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DTSTART:19700101T000000
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BEGIN:VEVENT
DTSTAMP:20241014T203102Z
LOCATION:McArthur Ballroom
DTSTART;TZID=America/Phoenix:20240912T173000
DTEND;TZID=America/Phoenix:20240912T183000
UID:HFESAM_ASPIRE - Presented by HFES_sess108_POS113@linklings.com
SUMMARY:22. Teaching ChatGPT: Attempting to Demonstrate the Protégé Effect
  With a Large Language Model Learner
DESCRIPTION:Poster\n\nZachary Tidler (Georgia Institute of Technology)\n\n
 It is well known that teaching others can benefit the teacher's understand
 ing. This is commonly known as the "learning-by-teaching" or "Protégé" eff
 ect. The effect is leveraged in systems such as the "see one, do one, teac
 h one," approach, common to medical training. However, its applicability i
 s limited when no additional learner is available. Addressing this limitat
 ion, researchers have explored non-interactive learning-by-teaching method
 s (such as simply imagining the learner) with mixed outcomes. As technolog
 y advanced, focus shifted to using teachable software agents to substitute
  for human learners. Teaching the agents was shown to be beneficial, but m
 ost were restricted to predefined content. Recent advances in artificial i
 ntelligence have enabled more open-ended interactions with conversational 
 agents. This study was an investigation of whether a general-purpose chatb
 ot, ChatGPT, can serve as a teachable agent and replicate the learning-by-
 teaching/Protégé effect. The effect was not replicated but the study desig
 n is informative for future efforts.\n\nTrack: Aging, Augmented Cognition,
  Children's Issues, Communications, Cybersecurity, Education, Environmenta
 l Design, General Sessions, Human AI Robot Teaming (AI), Macroergonomics, 
 Occupational Ergonomics, Student Forum, Surface Transportation, Sustainabi
 lity, System Development
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