INTEGRATING MICROETHICS AND INTEGRATING MICROETHICS AND MACROETHICS IN GRADUATE MACROETHICS IN GRADUATE

SCIENCE ANDSCIENCE ANDENGINEERING EDUCATIONENGINEERING EDUCATION

Joseph HerkertJoseph HerkertKarin EllisonKarin Ellison

Heather CanaryHeather Canaryand Jameson Wetmoreand Jameson Wetmore

Integrating Microethics and Macroethics in Graduate Integrating Microethics and Macroethics in Graduate Science and Engineering Education:Science and Engineering Education:

Development and Assessment of Instructional Development and Assessment of Instructional Models NSF/EESE #0832944Models NSF/EESE #0832944

• Develop integrated learning objectives for graduate students

• Apply learning objectives in four educational models

• Assess student learning• Share knowledge and materials

Project Team Project Team

Joseph Herkert, ASU, PIJoseph Herkert, ASU, PI

Heather Canary, Utah, Co-PIHeather Canary, Utah, Co-PI

Karin Ellison, ASU, Co-PIKarin Ellison, ASU, Co-PI

Jameson Wetmore, ASU,Jameson Wetmore, ASU,Co-PICo-PI

JoAnn Williams, ASUJoAnn Williams, ASU

Ira Bennett, ASUIra Bennett, ASU

Brad Allenby, ASUBrad Allenby, ASU

Jonathan Posner, ASUJonathan Posner, ASU

Joan McGregor, ASUJoan McGregor, ASU

Dave Guston, ASU Dave Guston, ASU

ConsultantsConsultants

Deborah Johnson, VirginiaDeborah Johnson, Virginia

Rachelle Hollander, NAERachelle Hollander, NAE

Nick Steneck, MichiganNick Steneck, Michigan

Advisory CouncilAdvisory Council

Kristen Kulinowski, RiceKristen Kulinowski, Rice

Dean Nieusma, RPIDean Nieusma, RPI

Sarah Pfatteicher, Sarah Pfatteicher, WisconsinWisconsin

Karl Stephan, Texas StateKarl Stephan, Texas State

Coordination WorkshopCoordination WorkshopFeb 2009Feb 2009

• Consultants presented Consultants presented background of grad background of grad education in science education in science and engineering ethicsand engineering ethics

• ASU team members ASU team members presented four modelspresented four models

• DiscussionsDiscussions Issues and outcomesIssues and outcomes PedagogyPedagogy Assessment modelsAssessment models

Four Educational Models Four Educational Models

• Stand-alone courseStand-alone course

• Technical course with embedded ethics Technical course with embedded ethics contentcontent

• Online/Classroom hybridOnline/Classroom hybrid

• Lab group engagementLab group engagement

Fundamentals of Biological DesignFundamentals of Biological Design

• Micro- and macroethical Micro- and macroethical content included in a content included in a required technical course required technical course for scientists and engineersfor scientists and engineers

• Ethics introduced in context Ethics introduced in context with other professional with other professional knowledge and skillsknowledge and skills

• Model takes advantage of Model takes advantage of learning opportunities as learning opportunities as they arisethey arise

Introduction to RCR in the Life Science Introduction to RCR in the Life Science

• Classroom/Online HybridClassroom/Online Hybrid• One-credit courseOne-credit course• Required for some life science graduate Required for some life science graduate

studentsstudents• Taught every other semesterTaught every other semester• Students prepare using online materialsStudents prepare using online materials

CITI Program RCR modulesCITI Program RCR modules ASU, “The Humane Care and Use of Laboratory ASU, “The Humane Care and Use of Laboratory

Animals”Animals” NIH, "Protecting Human Research Participants." NIH, "Protecting Human Research Participants."

• Classroom sessions focus on case analysis and Classroom sessions focus on case analysis and discussiondiscussion

Science Policy for Scientists and Science Policy for Scientists and EngineersEngineers

• Stand-alone courseStand-alone course• One-creditOne-credit• Meets CHM 501 requirementMeets CHM 501 requirement• Taught every semester Taught every semester • Topic and focus change each Topic and focus change each

semestersemester• Called “science policy for Called “science policy for

scientists and engineers” to scientists and engineers” to enhance the macroethical enhance the macroethical content and avoid student and content and avoid student and advisor biases toward the advisor biases toward the E(thics) word E(thics) word

• Students choose half of the Students choose half of the readings to ensure coverage of readings to ensure coverage of timely topics of interesttimely topics of interest

Lab Group Engagement Lab Group Engagement

Goal: To create a place where expertise from various fields can Goal: To create a place where expertise from various fields can be exchanged, discussed, debated, and shared; will create an be exchanged, discussed, debated, and shared; will create an environment where both ethicists and scientists learn more environment where both ethicists and scientists learn more about the ethics of emerging technologies. about the ethics of emerging technologies.

Three Research QuestionsThree Research Questions

1.1. Will this method provide an opportunity to help scientists and Will this method provide an opportunity to help scientists and engineers understand the ethical and social implications of engineers understand the ethical and social implications of their work? their work?

2.2. Will this method empower those who shape the direction of Will this method empower those who shape the direction of innovation to reflect on the social implications of their work? innovation to reflect on the social implications of their work?

3.3. Can ethicists gain access to information in laboratories about Can ethicists gain access to information in laboratories about future technologies that are not readily available in other future technologies that are not readily available in other places? places?

AssessmentAssessment• Fall 2009 - Spring 2011Fall 2009 - Spring 2011

– Embedded Model (N = 21)Embedded Model (N = 21)– Stand-Alone Model (N = 14)Stand-Alone Model (N = 14)– Hybrid Model (N = 20)Hybrid Model (N = 20)– Lab Model (N = 2; excluded from analysis)Lab Model (N = 2; excluded from analysis)– Control Group (N = 26) Control Group (N = 26)

• Study-specific outcome measures for: data management, Study-specific outcome measures for: data management, conflicts of interest, sustainability, military researchconflicts of interest, sustainability, military research- - Knowledge of relevant standardsKnowledge of relevant standards

- Ethical sensitivity- Ethical sensitivity- Ethical reasoning- Ethical reasoning

Existing measures of moral reasoningExisting measures of moral reasoning– Engineering and Science Issues Test (ESIT), Borenstein, Kirkman & Engineering and Science Issues Test (ESIT), Borenstein, Kirkman &

Swann, 2005Swann, 2005– Moral Judgment Test (MJT), Lind, 2002Moral Judgment Test (MJT), Lind, 2002

• Student-instructor communication (post test only)Student-instructor communication (post test only)

Knowledge of Relevant Standards Knowledge of Relevant Standards

• Summed Scale; Possible Range = 0 – 16Summed Scale; Possible Range = 0 – 16• Increase from pretest to posttest, experimental Increase from pretest to posttest, experimental

groups:groups: t(54) = 5.02, p < .001t(54) = 5.02, p < .001 MMAA = 11.89, SD = 2.15; M = 11.89, SD = 2.15; MBB = 13.31, SD = 04 = 13.31, SD = 04

• Significant group differences on posttest:Significant group differences on posttest: F(3,78) = 11.03, p < .001F(3,78) = 11.03, p < .001 All three experimental groups significantly higher than All three experimental groups significantly higher than

Control groupControl group Hybrid group significantly higher than Stand Alone Hybrid group significantly higher than Stand Alone

and Embedded groupsand Embedded groups

Sensitivity to Ethical Issues Sensitivity to Ethical Issues

• Mean of 14 Items on 1 – 5 ScaleMean of 14 Items on 1 – 5 Scale• Increase from pretest to posttest, experimental Increase from pretest to posttest, experimental

groups:groups: t(53) = 3.03, p < .01t(53) = 3.03, p < .01 MMAA = 3.37, SD = .38; M = 3.37, SD = .38; MBB = 3.54, SD = .43 = 3.54, SD = .43

• Significant group differences on posttestSignificant group differences on posttest F(3,78) = 3.99, p = .01F(3,78) = 3.99, p = .01 Control group significantly lower than all experimental Control group significantly lower than all experimental

groupsgroups No significant differences between experimental No significant differences between experimental

groupsgroups

Engineering & Science Issues Test (ESIT) Engineering & Science Issues Test (ESIT) (Borenstein et al., 2009) (Borenstein et al., 2009)

• Two outcome scoresTwo outcome scores P-Score = percentage of postconventional reasoningP-Score = percentage of postconventional reasoning N2-Score = uses P-Score & accounts for absence of N2-Score = uses P-Score & accounts for absence of

preconventional thinkingpreconventional thinking

• No overall significant gains in P-ScoreNo overall significant gains in P-Score• Increase from pretest to posttest, experimental Increase from pretest to posttest, experimental

groups:groups: T(53) = 2.54, p < .05T(53) = 2.54, p < .05 MMAA = 8.22, SD = 3.92; M = 8.22, SD = 3.92; MBB = 9.25, SD = 4.37 = 9.25, SD = 4.37

ESIT, ContinuedESIT, Continued• Significant group differences in N2-Score Significant group differences in N2-Score

F(3,77) = 5.36, p < .01F(3,77) = 5.36, p < .01 All experimental groups significantly higher than Control All experimental groups significantly higher than Control

groupgroup

Student-Instructor CommunicationStudent-Instructor Communication

• Instructor Argumentativeness (1-50) – productive & Instructor Argumentativeness (1-50) – productive & positive engagement in content argumentspositive engagement in content arguments

• Instructor Verbal Aggressiveness (1-50) – counter-Instructor Verbal Aggressiveness (1-50) – counter-productive & negative verbal attacksproductive & negative verbal attacks

• Out-of-Class Communication (1-45) – interactions with Out-of-Class Communication (1-45) – interactions with instructor outside of classroom contextinstructor outside of classroom context

• Supportive Classroom Climate (1-40) – instructor fosters Supportive Classroom Climate (1-40) – instructor fosters safe environment for learning & discussionsafe environment for learning & discussion

• Defensive Classroom Climate (1-45) – instructor fosters Defensive Classroom Climate (1-45) – instructor fosters negative & defensive environmentnegative & defensive environment

• Open-ended questions: most memorable discussion; Open-ended questions: most memorable discussion; effective & ineffective teaching methods; value & effective & ineffective teaching methods; value & relevance of discussions; perceived role in societyrelevance of discussions; perceived role in society

Communication AnalysesCommunication Analyses• All experimental groups team-taught with 2 or 3 All experimental groups team-taught with 2 or 3

instructorsinstructors• Aggregate instructor communication means compared Aggregate instructor communication means compared

across groups, only 1 group difference:across groups, only 1 group difference: Instructor Verbal Aggressiveness, Embedded Group Instructor Verbal Aggressiveness, Embedded Group

higher (M = 18.33) than Hybrid Group (M = 14.21)higher (M = 18.33) than Hybrid Group (M = 14.21)• Ethical Sensitivity (posttest) significant correlations with Ethical Sensitivity (posttest) significant correlations with

Defensive Classroom Climate (r=-.37, p=.01) and Out-of-Defensive Classroom Climate (r=-.37, p=.01) and Out-of-Class Communication (r=-.35, p=.01).Class Communication (r=-.35, p=.01).

• Supportive Classroom Climate & Argumentativeness Supportive Classroom Climate & Argumentativeness (r=.42, p=.01); Supportiveness & Out of Class (r=.42, p=.01); Supportiveness & Out of Class Communication (r=.57, p=.01)Communication (r=.57, p=.01)

• Defensive Classroom Climate & Verbal Aggressiveness Defensive Classroom Climate & Verbal Aggressiveness (r=.55, p=.01)(r=.55, p=.01)

Assessment Conclusions Assessment Conclusions

• Students in ALL experimental groups showed gains; Students in ALL experimental groups showed gains; gains significantly higher than control group gains gains significantly higher than control group gains

• All instructional models improve students’ ethical All instructional models improve students’ ethical knowledge, sensitivity, and reasoning knowledge, sensitivity, and reasoning

• Study-specific measures of knowledge of standards and Study-specific measures of knowledge of standards and ethical sensitivity tap changes and correlate with existing ethical sensitivity tap changes and correlate with existing measures measures

• ESIT more appropriate for this population than MJT ESIT more appropriate for this population than MJT • Study-specific measure of moral reasoning might not be Study-specific measure of moral reasoning might not be

robust; ESIT seems more effective to measure changesrobust; ESIT seems more effective to measure changes• Instructor-student communication related to student Instructor-student communication related to student

ethical sensitivity and to student perceptions of ethical sensitivity and to student perceptions of classroom climateclassroom climate

November 10-11, 2011November 10-11, 2011Tempe, ArizonaTempe, Arizona

This two day meeting will bring together a wide array of This two day meeting will bring together a wide array of educators to share the programs, materials, and experience educators to share the programs, materials, and experience they’ve already developed as well as pioneer new strategies they’ve already developed as well as pioneer new strategies to help scientists and engineers understand the social and to help scientists and engineers understand the social and ethical implications of research. ethical implications of research.

Sponsored by the ASU Center for Nanotechnology in Society, the Sponsored by the ASU Center for Nanotechnology in Society, the Consortium for Science, Policy & Outcomes, the National Consortium for Science, Policy & Outcomes, the National Nanotechnology Infrastructure Network, and ASU NSF/EESE GrantsNanotechnology Infrastructure Network, and ASU NSF/EESE Grants

Acknowledgements Acknowledgements

• National Science FoundationNational Science Foundation

• Biological Design Ph.D. ProgramBiological Design Ph.D. Program

• Center for Biology and SocietyCenter for Biology and Society

• Center for Nanotechnology and SocietyCenter for Nanotechnology and Society

• Consortium for Science, Policy & Consortium for Science, Policy & OutcomesOutcomes

• Lincoln Center for Applied Ethics Lincoln Center for Applied Ethics