Guided Pathways to Success at SIUC

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Guided Pathways to Success at SIUC

• Combining streamlined degree paths
• with early-warning intervention 

• Scaling Up Effective Practices in Higher
  Education
• October 31st , 2013

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Presentation Outline

• Some background and definitions
• A look at the Process Flowchart (Logic Model)
• Essential Components
• General Education Credit Hour Reduction
• Remove course redundancies across programs
• Where we are at SIUC
• Predictive capability of Early intervention
  metrics
• Flexible Components
• Lessons Learned and Potential Pitfalls

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Purpose and Outcomes

• Purpose
• Removing barriers to and providing support for
  successful degree completion
• Provide data-driven support structures for
  students to remain on degree paths
• Outcomes
• Increased retention rates
• Increased graduation rates
• Easily calculated metrics

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Process Flowchart
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Essential Components

• Top-level Institutional Commitment
• Broad-based General Education Faculty Committee
• Significant institutional buy-in to curricular
  technology platforms for student data collection
  (For Early Warning system)

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Step 2
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General Education Credit Hour Reduction

• General Education requirements represent the
  first programmatic step in the process of
  streamlining degrees
• The requirements cut across degree programs, so
  streamlining has broad impact
• Institutionally, it is (almost) mandatory to have
  a well-respected faculty committee that oversees
  this work
• The work at SIU is done by the Core Curriculum
  Executive Council

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Core Curriculum Reduction at SIU

• Creativity and flexibility required for double
  dipping across degree paths
• STEM Fields
• Students in use advanced courses in science and
  math to satisfy general education requirements in
  these categories.
• Microeconomics or Macroeconomics satisfies a
  general education requirement in Social Science.
• Art and Design
• Students take courses in Art History to satisfy
  their general education Humanities requirement

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Step 3
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Remove course redundancies across programs

• Much harder work, since it involves program
  changes at department level
• Again, look for changes with broad impact in
  areas that cut across Colleges and Departments
• Work can often help to reconsider the design of
  important courses
• Example Statistics

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Statistics Redesign at SIUC

• Why the proliferation of Statistics courses?
• Those (!!) Mathematicians just want to
  teach Math!
• Our program is special. It requires both a
  statistics course and an experimental design
  course. (Because our experiments are really
  special!)
• Cooperation from the Chairs of Math and
  Educational Psychology
• Core Statistics and Research Design taught in
  Large Lecture Sections with Hybrid/Flipped
  classrooms (1 lecture a week)
• Twice a week students meet in small departmental
  level section in computer labs for discipline
  specific material
• Win-win for departments by optimizing faculty
  resources.

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Where are we in the process?
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OK-Now weve got the degree path. How do we keep
them on it?

• Keeping students on the optimally designed degree
  path is at least as important as designing the
  degree path.
• Computer-aided instruction (CAI) platforms permit
  real-time data retrieval.
• CAI allows integration across programs and
  courses.

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Early Intervention Metric in Math at SIU

• Week 3
• For all students in Math 107-108 (Intermediate
  Algebra/College Algebra)
• 25(In-class pretest) 25(HW) 50(Test 1)
• 25 (preparation) 25(motivation) 50
  (achievement)
• RED 0 to 55
• ORANGE 56 to 65
• YELLOW 65 to 75
• GREEN 76 to 100
• Students also receive an intervention score in
  week 7 and week 11 that is simply their course
  grade at that time.
• All of this data is given to the students and to
  colleges and advising staff.

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Does the Early Intervention Metric Correctly
Identify Students?

• Intermediate Algebra Success rate of Week 3
  metric (C or better)
• Red/Orange 22/86 (25.6)
• Yellow 5/12 (41.6)
• Green 54/64 (84.4)
• College Algebra Success rate of Week 3 metric
  (C or better)
• Red/Orange 31/155 (20)
• Yellow 18/40 (45)
• Green 142/193 (73.6)

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Early-intervention platforms for student data
collection

• The success of the Early Intervention System in
  Math has prompted the SIUC Provost to put
  together a Task-force on Early Intervention
  Technology.
• Coordinate data collection and metrics across
  critical gateway courses
• Coordinate software platforms for seamless
  integration of data

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What are the Flexible Components for your campus?

• Mechanism for General Education streamlining
• Campus curricular integration methods.
• Campus course articulation and course
  equivalencies
• Early intervention metric structure

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Lessons Learned and Potential Pitfalls

• Strong leadership an essential requirement
• Departments will try to protect credit hour
  generation and core courses.
• Try to create "win-win" situations when
  eliminating course redundancies.