Advancing the
Completion Agenda
Improving Gateway Courses
with Analytics
Chad Brown, Ph.D.
Provost & Exec. Vice President
Zane State College
Andrew K. Koch, Ph.D.
Executive Vice President
John N. Gardner Institute
James Willis, Ph.D.
Educational Assessment Specialist
Purdue University
Session Overview
• The problem
• Gateway course data – What we have learned
– Foundations of Excellence® institutions
– The Toolbox and The Toolbox Revisited
– Some Anecdotal Reasons for High DFWI Rates
•
•
•
•
Learner analytics overview
Zane State College – A Case Study
The Gateways to Completion Pilot Effort
Questions & discussion
Gateway “Killer” Courses
• Courses with high rates of unsuccessful
outcomes (DFWI rates)
– Courses with DFWI rates of 30% or higher
– These courses “kill” a student’s GPA, motivation,
academic progress, etc.
– Serve as “gatekeeper” to further study and
degree completion
What is your institution’s definition?
It’s about . . .
Why
Addressing
Gateway
Course
Performance
Matters
• Teaching
• Learning
• Student Support
• Student Performance
It’s also about . . .
Why
Addressing
Gateway
Course
Performance
Matters
• Institutional Performance
– Performance-Based Funding
• National Well Being
– The Completion Agenda
Why else does it matter to you?
Foundations of Excellence®
(FoE) Institutions
Focus: The institution
Unit of Analysis: The entire first year
Method: Nine Dimensions
Application: Of data to action
Results: Retention and revenue gains (IPEDS data)
Foundations of Excellence Institutions: 2003-2013
(C) John N. Gardner Institute for
• FoE institutions identified
High
Enrollment
Courses
and DFWI
Rates
– the 5 courses with the highest
enrollment of new students
– the number of new students
enrolled in those courses &
– the number new students who
receive a D, F, W, or I
• Rate calculated from
these numbers
High Enrollment Courses by DFWI Rates
for 2-Year Institutions
Field
Math – developmental
Math – college level
English – developmental
History
Sociology
Computer
PE / Health
English – college level
Political Science
Psychology
Biology
FYS/ Success
Speech
Number of Courses
DFWI Rate
71
12
25
12
14
26
3
82
7
46
8
21
19
46
42
41
39
37
35
35
35
32
32
31
29
25
High Enrollment Courses by DFWI Rates
for 4-Year Institutions
Field
Economics
Accounting/Finance
Math – developmental
Math – college level
History
Biology
Psychology
Chemistry
Political Science
Philosophy
Fine Arts
Sociology
English – college level
Computer
Health/PE
Speech
FYS/ success
Religion
Number of Courses
4
3
23
48
21
18
51
7
9
7
5
20
105
8
12
26
30
6
DFWI Rate
46
43
40
38
30
29
27
26
25
24
23
22
21
20
19
18
15
9
Percentage of High Enrollment Courses
that Are High Risk
Percent of Courses with DFWI rate of 30% or More
Academic Year
2-Year Institutions
4-Year Institutions
2004-2005
70%
32%
2005-2006
69%
30%
2006-2007
80%
36%
2007-2008
62%
25%
2008-2009
63%
51%
2009-2010
71%
27%
Overall
70%
32%
Answers in the Toolbox
Academic Intensity, Attendance
Patterns,
and Bachelor’s Degree Attainment
By Clifford Adelman
Some
Anecdotal
Reasons for
High DFWI
Rates
• Lack of institutional
identification of courses
• Students lack of academic
preparation (especially in mathematics)
• Inadequate or nonexistent
placement procedures
• Late enrollment; missed
classes
• Faculty grading pattern; lack of
early feedback
• Lack of institutional action/plan
Challenge: How do you find the student at risk?
http://www.youthareawesome.com/wp-content/uploads/2010/10/wheres-waldo1.jpg
Challenge: How do you find the student at risk?
http://www.youthareawesome.com/wp-content/uploads/2010/10/wheres-waldo1.jpg
Effective use, best practices, what we know…
Interventions – Analytics is the
tool for Actionable intelligence
Discussing interventions
Data driven best practices
• Faculty involvement
– Timing
– Early
– Frequent
• Up-to-date (cumulative)
Message Content
• Efficacy research
– Alter the messages
– Provide
• Facts
• Advice
– Demonstrate concern
– Keep them short
– Make them relevant to current course activities
Institutional Challenge
• Data in many places, “owned” by many
people/organizations
• Different processes, procedures, and regulations
depending on data owner
• Everyone can see potential, but all want
something slightly different
• Sustainability
– “Can’t you just…”
– “Can’t s/he just…”
• Faculty participation is essential
Myths of Analytics:
Analytics is...
• a solitary process
• a complex set of
algorithms that no one
understands
• a process that doesn’t
include students
• just a fad. Institutions
can ignore using data
to make decisions.
Analytics is
about...
• Actionable intelligence
• Moving research to practice
• Basis for design, pedagogy,
self-awareness
• Changing institutional culture
• Understanding the limitations
and risks
New
Possibilities
• Using data that exists on
campus
• Taking advantages of existing
programs
• Bringing a “complete picture”
beyond academics
• Focusing on the “action” in
“actionable intelligence”
Navigating the Data!
Creating Synergies ~
Improving Success
• Using Analytics to:
– Support the College’s Strategic Plan
– Advance Assessment of Student Learning Outcomes
– Advance the Student Success Initiative
Guiding
Principles
•
•
•
•
•
Access
Quality
Image
Stewardship
Climate
Creating Synergies ~
Improving Success
• Using Analytics to:
– Support the College’s Strategic Plan
– Advance Assessment of Student Learning
Outcomes
– Advance the Student Success Initiative
Assessing
SLO’s
•
•
•
•
Accessible
Meaningful
Relational
Timely
Creating Synergies ~
Improving Success
• Using Analytics to:
– Support the College’s Strategic Plan
– Advance Assessment of Student Learning Outcomes
– Advance the Student Success Initiative
Student
Success
•
•
•
•
•
•
Early Intervention
Clear Feedback
Accountability
Faculty Engagement
Student Engagement
Peer Benchmarking
Building on the past
Summing Up
Success in gateway courses is about:
• Student excellence
• Institutional excellence
• Society at-large
– Enfranchisement
– Social mobility
– Social justice
• National economic competitiveness
• National Completion Agenda
Some
Anecdotal
Reasons for
High DFWI
Rates
• Lack of institutional identification
of courses
• Students lack of academic
preparation (especially in mathematics)
• Inadequate or nonexistent
placement procedures
• Late enrollment; missed classes
• Faculty grading pattern; lack of
early feedback
• Lack of institutional action/plan
A Logical Extension of Our Work
TM
TM
The Proposed Solution
TM
TM
What is G2C?





Action Planning
Data-Based Decision Making
Quality Improvement
Ongoing (Three-Year)
More Than Tech Tools
 Links Strategic Planning,
Continuous Quality
Improvement, and Predictive
Analytics
 Local, Regional, and National
We Need You
The G2C Pilot
How do I Learn More?
Upcoming
Information
Webinars
 March 14, 2013, 2-3 pm (EST)
 April 4, 2013, 2-3 pm (EST)
 April 25, 2013, 10-11 am (EST)
jngi.org/G2C
Website
Website
Featured
Speakers
Freeman A. Hrabowski, III
President,
University of Maryland,
Baltimore County
www.jngi.org/gateway/
Katherine J. Denniston
Acting Director, Division of
Undergraduate Education,
National Science Foundation
Questions and
Discussion
“”
Contact
Information
Dr. Chad Brown
Provost & Executive Vice President
Zane State College
cbrown@zanestate.edu
740-588-1260
Dr. Andrew (Drew) K. Koch
Executive Vice President
John N. Gardner Institute for
Excellence in Undergraduate Education
koch@jngi.org
828-877-3549
Dr. James Willis
Educational Assessment Specialist
Academic Technologies
Information Technology at Purdue
Purdue University
jewillis@purdue.edu
765-494-0588