url
	http://core.miserver.it.umich.edu/omeka-s/s/ire/item/4734
o:resource_class
	ire:ConferencePaper
ire:id
	PUIE5MQD
ire:class
	ire:ConferencePaper
ire:year
	2014
ire:author
	Piety, Philip J.
	Hickey, Daniel T.
	Bishop, M. J.
ire:title
	Educational Data Sciences: Framing Emergent Practices for Analytics of Learning, Organizations, and Systems
ire:isbn
	978-1-4503-2664-3
ire:doi
	https://doi.org/10.1145/2567574.2567582 10.1145/2567574.2567582
ire:url
	https://doi.org/10.1145/2567574.2567582 Official Publisher's Webpage (ACM Digital Library)
	https://www.researchgate.net/publication/262242184_Educational_data_sciences_-_Framing_emergent_practices_for_analytics_of_learning_organizations_and_systems Full-text PDF Shared by Author (ResearchGate)
ire:date
	2014
ire:dateAdded
	11/25/2022 1:21
ire:dateModified
	11/25/2022 1:21
ire:dateAccessed
	11/24/2022
ire:pages
	193–202
ire:shortTitle
	Educational data sciences
ire:series
	LAK '14
ire:publisher
	Association for Computing Machinery
ire:place
	New York, NY, USA
ire:catalog
	ACM Digital Library
ire:status
	Published Text
ire:genre
	Theoretical
ire:peer
	No
ire:keywords
	analytic approaches
	big data
	data-driven decisions
	educational data mining
	educational data science
	learner analytics
	learning analytics
	methods
	theories and theoretical concepts for understanding learning
	tools for sense-making in learning analytics
ire:resourceType
	Research/Scholarly Media
ire:inPublication
	Proceedings of the Fourth International Conference on Learning Analytics And Knowledge
ire:apa
	Piety, P. J., Hickey, D. T., & Bishop, M. J. (2014). Educational data sciences: Framing emergent practices for analytics of learning, organizations, and systems. Proceedings of the Fourth International Conference on Learning Analytics And Knowledge, 193–202. https://doi.org/10.1145/2567574.2567582
ire:openAccess
	Yes

--