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Data Driven Changes in Mathematics at Danville Area Community College
David Harby, TrusteeDr. Ronald Serfoss, Trustee
Kathy R. Sturgeon, Dean of Math, Sciences & Health ProfessionsAmber Anderson, Mathematics Faculty
Achieving the Dream
Intermediate Algebra &
Flipped Learning
Mathematics Pathways
Co-Requisites
Mathematics Placement
Mathematics Changes at
Danville Area Community
College
Achieving the Dream
• Lumina Foundation Initiative, largest non-government reform movement
• 35 states and the District of Columbia participate in the hopes of increasing student success/completion particularly for low-income students and students of color.
• Focuses on transformation and generation of a knowledge-base that is– Evidence-based
– Student-centered
– Equity and excellence based
• Danville Area Community College is a Leader College.
Discussion Structure
Input
Implemented Changes
Collected Data
Next Steps
Achieving the Dream
Intermediate Algebra &
Flipped Learning
Mathematics Pathways
Co-Requisites
Mathematics Placement
Mathematics Changes at
Danville Area Community
College
National Research
• Sixty percent of the institutions that offer developmental math contain a sequence of atleast two courses (Cafarella, 2014).
• Students who place three levels below their first credit-bearing mathematics course have a 10% pass rate. Students who place two levels below their first credit-bearing mathematics course have an 18% pass rate (Mireles, 2014).
• Eighty-one percent of students who took development math did not complete a degree or transfer (Cafarella, 2014).
Math Placement
Input
Implemented Changes
Collected Data
Next Steps
National Research (Continued)
• GPA is the best predictor, particularly for 2-yr colleges, of academic performance as it measures the academic self-confidence and achievement motivation (Robbins, 2006).
• Multiple-measures for students near placement cut-off are required (Belfield, 2012).
• Cutoffs for placement scores may be too high resulting in under placement and decreased completion (Scott-Clayton, 2014).
Math Placement
Input
Implemented Changes
Collected Data
Next Steps
Evolving Role of Placement Exams (Burdman, 2011)
• Placement exams are high-stakes tests.
• Placement exams are week predictors of success in gateway courses.
• The effectiveness of traditional developmental education is unclear.
• Accelerating some students through or out of development courses seems promising.
• Math and English assessments provide at best a narrow picture of student readiness for college.
Math Placement
Input
Implemented Changes
Collected Data
Next Steps
2015FA Developmental Math Vs. General Population*
DEVM General Population
Total 92 2281
First Generation
Yes 75 81.52% 1464 64.18%
No 14 15.22% 679 29.77%
Unknown 3 3.26% 138 6.05%
Race
White 55 59.78% 1659 72.73%
Black 31 33.70% 324 14.20%
Hispanic 1 1.09% 75 3.29%
Asian/Pacific Islander 1 1.09% 39 1.71%
American Indian/Alaskan Native - 0.00% 11 0.48%
Multi-racial - 0.00% 1 0.04%
Unknown 4 4.35% 172 7.54%
Gender
Male 25 27.17% 905 39.68%
Female 67 72.83% 1376 60.32%
Age
<20 28 30.43% 1036 45.42%
20-24 28 30.43% 571 25.03%
25+ 36 39.13% 674 29.55%
FT/PT
FT 53 57.61% 1048 45.94%
PT 39 42.39% 1233 54.06%
Pell Eligible
Yes 55 59.78% 863 37.83%
No 37 40.22% 1418 62.17%Dan
ville
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70% of students are placed in some form of Development Education.
More Likely to be placed in developmental math:First GenerationBlackMaleOver 20Full-timePell Eligible
Other Studies:Pell Eligible students are more like to be successful while Black students are less likely to be successful.
Stair Steps of Developmental Math
DEVM98
SR = 67%
DEVM99
SR = 54%
DEVM100
SR = 53%
MATH101
SR = 53%
MATH105
SR = 48%
Non-Credit Bearing
Math Placement
Input
Implemented Changes
Collected Data
Next Steps DEVM 98 DEVM 99 DEVM 100 MATH 101 MATH 105 MATH 111 MATH 115
67%
54% 53% 53%
48%
54%
62%
Success Rate2
Math Placement
Input
Implemented Changes
Collected Data
Next Steps
Students who begin in the entry level developmental mathematics are not likely to place in higher level
courses.
Four Keys to College and Career Readiness
Math Placement
Input
Implemented Changes
Collected Data
Next Steps
Key Description Measurable by Current Placement Test?
Content
Knowledge
Terms, facts, concepts, ideas, etc. Yes, but does it
match
curriculum.
Cognitive
Strategies
Strategies such as hypothesizing,
analyzing, evaluating, organizing,
communicating.
Yes, but limited.
Learning
Skills &
Techniques
Skills & behaviors including
persistence, motivation, goal setting,
note taking (similar to non-cognitive
skills or social emotional learning).
No
Transition
Knowledge &
Skills
Postsecondary awareness (e.g.
application and financial aid
processes, course selection and
academics planning) and skills.
No
• Course Success Rates for 1st time Math Placement Takers were compiled for Fall 2011-Summer 2014 for each placement test.
• Scores and Success Rates were reviewed and adjustments were made to placement scores to include success rates of 50% or higher.
Math Placement
Determining Placement ScoresInput
Implemented Changes
Collected Data
Next Steps
Course Success Rates for First Time Math Takers, 2011Fa-2014Su
# rate # rate # rate
<20 8 25% <20 9 67% <20 5 40%
20 4 50% 20 2 100% 20 1 100%
21 3 33% 21 4 50% 21 1 0%
22 4 25% 22 4 25% 22 6 33%
23 1 100% 23 7 43% 23 3 0%
24 4 75% 24 4 25% 24 3 33%
25 5 100% 25 6 67% 25 5 20%
26 4 75% 26 3 100% 26 3 33%
27 8 50% 27 4 50% 27 7 29%
28 2 50% 28 8 50% 28 8 50%
29 4 50% 29 8 75% 29 3 67%
30 3 67% 30 8 100% 30 9 11%
31 3 67% 31 5 100% 31 9 67%
32 2 50% 32 4 100% 32 10 60%
33 3 67% 33 7 100% 33 6 50%
34 3 100% 34 2 50% 34 5 40%
35 3 0% 35 6 50% 35 10 30%
36 1 100% 36 1 100% 36 5 40%
37 5 100% 37 2 100% 37 7 29%
38 5 20% 38 5 80% 38 9 56%
39 6 67% 39 3 67% 39 7 57%
40 6 67% 40 2 100% 40 10 60%
41 2 50% 41 2 100% 41 6 33%
42 4 100% 42 3 100% 42 10 80%
43 5 100% 43 1 100% 43 9 67%
44 0 44 3 33% 44 12 58%
45 3 100% 45 0 45 5 40%
46 3 67% 46 2 100% 46 9 56%
47 1 100% 47 2 50% 47 5 20%
48 3 100% 48 2 50% 48 5 40%
By COMPASS Numeric/Pre-AlgebraMATT 132 MATT 104 MATH101
MATT132: Elementary Technical MathMATT104: Business Mathematics
MATH101: Basic Algebra
Proposed
MATT 132, DEVM 098
MATT 104, DEVM 100
MATH 101, 107
MATH 105, 118, MATT
133
MATH 111, 115, 134
MATH 114, 120, 125, 135, 137,
161
ASSET Numerical 0 29 40
Elem. Alg. 0 26 33 46
Inter. Alg. 30 35 40
Coll. Alg. n/a 30 41
COMPASS Numeric 0 26 40
Algebra 0 16 23 44
Coll. Alg. n/a 28 51
ACT n/a n/a n/a 17 19 23
SAT n/a n/a n/a 350 400 560
decrease
increase
Changing Placement
• ASSET Numerical showed little placement value, resulting in an adjustment of tests given based on HS mathematics courses.
Math Placement
Input
Implemented Changes
Collected Data
Next Steps
• High school mathematics transcripts
• Placement testing
Math Placement
Multiple MeasuresInput
Implemented Changes
Collected Data
Next Steps
• Continue to Implement
– 36% decrease in students placed in the entry development math.
– 44% decrease in students placed in the exiting development math.
• Review student success/completion
– First mathematics course
– Progression through mathematics sequence by placement cohort
• Adopt a new placement tool.
Math Placement
Input
Implemented Changes
Collected Data
Next Steps
Features of Good Placement
• Accuracy and repeatability
• Low-stakes examination environment
• Targeted remediation
• Strong association with student outcomes
• Comprehensive topic coverage
• Useful data from placement
Math Placement
Input
Implemented Changes
Collected Data
Next Steps
Achieving the Dream
Intermediate Algebra &
Flipped Learning
Mathematics Pathways
Co-Requisites
Mathematics Placement
Mathematics Changes at
Danville Area Community
College
National Research• Some 60% of community college students
have to take remedial mathematics (Ashford, 2011).
• Some 60% of the nation’s 13 million community college student are unprepared and enroll in at least one development math course; however less than a quarter of the students in development math earn a degree or credential within eight years (Silva, 2013).
• Approximately 2/3 of community college students referred to a remedial mathematics sequence do not complete it (Cullinane, 2010).
Co-Requisites
Input
Implemented Changes
Collected Data
Next Steps
National Research (Continued)
• Concurrent support classes have had a success rate of approximately 20% higher than other courses (Cooper, 2011).
• Overall research supported compressed/accelerated development math courses (Cafarella, 2014; Woodard & Burkett, 2010; Sheldon & Durdella, 2010).
Co-Requisites
Input
Implemented Changes
Collected Data
Next Steps
Merging Courses
• MATH107: Applied Mathematics (credit bearing) and DEVM100 offered concurrent.
• Students with DEVM100 placement are extended invitations.
• Development math instructor provides support structure for successful completion of MATH107: Applied Mathematics.
Co-Requisites
Input
Implemented Changes
Collected Data
Next Steps
• Awaiting data collection.
Co-Requisites
Input
Implemented Changes
Collected Data
Next Steps
Achieving the Dream
Intermediate Algebra &
Flipped Learning
Mathematics Pathways
Co-Requisites
Mathematics Placement
Mathematics Changes at
Danville Area Community
College
Information Awareness
• Student progression to MATH115: Survey of Statistics was stunted.
• Illinois Community College Board Webinar
– Math Pathways
– Transition Courses
• IMACC Conference
• Statway Tentative Results
Math Pathways
Input
Implemented Changes
Collected Data
Next Steps
• Math Pathways
– STEM vs Non-STEM pathway
– Accelerated development math pathway for non-STEM
• Emphasis on critical thinking/problem solving
• Collaborative learning
• Employing technology
Math Pathways
Input
Implemented Changes
Collected Data
Next Steps
• Math Pathways– Limited sample size
– Although enrollment is declining, the number of students successfully completing 115 and 111 have increased.
– MATH107: Applied Mathematics appears to have a greater success rate than MATH105: Intermediate Algebra
• Could imply that they will be more likely to complete development math sequence quicker.
• Could imply that they have a greater chance of completing coursework by taking MATH107: Applied Mathematics
Math Pathways
Input
Implemented Changes
Collected Data
Next Steps
• Math Pathways
– Success rate data by placement cohorts
– Success rate data by instructional technique
– Consider expansion of the accelerated pathways to include College Algebra
Math Pathways & Boot Camp
Input
Implemented Changes
Collected Data
Next Steps
Achieving the Dream
Intermediate Algebra &
Flipped Learning
Mathematics Pathways
Co-Requisites
Mathematics Placement
Mathematics Changes at
Danville Area Community
College
• Research– Inquiry-oriented mathematics courses affect
retention and success rates (Nabb, 2011)
– Inquiry Learning does not negatively affect success in future coursework (Kogan, 2014).
• The Problem– Success rate data for MATH105: Intermediate
Algebra: Intermediate Algebra varied from 35%-50% depending on the instructor.
– Success rates were below the national average.
– Skill levels of the incoming students were declining suggesting that success rates would not improve.
Intermediate Algebra & Flipped Learning
Input
Implemented Changes
Collected Data
Next Steps
Identifying the Root
• Faculty agreed that the students’ failure to complete their homework was the greatest negative factor affecting the success rates.
Intermediate Algebra & Flipped Learning
Input
Implemented Changes
Collected Data
Next Steps
The Pilot Solution (2010)
Intermediate Algebra & Flipped Learning
Input
Implemented Changes
Collected Data
Next Steps
Traditional LectureInstructor Assigned
Homework
Cooperative learningInquiry-based learning
Mastery learning
The Tentative Results
• Retention after Early Verification was 29% higher.
• Test scores for the first four chapters were 5-45% higher than traditional sections.
• Substantial improvement was recorded for retakes.
• Student assigned homework increased motivation to complete the assignments.
• Student usage of the textbook increased.
Intermediate Algebra & Flipped Learning
Input
Implemented Changes
Collected Data
Next Steps
The Tentative Results
• Students worked more problems with this method both in and outside of the classroom.
• Students grew to appreciate the course technique, once they overcame the unfamiliarity of the course.
• Student requested more “lecture” materials.
Intermediate Algebra & Flipped Learning
Input
Implemented Changes
Collected Data
Next Steps
Current Model (2014)• Cooperative learning
• Inquiry-based learning
• Mastery learning (Mandatory)
• Flipped Class
– Professional Development
– Pre-recorded YouTube lectures
• Professional Learning Community
– Improvement Focus
– Support
– Consistency
Intermediate Algebra & Flipped Learning
Input
Implemented Changes
Collected Data
Next Steps
Results
Intermediate Algebra & Flipped Learning
Input
Implemented Changes
Collected Data
Next Steps
Results
Intermediate Algebra & Flipped Learning
Input
Implemented Changes
Collected Data
Next Steps
• Scaling Up for all courses
• Continue Professional Development & Professional Learning Community
• Implementing Persistence/Mindset Theory
• Data comparison for traditional/current placement cohorts
– Success/Completion Rates• MATH105: Intermediate Algebra:
Intermediate Algebra
• MATH111: College Algebra
Intermediate Algebra & Flipped Learning
Input
Implemented Changes
Collected Data
Next Steps
Achieving the Dream
Intermediate Algebra &
Flipped Learning
Mathematics Pathways
Co-Requisites
Mathematics Placement
Mathematics Changes at
Danville Area Community
College
Works Cited
• Ashford, Ellie. "New approaches to developmental math stress relevance." Community College Times - American Association of Community Colleges. N.p., 7 June 2011. Web. 12 Aug. 2015. <http://www.ccdaily.com/Pages/ Academic-Programs/ New-approaches-to-developmental-math-stress-relevance.aspx>.
• Belfield, Clive R. Predicting Success in College: The Importance of Placement Tests and High School Transcripts. Research rept. no. 42. N.p.: n.p., 2012. community college research center. Web. 12 Aug. 2015. <http://ccrc.tc.columbia.edu/media/k2/attachments/ predicting-success-placement-tests-transcripts.pdf>.
• Bostian, Brad. "Why Traditional Placement Testing Is Being Replaced by Multiple Measures." league.org. N.p., Dec. 2012. Web. 12 Aug. 2015. <http://www.league.org/blog/post.cfm/ why-traditional-placement-testing-is-being-replaced-by-multiple-measures>.
• Burdman, Pamela. 2012Where to Begin? The Evolving Role of Placement Exams for Students • Cafarella, Brian V., B.S., M.Ed. "EXPLORING BEST PRACTICES IN DEVELOPMENTAL
MATHEMATICS." Diss. Doctor of Philosophy in Educational Leade rship, 2013. Print.
• Cullinane, Jenna, and Philip Uri Treisman. "An NCPR Working Paper Improving Developmental Mathematics Education in Community Colleges: A Prospectus and Early Progress Report on the Statway Initiative." The National Center for Postsecondary Education: n. pag. Post secondary research. Web. 12 Aug. 2015.
Works Cited (continued)
• Kogan, Marina, and Sandra L. Laursen. "Assessing Long-Term Effects of Inquiry-Based Learning: A Case Study from College Mathematics." Open Access39.3 (2013): 183-99. Print.
• Mireles, Selina V., Taylor W. Acee, and Lindsey N. Gerber. "Focus: Sustainable Mathematics Successes." Journal of Developmental Education 38.1 (2014): 26-36. Print.
• Nabb, Keith A. "Try ing Something New: Unlecturing Mathematics." Innovation Abstracts 32.6 (2011): 1-2. Print.
• Sheldon, C.Q., & Durdella, N.R. (2010). Success rates for students taking compressed and regular length developmental courses in the community college. CommunityCollege Journal of Research and Practice,34(1/2), 39-54. East Lansing, MI: National Center for Research on Teacher Learning.(ERICDocument Reproduction Service No. EJ881541)
• Scott-Clayton, Judith, Peter M. Crosta, and Clive R. Belfield. "Educational Evaluation and Policy Analysis." American Educational Research Association36 (2014): 371-93. SAGE Journals Online. Web. 12 Aug. 2015.
• SILVA, ELENA, and TAYLOR WHITE. "PATHWAYS TO IMPROVEMENT USING PSYCHOLOGICAL STRATEGIES TO HELP COLLEGE STUDENTS MASTER DEVELOPMENTAL MATH." Carnegie Foundation for the Advancement of Teaching: n. pag. carnegie foundation. Web. 12 Aug. 2015.
Works Cited (continued)
• Slover, Laura, and Jeffrey Nellhaus. "Illinois P-20 Council." PARCC, Inc. 25 Apr. 2014. Print.
• Smith Jaggars, Shanna, et al. "Community College Review." Sage: n. pag. SAGE Journals Online. Web. 12 Aug. 2015. <https://www.coconino.edu/resources/ files/pdfs/presidents-office/strategic-planning-process/Articles/ three_accelerated_development.pdf>.
• Unraveling the differential effects of motivational and skills, social, and self-management measures from traditional predictors of college outcomes. Robbins, Steven B.; Allen, Jeff; Casillas, Alex; Peterson, Christina Hamme; Le, Huy Journal of Educational Psychology, Vol 98(3), Aug 2006, 598-616. p://dx.doi.org/10.1037/0022-0663.98.3.598
• Woodard, T. (2004). The effects of math anxiety on post-secondary developmental students as related to achievement, gender, and age. Inquiry, 9(1).East Lansing, MI: National Center for Research on Teacher Learning.(ERIC Document Reproduction Service No. EJ876845)