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UID:pretalx-sips2026-dc-TQPLDN@pretalx.com
DTSTART;TZID=EST:20260608T133000
DTEND;TZID=EST:20260608T150000
DESCRIPTION:Traditional psychology curricula focus heavily on frequentist p
 arametric statistics (e.g.\, ANOVA\, regression). However\, as AI becomes 
 ubiquitous\, undergraduates can benefit from understanding the conceptual 
 similarities and differences between these traditional models and Machine 
 Learning approaches. This session aims to explore concrete strategies for 
 introducing AI modeling to psych students. We will discuss how to use exis
 ting knowledge of linear models to explain ML concepts. We will also discu
 ss whether AI literacy is best served as an integrated component of existi
 ng statistics courses or as a standalone Psychology AI requirement/electiv
 e. Participants can share pedagogical tools and reflect on how to transiti
 on students from point-and-click software to more flexible modeling framew
 orks. Whether you are a student\, teach statistics\, have experience with 
 AI\, or mentor students and researchers\, join us to brainstorm a modern s
 tats toolkit that prepares the next generation of psychological scientists
  for an AI-integrated field
DTSTAMP:20260524T192027Z
LOCATION:HA Room 2416
SUMMARY:Bridging the Gap - Integrating Machine Learning Education into Unde
 rgraduate Psychology Statistics - Jesús\, Lucy Su
URL:https://pretalx.com/sips2026-dc/talk/TQPLDN/
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