The New Chalk: How Machine Learning Can Benefit Higher Education
Machine learning, AI and other algorithmic technologies have long promised to enhance the learning experience for college instructors and students.
But what can these technologies actually deliver? What’s required to implement them effectively? And how can they operate in a way that’s both equitable and transparent?
Andrew Jones, a data scientist here at Knewton, joined a panel discussion hosted by EdSurge this week in NYC that sought to answer some of these questions.
The panel, which included a group of educators and education technologists, covered a range of issues, including how machine learning technologies are perceived by students, specific areas where machine learning can make an impact on learning, and the barriers that must be overcome for this technology to be implemented successfully.
When asked to suggest the tough questions that instructors should ask before implementing machine learning technologies in their classroom, Andrew urged instructors to push for greater transparency into how a company’s algorithms work. “Asking what is being optimized for, and why, can give you a sense of [whether a tool] is focused on student outcomes, or whether it is about getting a prediction that’s right more often,” he said.
Toward the end of the session, the focus shifted to instructors themselves — and the role they will play in courses that increasingly feature machine learning technologies, such as virtual assistants
Andrew underscored the central role of the instructor, saying: “I’d rather see machine learning reach the level of chalk.”
You can find a full recap of the event over on EdSurge.