1. Student Equity Planning August 4, 2015 2nd Meeting
Brad C. Phillips, Ph.D.
President/CEO
Twitter bphillipsiebc

2. An Exercise
Thinking back about what the one thing you did that made the most difference in student success over the summer, what would that be?

3. IEBC Role: Assist With the Student Equity Plan
Plan is for all students
What the research shows
What we have learned
Process
Begins with data
Integrating the student voice
Examine policies and practices
Perform a gap analysis
Develop criteria
Propose interventions
Integrate project management
Develop an evaluation plan

4. IEBC Role: Assist With the Student Equity Plan
Plan is for all students
What the research shows
What we have learned
Process
Begins with data
Integrating the student voice
Examine policies and practices
Perform a gap analysis
Develop criteria
Propose interventions
Integrate project management
Develop an evaluation plan

5. Role of the Student Equity Committee
Charged with determining gaps in student performance
Engage in discussions around developing the institutional response
Developing the Student Equity Plan for the CCCCO
Due in November
Need to advocate for the activities
What authority does the committee have beyond making recommendations?

6. IEBC Approach What is the issue? (Summer)
*What questions do you want to answer
*What do you want to know?
Determine data necessary to understand the issue (Summer)
Student focus groups (early fall)
Review data and policies (summer)
Use data to make judgments and make decisions (fall)

7. Your Data Will Suggest Paths to Improving Outcomes
Remediation
Preparation
Persistence
Special Populations
Student Services
Instruction

8. Our Educational System
We are perfectly designed to get the results we are achieving.

9. Our Educational System
We are perfectly designed to get the results we are achieving. What does this mean for MSJC?

10. Our Educational System

13. Transformation is Possible: The Odessa College Example
West Texas
White dominated culture
Significant emerging Latino population
On the states defunded list
Poor morale
Very us/them mentality

14. Odessa College

15. Odessa College

16. Transformation is Possible: The Odessa College Example
Drop Rate Improvement Program
Faculty training on course retention strategies
Success coaches
Mentoring
Use of data to drive conversations
Two 8 week mini-mesters within a semester
Meta majors
Everything done at scale

17. Why Culture Matters Habit and Culture
“Culture eats strategy for breakfast.” -Steve Jobs
“Organizational culture is the sum of values and rituals which serve as ‘glue’ to integrate the members of the organization.”- Richard Perrin
In educational institutions, habits result in longstanding behaviors that most staff cannot tell you why they are done. These behaviors are not necessarily logical.
Habit exercise

18. Habit Loop
Charles Duhigg’s definition of habit. Source of picture is:

19. Changing habits
“The evidence is clear: If you want to change a habit, you must find an alternate routine, and your odds of success go up dramatically when you commit to changing as part of a group.”
“Belief is essential, and it grows out of a communal experience, even if the community is only as large as two people.”
The Power of Habit: Why We Do What We Do In Life and Business C. Duhigg

20. The Odessa Example Odessa Example
All of their work began around using data
What does habit change/culture change look like?
What were the change drivers?
What habits around examining data exist in your organization?

21. Let’s Talk MSJC Data - A cautionary tale: Elizabeth Kubler-Ross and Data Use

22. A note on perspective

23. A Quick Test
Here is a simple puzzle. Do not try to solve it but listen to your intuition:
A bat and ball cost $1.10. The bat costs one dollar more than the ball. How much does the ball cost?

24. A Quick Test
10¢
The distinctive mark of this easy puzzle is that it evokes an answer that is intuitive, appealing, and wrong.
If the ball costs 10¢, then the total cost will be $1.20 (10¢ for the ball and $1.10 for the bat), not $1.10. The correct answer is 5¢.

25. Leading & Lagging Indicators
Borrowed from the fields of economics and business
Leading indicators are in your control and lead to your hoped-for success
Lagging indicators are affected by what you do to influence your leading indicators
What are your key leading and lagging indicators?

26. Data Review Template  Is this information accurate?
 What jumps out at you and why?
 What are the themes?
 Is there comparison data available?
 Does this information challenge current assumptions about this population?
 What might be contributing to success?
 What might be detracting from success?
 Is this the data we need to make a decision?
 What is the most important information?
 What is missing?

27. Mt. San Jacinto College Award winning faculty Active foundation
Strong student scholarship awards
Award winning facilities master plan
Strong ties to the community
Improved overall outcomes over time

28. Your Data – Preliminary Observations (what we talked about at the last meeting)
Enrollment relatively flat
Hispanic enrollment increasing up 7% in two years
Differential success rates for all course levels – some as high as 15%
Some populations have retention rates that are disproportionality high compared with their success rates
Similar statistics for those working to move out of pre-collegiate course to collegiate level (could be higher for English, above average for math)
Low income and foster youth stats are low
Completion rates are pretty good but could be higher
Achievement gap is holding or getting larger

29. Data Review Template  Is this information accurate?
 What jumps out at you and why?
 What are the themes?
 Is there comparison data available?
 Does this information challenge current assumptions about this population?
 What might be contributing to success?
 What might be detracting from success?
 Is this the data we need to make a decision?
 What is the most important information?
 What is missing?

30. Why It Matters

31. Your Data – Fall 2011 First Time in College Cohort
Course Success Rates (A, B, C or credit)
Overall 68% (N=3620)
One third of all new student enrollments are not successful
One-third NOT Successful

32. Overall Course Success Rate : 68%
African American Success Rate – 51%
49% NOT Successful

33. Your Data – Fall 2011 First Time in College Cohort
Course Success Rates (A, B, C or credit)
Overall 68% (N=3620)
One third of all new student enrollments are not successful
51% success rates for AA (n=311)
Almost half are NOT successful
60% for year olds (n=654)
4 out of 10 are NOT successful

34. Your Data – Persistence
Fall 2007 Cohort
64% still here in Spring 08
50% are gone in Fall 08
4.4% transferred
2.2% earned an award
Fall 2011 Cohort
75% still here in Spring 12
45% are gone in Fall 12
2.6% transferred
0.5% earned an award
Next time we will share break-outs by demographics

35. Examination of Policies
How is the policy actualized
What really happens?
What are the exceptions?
Who can investigate what?
Assignments
One paragraph that answers the questions above

36. Examination of Policies
Admission
Registration
Matriculation (Orientation, advising, etc)
Assessment
Placement
Development education/remediation
Attendance
Attendance tracking (Class)
Early alert
Probation
Financial aid disbursement
Dual enrollment
Faculty professional development
Staff professional development
Adjunct faculty commitment

37. Next Meeting Basic skills data Completion data
Special program outcomes
Policy review