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Eight (Maybe Ten) is Enough:
Successful Methods for Application Control
Steve Frappier, Director of College Counseling
Claudia Jolivert, Associate Director of College Counseling
Ransom Everglades School, Miami, FL
www.ransomeverglades.org
Overview of “Eight is Enough”
Concerns:
- Fear of “The Wrong Choice”
- Why “Application Control”?
Conversations:
- “Getting to Know You” by Junior Year
- “Getting to Know You” by Senior Year
Data:
- “Backwards-Mapping”
- Common Data Sets
Methods:
- A new use for “Interest” and “Expect”
- Making a “Lava Lamp” chart
Concerns:
Fear of “The Wrong Choice”
Concerns:
Why “Application Control”?
Multiple Points of View
Student: “I want options and back-ups and choices. I want to reach for
goals and dreams, and I want to make myself and others proud.”
Counselor: “I don’t want to ‘feed the machine’ with students’ applications, nor do
I want to see low yields at colleges that are good to us.”
Marketplace:
Wall Street Journal article (04/05/12):
- In 2011, 29% of seniors applied to 7 or more schools
NACAC-based data (2010)
- average applications per student: about 4
- average university yield: 45%
Concerns:
Why “Application Control?”
Challenges to acknowledge:
Ease of the Common Application
(although we requested it!)
Increased need for “financial safeties”
Applications submitted based on
perceived “hooks,” audition, portfolio,
legacy, “connections,” athletic
recruitment, “really good essay,” etc.
Stories of exceptions and outliers
Conversations: “Getting to Know You”
by the end of Junior Year
What we believe in:
Guiding students toward a well-balanced
list of schools that will allow for a
choice (i.e., at least two affordable
options) by graduation
That admissions is more of a science
versus a pure lottery
That “chances” are based on historical
data
Conversations: “Getting to Know You”
by the end of Junior Year
Toolbox Items, to assess each student
in person and/or on paper:
Request student questionnaire and/or
self-narrative
Review teacher comments
Track or observe visibility on campus
Conduct appointments and exchange
e-mails
Request parental questionnaire
Conversations: “Getting to Know You”
by the fall of Senior Year
Introducing a reality check – “Can you …
… afford the application fees and test scores?”
… write and revise clear and original essays by the deadline?”
… prepare for and attend all of the interviews, shortly after applying?”
… handle all of the potential ‘no’ or ‘maybe’?”
… afford (in time and money) to visit your potential options in April?”
… provide three unique reasons why you are applying?”
While providing and discussing …
… previous years’ results from within the high school
… recent results from the admissions marketplace
Data:
“Backwards-Mapping”
Reconstructing a process from the result,
back to the origin
De-emphasizing the “wrong” numbers:
Application Volume
Overall Admit Rate
Middle-50% Ranges
Rankings
“Record-lows” and “Record-highs”
Data:
“Backwards-Mapping”
“Better” numbers?
What is the number of enrolled
freshmen? (Exactly how big is the
airplane that we’re wanting to fly?)
What are the attributes and
demographics for the past freshman
class that the college has published
and is celebrating?
Data:
“Backwards-Mapping”
Community attributes – frequently published or inferred:
Male / Female ratio
Multicultural percentages, including International students
Geographic Distribution
Spaces filled through Early Decision vs. remaining space for Regular Decision
Number of Freshmen per academic subdivision (Arts & Sciences vs. Engineering, etc.)
Type of High School (public, private/independent, boarding, home, etc.)
Legacy ratio
Socio-economic diversity (Pell-Grant Eligibility, First-Generation College-Bound)
Quantity of varsity sports teams
Data:
“Backwards-Mapping”
Case: Asian-American female in Florida applying regular decision to Columbia.
Context: In 2010, Columbia College (within Columbia University) had 1096 freshmen.
- 43% of the class filled Early Decision
- 15% from the South
- 25% Asian and Asian-American
- 49% female
Question: How many students “like your student” were probably in this freshman class?
Analysis: 43% of the 1096 freshmen (471 students) were admitted Early Decision,
which left 625 spaces regular decision
Then, assuming an equal distribution of students based on published data:
625 regular decision slots x 49% female x 25% Asian-American x 15% South =
11-12 enrolled students from regular decision … “Do you apply?”
Data:
Common Data Sets (CDS)
A public, annual report of institutional data, which can often be found in the
university’s web site under the Office of Institutional Research (IR Office)
Focus on Section “C” – which is for first-year admissions and enrollment
analysis (4-6 pages)
The CDS can reveal gender differences in admit rate, can show whether
more enrolled students use ACT or SAT, and other useful metrics
These data sources, in combination with our own school’s results, help us
in crafting “expectation” levels for our students
Methods:
A new use for “Interest” and “Expect”
Case:
“C’mon, it’s already October. It
will be easier for me to apply to
these 20-something schools than
to convince my parents
otherwise.”
Context:
A student’s self-made list, based
on self-prescribed “chances.”
This was an “A-” student with
great rigor, no demographic
hooks, a 32 ACT, and two
Subject Tests in the low-700’s.
Question:
How do we advise from here?
Top
Choice
High
Medium-
High
Medium
Medium-
Low
Low
Safety
80+%
Likely
60-80%
Possible
40-60%
Reach
20-40%
Unlikely
< 20%
Methods:
The “Lava Lamp Chart”
 Within Family Connection, have the student indicate an “Interest” level for each
school on the Prospective list (1) prior to meeting and (2) regardless of “chances.”
 Prescribe “Expect” with student, then write names of colleges in cells.
Methods:
The “Lava Lamp Chart”
Closing Observations
Anticipating non-admission might
actually be becoming easier in our “new
normal” era of high volume.
Some individual, qualitative aspects
(such as non-elite athletics and essays)
seem to be mattering less, as hyper-
selective schools engineer attribute- holders
into a freshman class.
Declaring these realities – and proving
how you got to these conclusions – can help
to envision April 1 results and reactions to
those results.
Closing Observations
Eight applications can “get it done:”
“I had at least two great choices.”
“I left myself room for interests that
developed throughout senior year.”
“I didn’t hear a lot of ‘no’ or ‘maybe’.”
“You helped me to challenge myself.”
Ten applications can allow for additional
“financial safeties” and/or merit-based
scholarship opportunities.
Thank you and Q & A
Claudia Jolivert
cjolivert@ransomeverglades.org
Steve Frappier
sfrappier@ransomeverglades.org
WWF: bjorkchop
Your Feedback Matters!
Thank you for attending the
Naviance Summer Institute 2013!
We greatly appreciate your feedback, please
complete a brief evaluation for this session at:
http://go.naviance.com/evaluations

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Eight, maybe ten applications enough!

  • 1. Eight (Maybe Ten) is Enough: Successful Methods for Application Control Steve Frappier, Director of College Counseling Claudia Jolivert, Associate Director of College Counseling Ransom Everglades School, Miami, FL www.ransomeverglades.org
  • 2. Overview of “Eight is Enough” Concerns: - Fear of “The Wrong Choice” - Why “Application Control”? Conversations: - “Getting to Know You” by Junior Year - “Getting to Know You” by Senior Year Data: - “Backwards-Mapping” - Common Data Sets Methods: - A new use for “Interest” and “Expect” - Making a “Lava Lamp” chart
  • 3. Concerns: Fear of “The Wrong Choice”
  • 4. Concerns: Why “Application Control”? Multiple Points of View Student: “I want options and back-ups and choices. I want to reach for goals and dreams, and I want to make myself and others proud.” Counselor: “I don’t want to ‘feed the machine’ with students’ applications, nor do I want to see low yields at colleges that are good to us.” Marketplace: Wall Street Journal article (04/05/12): - In 2011, 29% of seniors applied to 7 or more schools NACAC-based data (2010) - average applications per student: about 4 - average university yield: 45%
  • 5. Concerns: Why “Application Control?” Challenges to acknowledge: Ease of the Common Application (although we requested it!) Increased need for “financial safeties” Applications submitted based on perceived “hooks,” audition, portfolio, legacy, “connections,” athletic recruitment, “really good essay,” etc. Stories of exceptions and outliers
  • 6. Conversations: “Getting to Know You” by the end of Junior Year What we believe in: Guiding students toward a well-balanced list of schools that will allow for a choice (i.e., at least two affordable options) by graduation That admissions is more of a science versus a pure lottery That “chances” are based on historical data
  • 7. Conversations: “Getting to Know You” by the end of Junior Year Toolbox Items, to assess each student in person and/or on paper: Request student questionnaire and/or self-narrative Review teacher comments Track or observe visibility on campus Conduct appointments and exchange e-mails Request parental questionnaire
  • 8. Conversations: “Getting to Know You” by the fall of Senior Year Introducing a reality check – “Can you … … afford the application fees and test scores?” … write and revise clear and original essays by the deadline?” … prepare for and attend all of the interviews, shortly after applying?” … handle all of the potential ‘no’ or ‘maybe’?” … afford (in time and money) to visit your potential options in April?” … provide three unique reasons why you are applying?” While providing and discussing … … previous years’ results from within the high school … recent results from the admissions marketplace
  • 9. Data: “Backwards-Mapping” Reconstructing a process from the result, back to the origin De-emphasizing the “wrong” numbers: Application Volume Overall Admit Rate Middle-50% Ranges Rankings “Record-lows” and “Record-highs”
  • 10. Data: “Backwards-Mapping” “Better” numbers? What is the number of enrolled freshmen? (Exactly how big is the airplane that we’re wanting to fly?) What are the attributes and demographics for the past freshman class that the college has published and is celebrating?
  • 11. Data: “Backwards-Mapping” Community attributes – frequently published or inferred: Male / Female ratio Multicultural percentages, including International students Geographic Distribution Spaces filled through Early Decision vs. remaining space for Regular Decision Number of Freshmen per academic subdivision (Arts & Sciences vs. Engineering, etc.) Type of High School (public, private/independent, boarding, home, etc.) Legacy ratio Socio-economic diversity (Pell-Grant Eligibility, First-Generation College-Bound) Quantity of varsity sports teams
  • 12. Data: “Backwards-Mapping” Case: Asian-American female in Florida applying regular decision to Columbia. Context: In 2010, Columbia College (within Columbia University) had 1096 freshmen. - 43% of the class filled Early Decision - 15% from the South - 25% Asian and Asian-American - 49% female Question: How many students “like your student” were probably in this freshman class? Analysis: 43% of the 1096 freshmen (471 students) were admitted Early Decision, which left 625 spaces regular decision Then, assuming an equal distribution of students based on published data: 625 regular decision slots x 49% female x 25% Asian-American x 15% South = 11-12 enrolled students from regular decision … “Do you apply?”
  • 13. Data: Common Data Sets (CDS) A public, annual report of institutional data, which can often be found in the university’s web site under the Office of Institutional Research (IR Office) Focus on Section “C” – which is for first-year admissions and enrollment analysis (4-6 pages) The CDS can reveal gender differences in admit rate, can show whether more enrolled students use ACT or SAT, and other useful metrics These data sources, in combination with our own school’s results, help us in crafting “expectation” levels for our students
  • 14. Methods: A new use for “Interest” and “Expect” Case: “C’mon, it’s already October. It will be easier for me to apply to these 20-something schools than to convince my parents otherwise.” Context: A student’s self-made list, based on self-prescribed “chances.” This was an “A-” student with great rigor, no demographic hooks, a 32 ACT, and two Subject Tests in the low-700’s. Question: How do we advise from here?
  • 15. Top Choice High Medium- High Medium Medium- Low Low Safety 80+% Likely 60-80% Possible 40-60% Reach 20-40% Unlikely < 20% Methods: The “Lava Lamp Chart”  Within Family Connection, have the student indicate an “Interest” level for each school on the Prospective list (1) prior to meeting and (2) regardless of “chances.”  Prescribe “Expect” with student, then write names of colleges in cells.
  • 17. Closing Observations Anticipating non-admission might actually be becoming easier in our “new normal” era of high volume. Some individual, qualitative aspects (such as non-elite athletics and essays) seem to be mattering less, as hyper- selective schools engineer attribute- holders into a freshman class. Declaring these realities – and proving how you got to these conclusions – can help to envision April 1 results and reactions to those results.
  • 18. Closing Observations Eight applications can “get it done:” “I had at least two great choices.” “I left myself room for interests that developed throughout senior year.” “I didn’t hear a lot of ‘no’ or ‘maybe’.” “You helped me to challenge myself.” Ten applications can allow for additional “financial safeties” and/or merit-based scholarship opportunities.
  • 19. Thank you and Q & A Claudia Jolivert cjolivert@ransomeverglades.org Steve Frappier sfrappier@ransomeverglades.org WWF: bjorkchop
  • 20. Your Feedback Matters! Thank you for attending the Naviance Summer Institute 2013! We greatly appreciate your feedback, please complete a brief evaluation for this session at: http://go.naviance.com/evaluations

Editor's Notes

  1. What resulted was – unexpectedly – the most ground-breaking usage of Naviance that we had encountered as a staff!
  2. Within Family Connection, have the student indicate an “Interest” level for each school on the Prospective list (1) prior to meeting and (2) regardless of “chances .” For making a “Lava Lamp” chart, we amend the four Naviance choices, by adding two additional levels: Low , (Med-Low), Medium , (Med-High), High , Top Choice In a student meeting, discuss your office ’s data and/or scattergrams. Make notes. Prescribe “Expect” likelihood categories. Give caveats as you walk through. Also, instead of “Far Reach,” we often anecdotally use the term “Unlikely.” Plot “Interest Level” vs. “Expectations” – this is the actual “Lava Lamp Chart.” Students’ interests can “cool” or “heat up.” New testing and/or significant grade changes could change the “Expectations.” To condense to 8-10 applications, encourage 1-2 applications per column of selectivity, to diversify the portfolio of schools.