working with learning analytics (259000506)
DESCRIPTION
TED-Style PresentationDifferences among Institutional Faculty and Staff in Learning Analytics Readiness LevelsKimberly Arnold, Senior Evaluation Consultant, University of Wisconsin-MadisonSteven Lonn, Assistant Director, USE Lab and Learning Analytics Specialist, University of Michigan-Ann ArborThe Learning Analytics Readiness Instrument (LARI) was developed with the idea that institutions need in-depth information to aid in the implementation of learning analytics. During data collection for the beta version of the LARI, over 300 responses were received from 23 diverse institutions. This presentation will focus on the differences observed between various classifications of faculty and staff completing the LARI both within and across institutions when examining readiness for systemic learning analytics initiatives. Participants will be able to add their own insight to the findings, as well as discuss their own challenges with learning analytics readiness.OUTCOMES: Understand the underpinnings of the LARI * Recognize the components constituting readiness for learning analytics * Learn about differences in responses from various respondents and institutions * Identify challenges and weaknesses to implementation at your own campus Creating a Framework for an Institutional, Data-Driven Approach to Student SuccessBeth Mulherrin, Assistant Dean, Undergraduate Initiatives, University of Maryland University CollegeJack Neill, Senior Director, Data Analysis, Undergraduate Initiatives, University of Maryland University CollegeAnalytic tools such as predictive models, early alert systems, and dashboards require an integrated approach to maximize institutional impact. Disparate initiatives and data sources within an institution can make it challenging to systematically evaluate and understand the impact of various efforts to improve student success. University of Maryland University College (UMUC) is creating an institutional approach to organizing, implementing, and evaluating student support services and interventions to improve outcomes. Learn how UMUC is tackling this challenge by developing a common data framework for identifying at-risk students, coordinating intervention efforts, and systematically evaluating initiatives. OUTCOMES: Learn about various analytic tools and strategies for evaluating student success initiatives * Determine pathways for creating an integrated, data-driven approach to student success at your institution * Evaluate your institutional capacity to leverage analytic tools in a holistic way http://www.educause.edu/events/eli-virtual-annual-meeting-2015/2015/working-learning-analyticsTRANSCRIPT
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Differences among Institutional
Faculty and Staff in Learning
Analytics Readiness Levels
Kimberly Arnold, University of Wisconsin-Madison Steven Lonn, University of Michigan Additional contributions by: Mathew Pistilli, Indiana University-Purdue University Indianapolis Meghan Oster, University of Michigan
#ELI2015 @kimberlyarnold @stevelonn
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Poll
How is your institution pursuing learning analytics?
Were not currently pursuing learning analytics
Were doing some exploration, but were still planning
Were engaged in early pilots
Were trying to scale learning analytics
Were providing production level learning analytics
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What is LARI?
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Sheila MacNeill https://farm6.staticflickr.com/5476/14177301945_0b1720bb70_s.jpg
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https://www.flickr.com/photos/zaxl4/16950197 https://www.flickr.com/photos/theenmoy/14775357265
Framework for Development
http://fc04.deviantart.net/fs70/i/2012/097/5/f/innovative_cube_by_killbash-d4vaq20.jpg
Parsimony Practicality Proactive
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http://upload.wikimedia.org/wikipedia/commons/5/59/US_Navy_090718-N-4928B-058_Hospital_Corpsman_1st_Class_Edward_Hourican,_assigned_to_Naval_Mobile_Construction_Battalion_(NMCB)_40,_fastens_a_sheet_of_plywood.jpg
http://upload.wikimedia.org/wikipedia/commons/f/f0/DARPA_Big_Data.jpg
http://upload.wikimedia.org/wikipedia/commons/b/b4/CTA_loop_junction.jpg
http://pixabay.com/static/uploads/photo/2014/11/04/08/07/mark-516277_640.jpg
https://www.flickr.com/photos/batega/2056949264/
Ability
Data
Governance / Infrastructure
Culture / Process
Overall Readiness
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Who Participated?
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Beta Participants
Assoc/Pub-R-L, Bac/A&S,& Bac/Diverse
Masters Large & Research Universities (High Research Activity)
Research Universities(Very High ResearchActivity)
5 institutions 129 respondents
15 institutions 337 respondents
4 institutions 84 respondents
#ELI2015 @kimberlyarnold @stevelonn
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Results
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Poll
Which domain of the LARI is rated highest across all
institution types?
Ability
Data
Governance/Infrastructure
Culture/process
Overall Readiness Perception
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Overall Averages by Domain
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Overall Averages by Domain and Institution Type (n=550)
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Role Analysis by Domain
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Role Analysis by Domain
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Role Analysis by Institution Type by Domain
#ELI2015 @kimberlyarnold @stevelonn
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Role Analysis by Institution Type by Domain
#ELI2015 @kimberlyarnold @stevelonn
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Role Analysis by Institution Type by Domain
#ELI2015 @kimberlyarnold @stevelonn
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Takeaways
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Takeaways
No beta institution is at an optimal level of readiness
for enterprise learning analytics
Data highest perceived domain overall
Culture / Process and Overall Readiness
Perceptions lowest perceived domains overall
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Perceptions strongly related to institutional type
Role type is fairly consistent regardless of institution
type
IT has a more favorable view of some domains
than Deans / Faculty
Institution type drives readiness perceptions more
than role
#ELI2015 @kimberlyarnold @stevelonn
Takeaways
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[email protected] [email protected] https://sites.google.com/a/umich.edu/lari/
#ELI2015 @kimberlyarnold @stevelonn