@article{jayaprakash_early_2014,
	title = {Early {Alert} of {Academically} {At}-{Risk} {Students}: {An} {Open} {Source} {Analytics} {Initiative}},
	volume = {1},
	issn = {1929-7750},
	shorttitle = {Early {Alert} of {Academically} {At}-{Risk} {Students}},
	url = {https://eric.ed.gov/?id=EJ1127037},
	abstract = {The Open Academic Analytics Initiative (OAAI) is a collaborative, multi-year grant program aimed at researching issues related to the scaling up of learning analytics technologies and solutions across all of higher education. The paper describes the goals and objectives of the OAAI, depicts the process and challenges of collecting, organizing and mining student data to predict academic risk, and report results on the predictive performance of those models, their portability across pilot programs at partner institutions, and the results of interventions on at-risk students.},
	language = {en},
	number = {1},
	urldate = {2020-05-26},
	journal = {Journal of Learning Analytics},
	author = {Jayaprakash, Sandeep M. and Moody, Erik W. and Lauría, Eitel J. M. and Regan, James R. and Baron, Joshua D.},
	year = {2014},
	note = {Publisher: Society for Learning Analytics Research},
	pages = {6--47},
}

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