SMART - STUDENT MODELING APPROACH FOR RESPONSIVE TUTORING

This paper describes a new student modeling paradigm called SMART. The premise is that a single, principled approach to student modeling, in volving both theoretical and empirical methods, can render automated i nstruction more efficacious across a broad array of instructional doma ins. After defining key terms and discussing limitations to previous s tudent modeling paradigms, I describe the SMART approach, as embedded within a statistics tutor called Stat Lady (Shute and Cluck, 1994). SM ART works in conjunction with a tutor design where low-level knowledge and skills (i.e., curricular elements) are identified and separated i nto three main outcome types. Throughout the tutor, curricular element s with values below a pre-set mastery criterion are instructed, evalua ted, and remediated, if necessary. The diagnostic part of the student model is driven by a series of regression equations based on the level of assistance the computer gives each person, per curriculum element. Remediation on a given element occurs when a subject fails to achieve mastery during assessment, which follows instruction. Remediation is precise because each element knows its location within the tutor where it is instructed and assessed. I end with a summary of results from t wo controlled evaluations of SMART examining the following research is sues: (a) diagnostic validity, (b) individual differences in learning from Stat Lady, (c) affective perceptions of the tutorial experience, and (d) contributions of mastery and remediation to learning outcome a nd efficiency. Comments about related and future research with this pa radigm are offered.