Learning Analytics with
28 August 2012
Blackboard
Dan Peters
dan.peters@blackboard.com
@danspeters
7 March 2013
“The Third Wave”
- Malcom Brown, Director of EDUCAUSE Learning Initiative
2
“The Third Wave”
- Malcom Brown, Director of EDUCAUSE Learning Initiative
Learning Management
System
2000
2005
2010
2015
3
“The Third Wave”
- Malcom Brown, Director of EDUCAUSE Learning Initiative
Web 2.0
Learning Management
System
2000
2005
2010
2015
4
“The Third Wave”
- Malcom Brown, Director of EDUCAUSE Learning Initiative
Web 2.0
Learning Management
System
2000
2005
2010
2015
5
“Academic Analytics”
• Refers to a collective set of “business
intelligence” activities to support the mission of
the institution
• Includes:
– Data warehousing
– Reporting
– Predictive modeling
• Modeling is based on program and population
specific factors designed to improve:
– Retention
– Performance
*Campbell, J. P., DeBlois, P. B., & Oblinger, D. G. (2007). Academic analytics:
A new tool for a new era. EDUCAUSE Review, 42 (4), 40-42
What Do We Need For Learning
Analytics?
• Data
• Predictive Modeling – (Questions and
Results)
• Reports/Views of Data
• Continual process
Best Practices
Defined Metrics
Business Rules
Derived Information
Where to Begin?
• Will data REALLY optimize educational
experience?
• Uncertainty about where to start
• No established industry best practice about what to measure
• No established industry best practice around methodology
• Organizational Culture, Learning Culture and
Status Quo
• Enterprise concern about what the data will show
• Competing priorities and lack of incentive for collaboration
between different groups
• Siloed data across the enterprise sure doesn’t help
- 2011 Online Educa Berlin, Ellen Wagner, Sage Road Solutions, LLC
Questions
• Are students engaged in their courses?
• How does level of activity influence grades?
• Can we identify and interact with “at-risk”
students before they fail?
• Can we motivate students through
comparison?
• What are the correlations between use of
certain LMS tools and student success?
• Are we meeting our adoption goals?
Data
Instructor
Attributes
User
Activity
Data
Course
Item
Data
Student
Attributes
Course
Attributes
Grade
Center
Results
Final
Grades
Enterprise Level Analyses
Trend Analyses
Metrics and Correlations
Student
System
Predictions
Predictions
Predictions
Predictions
Predictions
Views on Data
Dashboards
Reports
Dynamic Analysis
Information Needs Vary
But There Are Common Themes
On Demand
Easy to Access
and
Easy to Digest
DATA TO HELP ME
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About Blackboard Analytics for Learn:
www.blackboardanalytics.com
Improve decision making.
Improve institutional performance.