Common themes in the Recently Adopted Undergraduate and Master's Curriculum Recommendations. A. John Bailer

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1 Common themes in the Recently Adopted Undergraduate and Master's Curriculum Recommendations A. John Bailer Abstract #314570, Common themes in the Recently Adopted Undergraduate and Master's Curriculum Recommendations Session # 12 on Sunday, 8/9/2015 beginning at 2:00 PM 1

2 Outline 1. Recap of the Master s degree workgroup process and outcomes 2. Comparison of recommendations, key points, pedagogy, 3. Wrap up 2

3 1. Recap of the Report of the Master s Degree Learning Outcomes Workgroup workgroup was formed by Bob Rodriguez, 2012 ASA (American Statistical Association) President Members of the workgroup: John Bailer, Roger Hoerl, David Madigan, Jill Montaquila, Tommy Wright. Statement of task: Develop guidelines, framed as learning outcomes, for master s degree programs in statistics and biostatistics that are responsive to the needs of stakeholders who employ such graduates. 3

4 Strategy: Conducted two surveys i. recent Master s graduates ii. employers of Master s graduates Timeline: i. Constructed survey forms and submitted them for review by the ASA Survey Committee (Fall 2011) ii. Compiled list of recent graduates from contacting ASA Caucus of Academic Reps and other schools not covered by the Caucus (Fall 2011) iii. Sample of recent graduates selected and contacted for phone survey (Spring 2012) iv. List of employers compiled from solicitation from ASA Board of Directors, Caucus of Academic Reps and other contacts (Summer 2012) v. Employer survey ed with reminder sent two weeks later (Fall 2012) vi. Results compiled, report produced and disseminated (late Fall 2012) 4

5 Results Recent graduates 1. Names of 366 graduates provided by 21 schools 2. Number of graduates/school ranged from 1 to 110 (M=12, Q1=7, Q3=17) 3. Interviews were completed for 29 recent graduates from the 115+ contacted from 13 different schools 4. Responses to interview questions were grouped into common topic categories 5

6 Knowledge/Skills learned in school that helped you perform your first job? (double arrows: 10+ of 29; single arrow: 3 of 29) Stat/ math bkgd Knowledge/skills learned in grad school that helped GET FIRST JOB Experience Specific stat method Programming Communication 6

7 Knowledge/Skills that helped you perform your first job? (double arrow: 10+ of 29) v Stat/ math bkgd Knowledge/skills helped PERFORM 1 st JOB Experience Specific stat method Programming Communication 7

8 Knowledge/skills graduates wished they had more in school (double arrows: 12 (programming) / 7 (specif stat method) of 29; single thin arrow: 3- of 29) WISHED HAD MORE Experience Specific stat method Programming Communication 8

9 Swapping courses in grad programs (double arrows: 6-7 of 29) 9

10 Results Employers 1. Names and contacted information for 68 employers of Master s graduates were generated. 2. Responses for 19 employers (28%) were generated from an contact with a follow-up reminder two weeks later. 3. Note: two employers responded with a general that did not explicitly address specific questions. 4. Employer organizations: university-based collaborative study centers/academic medical research settings (5), federal government (3 ), contract research organizations (2), survey organiz. (2), and financial/banking (2). Remaining organizations (each 1) : clinical trials consulting, pharmaceutical, public policy non-profit, consumer products, clinical research organization, or manufacturing. 5. Responses to interview questions were grouped into common topic categories (dark, double arrows => more than 10 respondents mentioned this topic; single arrows => 3-8 respondents) 10

11 Characteristics of the top two candidates (double arrows: 10+ [14 communication] of 29; single arrow: 8- [8=attitude] of 29) Stat/ math bkgd Thinking / problem solving TOP TWO candidates Attitude / Personality Advanced stat method Collaborative / teamwork Programming Communication Experience 11

12 What made hires successful? (double arrows: 10+ [14 attitude/personality] of 29; single arrow: 6- [6 thinking/problem solving of 29) Made Hires Successful Stat/ math bkgd Thinking / problem solving Attitude / Personality Collaborative / teamwork Programming Communication Experience 12

13 What knowledge/ skills were required and critical? (double arrows: 10+ [12 communication] of 29; single arrow: 5- [5 adv stat methods & communic.] of 29) REQUIRED and CRITICAL skills Stat/ math bkgd Thinking / problem solving Attitude / Personality Advanced stat method Collaborative / teamwork Programming Communication Experience 13

14 Deficits in recent hires? (double arrow: 9 of 29; single arrow: 6- [6 communication] of 29) Deficits in recent hires Stat/ math bkgd Thinking / problem solving Attitude / Personality Advanced stat method Collaborative / teamwork Programming Communication 14

15 Master s Degree Workgroup Recommendations 1: Graduates should have a solid foundation in statistical theory and methods. 2: Programming skills are critical and should be infused throughout the graduate student experience. 3: Communication skills are critical and should be developed and practiced throughout graduate programs. 4: Collaboration, teamwork, and leadership development should be part of graduate education. 5: Students should encounter non-routine, real problems throughout their graduate education. 6: Internships, co-ops or other significant immersive work experiences should be integrated into graduate education. 7: Programs should be encouraged to periodically survey recent graduates AND employers of their recent graduates. Evaluate success of their programs and to examine if other programmatic changes are warranted. 15

16 Report: Report: Project INGenIOuS strategies for advancing the mathematics and statistics workforce 16

17 2. Comparison of recommendations in Master s workshop report and the curriculum guidelines for undergraduate programs in statistical science Master s recommendations Strong Foundation in stat theory and methods Programming skills infused throughout the grad experience Ugrad KEY POINTS Increased importance of data science Communication skills critical need to Ability to communicate be developed & practiced Collaboration, teamwork & leadership development Encounter non-routine, real problems More diverse models and approaches; Real applications Internships, co-ops or other significant immersive work experiences Survey recent grads and employers 17

18 Master s recommendations Ugrad SKILLS NEEDED Strong Foundation in stat theory and Statistical methods and theory; methods Mathematical Foundations Programming skills infused Data manipulation and computation throughout the grad experience Communication skills critical need to Statistical Practice be developed & practiced Collaboration, teamwork & leadership development Encounter non-routine, real problems Discipline-Specific knowledge Internships, co-ops or other significant immersive work experiences Survey recent grads and employers 18

19 Master s recommendations Strong Foundation in stat theory and methods Programming skills infused throughout the grad experience Communication skills critical need to be developed & practiced Collaboration, teamwork & leadership development Encounter non-routine, real problems Internships, co-ops or other significant immersive work experiences Survey recent grads and employers Ugrad CURRICULUM FOR STAT MAJOR Stat methods and theory (Stat Theory, EDA, Design, Models); Math Foundations Data manipulation and computation (use of 1+ prof stat software, data manip documented, reproducible, prog concepts, comp intensive mthds) Stat practice (interact & commun with clients; eff tech writing, present, viz) Stat practice (teamwork & collaboration) 19

20 Master s recommendations Strong Foundation in stat theory and methods Programming skills infused throughout the grad experience Communication skills critical need to be developed & practiced Ugrad Pedagogical Considerations Encourage synthesis of theory, methods, computation and applic. Exp with stat computing and datarelated skills early and often Freq opportunities to refine communicate skills tied to instr in tech stat skills Provide opportunities to work in teams Collaboration, teamwork & leadership development Encounter non-routine, real problems Develop flexible problem solving skills; problems with substantive context Internships, co-ops or other significant immersive work experiences Survey recent grads and employers 20

21 Summary Master s workgroup Ugrad curric guidelines Topic rec. Strong Foundation in stat theory and methods Programming skills infused throughout the grad experience Communication skills Collaboration, teamwork & leadership development Encounter non-routine, real problems Internships, co-ops or other significant immersive work experiences ± (could be viewed as natural extension of particular guidelines)*** Survey recent grads and employers (encouraged in Next Steps ) 21

22 3. Wrap-up While the process to generate recommendations differed between the two workgroups (Master s and ugrad curriculum guidelines), the identified topics and categories were remarkably similar The surveys of recent graduates and employers gave some relative weighting of categories Graduates o noted that PROGRAMMING skills, stat/math bkgd and specific methods helped get first jobs o performance was impacted by these skills and COMMUNICATION and EXPERIENCE. 22

23 Employers o PROGRAMMING (broadly defined) was associated with being a top candidate, successful hire, deficit in some, required, critical and desired skill by employers of recent graduates. o STAT/MATH BKGD and COMMUNICATION were the associated with top candidates, successful hires and required and critical skills. Deficit in these skills = not hired Successful hires also possessed skills in COLLABORATION, TEAMWORK, LEADERSHIP ATTITUDE / PERSONALITY 23

24 Final thoughts: Exciting to see this convergence in undergraduate and Master s degree recommendations Challenge will be in implementation For example, what does infusing the computing in the curriculum mean? Are faculty members prepared to do this? How would doctoral degree requirements differ? { conjecture: many categories in common but preparation for independent research would change the weights } Implications for training the next generation of statistics faculty members? Implication for retraining the current generation of statistics faculty members? 24

25 Thank you for your interest! John Bailer Department of Statistics Miami University Oxford, Ohio USA T: (STAT!) 25