The Impact of Decision Agency & Granularity on Aptitude Treatment Interaction in Tutoring

In this study, we explored the impact of the decision agency (Student vs. Tutor) and granularity (Problem vs. Step) across students with different levels of incoming competence (High vs. Low). Students were randomly assigned to four conditions and split into High and Low groups based on their pre-test scores. All students used the same Intelligent Tutoring System (ITS) called Pyrenees, followed the same general procedure, studied the same training materials, and worked through the same training problems. The only substantive differences among the four conditions were decision agency and granularity. That is: who decided to present an example or to solve a problem: the student or the ITS tutor; and was the decision made problem-by-problem or step-by-step? Our overall results showed that there were significant different impacts of the decision agency and granularity between High and Low students on learning performance. More specifically, for High students granularity was the more dominant factor in that step level decisions can be more effective than problem level decisions regardless of the decision agency; for Low students there was a significant interaction effect in that: Low students benefit significantly more when they were making problem-level decisions than making step-level decisions, but no significant difference was not found when the decisions were made by the tutor. Much to our surprise, both High and Low groups showed strong decision-making preference for problem solving over worked example at both problem and step levels.