Craft Data Science Insights: A 40-Minute Exploration – Session #1

Get ready to be inspired! This miniseries brings together five brilliant young minds from education, psychology, learning science, and survey methodology. They’ll share their innovative solutions to challenges powered by AI and data science.

Sequence Mining on Process Data in Digital-Based Large-Scale Assessments

Qiwei He, Georgetown University

Increased use of computer-based assessments brings a great opportunity to track process data with the aim to gain a deeper insight about respondents’ test-taking behavioral patterns and problem-solving strategies. The fine-grained process data are often in complex and multidimensional form that call for data mining methods in addition to classical psychometric models. In this talk, I will give a brief overview about why and how to use process data in digital-based large-sale assessments with a variety of sequence mining methods, such as n-grams model, sequence similarity measures, and latent sequence modeling. The goal of these studies is to leverage sequential process data in large-scale assessments to assist in understanding how respondents interact with the items administered, thus support test construction, enhance latent ability estimation, improve validity of conclusions, and facilitate cross-national comparisons. A new trend of incorporating process data in adaptive testing and quality assurance will also be discussed.

View event recording: https://youtu.be/9Dl1ewGxTRA

Dr. Qiwei He

About the Presenter

Dr. Qiwei He is Associate Professor in the Data Science and Analytics Program and Director of the AI-Measurement and Data Science Lab at Georgetown University. Her research focuses on advancing methodologies in sequence mining, text mining, psychometric modeling, and machine learning on new data sources such as process data and textual data collected in digital-based assessments in education, psychology, psychiatry, and public health. Prior to this appointment, Dr. He was a Senior Research Scientist in the Advanced Psychometrics and Data Science Center at Educational Testing Service (ETS) for over nine years, overseeing research on innovative item type development, technology-based environment design, and sequential process data analyses in national and international large-scale assessments such as PISA, PIAAC and NAEP, as well as in K-12 education assessments and learning projects. Dr. He was appointed as OECD Thomas J. Alexander Fellow in 2018 and has been serving on the Psychometrics and Educational Evaluation Panel for UNESCO Institute for Statistics and Policy Linking Panel for USAID since 2020. She was the recipient of NCME Annual Award of Exceptional Achievement in 2023, NCME Jason Millman Promising Measurement Scholar Award in 2019 and NCME Alicia Cascallar Outstanding Paper of Early-Career Scholar Award in 2017.

Dr. Qiwei He
Associate Professor
Director of AI-Measurement and Data Science Lab
Data Science and Analytics Program
Georgetown University

Contact: Hua-Hua Chang, chang606@purdue.edu