Successfully reported this slideshow.

Data-Driven Decision Making in Addressing Study Abroad Barriers

1

Share

Upcoming SlideShare
Study Abroad Presentation
Study Abroad Presentation
Loading in …3
×
1 of 32
1 of 32

Data-Driven Decision Making in Addressing Study Abroad Barriers

1

Share

Download to read offline

Data drives decision-making at the highest levels of institutional leadership. This session will use a case of one institution to explore how its global education center collaborates with its institutional research office to determine barriers to studying abroad and compete for campus resources. Using actual data, panelists will guide roundtable discussions on moving from anecdotal observations through data analysis to policy decisions by senior administrators. Information will be provided about how to work with data, what types of data your institutional research office can provide, and how a chief academic officer makes decisions on academic priorities and resource allocation.

Data drives decision-making at the highest levels of institutional leadership. This session will use a case of one institution to explore how its global education center collaborates with its institutional research office to determine barriers to studying abroad and compete for campus resources. Using actual data, panelists will guide roundtable discussions on moving from anecdotal observations through data analysis to policy decisions by senior administrators. Information will be provided about how to work with data, what types of data your institutional research office can provide, and how a chief academic officer makes decisions on academic priorities and resource allocation.

More Related Content

Similar to Data-Driven Decision Making in Addressing Study Abroad Barriers

More from CIEE

Related Books

Free with a 14 day trial from Scribd

See all

Data-Driven Decision Making in Addressing Study Abroad Barriers

  1. 1. The Elon Commitment: Data-Driven Decision Making in Addressing Study Abroad Barriers CIEE Annual Conference November 21, 2014 Baltimore, MD
  2. 2. Introductions Woody Pelton, Dean of Global Studies Paul J. Geis, Associate Director of Study Abroad Rod Springer, Executive Director of Institutional Effectiveness Steven House, Provost and Vice President for Academic Affairs
  3. 3. Elon University profile  Private, selective, liberal arts  6,483 students with 5,782 undergrads  Theme #1 in our 10 year plan is a commitment to diversity and global engagement, including a  commitment for 100% access to global engagement
  4. 4. Underrepresented  Diverse backgrounds  Men  STEM  Athletes  High need  First generation  Community College  Non-traditional age  Performing arts Barriers  Finances  Curriculum  Athletics  Campus Involvement  Fear (students & parents)  Health (physical/mental)  Probation status
  5. 5. Assumptions and Anecdotes  Do demographics tell us about the barriers?  What assumptions do we make?  What does the data actually tell us?
  6. 6. 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% All Students Women Men Non-white students Athletes % of Elon Students Who Studied Abroad
  7. 7. 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% All Students Women Men Non-white students Athletes All Students No Football % of Elon Students Who Studied Abroad
  8. 8. Slide with useful data/chart re: majors and men NO ATHLETES WITH ATHLETES Sport Event Mgmt Male/Female ratio 45%, 55% 56%, 44% % of Females who Study Abroad 86% 78% % of All Majors who Study Abroad 73% 50% % of Males who Study Abroad 57% 29% Exercise Science Male/Female ratio 27%, 73% 29%, 71% % of Females who Study Abroad 77% 74% % of All Majors who Study Abroad 68% 64% % of Males who Study Abroad 44% 40%
  9. 9. What the data does tell us  Men are underrepresented across the board  25% of students with no financial need did not study abroad  Disparities by major
  10. 10. % Athlete % Study Abroad Arts Administration, Engineering, Engineering Mathematics, Env. Studies/Env. Engineering, French, International Economics 0% 100.00% International Studies 2% 98.18% International Business 9% 95.45% Art History 0% 92.59% Public Health Studies 0% 88.89% Human Services Studies 6% 80.80% Religious Studies 8% 80.56% Strategic Communications 5% 79.87% Environmental Studies 3% 79.49% Elementary Education 5% 77.22% Psychology 5% 75.00% Marketing 8% 74.76% Economics 15% 74.55% Biology 4% 73.19% English 1% 72.61% Mathematics 9% 72.00% Accounting 9% 71.15% AVERAGE 8.05% 70.95% % Athlete % Study Abroad AVERAGE 8.05% 70.95% Finance 10% 70.83% Communications 3% 70.43% Physics 20% 70.00% Theatre Studies 0% 70.00% Media Arts and Entertainment 6% 67.45% Entrepreneurship 11% 66.04% Philosophy 8% 65.79% Music Education 0% 64.29% Exercise Science 20% 64.18% Public Administration 3% 63.64% Environ/Ecological Science 16% 63.16% Biochemistry 3% 62.50% Management 13% 60.98% Sociology 12% 60.98% Special Education 5% 58.97% Computer Science 11% 54.05% Computer Information Syst 6% 51.52% Music Technology 5% 50.00% Sport and Event Management 36% 46.94% Music Theatre 0% 42.31% Theatre Arts 0% 39.58%
  11. 11. What the data does not tell us  Barriers (real or perceived)  Qualitative  The full story  Institutional context  Expertise
  12. 12. Institutional Research  What is IR?  IR provides information to various stakeholders so that more informed decisions can be made.  What data does IR have access to?  Typically – lots of data access. Our goal is to turn that data into information.
  13. 13. Correlation Being a Female Being an Athlete Having more NEED (dollars) Spearman's rho Study Abroad Y/N Correlation Coefficient .235** -.231** -.152** Sig. (2-tailed) <0.001 <0.001 <0.001 2 ) Effect-Size (r .06 moderate .05 moderate .02 small Observations 4,482 4,482 1,597 **. Correlation is significant at the 0.01 level
  14. 14. Study Abroad by EFC Level 4-years of graduating students Estimated Family Contribution (EFC) Have Need (Headcount) Have Need (Percent) No Yes No Yes Study Abroad Study Abroad Study Abroad Study Abroad No Yes No Yes No Yes No Yes EFC <= 5,000 196 236 45% 55% EFC 5,001 - 10,000 86 133 39% 61% EFC 10,001 - 20,000 153 289 35% 65% EFC >20,000 140 364 28% 72% EFC = Full Cost 727 2,158 25% 75% All 727 2,158 575 1,022 25% 75% 36% 64%
  15. 15. Gender and Athletics Yes* Study Abroad Sport No Yes Baseball 97% 3% Softball 88% 12% Men-Basketball 57% 43% Women-Basketball 33% 67% Men-Cross Country 38% 63% Women-Cross Country 22% 78% Men-Golf 44% 56% Women-Golf 36% 64% Men-Soccer 88% 12% Women-Soccer 46% 54% Men-Tennis 82% 18% Women-Tennis 56% 44% Football 87% 13% Volleyball 13% 88% Total 66% 34% *May not sum to 100% due to rounding
  16. 16. Financial Need Students Who Have Need Graduates Study Abroad? No Yes Difference 2010 $24,692 $22,951 $1,741 2011 $27,154 $23,128 $4,026 2012 $28,143 $23,014 $5,129
  17. 17. Selected Majors 2010-2013 May Graduates Have Need Gender White/Non-White Athlete Study Abroad Total % No % Yes % Female % Male % White % non- White % No % Yes % Yes Institutional Average (unduplicated headcount) 64% 36% 61% 39% 83% 17% 92% 8% 71% 4,482 Major (includes double/triple majors) Public Health Studies 67% 33% 100% 0% 100% 0% 100% 0% 89% 18 Economics 66% 34% 25% 75% 81% 19% 85% 15% 75% 110 Biology 63% 37% 72% 28% 87% 13% 96% 4% 73% 138 Institutional Average = 72% Finance 73% 27% 23% 77% 85% 15% 90% 10% 71% 192 Exercise Science 65% 35% 71% 29% 84% 16% 80% 20% 64% 201 Management 67% 33% 40% 60% 78% 22% 87% 13% 61% 82 Sport and Event Management 62% 38% 39% 61% 78% 22% 64% 36% 47% 147
  18. 18. Other Data Sources  Survey Data  Global Perspective Inventory (GPI)  Before College Survey of Student Engagement (BCSSE)  National Survey of Student Engagement (NSSE)  Multi-Institutional Survey of Leadership (MSL)  Others (e.g., locally developed surveys)  Focus Group/Interviews  National Student Clearinghouse
  19. 19. Higher Education Under Pressure
  20. 20. “Disruptive Forces and Innovation” The Elon Commitment:  “A tsunami is coming” David Brooks - NY Times  A combination of forces now “destabilize the residential college…business model over the long run” Moody’s Report  Learning? “Not much” Academically Adrift  Changing students Demographics
  21. 21. The Elon Commitment: “There is still huge value in the residential college experience and the teacher-student and student-student interactions it facilitates. But to thrive, universities will have to nurture even more of those unique experiences while blending in technology to improve education outcomes in measurable ways at lower costs. We still need more research on what works, but standing still is not an option.” Thomas Friedman, The Professors’ Big Stage, New York Times, March 5, 2013
  22. 22. The Elon Commitment: In March 2012 Sebastian Thrun, the CEO of Udacity, predicted that “fifty years from now there will be only 10 institutions in the world delivering higher education and Udacity has a shot at being one of them.” (The Stanford Education Experiment Could Change Higher Learning Forever, Wired, March 2012) MOOC – Massive – Open – Online – Course
  23. 23. What is College For? The Elon Commitment: “Since there are now innumerable other (and cheaper) ways to be educated, why are we doing this? … Colleges with a compelling answer to these questions – where everyone on campus knows the answers – are going to be fine. … We each need to figure out what our college is for. ... If a college’s true product is a transformed student, then the main effect of the next decade should be to redouble every school’s commitment to that cause.” Dan Currell, “What is College For?” Inside Higher Education
  24. 24. What is Elon For? – Engaged Learning Our core message: Engaged Learning
  25. 25. What is Elon For? – Engaged Learning Theme 1 - An unprecedented university commitment to diversity and global engagement
  26. 26. What is Elon For? – Engaged Learning 1. Finalize a strategy to assure that 100% of Elon students have access to a global experience either domestically or abroad, including a process to create award packages for students participating in a global experience. 6. Implement international recruitment strategic plan, including partnership with American Language Academy to continue increasing international enrollment at Elon.
  27. 27. What is Elon For? – Engaged Learning Decisions Based on Study Abroad Data: • Built Global Neighborhood and Global Commons • Shifted fellows grants to primarily support Study Abroad and Study USA • Increased financial aid for global education - $150,000/year for 3 consecutive years • Increased first year admissions target by 50 students (i.e. from 1,400 to 1,450) following jump in fall semester abroad enrollments • Developed Shanghai Center – for business majors - with internships • Hired Associate Dean and Director of International Admissions
  28. 28. What we have done at Elon?  Scholarship funding  Asia Center  Elon Experiences Grant  Increased ELR  Global Neighborhood
  29. 29. Have you worked with your institutional research office to obtain and analyze data? (Do you even know them?) How have you collaborated? What has surprised you in looking more deeply at data on your campus? Have you debunked any myths or assumptions? In the coming year, how can you more effectively utilize data to better inform your office’s outreach to underrepresented students, advocacy for resources, and/or addressing of barriers?
  30. 30. Q & A
  31. 31. Contact Woody Pelton: wpelton@elon.edu Paul J. Geis: pgeis@elon.edu Rod Springer: springer@elon.edu Steven House: shouse@elon.edu

Editor's Notes

  • Panelists Introduce themselves (name, title, and quick view of job responsibility)

    Woody – finish-up with quick overview of the format of the session:
    Brief overview of the context
    Exploration of assumptions and anecdotes
    Working with institutional data
    Moving to a decision
    Brief small group conversation
    Q&A
  • Elon University:
    Private, selective, liberal arts university
    6,483 students (5,782 undergrads)
    Elon College, the College of Arts & Sciences, and three undergraduate professional schools of business, communications, and education
    #1 master’s level for study abroad; 72% of Class of 2014 studied abroad

    100% access mandate in Elon Commitment
    Global engagement figures prominently in the leading commitment in the Elon Strategic Plan, initiated in 2010
    “An unprecedented university commitment to diversity and global engagement”
    Double need-based financial aid
    Provide 100 percent study abroad access
    Triple international student enrollment and create a campus community that better reflects the world’s diversity
    Be a national leader in preparing students to succeed in a multicultural world
    Build a multi-faith center and promote interfaith dialogue
    Develop the Elon Academy as a national model
    Elon views “global” opportunities broadly, including domestic programs with intentional, facilitated encounters with difference in the US


    Underrepresentation vs. Barriers in Study Abroad (poll audience and add to white flipchart or PowerPoint slide)
    What groups of students do not go abroad (underrepresented)?
    This informs how we conduct outreach
    What challenges do students face in trying to study abroad (barriers)?
    This informs resource allocation and programmatic structure
  • Underrepresentation vs. Barriers in Study Abroad (poll audience and add to white flipchart or PowerPoint slide)

    Enter audience responses into slide or onto flip chart if available
    Anticipated Responses for Underrepresented
    Men
    STEM students
    Athletes
    Students of diverse backgrounds
    First-gen
    Non-traditional students
    Community College students

    Anticipated Responses for Barriers
    Money/finances
    Curricular restraints
    Athletics obligations
    Campus involvement
    Lack of family support
    Fear?

    Summary of what these lists represent:
    These two issues are very related but are not the same. People often confuse/mix the terms.
    UNDERREPRENTATION: Tells us what groups of students do not go abroad
    This informs how we conduct outreach and/or to whom
    BARRIERS: Are the challenges students face in trying to study abroad
    This informs resource allocation and programmatic structure



  • No surprises for most of us in the groups listed (men, students of diverse backgrounds, STEM, athletes, etc)
    Highlight some of the Elon data
    What do the demographics tell us about the barrier? What assumptions do we make? Let’s look at some examples…
  • This data is compiled from the combined Elon graduating classes over four years (4,482 students)
    Example: Athletics/football from Elon University – what are we going to see happen to these figures if we remove the football team from the calculations?
    Expected answers from audience: men and non-white will shoot up.
    What does the analysis actually show?
  • Black/African-American, male is linked to football/athletics -- I have frequently heard intl education colleagues from Predominantly White Institutions put the issue of low male and African-American participation on the shoulders of the football team – or athletics more broadly. In the case of Elon, and I would suspect many of your schools, the data does not fully support this
    Pointing the finger at other parts of campus is an easy way for different groups to get themselves off the hook

  • What the basic data is not telling us?
    The “why” – the actual barrier, real or perceived
    Do males not study abroad because they are male? Because they are in highly structured majors? Because they are on athletic teams with seasons that span both semester?
    Study Abroad Office tends to have limited information
    Who goes abroad
    General student population (from fact book)
    We don’t have the complex data (or expertise) that allows us to look into this deeply. We don’t have free access to the data on who does not study abroad.

  • What the basic data is not telling us?
    The “why” – the actual barrier, real or perceived
    Do males not study abroad because they are male? Because they are in highly structured majors? Because they are on athletic teams with seasons that span both semester?
    Study Abroad Office tends to have limited information
    Who goes abroad
    General student population (from fact book)
    We don’t have the complex data (or expertise) that allows us to look into this deeply. We don’t have free access to the data on who does not study abroad.
  • Institutional Data (Rob, 10-12 minutes)
    What does IR do?
    Poll audience: how many have worked directly with IR?
    IR can have a different title and report to a different area on your campus (IE reporting to the President or VP Finance)
    What data does IR have access to?
    Full student demographics
    Financial aid
    Academic performance
    Athletic affiliation
    Greek life membership
    Major surveys (NSSE, BCSSE)
  • Institutional Data (Rob, 10-12 minutes)
    Correlation is not causation. But, correlation does give us an idea of the strength and direction of a relationship.
    Being female is positively correlated with Study Abroad
    Being an Athlete is negatively correlated with Study Abroad
    Having more Need is negatively correlated with Study Abroad


  • Institutional Data (Rob, 10-12 minutes)
    Take a minute and review this slide
    What does it tell us?
    Most of our students have no need.
    Majority of our non-Study Abroad students have no need: 727 versus 575.
    Nearly 2/3rds of Have-Need students study abroad
    We clearly see a pattern: More need and less study abroad


  • Institutional Data (Rob, 10-12 minutes)
    It is clear that men study abroad less than women in all comparable sports teams.
    Baseball vs Softball
    Basketball
    Cross Country
    Golf
    Soccer
    Tennis


  • Institutional Data (Rob, 10-12 minutes)
    This chart is clearly showing an increase in the average need for those who had need and whether or not they studied abroad.
    N-counts for Have-Need and No study abroad are approximately 150 for any given graduating class.



  • Institutional Data (Rob, 10-12 minutes)
    This chart shows the value of drilling into the data.
    Simply looking at study abroad by major might be misleading.
    Remember what we already know about NEED, Gender, and Athlete relation to study abroad…what do you expect to find?

    Some of these findings could be anticipated based upon what we know and others not so. But what about what we don’t know…what the data doesn’t tell us…don’t discount the curriculum structure…what is needed and offered for the major or the impact of being a double/triple major.

    Why is that the greatest number of students who do not study abroad have ZERO need?


  • Institutional Data (Rob, 10-12 minutes)
    Our general process is to use existing data resources first and then we move to other sources. If conducting longitudinal studies is key for you, then make sure resources can be merged/tracked over time and be sure to get the most N as possible as students will drop out of follow-up participation for many reasons (e.g., attrition, motivation, timing of survey, stop-outs).

    Survey data resources are available at Elon since we conduct regular and on-going surveys.
    Example: BCSSE may have some promise for Elon …it has a single scale that appears promising – High School Academic Engagement

    But, just like “the numbers will only take you so far”, the same is true for surveys…many times focus groups provide a much richer source of information.

    There are other data resources to consider…such as the National Student Clearinghouse (a national database if your school participates 98% of schools do participate). NSC can tell you the other schools your students attend either after leaving your school or as a dual enrollment.

    We’ve talked a lot about students, but there are other groups that can influence study abroad participation…such as faculty, staff, parents/guardians, and friends…keep these in mind when conducting studies.

    We are just beginning to explore other sources and there could be better and more relevant resources.


  • Small Group Discussion (Woody, 7-10 minutes) – sheets with these full prompts will be given out
    Have you worked with your IR office to obtain and analyze data? (Do you even know them?) How have you collaborated?
    What has surprised you in looking more deeply at data on your campus? Have you debunked any myths or assumptions?
    In the coming year, how can you more effectively utilize data to better inform your office’s outreach to underrepresented students, advocacy for resources, and/or addressing of barriers?
    Share brief highlight(s) from each group
  • Small Group Discussion (Woody, 7-10 minutes) – sheets with these full prompts will be given out
    Have you worked with your IR office to obtain and analyze data? (Do you even know them?) How have you collaborated?
    What has surprised you in looking more deeply at data on your campus? Have you debunked any myths or assumptions?
    In the coming year, how can you more effectively utilize data to better inform your office’s outreach to underrepresented students, advocacy for resources, and/or addressing of barriers?
    Share brief highlight(s) from each group
  • Panelists Introduce themselves (name, title, and quick view of job responsibility)

    Woody – finish-up with quick overview of the format of the session:
    Brief overview of the context
    Exploration of assumptions and anecdotes
    Working with institutional data
    Moving to a decision
    Brief small group conversation
    Q&A
  • ×