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Save the Dates

22st Annual OLC International Conference
November 16-18, 2016 | Orlando, Florida | Walt Disney World Swan/Dolphin Resort

OLC Innovate 2016 - Innovations in Blended and Online Learning
April 20-22, 2016 | New Orleans, LA | Sheraton New Orleans Hotel

Using Analytics to Inform "Tactical" Design Decisions

#Twitter: 
#blended20911
Presenter(s)
Hae Okimoto (University of Hawaii System, USA)
Casey Sacks (Colorado Community College System, USA)
Karen Swan (University of Illinois Springfield, USA)
Karen Vignare (UMUC, USA)
Session Information
July 8, 2014 - 1:00pm
Track: 
Institutional Leadership and Strategy
Areas of Special Interest: 
Institutional Initiatives
Major Emphasis of Presentation: 
Innovation and Experimentation
Institutional Level: 
Multiple Levels
Audience Level: 
All
Session Type: 
Information Session
Location: 
Governor's Square 15
Session Duration: 
50 Minutes
Session: 
Information Session 1
Virtual Session
Abstract

Engage in discussion with institutional representatives about how they are using the Predictive Analytics Reporting (PAR) Framework to inform tactical decision making concerning blended solutions.

Extended Abstract

Engage in a discussion with representatives of community college systems in Colorado and
Hawaii, University of Maryland University College, and the University of Illinois Springfield about how they are using the Predictive Analytics Reporting (PAR) Framework to inform their tactical decision making around course and program design, decision making which has led them to blended solutions.

The Predictive Analytics Reporting (PAR) Framework is a non-profit multi-institutional data mining collaborative that brings together 2 year, 4 year, public, proprietary, traditional, and progressive institutions to collaborate on identifying points of student loss and to find effective practices that improve student retention in U.S. higher education. With sixteen WCET member institutions, over 1,700,000 anonymized student records and 8,100,000 institutionally de-identified course level records, the PAR Framework offers educational stakeholders a unique multi-institutional lens for examining dimensions of student success from both unified and contextual perspectives.

The PAR Framework collaborators are also working on developing tools to support decision making at the local institutional level. These include: tools for identifying local predictors of retention and progression, tools for exploring institutional data, tools for benchmarking local retention and progression outcomes against other similar institutions along a variety of dimensions, and a tool for identifying and classifying interventions aimed at improving student success along two dimensions - predictors of retention and progression and time in students' academic life cycle.

What does all this data mean and how can it help with decisions around redesign? This session is for those interested in "tactical" redesign focused on blended solutions. We will discuss how data and analytics can be used in both a broad sweep at the program and course structural levels, as well as in the more detailed exploration of student behaviors and their impact within courses and programs. Audience participation will be encouraged.