+
WHAT PAR IS:
WHAT PAR IS NOT:

Predictive modeling to determine
student attrition risk

NOT a required tool for faculty or
advisors

Visual presentation of commonly
defined data to allow for
benchmarking to comparison
groups

NOT to replace other measures of
student success and progression

Currently being implemented at

Recently acquired by Hobson’s
(and Starfish)

NOT just at UND
all institutions in the NDUS

NOT just another software
separate from what we already
have
PAR HIGHLIGHTS
DATA INPUTS:







Student demographics and descriptive
data – gender, race, prior credits, high
school information, transfer GPA
Student course information – subject,
start/end dates, grades, delivery mode
Student financial information – FAFSA on
file, Pell received
Student academic progress (called
credential) provides the major, not
student progress in the major
Course catalog – subject, course number,
course title, course description, credit
range
Over 70 different individual data points
UND data from 2009-2015 – data added
each semester
FOR UND:

Taking a majority of courses
online

Non-traditional age (older than
24)

Low on-going GPA (less than 2.0)

Developmental Education
Requirements more than 50% of
the courses taken
RESULTS
MOST UND STUDENTS
ARE HERE:
ZERO ONLINE
COURSES
HIGH RISK FOR
COURSE SUCCESS &
RETENTION
FULLY ONLINE
RESULTS
NOW
SOON
FUTURE
PAR RESULTS DRIVE STARFISH
FLAGS:
• Students that drop 3-6 or
6+ credits
• Both student and advisor
receive an e-mail
PAR SCORE TO PREDICT
Course Explorer: Identify and
explore barrier courses
STARFISH PROGRESS SURVEY:
• A separate survey and
communications plan is
used for online courses to
address the retention
concerns raised by PAR
results for our online
population
LIKELIHOOD OF
RETAINING EACH STUDENT
Available in Starfish
Student Explorer: Enhanced
predictive risk score
meaningful interventions
integrated
COACHING & ADVISING
NETWORK
FALL 2016 iCAN:
Pilot iCAN concepts in College
Student Success Center
tracking student outcomes
results
THAT MATTER
of Business & Public Administration &
WHO CAN HELP
DATA STRATEGY TEAM:
Data leads for PAR
•

Lori Lindenberg – lori.Lindenberg@und.edu
•

John Mitzel – john.mitzel2@und.edu
•

PHONE: 777-2498
Analyzing PAR results at an aggregate
level
Developing a plan for real-time scoring
in Starfish
Developing a methodology for tracking
interventions to integrate into model and
drive real-time adjustments to PAR
scores in Starfish
iCAN GROUP

Thomasine Heitkamp –
thomasine.heitkamp@und.edu

Lisa Burger – lisa.burger@und.edu
iCAN Group Co-Chairs
•
•
•
Leading Starfish implementation
Driving iCAN pilot
Creating faculty champions for advising
& retention by involving faculty in
decisions