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Maryland Assessment Research Center (MARC)

2022 (Virtual) MARC Conference

The Twentieth Annual MARC Conference

Machine Learning, Natural Language Processing, and Psychometrics

Conference will be hosted on Zoom, Nov. 3rd-4th, 2022

For questions about registration or the conference please contact Fisk@umd.edu

Click here for info on the pre-conference workshop (Nov. 2nd, 2022. 9am - 4pm)

Live streaming video will be available online after the conference for repeated viewing.

Presentation Schedule

* Eastern standard time (EST)


November 3rd (Thursday)
Morning Session I
8:50-9:00am	Welcome and Introduction	Hong Jiao (��Ů)
9:00-9:50am	The item factory: intelligent automation in support of test development at scale MARCES Nov 2022-Alina.pptx	Alina von Davier, Andrew Runge, Yigal Attali, Yena Park, Kevin Yancey, Geoff LaFlair, André Horie (Duolingo)
10:00-10:50am	Applications of transformer neural networks in assessment, from item development to scoring 2022_MARC_presentation_transformers_Lottridge.pptx	Susan Lottiridge (Cambium)
11:00-11:50am	Leveraging process data analytics, natural language processing and machine learning to support remotely proctored assessments MARC2022_Analytics_AI_JHao.pdf	Jiangang Hao (Education Testing Service)
Lunch Break
Afternoon Session
1:00-1:50pm	Mending the mess babel has left us with: cross-lingual automatic coding in international large-scale assessments 2022-11-03.MARCC_compiled-Fabian_0.pdf	Fabian Zehner (Leibniz Institute for Research and Information in Education)
2:00-2:50pm	Estimating contextual word-level item parameters using BERT in an IRT framework marc-2022-bert-irt-public.pptx	Kevin Yancey, Andrew Runge, JR Lockwood, Geoff LaFlair (Duolingo)
3:00-3:50pm	Keeping humans in the loop when implementing augmented intelligence solutions for common test development challenges MARC_Swygert_Micir_102822.pdf	Kimberly Swygert, Ian Micir (National Board of Medical Examiners)


November 4th (Friday)
Morning Session
9:00-9:50am	Data-driven item selection and generation in assessments and learning datadriven-Andrew Lan.pdf	Andrew Lan (University of Massachusetts Amherst)
10:00-10:50am	From adaptive testing to personalized adaptive testing: applications of machine learning algorithms MARC2022_OkanBulut.pdf	Okan Bulut (University of Alberta)
11:00-11:50am	Leveraging process data in large-scale assessments with sequence mining Process Data_MARC_QiweiHe_v1.pdf	Qiwei He (Education Testing Service)


Lunch Break
Afternoon Session
1:00-1:50pm	Applying machine learning to assess next generation science learning Zhai_Maryland-ML for NGSA_2022_10_27.pdf	Xiaoming Zhai (University of Georgia)
2:00-2:50pm	An AI-based platform for real time assessment, scaffolding, and alerting on students’ science practices. Gobert presentation for MARC 2022.pdf	Janice Gobert (Rutgers University)
2:50-3:00pm	Closing remarks	Robert Lissitz (��Ů)