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UID:pretalx-wombat-2025-79GEP8@conf.nectric.com.au
DTSTART;TZID=AEST:20250930T110000
DTEND;TZID=AEST:20250930T113000
DESCRIPTION:Generative AI tools\, like ChatGPT\, haven’t necessarily crea
 ted new challenges in data science education. Rather\, the availability an
 d rapidly growing capabilities of these tools have exposed weaknesses in l
 earning design and assessment that educators have been ignoring for a whil
 e. \n\nIn this talk\, I will draw on my experience in teaching psychology 
 students about computational reproducibility and the value of R-based data
  workflows. I will argue for the need to rethink what learning to learn lo
 oks like and talk about how we might reframe assessment as the process of 
 gathering evidence that learning has occurred. \n\nThere is no avoiding th
 e fact that students now need to learn how to learn alongside Generative A
 I. Data science educators can help them by designing learning experiences 
 that build self-regulated learning skills and normalise what real learning
  feels like.
DTSTAMP:20260824T015846Z
LOCATION:8.03
SUMMARY:Rethinking data science education in the age of genAI - Jenny Richm
 ond
URL:https://conf.nectric.com.au/wombat-2025/talk/79GEP8/
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