Learning Analytics and the Future of Change in the Classroom
Deau: Early identification of at-risk students. You know, the small to mid-range universities are really dealing with enrollment challenges and making sure they show value to their student population. So helping them through the process and identifying early interventions are key.
Personalized learning, modifying curriculum, improving the curriculum, optimizing learning resources, and enhancing teaching strategies really across the board. Student success initiatives, identifying trends and patterns and just overall continuous improvement and ROI for the institution.
CT: What do IT leaders need to know about data architecture and governance in the context of learning analytics?
Deau: We're an organization that promotes common frameworks and standards to help improve the experience and the digital learning that happens in a university or college. The key to that is data integration, getting all these ed tech tools to talk to one another, to have a common framework for the data that you collect; to be able to scale it is key. In the end, the institutions themselves need to think about that data privacy and security, meaning the ownership and access along with all of that key infrastructure. But that is going to be so unique to each institution that we try to focus on the things that we can control, which is working across the market with our members to make sure they're getting the data in a common framework that they can really use once they start collecting it. Because as you know, their data can come in a wide variety of formats, and you need to have a common thread that ties them all, which our standards do.
CT: Can you talk about where learning analytics is heading? And also, I'd be really interested to hear your take on how you think AI is going to be impacting learning analytics. Obviously AI has gone through a transformation itself recently.
Deau: Having been an educator — I'm a trained teacher — I've always leveraged technology for helping my students learn. And I see that in the kind of work that I do today. I'm not in the teaching field, but I am definitely in the teaching mindset. Seeing how we can leverage technology for learning has really been a personal passion of mine. So personalized learning at scale is, I think, an area where AI is going to contribute greatly. And that is something that our organization thinks about. In fact, one of our leadership imperatives is personalized learning, and thinking about how we can make learning accessible for every individual. That's one key.
Real-time analytics for getting that data back in real time has been challenging because of the infrastructure, but I think AI is going to change some of that and make it a lot easier to collect and analyze that data as it comes in.
I think also in the immersive technologies. This is kind of in the personalized learning thread, but immersive technologies are going to benefit from AI in the analytics element of it, automating assessment and feedback. In fact, there's been some experiments I think, with generative AI as a teaching assistant. I think that's kind of fascinating. It comes with all sorts of challenges and concerns. But certainly, people are starting to try that right now.
Also in our organization, we think a lot about upskilling and the future of work and making sure that students can represent their learning in meaningful ways and skills and competencies. And we think that AI will likely play a significant role in helping learners, whether they're in a higher ed setting, or just continuously learning new skills and adapting to the workforce.
But then, you know, you talk about all those really wonderful things. And then you get to the sort of the cautionary tale in there. And that's ethics in AI and really ensuring that we're understanding what's underneath those algorithms and addressing bias and fairness in the use of these because that can impact different populations in significant ways. And so we need to do our best ethically in the use of these technologies.