Join us for this lunchtime seminar exploring meaningful patterns in data from large-scale assessments. If you can't make it in person, please join the meeting online.

Computer-based assessments offer unprecedented opportunities to capture rich, granular computer log data through human-machine interactions, providing deeper insights into test-takers’ strategies and behaviors. This multidimensional sequential log data, encompassing actions, time intervals, eye-tracking, and more, poses challenges for traditional unidimensional sequence models. This talk presents an overview of sequence mining techniques applied to unstructured log data, with the goal of advancing item design and measurement frameworks.

Two case studies are highlighted to illustrate the application of sequence mining in educational assessments. The first explores missing response patterns in a computational thinking assessment using Dynamic Time Warping (DTW) method, identifying potential causes of nonresponse and predicting missing values based on log data. The second investigates behavioral features of resilient students in scientific inquiry tasks, applying the Time-Warped Longest Common Subsequence (T-WLCS), a method originally developed for musical retrieval—to uncover interpretable patterns in student interactions.

The presentation will also discuss the broader potential of integrating AI techniques with log data in large-scale assessments, exploring opportunities for more adaptive, inclusive, and behaviorally informed measurement systems.

About the speakers

Dr. Qiwei (Britt) He is Provost’s Distinguished Associate Professor in the Data Science and Analytics Program, and Founder and Director of the AI-Measurement and Data Science Lab at Georgetown University in the United States. Her research interests are broadly situated in the field of psychometric modeling and machine learning, with specific devotion to methodology advancement in sequential log data analysis, sequence mining, text mining, multimodal data analysis (eye-tracking and immersive virtual reality), artificial intelligence for interactive design, automated item generation and scoring systems in national and international large-scale assessments such as PISA, PIAAC and NAEP. Dr. He was appointed as Huges Hall Visiting Fellow at University of Cambridge (2025-2026), OECD Thomas J. Alexander Fellow (2017-2019), and currently serves in the Expert Group for PISA-Vocational Education and Training, and the Board on Human-System Integration at the National Academies of Science, Engineering and Medicine in the United States. She received the U.S. National Council on Measurement in Education (NCME) Annual Award of Exceptional Achievement in 2023, the NCME Jason Millman Promising Measurement Scholar Award in 2019, and the NCME Alicia Cascallar Outstanding Paper of Early-Career Scholar Award in 2017.

Discussant: Professor Constant Leung
Chair: Dr David Pepper

Lunch will be provided at this event.

Questions? Please get in touch with the ECS Research team (research-ecs@kcl.ac.uk)