Recent Advances in Conversational Intelligent Tutoring Systems

摘要

The vision of one-on-one human tutoring being the most effective solution to instruction and learning has attracted the attention of many for decades. Encouraged by the effectiveness of one-on-one human tutoring (Bloom 1984), computer tutors that mimic human tutors have been successfully built with the hope that a computer tutor could be available to every child with access to a computer. An extensive review of tutoring research by VanLehn (2011) showed that computer tutors are as effective as human tutors. VanLehn reviewed studies published between 1975 and 2010 that compared the effectiveness of human tutoring, computer-based tutoring, and no tutoring. The conclusion was that the effectiveness of human tutoring is not as high as it was originally believed (effect size d = 2.0) but much lower (d = 0.79). The effectiveness of computer tutors (d = 0.78) was found to be as high as the effectiveness of human tutors. So, there is something about the one-on-one connection that is critical, whether the student communicates with humans or computers. Graesser, Person, and Magliano (1995) argued that the remedial part of tutorial interaction in which tutor and tutee collaboratively improve an initial answer to a problem is the primary advantage of tutoring over classroom instruction. Chi, Siler, and Jeong (2004) advanced a related hypothesis: tutoring enhances students' capacity to reflect iteratively and actively on domain knowledge. Furthermore, one-on-one instruction has the advantage of engaging most students' attention and interest as opposed to other forms of instruction such as lecturing or monologue in which the student may or may not choose to pay attention (VanLehn et al. 2007).