Remedial Mathematics and Beyond:
A Faculty-Led Project for
Curriculum Alignment and Streamlining of
Quantitative Requirements at Community Colleges
Panelists:
Alexandra W. Logue, CASE, Graduate Center
Mari Watanabe-Rose, Central Office of Academic Affairs
Susan Licwinko, Borough of Manhattan Community College
Ross Tippit, Borough of Manhattan Community College
Rebecca Walker, Guttman Community College
Alia Tyner-Mullings, Guttman Community College
Olen Dias, Hostos Community College
Kate Wolfe, Hostos Community College
The City University of New York
First Annual LaGuardia Community College Developmental Mathematics Conference
April 15, 2016
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Supported by:
The Teagle Foundation
The Spencer Foundation
The City University of New York
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Completion of Mathematics Remediation is the Single
Largest Barrier to Increasing College Graduation Rates:
• CUNY data are typical of national data.
• 76% of fall 2014 new CUNY community college freshmen
were assessed as needing remedial mathematics.
• 38% of students in the highest-level (elementary algebra)
fall 2014 CUNY remedial math course passed.
• Many students assigned to remedial math never take it.
• Most students assigned to remedial math do not complete
it.
• Students cannot satisfy their general education (Common
Core) CUNY quantitative requirement without first
completing remedial math.
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Implications of the relationship between
graduation and remediation
• Most recent CUNY graduation data:
o 18% of CUNY community college students initially
assessed as needing remedial math graduate within four
years.
o 35% of CUNY community college students with no initial
remedial need graduate within four years.
• These data represent huge amounts of wasted money and
time, and lives unfulfilled.
• Years, decades, of trying to make small changes in how
remedial math courses are taught have made little difference
in course success rates.
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But there is hope...
• Various strategies to help degree progress of
students assessed as needing remedial math,
including corequisite remediation, have been
showing positive outcomes.
• For example…
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Mainstreaming Remedial Math Students Randomized
Controlled Trial (Fall 2013) – Course Pass Rates
70
n=246
60
n=227
% Passed
50
55.7%
n=244
44.9%
40
39.3%
30
20
10
0
EA
(Traditional
Remediation)
EA-WS
Stat-WS
(Traditional Remediation (College-Level Course +
+ Workshop)
Workshop)
717 research participants were randomly assigned to one of the three groups.
(Logue, Watanabe-Rose, & Douglas, 2016)
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Mainstreaming Remedial Math Students RCT (Fall 2013)
– Quantitative-Course Status after Three Semesters
EA (n=244)
50%
EA-WS (n=227)
Stat-WS (n=246)
34%
45%
38%
34%
5%
16%
21%
57%
As of the end of Fall 2014…
basic quantitative skills not proficient
basic quantitative skills proficient but have not passed a college-level quantitative course
passed college-level quantitative course
(Logue, Watanabe-Rose, & Douglas, 2016)
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... And there is more.
• Faculty from three CUNY community colleges have
committed to using such evidence to help students.
• These faculty and others will analyze and change
how quantitative education is delivered at their
colleges.
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These efforts will constitute:
PRIME: CUNY’s Project for Relevant and Improved
Mathematics Education (2016-2019)
Participants:
• Borough of Manhattan Community College
• Guttman Community College
• Hostos Community College
funded by the Teagle Foundation
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PRIME participants
• will determine what quantitative topics
students in different majors actually need.
• will streamline their curricula to focus on
those topics.
• will incorporate evidence-based curricular and
pedagogical reforms designed to increase
success in quantitative courses.
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Traditional
Courses
Alternative
Non-Stem
Courses
Course
Enrollment
Pass rate
DFW rate
ECO 100
370
65.6%
38.1%
ECO 201
857
86%
18.5%
ECO 202
187
89.8%
12.2%
Guttman Community College Team
•
•
•
•
•
Rebecca Walker – Professor of Mathematics
Karla Fuller – Assistant Professor of Science
Marla Sole – Assistant Professor of Mathematics
Alia Tyner-Mullings – Assistant Professor of Sociology
Joan Lucariello – Provost
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All remediation integrated into credit bearing classes
• City Seminar with Quantitative Reasoning component
– Using quantitative information to support a thesis
– First semester – Building number sense and proportional reasoning
– Second Semester – Quantifying change
• Statistics and Statistics A/B – Credit bearing Introductory
Statistics course 5 hours per week
–
–
–
–
One 12-week semester Basic Statistics for proficient students
Two 12-week semester sequence for students not proficient
Just in time algebra support
Extended time – 5 hours per week for two 12 week semesters
• Algebra Practicum – For Business and IT Majors
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Student Performance at End of First Year of Study
Cohort
Fall 2012
Fall 2013
Fall 2014
Pass Rate
# of Passing
% of Cohort Not
Statistics B
Proficient in Math at
Grades (A-D)
Entry that Earned
Number Not Earned During
Grades of A-D in
Proficient in the First Year Statistics B During the
Math at Entry
of Study
First Year of Study
248
238
344
116
129
229
47%
54%
67%
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Questions Guiding Our Work Ahead
• Are we addressing the correct topics with
the correct depth and rigor?
• How can we be more effective?
• How can we be more efficient?
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What will we do?
• Consider the learning objectives and the overall
structure of Quantitative Reasoning, Statistics,
and the Algebra Practicum
– Analysis of current curricula including content comparisons
– Comparison of current curricula and time on task to other
models
– Focus groups with faculty from various disciplines to better
understand the quantitative skills needed to be successful
– Student feedback about current courses
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What will we do?
• Assess and revise as needed the use of peer
tutors in Statistics, Quantitative Reasoning, and
the Algebra Practicum
• Explore piloting an alternative or additional
placement mechanism
– Consider possible means for placement mechanisms to be
better aligned with the courses students will be entering
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PRIME Project
Personnel
• Christine Mangino, Provost
• Mathematics
 Olen Dias, Deputy Chair, Associate Professor
 Edme Soho, Assistant Professor
 AJ Stachelek, Assistant Professor
 Amrit Singh, Adjunct Lecturer
• Natural Science
 Van Chan Phanh, Assistant Professor
• Behavioral and Social Sciences
 Kate Wolfe, Assistant Professor
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Why we need
PRIME?
 47% of Freshmen enrolled in a Math remedial
course
 Almost 17% of all students enrolled in a Math
remedial courses
 Currently takes 3 semesters or more to complete
Math remediation
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PRIME Goals
1. Streamlining Remediation: successfully complete the
required math course for graduation in 1 or 2 semesters,
instead of 3
 Current remediation path:
Basic Math Skills (MAT 10) or Arithmetic + Algebra (MAT
15)  Elementary Algebra (MAT 20)  Introduction to
College Math (MAT 100)
2. Curriculum Alignment
 In order to meet the needs of specific departments, MAT
courses will include more contextualization of activities
and projects as we redesign the MAT curriculum and even
link MAT courses with other departments
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Projected PRIME
Activities
1. Streamlining Remediation
 Elementary Algebra (MAT 20) (fail) 
Elementary Algebra (pass)  Statistics (MAT
120) (3 semesters)
 Elementary Algebra (NP/Fail)  Statistics +
MAT 20 (pass CEAFE) (2 semesters)
 Fail entrance exam  Statistics (MAT 120) +
MAT 20 (pass CEAFE) (1 semester)
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Projected PRIME
Activities
2. Curriculum Alignment
Develop problem-based curriculum (contextualization)
for departments such as Early Childhood Education,
Psychology and Liberal Arts for) in these courses:
Arithmetic + Algebra (MAT 15), Elementary Algebra
(MAT 20), Quantitative Reasoning (MAT 115) and
Statistics (MAT 120)
Explore linkage between Introduction to Statistics and
Psychology (Research Methods course)
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Projected PRIME
Activities
Year 1

Gather relevant information and revise math curriculum
MAT 10, MAT 100 (Introduction to College Math), MAT 115
(Quantitative reasoning), develop assessment rubrics,
submit to college governance
 Include problem-based curriculum for contextualization
(Elementary Arithmetic)
 Select & train peer leaders for Supplemental Instruction.
 Disseminate Information with Advisors/departments
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Projected PRIME
Activities
Year 2
 Assess & Revise math curriculum (MAT 10, MAT 100, MAT
115), use data from Office of Institutional Research (OIR)
 Revise MAT 120 (Statistics), submit to governance as pilot
(MAT120SI)
 Explore links to Research Methods in Psychology courses
 Revise MAT 150 (College Algebra), submit to governance as
pilot
 Disseminate information, work on conference proposals
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Projected PRIME
Activities
Year 3
 Pilot all courses (MAT 10, MAT 100, MAT 115, MAT 120)
 Assess and revise curriculum
 Launch new curriculum
 Disseminate information, work on conference
proposals, work on publications
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PRIME Summary
• All three colleges are using various methods to
streamline remediation, e.g.,
o
o
o
o
Combined courses
Corequisite remediation
Backward curricular design
Compressed courses
• All three are recognizing the value of the student’s time
o Many CUNY students face many challenges and so their education
deserves to be as efficient as possible
o Streamlining their quantitative remedial work will provide academic
momentum and/or decreased reward delay and/or increase
probability of finishing before there is an interruption
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PRIME Summary
• To quantify all of these factors we will be using
a novel metric to measure colleges’ progress:
the contact hours needed for a student to
successfully pass a college-level quantitative
course
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PRIME Summary
• This will allow us to compare different
completion strategies, both within and across
colleges
• Measures of quality of learning will be
conducted simultaneously
• Goal is to have as high-quality, efficient,
learning as possible
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Conclusions
• PRIME is relevant to all CUNY associate-degree
programs
• PRIME is critical for hundreds of thousands of
students across the United States
• PRIME is essential for increasing graduation
rates
• Colleges and faculty have important and
challenging roles to play in making these
changes
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Thank you
For more information about PRIME please contact:
Lexa Logue, Principal Investigator
alexandra.logue@cuny.edu
Mari Watanabe-Rose, Co-Investigator
mari.watanabe@cuny.edu
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