Practical Measurement and Productive Persistence: Strategies for Using Digital Learning System Data to Drive Improvement
Item
Title
Practical Measurement and Productive Persistence: Strategies for Using Digital Learning System Data to Drive Improvement
Abstract/Description
This paper outlines the development of practical measures of productive persistence using digital learning system data. Practical measurement refers to data collection and analysis approaches originating from improvement science, and productive persistence refers to the combination of academic and social mindsets as well as learning behaviors that are important drivers of student success within the Carnegie Foundation for the Advancement of Teaching’s Community College Pathways Network Improvement Community. Strategies for operationalizing noncognitive factors using learning system data as well as approaches for using them as improvement measures are described.
Author/creator
Date
In publication
Volume
3
Issue
2
Pages
116-138
Resource type
Research/Scholarly Media
Resource status/form
Published Text
Scholarship genre
Empirical
Open access/full-text available
Yes
Peer reviewed
Yes
ISSN
1929-7750
Citation
Krumm, A. E., Beattie, R., Takahashi, S., D’Angelo, C., Feng, M., & Cheng, B. (2016). Practical Measurement and Productive Persistence: Strategies for Using Digital Learning System Data to Drive Improvement. Journal of Learning Analytics, 3(2), Article 2. https://doi.org/10.18608/jla.2016.32.6
Rights
Copyright (c) 2016 Journal of Learning Analytics
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