EdUp EdTech Podcast Episode 123: Voices Unveiled - AI and Education
Updated Apr 03, 2026
AI in education is often discussed in broad terms. When I joined Holly Owens and Nadia Johnson on the EdUp EdTech podcast for episode "123: Voices Unveiled: AI and Education", I focused on a more practical question, one we explore in more depth in our piece on machine learning and mid-semester teaching evaluations: how can universities use AI to understand student feedback and improve the student experience?
During the conversation, I shared how my move into the education sector sharpened my interest in text analysis tools that reduce administrative effort without weakening the human side of learning. That matters because when teams spend less time manually sorting comments, they have more time to respond to what students are actually saying.
We also unpacked how Student Voice uses machine learning to interpret student feedback and turn open comments into themes institutions can act on. For universities, that means less guesswork when reviewing courses and more confidence that student voice is shaping teaching, support, and curriculum decisions. We also discussed why empathy still matters: the technology should help institutions listen better, not automate away judgement.
We ended by looking ahead to a more responsive model of education, where AI helps teams spot patterns earlier and support students more effectively. If you are exploring how to use AI in a way that stays grounded in student experience, especially when comparing HE-specific workflows with generic LLMs, this episode is a useful place to start.
If you want to see how this approach works in practice, explore Student Voice Analytics to see how universities analyse student comments with faster, more consistent feedback analysis.
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Related Entries
- Lexicon and Software Choice in Education Text Analysis
- The Best Text Analysis Software for Education
- Using machine learning for automated language analysis
- NSS open-text analysis methodology for UK HE
- Sentiment analysis for UK universities: a practical guide