Student Modeling Jan 30, 2006

Student Model Current state of knowledge Diagnosis: inferring a student model Student Modeling Problem: –Data: model, Process: diagnosis Not a simple input-output problem`

Uses of student models Advancement Offering unsolicited advice - “coach” Problem generation Adapting explanations

Three-D Space of Models Bandwidth –Mental (high), Intermediate, Final (low) Type of Knowledge Representation –Procedural: Flat vs. Hierarchical –Declarative Differences in Student/Expert Models –Overlays, Bugs & Bug-part Libraries

Bandwidth Amount and quality of information Three levels: –Mental states (approximate) –Intermediate states –Final states

Knowledge types Procedural –More direct solutions Declarative –Survey of all knowledge Continuum of solutions between 2 types Student models use a combination to solve problems like students

Knowledge Base Problem Solution Knowledge Base Problem Solution Interpretation Diagnosis

Student & Expert Models Two types of differences: –Misconceptions & missing conceptions Overlays: Only misconceptions Bug libraries: –Catalog of missing conceptions Bug-part libraries –Smaller catalog

Diagnostic Techniques 9 types –Model tracing –Path finding –Condition Induction –Plan recognition –Issue tracing –Expert systems –Decision trees –Generate and test –Interactive diagnosis

2 reasons intractable: –Preconceptions about role of student models –Theoretical and practical difficulties in building and using student models Bypassing the intractable problem of student modeling

Avoid guessing - build it in Don’t diagnose what you can’t treat Empathize with student’s beliefs, don’t label them as bugs Don’t feign omniscience - adopt a “fallible collaborator” role 4 slogans