tools first year results - university of cincinnati · 2020. 7. 21. · michelle ford | elearning...

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Michelle Ford | eLearning Analytics | University of Cincinnati Project Overview Institutional research manages, analyzes, and reports much data for an institution, but there is a wealth of data that usually goes untouched in higher education: data from learning technologies. The University of Cincinnati created the eLearning Analytics department to address the need for managing, analyzing, and reporting data related to student behavior during a course, through the LMS and other eLearning tool data. During the first year, the team focused on benchmarking the current state of eLearning at the University. During this next year, the team is focusing on operationalizing benchmarking processes and implementing learning analytics capabilities. Long-term Vision Self-service Tableau Dashboards To provide descriptive, diagnostic, and (limited) predictive analytics Research and Analysis To provide complex predictive and prescriptive analytics for action recommendations to support eLearning Strategic Initiatives Machine Learning To provide students, faculty, and staff individualized recommendations within Canopy portal What does it take? Tools Data Sources Data Architecture First Year Results Next Steps Reorganize department Refine dashboards for different audiences Standardize appearance of dashboards Analyze & present findings Real-time analytics Contact Information Email: [email protected] Phone: 513-556-2708 Tableau Public: https://public.tableau.com/profile/michelle.ford Professional Portfolio: https://michellerford.wordpress.com LinkedIn: https://LinkedIn.com/in/michellerford Twitter: @StatsN3rdGirl eLearning Analytics @ UC: http://www.uc.edu/provost/initiatives/elearning/ analytics/elearning-analytics.html Data Storage MS Excel MS Access Text/CSV files SQL Data Lake Data Blending Excel, Access, Tableau, R Rapid Insight Veera Data Visualization & Analytics Tableau SAS R Analyze Load Transform Extract PeopleSoft (SIS) Blackboard (LMS) SAP (HR and Financial data) Echo360 (ALP) Kaltura (Video repository) WebEx (Video conferencing) VitalSource (eTextbook) Starfish (Early alert) Footprints & SmartView (Learning Tech Support) SurveyMonkey & Qualtrics SharePoint (Knowledge Base) Misc. spreadsheets & databases Data Engineer for data wrangling Data blending tool (or SQL server) for transform ation and loading of data Data lake for a data storage place Data Analyst to analyze data and communic ate findings BI Specialist to visualize data Published 77 dashboards using a total of 25+ data sources Obtained RapidInsight Veera for data blending Honorable mention in IMS Global Learning Impact Award Insight into historical eLearning Tool usage Improved information surrounding learning technology support

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Page 1: Tools First Year Results - University of Cincinnati · 2020. 7. 21. · Michelle Ford | eLearning Analytics | University of Cincinnati Project Overview Institutional research manages,

Michelle Ford | eLearning Analytics | University of Cincinnati

Project OverviewInstitutional research manages, analyzes, and reports much data for an institution, but there is a wealth of data that usually goes untouched in higher education: data from learning technologies.The University of Cincinnati created the eLearning Analytics department to address the need for managing, analyzing, and reporting data related to student behavior during a course, through the LMS and other eLearning tool data. During the first year, the team focused on benchmarking the current state of eLearning at the University. During this next year, the team is focusing on operationalizing benchmarking processes and implementing learning analytics capabilities.

Long-term Vision

Self-service Tableau Dashboards

To provide descriptive, diagnostic, and (limited) predictive analytics

Research and Analysis

To provide complex predictive and prescriptive analytics for action recommendations to support eLearning Strategic Initiatives

Machine Learning

To provide students, faculty, and staff individualized recommendations within Canopy portal

What does it take?

Tools

Data Sources

Data Architecture

First Year Results

Next Steps

Reorganize department

Refine dashboards for different audiences

Standardize appearance

of dashboards

Analyze & present findings

Real-time analytics

Contact Information• Email: [email protected]• Phone: 513-556-2708• Tableau Public:

https://public.tableau.com/profile/michelle.ford• Professional Portfolio:

https://michellerford.wordpress.com• LinkedIn: https://LinkedIn.com/in/michellerford• Twitter: @StatsN3rdGirl• eLearning Analytics @ UC:

http://www.uc.edu/provost/initiatives/elearning/analytics/elearning-analytics.html

Data

Sto

rage

MS ExcelMS AccessText/CSV filesSQL Data Lake Da

ta B

lend

ing

Excel, Access, Tableau, RRapid Insight Veera

Data

Vi

sual

izatio

n &

An

alyt

ics

TableauSASR

Analyze

Load

Transform

Extract

PeopleSoft (SIS) Blackboard (LMS) SAP (HR and Financial data)

Echo360 (ALP) Kaltura (Video repository)

WebEx (Video conferencing)

VitalSource (eTextbook)

Starfish (Early alert)

Footprints & SmartView (Learning

Tech Support)

SurveyMonkey & Qualtrics

SharePoint (Knowledge Base)

Misc. spreadsheets & databases

Data Engineer for data

wrangling

Data blending tool (or

SQL server) for transformation and loading of

data

Data lake for a data storage

place

Data Analyst to

analyzedata and

communicate

findings

BI Specialist

to visualize

data

Published 77 dashboards using a total of 25+ data sources

Obtained RapidInsight Veera for data blending

Honorable mention in IMS Global Learning Impact Award

Insight into historical eLearning Tool usage

Improved information surrounding learning technology support