Constructing Knowledge from Dialog in an Intelligent Tutoring System: Interactive Learning, Vicarious Learning, and Pedagogical Agents

College students either interacted directly with an intelligent tutoring system, called AutoTutor, by contributing to mixed initiative dialog, or they simply observed, as vicarious learners, previously recorded interactive sessions. The mean pretest to posttest effect size (Cohen's d) across two studies was 1.86 in the interactive conditions and 1.12 in standard vicarious conditions. In Experiment 1, redundant onscreen printed text produced an effect size of 0.43, but the difference was not significant. In addition, the image of a talking head presenting AutoTutor's contributions to the dialog while displaying facial expressions, gestures, and gaze did not produce learning gains beyond those produced by the voice alone. In Experiment 2, the effect size was 0.71 when interactive tutoring was contrasted with the standard vicarious condition, but only 0.38 when compared to a collaborative vicarious condition. ********** Recent advances in educational technology, particularly computer-based courses (Anderson, Corbett, Koedinger, & Pelletier, 1995; Mayer, 2001), and distance learning (Barker & Dickson, 1996; Bourdeau & Bates, 1997; Moore & Kearsley, 1996; Roblyer & Edwards, 2000; Renwick, 1996; Spector, 2001), have created situations where learners are more and more likely to find themselves trying to gain knowledge in settings in which they are observers (Cox, Mckendree, Tobin, Lee, & Mayes, 1999; Fox Tree, 1999; Schober & Clark, 1989), rather than active participants. These advances have created a need for further empirical understanding of the conditions that promote learning among relatively isolated observers (e.g., Lee, Dineen, & McKendree, 1998; McKendree, Stenning, Mayes, Lee, & Cox, 1998). Little is currently known about how much is acquired by observers when compared to active participants in multimedia educational environments that are designed to promote learning (Mayer, 2001; Sweller, 1999; Wittrock, 1990). To address this issue, the present research was designed, in part, to contrast the relative learning gains of observers (i.e., vicarious learners) when compared to active participants in the learning process (Bandura, 1977; Lee et al., 1998; McKendree et al., 1998). Historically, the term vicarious learning was frequently used synonymously with observational learning, social learning, or modeling (Bandura, 1962; Rosenthal & Zimmerman, 1978). According to this perspective, by simply observing activities carried out by others, learners can master those activities without overt practice or direct incentives (Rosenthal & Zimmerman, 1978, p.xi). In two experiments, learners either interacted directly with an intelligent tutoring system (ITS), called AutoTutor (Graesser, Wiemer-Hastings, Wiemer-Hastings, Kreuz, & TRG, 1999), or they simply observed an interactive sessions. Experiment 2 also included a collaborative vicarious-learning condition. CONSTRUCTIVISM AND INTERACTIVE LEARNING According to constructivism, learners actively create meaning and knowledge by interacting with people and other objects. Rather than simply delivering information, learning environments should stimulate the learner to actively construct knowledge and provide feedback on the constructions. In the context of an ITS, knowledge construction is viewed as a sense-making activity in which the learner attempts to build a coherent representation of the tutorial contents and integrate it with existing knowledge (Graesser et al., 1999; Wittrock, 1974, 1990). Research supporting the epistemological stance of constructivist approaches to learning (Biggs, 1996; Bransford, Goldman, & Vye, 1991; Brown, 1988; Chi, deLeeuw, Chiu, & LaVancher, 1994; Derry, 1996; Mayer, 1997; Moshman, 1982; Palincsar & Brown, 1984; Papert, 1980; Piaget, 1952; Pressley & Wharton-McDonald, 1997; Rogoff, 1990; VanLehn, Jones, & Chi, 1992; Vygotsky, 1978) has a long history in psychology and education. …