Educational data mining methods for studying student behaviors minute by minute across an entire school year

In this talk, we discuss how educational data mining methods (cf. Baker & Yacef, 2009), conducted using log files of student use of Cognitive Tutor software for mathematics (Koedinger & Corbett, 2006), have significantly increased our scientific understanding of two behaviors that students engage in. The two behaviors studied are gaming the system and off-task behavior. Gaming the system is defined as attempting to succeed in an interactive learning environment by exploiting properties of the system rather than by learning the material (cf. Baker, Corbett, Koedinger, & Wagner, 2004). Examples of gaming within Cognitive Tutors include systematically guessing or abusing hints. Beyond Cognitive Tutors, gaming the system has been observed in assessment software (Walonoski & Heffernan, 2006), graded-participation newsgroups (Cheng & Vassileva, 2005), and educational games (Miller, Lehman, & Koedinger, 1999; Rodrigo et al, 2007). Off-task behavior (engaging in behavior that does not involve the system or the learning task) has been shown to occur with comparable frequency in Cognitive Tutors and traditional classrooms (cf. Baker et al, 2004). Both off-task behavior and gaming the system have been shown to be associated with poorer learning in Cognitive Tutors (Baker et al, 2004; Baker, 2007).