Progress in assessment and tutoring of lifelong learning skills: An intelligent tutor agent that helps students become better help seekers

Intelligent Tutoring Systems (ITSs) have been shown to enhance learning in a range of domains, including mathematics, physics, computer programming, electronics troubleshooting, database design, medical diagnosis, and others (Beal, Walles, Arroyo, & Woolf, 2007; Crowley et al., 2007; Gott & Lesgold, 2000; Graesser, Chipman, Haynes, & Olney, 2005; Koedinger & Aleven, 2007; Koedinger, Anderson, Hadley, & Mark, 1997; Martin & Mitrovic, 2002; Mitrovic et al., 2008; Mostow & Beck, 2007; Rickel & Johnson, 1999; VanLehn et al., 2005). In this chapter we take up the question whether ITSs can help learners foster lifelong learning skills. By this term we refer to skills and strategies that enable people to be effective learners in a range of domains. Domain-general learning skills are important “tools” for learners, because the formal schooling system cannot prepare students for all knowledge or skills they will ever need. Prior to the study reported in the current chapter, there was limited evidence that ITSs can support learners in acquiring lifelong learning skills. We feel we have interesting progress to report: We found evidence that an ITS can support students in becoming better at seeking help as they work with an ITS. Researchers have long studied the self-regulatory processes that effective learners exhibit in a range of learning environments, with and (primarily) without computers. This line of work has produced a number of comprehensive theoretical frameworks for self-regulated learning (Pintrich, 2004; Winne & Hadwin, 1998; Zimmerman, 2008). Other work has focused on creating instructional interventions that emphasize self-regulatory or metacognitive aspects of learning, including successful classroom programs for: learning to read with understanding through reciprocal teaching (Palincsar & Brown, 1984); self-assessment and classroom discussion thereof related to a science inquiry cycle (White & Frederiksen, 1998); using self-addressed metacognitive questions in the domain of mathematics learning (Mevarech & Fridkin, 2006); and reflecting on quiz feedback in college-level remedial mathematics (Zimmerman & Moylan, 2009).