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Modeling across the Curriculum The STEM Disciplines What are some key issues? How is the community responding? What curricular changes/ improvements are.

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Presentation on theme: "Modeling across the Curriculum The STEM Disciplines What are some key issues? How is the community responding? What curricular changes/ improvements are."— Presentation transcript:

1 Modeling across the Curriculum The STEM Disciplines What are some key issues? How is the community responding? What curricular changes/ improvements are needed? The First Two Years of College Math: Building Student Success Peter Turner SIAM Vice President for Education Dean of Arts & Sciences, Professor of Mathematics and Computer Science, Clarkson University pturner@clarkson.edupturner@clarkson.edu vpeducation@siam.orgvpeducation@siam.org * NSF/EHR/DUE Awards 1206230 & 1352973, Education and Human Resources Directorate

2 Key issues: Some of them Preparation & Readiness for STEM majors CU STEM admissions data Outdated curricula and delivery methods PCAST Engage to Excel Math 2025 Workforce issues Very few “future math profs” in large core math classes Teach the students we have, not the ones we dream of INGenIOuS Student “demands” for relevant education BUT with care over “training vs. education” CBMS Forum October 2014 The First Two Years of College Math: Building Student Success 2

3 CBMS Forum October 2014 The First Two Years of College Math: Building Student Success 3 STEM doesn’t happen

4 So, what is being done? Multiple initiatives in the Math Sciences community Modeling across the Curriculum TPSE-Math MAA-led Common Vision for Undergraduate Math in 2025 CSE Future Workshop Multiple curricular reports: CUPM Guidelines (2015?) Greater emphasis on applied topics than previously SIAM Report on Undergraduate CS&E (2011) SIAM Report on Applied Math undergraduate programs (2014) Future Directions in CSE Workshop, August 2014 INGenIOuS CBMS Forum October 2014 The First Two Years of College Math: Building Student Success 4

5 So, what is being done? Changing nature of both Math majors and of “service” courses Modeling, computation, statistics Project-based learning Teamwork, etc. SIAM Undergraduate Research Online, SIURO MAA-SIAM PIC (preparation for Industrial Careers) Math project More internship opportunities Implications for K-12 and Teacher Preparation CBMS Forum October 2014 The First Two Years of College Math: Building Student Success 5

6 Modeling across the Curriculum Two SIAM-NSF Workshops August 30 -31, 2012 at NSF January 12- 14, 2014 at ASA Draft report near complete Engage and Keep Young People in STEM, from K12 through Undergrad (and Grad) Studies, and into the Workforce CBMS Forum October 2014 The First Two Years of College Math: Building Student Success 6

7 MaC I Recommendations Four categories Expanding modeling in K-12 Development of a high school one semester, or one year modeling course (with stratified content) Develop modeling-based undergraduate curricula Develop a repository of materials for math modeling instruction and understanding CBMS Forum October 2014 The First Two Years of College Math: Building Student Success 7

8 MaC II Three primary topic areas: Early grades (Rachel Levy coordinating) Middle/High School (Katherine Socha) Undergrad curricula (Jeff Humpherys) MaC II process: Developing clear list of deliverables Intro from Joan Ferrini-Mundy Keynote on Math2025, Panel on opening afternoon advance this process CBMS Forum October 2014 The First Two Years of College Math: Building Student Success 8

9 MaC II Panel Used to “set the scene” and review some of the discussions at MaC I: Definition of modeling Stand alone vs. infusion Setting goals for MaC II sessions The role of algorithms Modeling at different educational levels and in different disciplinary contexts Assessment CBMS Forum October 2014 The First Two Years of College Math: Building Student Success 9 Panel members: Jeff Humpherys, Rachel Levy, Katherine Socha Moderator: Turner

10 Discussion Topics Programs: Courses, Programs, Degrees, Summer Experiences, Internships “Infusion” or stand alone? (“Trojan mice”) Materials: Books, Videos, Software, Posters, Websites, MOOCs? Informal education (MoMath?) Training: Pre-service and in-service Ways of interacting with teachers/ faculty/ TAs and students (and perhaps parents) CBMS Forum October 2014 The First Two Years of College Math: Building Student Success 10

11 Some MaC II undergrad recommendations* Proposal for NRC Study/Report Response to Joan Ferrini-Mundy’s Challenge to think about effective ways to educate students at the crossroads of: Mathematical modeling Data science Information science Computational science Computational thinking CBMS Forum October 2014 The First Two Years of College Math: Building Student Success 11 * Credit to Jeff Humpherys for some of this content

12 Modeling and the Pipeline: Attracting and retaining STEM students A study/paper on recommended topics to address: How to achieve the 34% increase in Engage to Excel. Multiple entryways? A non-calculus track for freshman modeling? Diversity Focus on Jobs! Teaching needs to match what we expect CBMS Forum October 2014 The First Two Years of College Math: Building Student Success 12

13 Two Recommendations for Professional Organizations Form a SIAM Activity Group (SIAG) in Applied Mathematics Education Done! SIAG Ed was approved at SIAM Council and Board in July Begins operation in January 2015 Plans for First SIAG Ed conference to coincide with, and broaden, MaC III SIAM Education VP needs to continue to work with other VPs and other societies New VP for Education starts in January 2015, Rachel Levy CBMS Forum October 2014 The First Two Years of College Math: Building Student Success 13

14 What are “new” key areas for undergrad math? A modern math sciences undergraduate education should include at least some introduction to Algorithms and Analysis (Data Structures, Approximation Theory, Numerical Analysis, Computational Science) Distributed Computing and Big Data (MPI, Hadoop, noSQL) Data Analytics (Regression, Estimation, SQL, R/Python) Modeling with Probability and Stochastic Processes Bayesian Statistics and Machine Learning Dynamical Systems (ODE, PDE, SDE) Optimization and Control CBMS Forum October 2014 The First Two Years of College Math: Building Student Success 14

15 Why? Actual Job from CareerBuilder.com CBMS Forum October 2014 The First Two Years of College Math: Building Student Success 15


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