Computerized learning environments can be characterized by the amount of learner control supported during the learning process. This dimension can be viewed as a continuum ranging from minimal (e.g., rote or didactic environments) to almost complete learner control (e.g., discovery environments). Two differing perspectives, representing the ends of this continuum, have arisen in response to the issue of the most optimal learning environment to build in intelligent tutoring systems (ITS). One approach is to develop an environment containing assorted tools and allow the learner freedom to explore and learn, unfettered (e.g., Collins & Brown, 1988; Shute, Glaser, & Raghavan, 1989; White & Horowitz, 1987). Advocates of an opposing perspective argue that it is more efficacious to develop straightforward learning environments that do not permit “garden path” digressions (e.g., Anderson, Boyle & Reiser, 1985; Corbett & Anderson, 1989; Sleeman, Kelly, Martinak, Ward, & Moore, 1989). This disparity between the positions becomes more complicated because the issue is not just which is the better learning environment; but rather, which is the better environment for what type(s) of persons, a classic aptitude-treatment interaction question (Cronbach & Snow, 1977).