Name
Title | ||
|---|---|---|
How Should Knowledge Composed of Schemas be Represented in Order to Optimize Student Model Accuracy? |
Abstract | ||
|---|---|---|
Most approaches to student modeling assume that students’ knowledge can be represented by a large set of knowledge components that are learned independently. Knowledge components typically represent fairly small pieces of knowledge. This seems to conflict with the literature on problem solving which suggests that expert knowledge is composed of large schemas. This study compared several domain models for knowledge that is arguably composed of schemas. The knowledge is used by students to construct system dynamics models with the Dragoon intelligent tutoring system. An evaluation with 52 students showed that a relative simple domain model, that assigned one KC to each schema and schema combination, sufficed and was more parsimonious than other domain models with similarly accurate predictions. |
Year | Venue | Field |
|---|---|---|
2018 | AIED | Intelligent tutoring system,Computer science,Artificial intelligence,System dynamics,Schema (psychology),Domain model,Machine learning |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
10 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sachin Grover | 1 | 14 | 2.70 |
| Jon Wetzel | 2 | 53 | 8.07 |
| Kurt VanLehn | 3 | 2352 | 417.44 |