sherpa, map, predictive analytics and dashboard: software designed for success
DESCRIPTION
Sherpa, MAP, Predictive Analytics and Dashboard: Software Designed for Success. Dr. Bob Bramucci, Vice Chancellor, Technology and Learning Services Jim Gaston, District Director of IT – Academic Systems. About Us. About the SOCCCD Two-college district in southern California - PowerPoint PPT PresentationTRANSCRIPT
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Sherpa, MAP, Predictive Analytics and Dashboard:
Software Designed for Success
Dr. Bob Bramucci, Vice Chancellor, Technology and Learning ServicesJim Gaston, District Director of IT – Academic Systems
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About Us About the SOCCCD
Two-college district in southern California Approximately 41,000 students (23,000 FTES)
Two Colleges, Three Campuses Saddleback College in Mission Viejo Irvine Valley College in Irvine Advanced Technology and Education Park (ATEP)
in Tustin
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SOCCCD Student Success Systems
MAP Sherpa
PredictiveAnalytics
StudentDashboard
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The Problem
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The Planets Align…
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Progress So Far
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Technology & Productivity
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Moore’s Law
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Computer Prices
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Communications Speed
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Search Time
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Computers often exhibit Exponential rather than Arithmetic efficiencies
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Disinvestment by States
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We Can’t Get There Alone 80-90% spent on salaries + benefits in K-12
and postsecondary education limit options (we can’t realistically double the number of people)
Declining state investment Economic history shows that technology
often produces exponential changes Is increased automation the answer?
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SOCCCD’s SECRETS
It’s not just what we created (an integrated suite of student success software applications)
It’s How We Built It.
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SOCCCD’s Secrets
1. Student-Centered Design2. Agile Software Development
MethodsInclusiveFlexible
3. Human-Centered Allocation of Function
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Student-Centered Design
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Agile Software Development
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Allocation of Function
Vs.
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Fitts’ ListHUMANS• Complex pattern
recognition and generalization
• Judgment under uncertainty
MACHINES• Rote calculation
• Routine, repetitive, precise movements
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Human-Centered Allocation of Function
We believe that simply replacing people with machines is NOT the best answer
Rather, we can allocate functions between humans and machines in a strategic way that allows people to leverage their unique human strengths--a “human-centered design” approach
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SOCCCD Student Success Systems
MAP Sherpa
PredictiveAnalytics
StudentDashboard
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My Academic Plan (MAP)
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Create a system that provides:
Self-service guide for students to develop academic plans
Tracking system for counselors and students to monitor progress toward goals
Automated assistance to help students select classes that achieve their goals
Integration with Project ASSIST to reduce data maintenance and increase accuracy
MAP Project Goals
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Design Team Counselors Students Articulation Staff
Timeline Discussions began in late 2004 Development began in Fall 2005 MAP went online on April 27, 2007
Technology Service Oriented Architecture (SOA) Integration with Project ASSIST
Process
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Usage Statistics - Plans Created
From: 4/27/07 to 2/23/14
Irvine Valley College Associates
12,865
Certificate
5,231
Transfer
57,209
Saddleback College Associates
32,148
Certificate
13,939
Transfer 80,258
Total: 201,650
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MAP Demonstration
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Sherpa
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Sherpa
So what is Sherpa?
Sherpa is a recommendation engine that guides students to make informed decisions regarding courses, services, tasks and information.
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Sherpa Architecture
Recommendations
Student Profile
Trigger
Nudge
TranscriptGPAEd GoalReg ActivityCurrent ClassesStatus
Courses
Services
Information
Tasks
Timing Event
Portal News Feed Email Text To-Do List Mobile
Feedback - RatingsFeedback - Preferences
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Let’s translate this into the real world…
Here is some advice for you…
?
ProfileNudge
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What makes a nudge, a nudge?
Timely
Relevant Actionable
Personal
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Recommendation Examples
Student Profile RecommendationNew student, not matriculated
Link to online orientation
GPA > 3.5 Link to honors programGPA < 2.0 Link to tutoring programTransfer student Courses that fulfill GE patternDoes not have academic plan
Link to MAP (academic planning tool)
Low assessment scores Recommend basic skills classesFirst time student Step-by-step instructionsReturning student Recommend classes based on
goals, success patterns and transcript details. Only display classes with an empty seat and that don’t conflict with student’s schedule
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Phased Approach Phase One – Closed Class Assistance
Assists students in finding a replacement class during registration
Phase Two – Profiles and Nudges Announcements, Email, SMS, Voice-To-Text
Phase Three – Portal Refresh Calendar, To-Do List and News Feed
Phase Four – Mobile In beta release
Phase Five – Predictive Analytics In development
Phase Six – Student Success Dashboard Beginning in Spring 2014
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Some Promising Early ResultsClosed Class Assistant:
Has directly resulted in over 20,000 enrollments since October 2010.
Matriculation Pilot:
Probation numbers dropped 39% one month after Sherpa notification.
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Results: More Engagement
Yesterday I gave an IVC “Freshman Advantage” presentation to almost 100 high school Seniors at Segerstrom High school. I have been giving these presentations for years. I cannot BEGIN to tell you the positive difference in the student’s behavior due to the Sherpa nudge. It is like they had been touched by an electrified cattle prod in a GREAT way! Students were literally crowded around me before the presentation SHOWING me the Freshman Advantage email message on their smart phone!!! They had a higher level of awareness, a feeling of more urgency to complete matriculation and a better understanding of the process.
- Irvine Valley College Outreach Specialist
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Sherpa Demonstration
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Predictive Analytics
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Uses
Early AlertCourse RecommendationAdaptive Learning
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Machine Learning
Decision treesNeural networksBayesian networksLearning AutomataSupport Vector Machines
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Three Math Models
•Global: is student predicted to fail any of his/her courses?•Specific: A,B,C,D,F grade prediction for any particular class a student might take•Regression Model
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Data Scientists
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Problem Structure
•Millions of movies—but you’ll only view a small subset•Thousands of courses—but the average student will only take a small subset
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Matrix Factorization
Model
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Student Success Dashboard
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Focus on Student Success
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Next Steps
ResearchScaling UpAdditional success
modules
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Our Roadmap