Integrating 'Macroethics' and 'Microethics' for Graduate Students in Science and Engineering

1. Integrating 'Macroethics' and 'Microethics' for Graduate Students in Science and Engineering Karin Ellison, Joseph Herkert, Heather Canary, Jameson Wetmore

2. 'Macroethics' and 'Microethics' for Science and Engineering Graduate Students NSF/EESE #0832944 • Develop integrated learning objectives for graduate students • Apply learning objectives in four educational models • Assess student learning • Share knowledge and materials

3. Joseph Herkert, PI Heather Canary, Co-PI Karin Ellison, Co-PI Jameson Wetmore, Co-PI JoAnn Williams Ira Bennett Brad Allenby Jonathan Posner Joan McGregor Dave Guston Consultants: Deborah Johnson Rachelle Hollander Nick Steneck Advisory Council: Kristen Kulinowski Dean Nieusma Sarah Pfatteicher Karl Stephan Project Team

4. Coordination Workshop • Consultants presented background of grad education in science and engineering ethics • Description of four models • Discussion groups on issues and outcomes • Discussion groups on pedagogy • Discussion of assessment models

5. Examples of Microethical issues • Identify students’ own interests and values • Professional norms, e.g. objectivity, transparency, accuracy, and efficiency • Realistic understanding of behaviors • Challenges of reward structures

6. Examples of Macroethical Issues • Role of sociotechnical systems in our daily lives • Overlapping contexts of research – institution, profession, economy, society • Ways to envision possible social implications of research • Ability to identify values and stakeholder interests • How different career paths lead to different implications and outcomes

7. Four Educational Models • Stand alone course • Technical course with embedded ethics content • Online/Classroom hybrid • Lab group engagement

8. Science Policy for Scientists and Engineers • Stand alone course • One credit course • Meets CHM 501 requirement • Taught every semester • Topic and focus change each semester • Called “science policy for scientists and engineers” to enhance the macroethical content and avoid student and advisor biases toward the E(thics) word • Students choose half of the readings to ensure that we cover timely topics of interest to them

9. Fundamentals of Biological Design • Micro- and macroethical content is included in a required technical course for scientists and engineers • Ethics is placed in context with other professional knowledge and skills • Model takes advantage of learning opportunities as they arise

10. Lab Group Engagement Goal: To create a place where expertise from various fields can be exchanged, discussed, debated, and shared; will create an environment where both ethicists and scientists learn more about the ethics of emerging technologies. Three Research Questions: • Can ethicists gain access to information in laboratories about future technologies that are not readily available in other places? • Will this method provide an opportunity to help scientists and engineers understand the ethical and social implications of their work? • Will this method empower those who shape the direction of innovation to be more reflective on the social implications of their work?

11. Bio 591: Introduction to Research Ethics • Classroom/Online Hybrid • One-credit course • Required for some life science graduate students • Taught every semester • Students prepare using online materials • CITI Program RCR modules • SERCEB, “The Dual-Use Dilemma in Biological Research.” • NIH, "Protecting Human Research Participants." • Classroom sessions focus on case analysis and discussion

12. Intro. to Research Ethics - Topics • Plagiarism • Approaches to the Ethics of Scientific Research • Sustainability • Misconduct • Responding to Problems • Data Management • Authorship • Peer Review • Mentors and Trainees • Collaboration in Research • Science and the Military • Conflicts of Interest • Animal Subjects • Human Subjects

13. Assessment • Existing measures of moral reasoning: • Moral Judgment Test (MJT), Lind, 2002 • Engineering and Science Issues Test (ESIT), Borenstein, Kirkman & Swann, 2005 • Study-specific outcome measures • Student-instructor communication (post test only)

14. Study-specific Outcomes

15. Fall 2009 Results Study-Specific Measures • Ethical Sensitivity (5-point scale): • Statistically significant increase in scores from pretest to posttest (pretest M = 3.29, posttest M = 3.55) • Knowledge of Relevant Standards (16 possible): • Statistically significant increase in scores from pretest to posttest (pretest M = 11.74, posttest M = 13.12) • Ethical Reasoning (4-point scale): • No difference in scores from pretest to posttest (M = 3.30) • Note: Items were developed to tap the same underlying process as existing measures, but for issues specific to this student population.

16. Fall 2009 ResultsExisting Measures • Moral Judgment Test (MJT): • Increase in scores from pretest to posttest, but not statistically significant (pretest M = 19.79, posttest M = 23.07) • Engineering & Sciences Issues Test (ESIT): • Statistically significant increase from pretest to posttest (pretest M = 7.88, posttest M = 9.64) • Note: No significant group differences between instructional models for any measures

17. Results Dissemination • Outcomes workshop September 2011 Project Participants (including students) 8-10 outside participants (partial travel support) • Web site http://www.cspo.org/projects/immgsee/

18. Thank You • National Science Foundation • Biological Design Ph.D. Program • Center for Biology and Society • Center for Nanotechnology and Society • Consortium for Science, Policy & Outcomes • Lincoln Center for Applied Ethics