Baker - Closing the Loop

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Using educational data mining to design tutor lessons that students don’t choose to game: “Closing the loop”

Summary Table

Study 1

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) 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

Gaming the system

Hypotheses

H1
H2
H3
H4

Independent Variables

Dependent Variables

Planned Experiments

Explanation

Further Information

Connections

Annotated Bibliography

References

Future Plans