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Download full textShi, Yang; Chi, Min; Barnes, Tiffany; Price, Thomas W. – International Educational Data Mining Society, 2022
Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…
Descriptors: Programming, Knowledge Level, Prediction, Instructional Innovation
Direct linkSamsa, Gregory P.; Thomas, Laine; Lee, Linda S.; Neal, Edward M. – Journal of Statistics Education, 2012
Clinicians have characteristics--high scientific maturity, low tolerance for symbol manipulation and programming, limited time outside of class--that limit the effectiveness of traditional methods for teaching multi-predictor modeling. We describe an active-learning based approach that shows particular promise for accommodating these…
Descriptors: Active Learning, Statistics, Mathematics Instruction, Prediction
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries
