Difference between revisions of "Short-term Performance and Learning Gains Prediction"
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Ogan et al. (2015) [https://link.springer.com/content/pdf/10.1007/s40593-014-0034-8.pdf pdf] | Ogan et al. (2015) [https://link.springer.com/content/pdf/10.1007/s40593-014-0034-8.pdf pdf] | ||
*Multi-national | *Multi-national models predicting learning gains from student's help-seeking behavior | ||
* | *Models built on only U.S.or combined data sets performed extremely poorly for Costa Rica | ||
*U.S. model | *Models performed better when built on and applied for the dataset, except for Philippines which was outperformed slightly by U.S. model | ||
Revision as of 06:22, 18 May 2022
Ogan et al. (2015) pdf
- Multi-national models predicting learning gains from student's help-seeking behavior
- Models built on only U.S.or combined data sets performed extremely poorly for Costa Rica
- Models performed better when built on and applied for the dataset, except for Philippines which was outperformed slightly by U.S. model
Yudelson et al. (2014) pdf
- Models discovering generalizable sub-populations of students across different schools to predict students' learning with Carnegie Learning’s Cognitive Tutor (CLCT)
- Models trained on schools with a high proportion of low-SES student performed worse than those trained with medium or low proportion
- Models trained on schools with low, medium proportion of SES students performed similarly well for schools with high proportions of low-SES students