Data calibration for statistical-based assessment in constraint-based tutors

作者：

Highlights：

• Item Response Theory models for constraint-based intelligent tutoring systems.

• Data-driven assessment of problem solving tasks.

• Data filtering criteria for Item Response Theory parameters estimation.

• Best model fit selection criteria.

摘要

•Item Response Theory models for constraint-based intelligent tutoring systems.•Data-driven assessment of problem solving tasks.•Data filtering criteria for Item Response Theory parameters estimation.•Best model fit selection criteria.

论文关键词：Learning analytics,Assessment,Constraint-Based Modeling,Intelligent Tutoring Systems,Item Response Theory

论文评审过程：Received 28 September 2015, Revised 14 January 2016, Accepted 18 January 2016, Available online 25 January 2016, Version of Record 20 February 2016.

论文官网地址：https://doi.org/10.1016/j.knosys.2016.01.024