SIG-Systematic Review and Meta-Analysis

Jihyun Lee, University of North Texas

Zero-Shot Learning and Support Vector Machine Methods for Automated Abstract Screening in Scoping Reviews - Moe Debbagh Greene, Virginia Commonwealth University; Michael Broda, Virginia Commonwealth University; Chin-Chih Chen, Virginia Commonwealth University; Chi-Ning Chang, Virginia Commonwealth University; Tzu-Wei Wang, Virginia Commonwealth University; Jeen Mariam Joy, Virginia Commonwealth University; Yuyan Xia, University of Kentucky

Using Artificial Intelligence for Efficient Screening and Coding for Meta-Analyses - Qi Zhang, American Institutes for Research; Sarah Sahni, J-PAL North America, MIT; Megha Joshi, American Institutes for Research; Martyna Citkowicz, American Institutes for Research; Kamal Middlebrook, American Institutes for Research; Laura Michaelson, American Institutes for Research

Integrating Machine Learning Into Systematic Reviews: Strengthening Evidence Synthesis - Emily Bolger, Michigan State University; Ying Wang, FHI 360; Rachel L. Renbarger, FHI 360; M. Danny Caballero, Michigan State University; Marius Nwobi, Michigan State University; Cassandra Lem, Michigan State University; Noah Finkelstein, University of Colorado - Boulder; Scott P. Simkins, North Carolina A&T State University; Taylor Boyd, Western Michigan University; Charles R. Henderson, Western Michigan University; Andrea L. Beach, Western Michigan University

MetaMate: Large Language Model to the Rescue of Automated Data Extraction for Educational Systematic Reviews - Xue Wang, Johns Hopkins University; Gaoxiang Luo, University of Pennsylvania

Large Language Models as Educational Research Critics: A Human-AI Comparison - Ella Anghel, Ben-Gurion University of the Negev; Di Xu, University of California - Irvine; Richard B. Arum, University of California - Irvine

Joshua R. Polanin, American Institutes for Research