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

MAPSherpa Predictive Analytics Student Dashboard

Vs.

MACHINES Rote calculation Routine, repetitive, precise movements

MAPSherpa Predictive Analytics Student Dashboard

From: 4/27/07 to 4/7/14 Irvine Valley CollegeAssociates 13,608 Certificate 5,405 Transfer 59,919 Saddleback CollegeAssociates 33,188 Certificate 14,354 Transfer82,820 Total: 209,294

Sherpa Sherpa is a recommendation engine that guides students to make informed decisions regarding courses, services, tasks and information.

Sherpa Architecture Recommendations Student Profile Trigger Nudge Transcript GPA Ed Goal Reg Activity Current Classes Status Courses Services Information Tasks Timing Event Portal News Feed Text To-Do List Mobile Feedback - RatingsFeedback - Preferences

Here is some advice for you… ? Profile Nudge

Timely Relevant Actionable Personal

Student ProfileRecommendation New student, not matriculatedLink to online orientation GPA > 3.5Link to honors program GPA < 2.0Link to tutoring program Transfer studentCourses that fulfill GE pattern Does not have academic planLink to MAP (academic planning tool) Low assessment scoresRecommend basic skills classes First time studentStep-by-step instructions Returning studentRecommend 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

 Phase One – Closed Class Assistance Assists students in finding a replacement class during registration  Phase Two – Profiles and Nudges Announcements, , 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 In planning phase now

Matriculation Pilot: Probation numbers dropped 39% one month after Sherpa notification.

Machine Learning Decision trees Neural networks Bayesian networks Learning Automata Support Vector Machines

Focus on Student Success

Questions?`