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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20251016T135128Z
LOCATION:Grand Hall J
DTSTART;TZID=America/Chicago:20251015T154000
DTEND;TZID=America/Chicago:20251015T160000
UID:HFESAM_ASPIRE 2025_sess136_LECT708@linklings.com
SUMMARY:Chatbot Memory: Uncovering How Mental Effort and Chabot Interactio
 ns Affect Short-Term Learning
DESCRIPTION:Alexandre Marois (Université Laval); Lavallée Isabelle (Univer
 sité de Sherbrooke); and Boily Gabrielle, Ramon Alaman Jonay, Bérénice Des
 rosiers, and Noémie Lavoie (Université Laval)\n\nDevelopments in artificia
 l intelligence (AI) disrupt our ways of living. Generative AI is particula
 rly representative of these changes as it can generate content traditional
 ly reserved to humans with increased efficiency and reduced effort. This i
 ncludes technologies like ChatGPT and other tools that exploit large langu
 age models, typically taking the form of conversational agents (chatbots) 
 that understand natural language and produce responses accordingly. These 
 technologies can be useful for self-regulated learning as is the case for 
 Web browsing and other Web-based tools. It is however unclear whether lear
 ning with chatbots may be efficient as opposed to other Web-based approach
 es given the reduced effort related with chatbot interactions. This study 
 assessed how chatbot interactions affect short-term learning and what role
  plays mental effort. We report impacts on memory and self-reported worklo
 ad of participants gathering information from the Internet or from a chatb
 ot for answering essay questions, followed by a surprise memory test.\n\nT
 rack: Education\n\nSession Chair: Arunkumar Pennathur (University of Texas
  at El Paso)\n\n
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