Baker - Closing the Loop
Using educational data mining to design tutor lessons that students don’t choose to game: “Closing the loop”
Summary Table
| PIs | Ryan Baker |
| Other Contributers | |
| Study Start Date | Spring, 2010 |
| Study End Date | |
| LearnLab Site | TBD |
| LearnLab Course | Algebra |
| Number of Students | TBD |
| Total Participant Hours | TBD |
| DataShop | TBD |
Abstract
This 12 month CMDM project proposes to “close the loop” on a data mining analysis previously conducted within the PSLC (Baker_Choices_in_LE_Space), showing that the previous analysis makes a contribution to improving student learning in in-vivo settings. In that previous study, a model of the differences between different tutor lessons (the Cognitive Tutor Lesson Variation Space, or the CTLVS1 -- full details on this model are given on the page Baker_Choices_in_LE_Space) was created, and used to study why some tutor lessons are gamed more than others in the Algebra tutor. The best model based on the CTLVS1 (developed via a combination of PCA and correlation mining) predicted over half of the variance in gaming, almost 6 times better than any previous model attempting to explain gaming through specific student individual differences.
In this study, we will choose a lesson from the Algebra tutor that is highly gamed, and modify it in accordance with the findings of that previous work, such that the modified lesson is predicted to lead to significantly less gaming.
Background & Significance
Glossary
Computational Modeling and Data Mining
Hypotheses
- H1
- H2
- H3
- H4
