Student Success for All: Common Data Definitions at Work

Ellen D. Wagner, Ph.D

VP Research, Hobsons

Hae Okimoto, Ph.D.

Dir Academic Technologies

University of Hawaii

Our nation’s focus on student success has generated

multiple ways of measuring progress and completion. The

commonly defined, openly shared data definitions developed

by the PAR Framework give Hobsons’s customers the

opportunities for conducting research comparative

evaluation and sharing best practices that are valid, reliable

and generalizable for ALL students and the people working

to ensure their success.

Student Success for All: Common Data Definitions at Work

Source: Tyton Partners, “Driving Towards a Degree, The Evolution of Planning and Advising in Higher Education, Part i,” 2016.

A Changing Landscape

Data Have Changed Everything

• Analytics have ramped up everyone’s expectations of

personalization, accountability and transparency.

• Academic enterprises cannot live outside the institutional focus

on tangible, measureable results driving IT, finance,

recruitment, content and other mission critical concerns

Learning Analytics Value Propositions

Continue to Migrate and Evolve

• Completion

• Retention/

• Gainful employment

• Personalization

• Quality

“The difference between what

we’re collecting and what we’re

reporting on is huge.”

-

Source: Yanosky, Ronald, with Pam Arroway. “The Analytics Landscape in Higher

Education,” 2015. Louisville, CO: EDUCAUSE Center for Analysis and Research

Data is Collected, Not Connected

Analytics Bring Order and Meaning to Data

Source: Johal, Navneet, “2015 ICT Enterprise Insights in the Higher Education Industry,” Ovum Research, 2015

The Promise of Analytics

Gartner Research Analytics Model, 2012

http://bit.ly/2o0t7Iy

Beyond Prescriptions: Machine Learning

http://bit.ly/2aoQwIx

But Wait, there’s More: Machine Learning to

Deep Learning and Artificial Intelligence

From Research to Practice

The Evolution of PAR Framework

2011

The PAR Framework

was founded as a

Gates Foundation

project within WICHE

as part of WCET.

PAR openly licenses

and publishes data

definitions and

Student Success

Matrix

2012

PAR became fully

independent, not-for-

profit software as a

service membership

collaborative.

2015

Hobsons acquired the

assets of PAR as part of

its portfolio of Student

Success solutions (which

includes Starfish).

20162013

PAR developed the

Student Success

Matrix as a common

way to classify

interventions.

PAR Framework Research Questions

• Can predictive analytics find students at risk with the data we have

in hand?

• Can risk differences between and among student sub-populations

in an institution be discerned?

• Will students from anomalous institutions be discernable?

PAR Framework Common Data Definitions

Student Demographics

• Gender

• Race

• Prior credits

• Permanent resident zip code

• High school information

• Transfer GPA

• Student Type

Course CatalogCourse Information

Student Academic ProgressStudent FinancialsLookup Tables

• Course location

• Subject

• Course number

• Section

• Start date / End date

• Initial grade / Final grade

• Delivery mode

• Instructor status

• Course credit

• Subject

• Course number

• Subject (long)

• Course title

• Course description

• Credit range

• Credential types offered

• Course enrollment periods

• Student types

• Instructor status

• Delivery modes

• Grade codes

• Institution characteristics

• FAFSA on file

• FAFSA file date

• Pell received / awarded

• Pell date

• Current major / CIP

• Earned credential / CIP

Pioneered early

alert and case

management

First to integrate

multi-source data

into common view

Added our 200th

higher education

institution

Joined

Hobsons

in 2015

Funded by Bill and

Melinda Gates

Foundation

Led development

of analytics-as-a-

service

First open source

inventory of

interventions

Joined

Hobsons

in 2016

A Decade of Student Success, UNIFIED

Priorities

• First-year student

success

• Adult and post-

traditional learners

• Programs to support

underrepresented

students

• Transfer students (up,

down, lateral) and

pathways

PAR Research Includes

• ”An Empirical Look at Intervention Effectiveness for Improving First Year

Experiences,” Presentation by PAR’s Ellen Wagner, PhD., Oct 2015

• “Expansion for Evaluation of CAPL 101/Jumpstart – UMUC Student

Success,” Report by PAR’s Ellen Wagner, Ph.D., Scott James, and

Cassandra Daston. June 2015

• “Retention, Progression, and the taking of Online Courses,” Online

Learning peer-reviewed study by Dr. Karen Swan (UIS) and PAR’s Scott

James and Cassandra Daston, June 2016

• “Predicting Transfer Student Success,” whitepaper by Scott James, PAR

Data Scientist. May 2015

• https://www.hobsons.com/resources/entry/improving-post-traditional-

student-success

Mission Alignment

Data Awareness Has Highlighted

Misalignments in the U.S. Education System

• Points of transition typically represent points of loss in the system.

• What can we do to optimize digitalization to increase student success, improve institutional

effectiveness and efficiency and reduce cost?

Hae Okimoto, Ph.D.

Interim VP, Student Affairs

Director, Academic Technologies

University of Hawaii System: On Becoming a Data-Empowered System

University of Hawaii System

“55% of Hawai‘i’s working age adults to have a 2- or 4-year college degree by the year 2025.”

43% 42%44%

0%

55%

2007 2011 2015 2019 2022 2025

% o

f P

op

ula

tio

n w

/ D

eg

ree

Current Trend

GOALCumulative

Degree Gap:

42,932 degree holders

Source: UH Institutional Research and Analysis Office, NCHEMS, & U.S. Census Bureau,

American Community Survey, 1-year estimates, 2006 to 2012

}

HGI Strategic Direction Measures - 2016Degrees &

Certificates

Earned

Grad Rates

4-YR

Grad &

Success

Rates 6-Yr or

150% CC

Enrollment

to Degree

Gap – NH

Enrollment

to Degree

Gap – Pell

STEM

Degrees &

Certificates

Awarded

UH Mānoa

UH Hilo

UH West

O‘ahu

Hawai‘i CC

Honolulu CC

Kapi‘olani CC

Kaua‘i CC

Leeward CC

Maui College

Windward CC

Met or Exceeded Goal Within 0.3% of Goal for “Enrollment to Degree Gap” measure. Met or exceeded baseline for other measures.Did Not Meet Goal

http://blog.hawaii.edu/hawaiigradinitiative/strategic-priorities/

PAR Student Watch ListHonolulu Community College – Associate in Science

Selected Students

Home Campus: Honolulu Community College

Program: HON-Natural Sciences

Pre-Major: Pre-Medicine

PAR Level 1

PAR Factors: #1 Associates student, #2 Enter with no prior credits, #3 Low cred...

1

COMPASS Reading: 27

Semester Entered: Fall 2014

Registered for: 13 Credits at any UH institution Spring 2016

Registered for: 12 Credits at any UH institution Fall 2015

High School: Central High School 5/2014

Registered for: 15 Credits at any UH institution Fall 2016

Applications: 201510 Applicant Accepted at Honolulu, 201510 Accepted at Leeward

ORG_MEMBERSHIP: HON-ALL-STUDENTS-FA2015, HON-FINANCIALAID-FA2015…

COMPASS Math: 28

Career Interest: Health Science (medicine, dentistry, pharmacy, nursing, physical t….

Immediate Ed Goal: Take courses to transfer to another college

Highest Ed Goal: Earn a Medical Degree

Highest Ed Goal Institution: University of Hawaii Manoa

GPS

60%

64%

35%

0% 50% 100%

Corequisite RemediationStudents Completing with % C or better

ENG 22 + ENG 100

ENG 100/100S

ENG 19 +ENG 22 + ENG 100

ENG 100/100T 56%

27%

82%27%

0% 50% 100%

MATH 22 + MATH 82(Consecutive Semesters)

MATH 82(4 credits)

MATH 75(1 Semester)

75%29%

70%29%

0% 50% 100%

MATH 82 + MATH 100*(Earned “C” or better 2nd

Semester)

MATH 103/88(1 Semester)

MATH 100/78

(1 Semester)

Colle

ge

Ma

th T

rack

Colle

ge

Alg

eb

ra T

rack

MATH 22 + MATH 82(Consecutive Semesters)

MATH 82 + MATH 103(Earned “C” or better 2nd

Semester)

* Transfer level courses MATH 100 / 111 / 115

2+ levels below transfer level 1 level below transfer level

Honolulu Community College Leeward Community College

25%

21%

28%

17%

25%

34%

19%

28%

37%

22%

31%

38%

23%

0%

10%

20%

30%

40%

50%

Total ≥15 Credits <15 Credits

2009 2010 2011 2012

UH Mānoa4-Year Graduation Rates of

First-Time Freshmen Cohorts, 2009-12

Graduation Years 2013-16

The Right 1515 to Finish

Action

is ImperativeEvidence

is Essential

Connections

are Critical

Time

is Valuable

Our Four Principles

Good data can

challenge and validate

your assumptions, and

catalyse innovation.

Knowledge is only the

beginning. You need to

turn data into action to

help all students.

To support students

effectively at scale, you

need to work together,

across functional groups.

Your students need your

best help now. You must

act both quickly and

strategically.

“This work has allowed us to

eliminate the duplication of services

by multiple departments and

streamline our programming to offer

first class interventions to our

student population.

Michelle Wiley, Student Support

Specialist, Penn State World

Campus

Evidence is Essential

“In order to achieve the

goals in our strategic plan,

it’s absolutely essential that

we approach student

success in a holistic way,

with good data to drive

decisions.

Mark Askren, CIO,

University of Nebraska -

Lincoln

Evidence is Essential

“We can’t just throw data at

faculty and expect them to

embrace it – and understand it –

unless they realize that there’s a

problem they’re trying to solve.”

Larry Dugan, Director of

Instructional Technologies,

Monroe Community College

(SUNY)

Connections are Critical

Source: Jankowski, Natasha A, “Unpacking Relationships: Instruction and Student Outcomes.” American Council on Education, 2017

Action is Imperative

“I believe that as an institution of

higher education, we have a

moral obligation to offer all that is

possible to assist with a student’s

success. “

Dr. Francis L. Battisti, Executive

Vice President and Chief

Academic Officer, SUNY Broome

Community College

Discussion and Questions

Thank you for joining us!