BEGIN:VCALENDAR VERSION:2.0 X-WR-CALNAME:EventsCalendar PRODID:-//hacksw/handcal//NONSGML v1.0//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York LAST-MODIFIED:20240422T053451Z TZURL:https://www.tzurl.org/zoneinfo-outlook/America/New_York X-LIC-LOCATION:America/New_York BEGIN:DAYLIGHT TZNAME:EDT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 DTSTART:19700308T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU END:DAYLIGHT BEGIN:STANDARD TZNAME:EST TZOFFSETFROM:-0400 TZOFFSETTO:-0500 DTSTART:19701101T020000 RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT CATEGORIES:College of Arts and Sciences,Thesis/Dissertations DESCRIPTION:Cognitive and Metacognitive Predictors of Probabilistic Learnin g: Individual Differences in the Weather Prediction Task by John Augusta A dvisor: Trina Kershaw Committee members: Judy Sims-Knight, Heloisa Alves A bstract: Decision making is a complex behavior that all people engage in, both in everyday situations and in professional or academic contexts. Unde rstanding how individuals make decisions under uncertainty has important i mplications for learning, training, and performance. This study examined h ow people learn probabilistic cue-outcome relationships using the Weather Prediction Task (WPT). This task expresses and captures the Multiple Cue P robability Learning (MCPL) paradigm that models real-world decision enviro nments. The cognitive processes of interest were fluid intelligence (Gf) a nd working memory capacity (WMC), with consideration of metacognition as a n additional factor. Prior research has not fully clarified how these cogn itive processes contribute to MCPL success and has not included metacognit ion as a factor for consideration. Participants completed the WPT along wi th individual difference measures. Results showed that participants improv ed across the WPT and showed high performance in the final test block. Sym metry Span (a WMC task) was the strongest predictor of the final test bloc k. Operation Span (a WMC task) and task-specific self-efficacy (metacognit ion) predicted performance in the initial learning block. General self-reg ulated learning measures were not significantly related to WPT performance . Findings suggest that learning in this environment may depend on differe nt predictors at different phases of the task. They also suggest that task -specific metacognitive measures may be more useful than general self-regu lation measures in this context. Meeting will occur in person and via Zoom .\nEvent page: https://www.umassd.edu/events/cms/psychology-ms-defense-by- john-augusta.php\nEvent link: https://umassd.zoom.us/j/98934728089?pwd=pZq haj6UwwrUCHoVYwtSvWevnl1Jqi.1 X-ALT-DESC;FMTTYPE=text/html:

Cognitive and Metacognitive Pre dictors of Probabilistic Learning: Individual Differences in the Weather P rediction Task by John Augusta

Advisor: Trina Kershaw

Comm ittee members: Judy Sims-Knight\, Heloisa Alves

Abstract: Decision making is a complex behavior that all people engage in\, both in everyday situations and in professional or academic contexts. Understanding how in dividuals make decisions under uncertainty has important implications for learning\, training\, and performance. This study examined how people lear n probabilistic cue-outcome relationships using the Weather Prediction Tas k (WPT). This task expresses and captures the Multiple Cue Probability Lea rning (MCPL) paradigm that models real-world decision environments. The co gnitive processes of interest were fluid intelligence (Gf) and working mem ory capacity (WMC)\, with consideration of metacognition as an additional factor. Prior research has not fully clarified how these cognitive process es contribute to MCPL success and has not included metacognition as a fact or for consideration. Participants completed the WPT along with individual difference measures. Results showed that participants improved across the WPT and showed high performance in the final test block. Symmetry Span (a WMC task) was the strongest predictor of the final test block. Operation Span (a WMC task) and task-specific self-efficacy (metacognition) predicte d performance in the initial learning block. General self-regulated learni ng measures were not significantly related to WPT performance. Findings su ggest that learning in this environment may depend on different predictors at different phases of the task. They also suggest that task-specific met acognitive measures may be more useful than general self-regulation measur es in this context.

Meeting will occur in person and via Zoom.

Event page: https://www.umassd.edu/events/cms/psychology-ms -defense-by-john-augusta.php
Event link: https://umassd.z oom.us/j/98934728089?pwd=pZqhaj6UwwrUCHoVYwtSvWevnl1Jqi.1

DTSTAMP:20260506T153144 DTSTART;TZID=America/New_York:20260513T130000 DTEND;TZID=America/New_York:20260513T140000 LOCATION:LIB 426 SUMMARY;LANGUAGE=en-us:Psychology MS Defense by John Augusta UID:52a33141be01c76f1e9451a85f135b62@www.umassd.edu END:VEVENT END:VCALENDAR