BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//NCME - ECPv6.15.18//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:NCME
X-ORIGINAL-URL:https://ncme.org
X-WR-CALDESC:Events for NCME
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20240310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20241103T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20250309T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20251102T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20260308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20261101T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250918T000000
DTEND;TZID=America/New_York:20251211T235959
DTSTAMP:20260404T162657
CREATED:20251029T194856Z
LAST-MODIFIED:20251029T194943Z
UID:10000006-1758153600-1765497599@ncme.org
SUMMARY:GSIC Fall 2025 Writing Group
DESCRIPTION:More details in the flyer below; go here to register. Contact Kayla Burt additional information.
URL:https://ncme.org/event/gsic-fall-2025-writing-group/
LOCATION:Minnesota
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251203T150000
DTEND;TZID=America/New_York:20251203T160000
DTSTAMP:20260404T162657
CREATED:20251023T174413Z
LAST-MODIFIED:20251023T201016Z
UID:10000002-1764774000-1764777600@ncme.org
SUMMARY:Coffee Hour with Educators of Measurement SIGIMIE
DESCRIPTION:
URL:https://ncme.org/event/coffee-hour-with-educators-of-measurement-sigimie/
LOCATION:Minnesota
CATEGORIES:Webinars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251210T160000
DTEND;TZID=America/New_York:20251210T170000
DTSTAMP:20260404T162657
CREATED:20251203T212232Z
LAST-MODIFIED:20251203T212752Z
UID:10000011-1765382400-1765386000@ncme.org
SUMMARY:AIME SIGIMIE Speaker Series: Predicting Item Difficulty for Pretest Items in Large-Scale Assessments
DESCRIPTION:This is presented by the AIME SIGIMIE.  \n\n\n\nPretesting items in large-scale assessments requires substantial time\, resources\, and financial investment. Accurately predicting item difficulty before any administration can streamline pretesting\, reduce costs\, and provide earlier feedback to item writers\, supporting targeted revisions that better align with intended difficulty. Effective difficulty prediction methods\, therefore\, have the potential to improve both efficiency and quality in item development and pool management. \n\n\n\nIn this study\, we evaluate a two-step hybrid framework for predicting the IRT-based difficulty of pretest items in large scale literacy assessments. First\, we fine tune transformer-based models on item text under multiple input configurations that vary the inclusion of stimuli\, stems\, options\, and associated skills. Second\, we feed transformer predictions\, together with handcrafted linguistic features\, into traditional machine learning models. Using real world pretest data\, we then examine the gains over the baseline model that only uses linguistic features\, the differences among transformer models\, and the contribution of each input source. Our results indicate that hybrid models consistently improve predictive accuracy while maintaining interpretability\, offering a practical companion tool for large scale assessment programs. \n\n\n\nRSVP\n\n\n\nAbout the Presenter\n\n\n\n\nYoungKoung Kim (College Board)\n\n\n\n\nMeeting Details\n\n\n\nhttps://umn.zoom.us/j/98791553326?pwd=TojUjPWwpzw7RaZ6Lc9UzWiAgyX3J3.1Meeting ID: 987 9155 3326 Passcode: 3HkRqw
URL:https://ncme.org/event/aime-sigimie-speaker-series-predicting-item-difficulty-for-pretest-items-in-large-scale-assessments/
LOCATION:Minnesota
CATEGORIES:Webinars
END:VEVENT
END:VCALENDAR