Heather E. Canary, University of Utah Joseph R. Herkert, Arizona State University

1. Microethics & Macroethics in Graduate Education for Scientists & Engineers: Developing & Assessing Instructional Models Heather E. Canary, University of Utah Joseph R. Herkert, Arizona State University Karin Ellison, Arizona State University Jameson M. Wetmore, Arizona State University

2. Acknowledgements • National Science Foundation: • NSF/EESE #0832944 • ASU Project Team: • Joseph Herkert, PI • Heather Canary, Co-PI (U of Utah) • Karin Ellison, Co-PI • Jameson Wetmore, Co-PI • JoAnn Williams • Ira Bennett • Brad Allenby • Jonathan Posner • Joan McGregor • Dave Guston • Consultants: • Deborah Johnson, Virginia • Rachelle Hollander, NAE • Nick Steneck, Michigan • Advisory Council: • Kristen Kulinowski, Rice • Dean Nieusma, RPI • Sarah Pfatteicher, Wisconsin • Karl Stephan, Texas State

3. Project Overview • Meet the increasing need to integrate instruction of microethical issues with instruction of macroethical issues: • “Microethics” = moral dilemmas & issues confronting individual researchers or practitioners • “Macroethics” = moral dilemmas & issues collectively confronting the scientific enterprise or engineering profession • 5 Project Goals: • Formulate educational outcomes for the integration of micro- and macroethicsin graduate science and engineering education • Develop and pilot different models for teaching micro- and macroethics to graduate students in science and engineering • Assess the comparative effectiveness of the instructional models • Facilitate adoption of the instructional models and assessment methods at other academic institutions • Provide for widespread dissemination of course materials and assessment results in the engineering, science, and ethics education communities.

4. Instructional Models • Stand-alone course (Science Policy for Scientists and Engineers-1 credit) • Technical course with embedded ethics content (Fundamentals of Biological Design) • Online/Classroom hybrid (Introduction to RCR in the Life Sciences – 1 credit) • Lab group engagement

5. Participants • Fall 2009 - Spring 2011 (Total N = 81) • Embedded Model (N = 21) • Stand-Alone Model (N = 14) • Hybrid Model (N = 20) • Lab Model (N = 2; excluded from analysis) • Control Group (N = 26) • Student Status: • Undergraduates 5 • Transitional 5 • Masters 20 • PhD 50 • Mean Age = 24.23 • Males = 55; Females = 26

6. Participants (cont’d.) • Academic Program: • Biodesign 21 • Engineering 30 • Chem/BioChem 9 • Biology 12 • Other 5 • Missing 4 • Previous Ethics Instruction: Yes = 36 • Previous S. R. Instruction: Yes = 22 • First Language: • English 54 • Chinese 10 • Indian Language 8 • Spanish 2 • Korean 2 • Other 5 • Ethnicity/Race: • White 41 • Asian 28 • Hispanic 6 • African American 3 • Other 3

7. Procedures • Nonequivalent Control-Group Quasi-Experiment • Survey measures of 3 desired learning outcomes: • Increased knowledge of relevant standards • Increased ethical sensitivity • Improved ethical reasoning • Engineering & Sciences Issues Test (ESIT) – short • Study-Specific Measures: • Knowledge of Relevant Standards (T/F/don’t know) • Ethical Sensitivity (1-5 scale) • Student-Instructor Interaction: • Out-of-classroom communication • Classroom climate (supportive/defensive) • Instructor verbal aggressiveness • Instructor verbal assertiveness • Frequency of informal ethics conversations

8. N2 Scores by Study Group Group 1 = Embedded; Group 2 = Stand-Alone; Group 3 = Hybrid; Group 5 = Control

9. Outcomes by Study Group Measure Embedded Stand-Alone Hybrid Control Mean Mean Mean Mean ____________________________________________________ Pretest N2-Score 8.11 7.62 8.39 6.64 Posttest N2-Score 8.70* 8.76* 10.14* 5.18 Pretest Knowledge 11.57 11.43 12.55* 10.42 Posttest Knowledge 12.90* 12.36* 14.40* 10.62 Pretest Ethical 3.44* 3.28 3.36 3.21 Sensitivity Posttest Ethical 3.48* 3.51* 3.60* 3.21 Sensitivity ____________________________________________________ Note: * indicates significantly higher than Control Group at p < .05 level.

10. Outcomes by Language Group Measure Native English Non-Native English Mean Mean N = 54 N = 27 ____________________________________________________ Pretest N2-Score* 8.53 5.82 Posttest N2-Score* 9.28 5.12 Pretest Knowledge* 11.83 10.59 Posttest Knowledge* 13.30 10.74 Pretest Ethical 3.40 3.16 Sensitivity* Posttest Ethical 3.61 3.08 Sensitivity* ____________________________________________________ Note: * indicates significant group differences at the p < .05 level.

11. Outcomes by Sex Group Measure Male Female N = 55 N = 26 Mean Mean ______________________________________________ Pretest N2-Score 7.31 8.30 Posttest N2-Score* 7.06 9.72 Pretest Knowledge 11.18 11.92 Posttest Knowledge* 12.02 13.35 Pretest Ethical Sensitivity 3.32 3.31 Posttest Ethical Sensitivity 3.42 3.45 ______________________________________________ Note: * indicates significant difference at the p < .05 level.

12. Student-Instructor Interaction • Classroom dynamics similar across instructional models: • 1 group difference in interaction variables – verbal aggressiveness higher in Embedded than in Hybrid • All other interaction variables statistically the same across instructional groups • Out-of-class communication associations: • With posttest ethical sensitivity (r = -.35, p < ,01) • With posttest ethics discussions with lab directors (r = .34, p < .05) • Frequency of ethics conversations increased: • Significantly with peers • Not significantly with lab directors/PIs

13. Implications • All models were effective in increasing knowledge, sensitivity, and moral reasoning • Knowledge gains highest in Hybrid Group: Consistent with previous research showing combining instructional modes more effective than either mode on its own • Language differences point to caution when using survey instruments with non-native English speaking samples • Sex differences might be related to language differences • Out-of-classroom communication points to importance of informal conversations and spillover effect of mentoring relationships • Students benefitted from flexible, interdisciplinary team of dedicated educators. • Successful integrative ethics education depends on commitment & cooperation of academic departments.