Presentation on theme: "Microethics & Macroethics in Graduate Education for Scientists & Engineers: Developing & Assessing Instructional Models Heather E. Canary, University of."— Presentation transcript:
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
Acknowledgements National Science Foundation: NSF/EESE # 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
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 macroethics in 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.
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
Participants Fall 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 Masters20 PhD50 Mean Age = Males = 55; Females = 26
Participants (cont’d.) Academic Program: Biodesign21 Engineering30 Chem/BioChem 9 Biology12 Other 5 Missing 4 Previous Ethics Instruction: Yes = 36 Previous S. R. Instruction: Yes = 22 First Language: English 54 Chinese10 Indian Language 8 Spanish 2 Korean 2 Other 5 Ethnicity/Race: White41 Asian28 Hispanic 6 African American 3 Other 3
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
N2 Scores by Study Group Group 1 = Embedded; Group 2 = Stand-Alone; Group 3 = Hybrid; Group 5 = Control
Outcomes by Study Group Measure Embedded Stand-Alone Hybrid Control Mean Mean Mean Mean ____________________________________________________ Pretest N2-Score Posttest N2-Score 8.70* 8.76* 10.14* 5.18 Pretest Knowledge * Posttest Knowledge 12.90* 12.36* 14.40* Pretest Ethical 3.44* Sensitivity Posttest Ethical 3.48* 3.51* 3.60* 3.21 Sensitivity ____________________________________________________ Note: * indicates significantly higher than Control Group at p <.05 level.
Outcomes by Language Group Measure Native English Non-Native English Mean Mean N = 54 N = 27 ____________________________________________________ Pretest N2-Score* Posttest N2-Score* Pretest Knowledge* Posttest Knowledge* Pretest Ethical Sensitivity* Posttest Ethical Sensitivity* ____________________________________________________ Note: * indicates significant group differences at the p <.05 level.
Outcomes by Sex Group Measure Male Female N = 55N = 26 Mean Mean ______________________________________________ Pretest N2-Score Posttest N2-Score* Pretest Knowledge Posttest Knowledge* Pretest Ethical Sensitivity Posttest Ethical Sensitivity ______________________________________________ Note: * indicates significant difference at the p <.05 level.
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
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.