Grading OSPE Questions with Decision Learning Trees: A First Step towards an Intelligent Tutoring System for Anatomical Education

Intelligent tutoring systems (ITSs) have been used for decades as a means for improving the quality of education for learners primarily by providing guidance to students based on a student model, e.g., predicting their knowledge level on a subject. There have been few attempts to incorporate ITSs into anatomical education. Objective structured practical examinations (OSPEs) are an important, albeit challenging, means of evaluation in anatomical education. This research aims to create an ITS for anatomical OSPEs, and as a crucial first step looks to create a machine learning-based approach for grading OSPEs. To that end, decision tree learning was evaluated with, and without, spellchecking to produce a grading tool using the answer key developed by instructional assistants. Using answers from 428 learners, the tool obtained an average accuracy of 96.8% (SD = 3.4%) across 60 questions.