2024-08-09-luzan24a.md

title	booktitle	year	abstract	layout	series	publisher	issn	id	month	tex_title	firstpage	lastpage	page	order	cycles	bibtex_author	author	date	address	container-title	volume	genre	issued	pdf	extras
Evaluation of the Instance Weighting Strategy for Transfer Learning of Educational Predictive Models	Proceedings of the 2024 AAAI Conference on Artificial Intelligence	2023	This work contributes to our understanding of how transfer learning can be used to improve educational predictive models across higher institution units. Specifically, we provide an empirical evaluation of the instance weighting strategy for transfer learning, whereby a model created from a source institution is modified based on the distribution characteristics of the target institution. In this work we demonstrated that this increases overall model goodness-of-fit, increases the goodness-of-fit for each demographic group considered, and reduces disparity between demographic groups when we consider a simulated institutional intervention that can only be deployed to 10% of the student body.	inproceedings	Proceedings of Machine Learning Research	PMLR	2640-3498	luzan24a	0	Evaluation of the Instance Weighting Strategy for Transfer Learning of Educational Predictive Models	19	28	19-28	19	false	Luzan, Mariia and Brooks, Christopher	given family Mariia Luzan given family Christopher Brooks	2024-08-09		Proceedings of the 2024 AAAI Conference on Artificial Intelligence	257	inproceedings	date-parts 2024 8 9	https://raw.githubusercontent.com/mlresearch/v257/main/assets/luzan24a/luzan24a.pdf