url
	http://core.miserver.it.umich.edu/omeka-s/s/ire/item/4754
o:resource_class
	ire:JournalArticle
ire:id
	4J5PWYMF
ire:class
	ire:JournalArticle
ire:year
	2019
ire:author
	Zheng, Guoguo
	Fancsali, Stephen Edward
	Ritter, Steven
	Berman, Susan
ire:title
	Using Instruction-Embedded Formative Assessment to Predict State Summative Test Scores and Achievement Levels in Mathematics
ire:issn
	1929-7750
ire:doi
	10.18608/jla.2019.62.11
ire:url
	https://learning-analytics.info/index.php/JLA/article/view/6131 Open Access Journal Webpage (Journal of Learning Analytics)
ire:date
	2019
ire:dateAdded
	11/25/2022 15:38
ire:dateModified
	11/25/2022 15:38
ire:dateAccessed
	11/25/2022 15:38
ire:pages
	153-174
ire:issue
	2
ire:volume
	6
ire:language
	en
ire:rights
	Copyright (c) 2019 Journal of Learning Analytics
ire:catalog
	learning-analytics.info
ire:extra
	Number: 2
ire:attachFile
	C:\Users\huynh\Zotero\storage\4GZ44VYE\Zheng et al. - 2019 - Using Instruction-Embedded Formative Assessment to.pdf
ire:status
	Published Text
ire:genre
	Empirical
ire:keywords
	predictive modeling
	intelligent tutorial systems
	formative assessment
	mathematics education
	accountability, assessment
ire:resourceType
	Research/Scholarly Media
ire:inPublication
	Journal of Learning Analytics
ire:apa
	Zheng, G., Fancsali, S. E., Ritter, S., & Berman, S. (2019). Using Instruction-Embedded Formative Assessment to Predict State Summative Test Scores and Achievement Levels in Mathematics. Journal of Learning Analytics, 6(2), Article 2. https://doi.org/10.18608/jla.2019.62.11

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