of beneficial

“Increasingly, it’s great to see so many people asking critical questions about the biases that you can get in training data, and in algorithms as well. We want to ask questions about whether people are trusting this technology. It’s all very well to talk about big data and AI, etc., but ultimately, no one’s going to use this stuff if they don’t trust it.” — Simon

“I’m always asking what’s the user experience going to be? How are we actually going to put something in front of people that they’re going to understand…” — Simon

“There are lots of success stories, and there are lots of failure stories. And that’s just what you expect when you’ve got edtech companies moving at high speed.” — Simon

“We’re dealing, on the one hand, with poor products that give the whole field a bad name, but on the other hand, there are some really great products out there that are making a tangible difference, and teachers are extremely enthusiastic about.” — Simon

“There’s good evidence now, about the impact that some of these tools can have on learning. Teachers can give some h