Does supporting multiple student strategies lead to greater learning and motivation? Investigating a source of complexity in the architecture of intelligent tutoring systems

Intelligent tutoring systems (ITS) support students in learning a complex problem-solving skill. One feature that makes an ITS architecturally complex, and hard to build, is support for strategy freedom, that is, the ability to let students pursue multiple solution strategies within a given problem. But does greater freedom mean that students learn more robustly? We developed three versions of the same ITS for solving linear algebraic equations that differed only in the amount of freedom given to students. One condition required students to strictly adhere to a standard strategy, the other two allowed minor and major variations, respectively. We conducted a study in two US middle schools with 57 students in grades 7 and 8. Overall, students' algebra skills improved. Contrary to our hypotheses, the amount of freedom offered by the system did not affect students' learning outcomes, nor did if affect their intrinsic motivation. Students tended to use only the standard strategy and its minor variations. Thus, the study suggests that in the early stages of problem-solving practice within a complex domain, an ITS should allow at least a small amount of freedom, validating, albeit to a limited degree, one source of complexity in ITS architectures. To help students develop strategic flexibility, a desirable outcome in many domains, more is needed than letting students chose their own solution strategy within a given problem. (C) 2012 Elsevier Ltd. All rights reserved