Name
Abstract | ||
|---|---|---|
We describe a methodology for simulating student behavior to predict the effects of skill-learning parameter changes on system behavior Validation against data collected after the changes were made shows that accurate predictions can be made despite a different cohort of students Furthermore, deviations from the predictions may help explain unexpected effects of other changes made to the tutoring system. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-13437-1_51 | Intelligent Tutoring Systems (2) |
Keywords | Field | DocType |
simulating student behavior,skill model change,accurate prediction,tutoring system,parameter change,student progress,system behavior validation,unexpected effect,different cohort,simulation model,data mining,data collection | Data science,Computer science,Artificial intelligence,Cohort,Machine learning | Conference |
Volume | ISSN | ISBN |
6095 | 0302-9743 | 3-642-13436-X |
Citations | PageRank | References |
1 | 0.40 | 3 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniel Dickison | 1 | 31 | 3.66 |
| Steven Ritter | 2 | 205 | 36.18 |
| Tristan Nixon | 3 | 136 | 14.44 |
| Thomas K. Harris | 4 | 257 | 21.93 |
| Brendon Towle | 5 | 57 | 8.38 |
| R. Charles Murray | 6 | 156 | 23.25 |
| Robert G. M. Hausmann | 7 | 75 | 12.13 |