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Enhancing Engineering Students' Ethical Reasoning: Situating Reflexive Principlism within the SIRA Framework

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Title: Enhancing Engineering Students' Ethical Reasoning: Situating Reflexive Principlism within the SIRA Framework
Language: English
Authors: Hess, Justin L., Beever, Jonathan, Zoltowski, Carla B., Kisselburgh, Lorraine, Brightman, Andrew O.
Source: Journal of Engineering Education. Jan 2019 108(1):82-102.
Availability: Wiley Periodicals, Inc. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA
Peer Reviewed: Y
Page Count: 21
Publication Date: 2019
Sponsoring Agency: National Science Foundation (NSF)
Contract Number: 1237868
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Engineering Education, Ethical Instruction, Thinking Skills, Instructional Effectiveness, Empathy, Perspective Taking, Graduate Students, Teaching Methods
Assessment and Survey Identifiers: Interpersonal Reactivity Index
DOI: 10.1002/jee.20249
ISSN: 1069-4730
Abstract: Background: Educating engineers to reason through the ethical decisions they encounter when developing or implementing new technologies is a critical challenge. However, engineering educators have not widely adopted a framework for preparing engineering students to analyze ethical issues. Purpose/Hypothesis: We developed and tested an approach for enhancing the ethical reasoning of engineering students. This approach integrates reflexive principlism, an ethical reasoning approach, within a structured learning framework, scaffolded, interactive, and reflective analysis, or SIRA. We hypothesized that students' ethical reasoning abilities and empathic perspective-taking tendencies would increase. Design/Method: We implemented and tested the integrated approach over five semesters with graduate-level engineering students through a quasi-experimental, controlled research design. We measured changes in ethical reasoning using the Engineering Ethical Reasoning Instrument (EERI) and the Defining Issues Test 2 (DIT2) and empathic tendencies using the Interpersonal Reactivity Index (IRI). We examined relationships among measures through correlation analysis. Results: The EERI instrumentation indicated that the approach significantly increased the ethical reasoning abilities of graduate-level engineering students. However, the DIT2 findings did not indicate change. The IRI indicated perspective-taking tendencies were enhanced and personal distress tendencies were reduced. Postcourse correlational data indicated moderate relationships between perspective-taking and ethical reasoning as measured by the IRI and the EERI indexes. Conclusions: This study provides a theoretical approach for developing ethical reasoning and empathic perspective-taking among graduate-level engineering students. It also provides a theoretical framework, a pedagogical approach, and evaluation methods that others may utilize.
Abstractor: As Provided
Entry Date: 2020
Accession Number: EJ1254180
Database: ERIC
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  Value: <anid>AN0134931137;6m401jan.19;2019Feb28.04:47;v2.2.500</anid> <title id="AN0134931137-1">Enhancing engineering students' ethical reasoning: Situating reflexive principlism within the SIRA framework </title> <p>Background: Educating engineers to reason through the ethical decisions they encounter when developing or implementing new technologies is a critical challenge. However, engineering educators have not widely adopted a framework for preparing engineering students to analyze ethical issues. Purpose/Hypothesis: We developed and tested an approach for enhancing the ethical reasoning of engineering students. This approach integrates reflexive principlism, an ethical reasoning approach, within a structured learning framework, scaffolded, interactive, and reflective analysis, or SIRA. We hypothesized that students' ethical reasoning abilities and empathic perspective‐taking tendencies would increase. Design/Method: We implemented and tested the integrated approach over five semesters with graduate‐level engineering students through a quasi‐experimental, controlled research design. We measured changes in ethical reasoning using the Engineering Ethical Reasoning Instrument (EERI) and the Defining Issues Test 2 (DIT2) and empathic tendencies using the Interpersonal Reactivity Index (IRI). We examined relationships among measures through correlation analysis. Results: The EERI instrumentation indicated that the approach significantly increased the ethical reasoning abilities of graduate‐level engineering students. However, the DIT2 findings did not indicate change. The IRI indicated perspective‐taking tendencies were enhanced and personal distress tendencies were reduced. Postcourse correlational data indicated moderate relationships between perspective‐taking and ethical reasoning as measured by the IRI and the EERI indexes. Conclusions: This study provides a theoretical approach for developing ethical reasoning and empathic perspective‐taking among graduate‐level engineering students. It also provides a theoretical framework, a pedagogical approach, and evaluation methods that others may utilize.</p> <p>Keywords: critical reflection; ethics; ethical reasoning; instructional methods; reflexive principlism</p> <p>Educating engineers to effectively evaluate ethical issues they may encounter in their careers is a critical challenge for a nation that is advancing science and engineering technologies at an ever‐increasing rate (National Science Board, [<reflink idref="bib54" id="ref1">54</reflink>]). This is particularly challenging for engineers when their professional codes of ethics do not specifically address an ethical issue (gray areas) or when they encounter conflicting guidance (value conflicts). Rapid changes in technology can create novel ethical concerns where the application of existing codes of ethics becomes blurred or uncertain (Berry, Borenstein, & Butera, [<reflink idref="bib10" id="ref2">10</reflink>]; Riley & Lambrinidou, [<reflink idref="bib66" id="ref3">66</reflink>]). Because of an increased awareness of the importance of ethics in engineering, there is a growing call for enhanced ethics training from a variety of professional entities including accreditation boards (ABET, [<reflink idref="bib1" id="ref4">1</reflink>]), professional societies (American Society for Civil Engineers, [<reflink idref="bib2" id="ref5">2</reflink>]), and scholars across engineering disciplines (Barry & Ohland, [<reflink idref="bib4" id="ref6">4</reflink>]; Herkert, [<reflink idref="bib31" id="ref7">31</reflink>]; Sheppard et al., [<reflink idref="bib73" id="ref8">73</reflink>]). However, many engineering schools still do not specifically prepare students to reason through the ethical challenges posed by these new, emerging technologies (Culver et al., [<reflink idref="bib19" id="ref9">19</reflink>]). Furthermore, engineering educators have struggled to demonstrate that their efforts have effectively helped students develop the higher levels of ethical reasoning necessary for such analysis (Colby & Sullivan, [<reflink idref="bib18" id="ref10">18</reflink>]).</p> <p>The need to incorporate ethical reasoning development into engineering professional preparation was identified more than a decade ago by the Engineer of 2020 report (National Academy of Engineering, [<reflink idref="bib53" id="ref11">53</reflink>]). Specifically, the National Academy of Engineering (NAE) indicated that engineers need to "possess a working framework upon which <bold>high ethical standards</bold> and a strong sense of <bold>professionalism</bold> can be developed" (p. 56). Here, NAE describes a framework as more than knowledge alone, extending it to one that also includes an assemblage of facts, principles, values, perspectives, and abilities, which, when taken together, enable one to recognize and reason through ethical problems to an optimal ethical decision situated in a specific context.</p> <hd id="AN0134931137-2">STUDY PURPOSE</hd> <p>The purpose of this study was to evaluate the extent to which an integrated approach of applying reflexive principlism (Beever & Brightman, [<reflink idref="bib9" id="ref12">9</reflink>]) within a structured pedagogical framework of scaffolded, interactive, and reflective analysis (SIRA, Kisselburgh et al., [<reflink idref="bib44" id="ref13">44</reflink>]) could be effective in developing ethical reasoning abilities and empathic perspective‐taking tendencies of engineering students. To test the effectiveness of this approach, this study was guided by the research question: "What are the impacts of introducing reflexive principlism grounded within the SIRA pedagogical approach on the development of graduate‐level engineering students' ethical reasoning?"</p> <hd id="AN0134931137-3">BACKGROUND AND THEORY</hd> <p>This section includes four subsections. First, we provide an overview of models of moral development, with a particular focus on the cognitive model of the neo‐Kohlbergians (Rest et al., [<reflink idref="bib64" id="ref14">64</reflink>]) upon which the instruments used to measure ethical reasoning in this study were based. Second, we describe an ethical reasoning approach, reflexive principlism, arguing for its alignment with engineering design processes to promote the highest stages of ethical reasoning. Third, we argue that advanced ethical reasoning can be reached only if it operates in tandem with empathic perspective‐taking. Finally, we argue that the development of advanced ethical reasoning needs to be situated within an iterative, structured, and supportive learning environment.</p> <hd id="AN0134931137-4">Cognitive models of moral development</hd> <p>Several prominent models of moral development emphasize the cognitive development of the learner (Gibbs, [<reflink idref="bib28" id="ref15">28</reflink>]; Kohlberg, [<reflink idref="bib45" id="ref16">45</reflink>]; Perry, [<reflink idref="bib60" id="ref17">60</reflink>]; Selman, [<reflink idref="bib71" id="ref18">71</reflink>]), with studies finding that progression of moral development is highly correlated with such cognitive capacities as comprehension (Rest, Bebeau, & Thoma, [<reflink idref="bib62" id="ref19">62</reflink>]) or flexibility and adaptation (Endicott, Bock, & Narvaez, [<reflink idref="bib26" id="ref20">26</reflink>]). The Kohlbergian ([<reflink idref="bib45" id="ref21">45</reflink>]) framework of moral development and its neo‐Kohlbergian adaptations (Rest et al., [<reflink idref="bib62" id="ref22">62</reflink>]) are often relied upon, either implicitly or explicitly, by engineering ethics education scholars (Barry & Ohland, [<reflink idref="bib3" id="ref23">3</reflink>]; Drake et al., [<reflink idref="bib23" id="ref24">23</reflink>]; Finelli et al., [<reflink idref="bib27" id="ref25">27</reflink>]; Lozano et al., [<reflink idref="bib48" id="ref26">48</reflink>]; Nair, [<reflink idref="bib52" id="ref27">52</reflink>]; Rudnicka, Besterfield‐Sacre, & Shuman, [<reflink idref="bib67" id="ref28">67</reflink>]; Self & Ellison, [<reflink idref="bib70" id="ref29">70</reflink>]) even though this model is not accepted <emph>tout court</emph> among moral developmental theorists (Gibbs, [<reflink idref="bib28" id="ref30">28</reflink>]; Gilligan, [<reflink idref="bib29" id="ref31">29</reflink>]; Jorgensen, [<reflink idref="bib41" id="ref32">41</reflink>]). For example, Gilligan ([<reflink idref="bib29" id="ref33">29</reflink>]) criticized Kohlberg's model as deemphasizing relational and care‐based modes of ethical development. According to Gilligan, Kohlberg's focus was on individuation and separation, whereas an ethic of care focuses on connection and relationships (Gilligan [<reflink idref="bib29" id="ref34">29</reflink>]).</p> <p>Cognitive models of development are particularly relevant for initiatives in ethics education addressing ethical reasoning. Perry ([<reflink idref="bib60" id="ref35">60</reflink>]), who developed one of the first models of intellectual/ethical development, concluded that it was essential for students to be able to manage multiple frameworks and competing perspectives when reasoning through any endeavor. Based on an extensive set of interviews with college students, he created a nine‐point scheme of intellectual/ethical development. In this model, individuals advance from an initial position where they perceive the world in dichotomous terms (i.e., good versus bad) to a final position in which the decision‐maker recognizes all knowledge as context‐dependent, conditional, and uncertain. To work through this complexity, the most advanced reasoners (i.e., Stage 9) in Perry's framework utilize ethical principles to justify their reasoning.</p> <p>Unlike for Perry, for whom ethical and cognitive development were intertwined, Kohlberg explicitly partitioned the two. According to Kohlberg ([<reflink idref="bib45" id="ref36">45</reflink>]), "moral stage is related to cognitive advance and to moral behavior, but our identification of moral stage must be based on moral reasoning alone" (p. 172). In addition, Kohlberg viewed moral development as separate but dependent upon one's "social perception or social perspective," suggesting "there is a horizontal sequence of steps in movement from logic to social perception to moral judgment" (p. 171). Kohlberg's model was longitudinal, encompassing development from childhood through adulthood. According to him, learners advance from preconventional stages, where they rely on obedience and self‐orientation, to postconventional stages, where they rely on universal ethical principles. Similar to Perry ([<reflink idref="bib60" id="ref37">60</reflink>]), Kohlberg's model suggests that ethical development culminates in a commitment to moral principles.</p> <p>The neo‐Kohlbergian theorists applied, expanded, and refined Kohlberg's framework in several ways. First, they reframed stages as "schema," or "general knowledge structures residing in long‐term memory" that are activated by external stimuli (Rest et al., [<reflink idref="bib64" id="ref38">64</reflink>], p. 389). This shift emphasizes that individuals are not rooted firmly in a given stage but rather their ethical reasoning, in situ, is dependent on their prior experiences, knowledge, and the decision‐making context. In alignment with this consideration, Rest et al. argued that tacit knowledge (such as that evoked by a multiple‐choice prompt) is a better mechanism for evaluating ethical development than verbal articulation alone (i.e., that evoked by an interview prompt such as in Kohlberg's study). Further, neo‐Kohlbergian theorists argue that schema are "more concrete than Kohlberg's stages," evidence of content rather than structure or "cognitive operations," and relative rather than "universal" (p. 384f).</p> <p>Despite the tensions and conflicts among varying theories and their prioritizations, the prevalence of the neo‐Kohlbergian model of moral development theory in engineering is a key reason why we utilized the Defining Issues Test 2 (DIT2) as a tool of analysis in this study for evaluating ethical reasoning development. It allows researchers to see how contemporary studies compare to previous efforts to understand ethical decision‐making. However, we complemented its use with two more contemporary analytic tools that include other aspects of ethical decision‐making as described below. Partnering analytic techniques enables us to evaluate the intersections between reasoning and sensitivity, both of which we agree are necessary components in the development of advanced levels of ethical decision‐making.</p> <p>The DIT2 exhibits similarities with Kohlberg's stages. For example, it depicts ethical reasoning cognitively with levels of variation and emphasizes an upward progression from preconventional toward postconventional reasoning. However, there are two key differences that we highlight as distinctions between it and Kohlberg's moral judgment interview. First, rather than emphasizing an invariant step‐wise progression, the DIT2 authors reconceptualized stages as "schema," where schema represent a tendency toward a specific type of reasoning stimulated by situational cues rather than an unwavering application of attributes of a given stage (Rest et al., [<reflink idref="bib64" id="ref39">64</reflink>]). Second, the postconventional reasoner of the DIT2 does not primarily emphasize justice but emphasizes multiple moral theories, for example utilitarianism and deontology, equally. Hence, beyond justice‐oriented reasoning, the DIT2 postconventional reasoner is generally open to reflecting on and, if necessary, criticizing societal norms.</p> <p>In addition to the DIT2, in this study we utilized the Engineering Ethical Reasoning Instrument (EERI). The key difference between it and the DIT2 is found in the scenarios presented (Zhu et al., [<reflink idref="bib84" id="ref40">84</reflink>]). Specifically, as past research suggests that engineering students were not engaged in nor saw the relevance of the DIT2 scenarios (Titus, Zoltowski, Huyck, & Oakes, [<reflink idref="bib78" id="ref41">78</reflink>]), the EERI was designed with scenarios familiar and relevant to these students, a change aligning with the rationale that it is necessary to evaluate engineering ethics by situating instrumentation in the discipline. Specifically, these scenarios are situated in engineering design and practice, and the authors developed cases based on actual engineering situations (Titus et al., [<reflink idref="bib78" id="ref42">78</reflink>]; Zhu et al., [<reflink idref="bib84" id="ref43">84</reflink>]) intended to engender familiarity in the respondents.</p> <p>Finally, we utilized the Interpersonal Reactivity Index (IRI) to measure and ascertain changes in empathic tendencies. This instrument, developed in social psychology (Davis, [<reflink idref="bib21" id="ref44">21</reflink>]), has recently been applied to engineering (Rasoal, Danielsson, & Jungert, [<reflink idref="bib61" id="ref45">61</reflink>]; Wang, Caroll, & Delaine, [<reflink idref="bib81" id="ref46">81</reflink>]). It provides a multidimensional approach for evaluating four empathic tendencies, perspective‐taking, fantasy, empathic concern, and personal distress.</p> <hd id="AN0134931137-5">Reflexive principlism as appropriate for advanced ethical reasoning</hd> <p>Neo‐Kohlbergian theorists emphasized four elements of advanced (postconventional) reasoning: (a) primacy of moral criteria, (b) appealing to ideals, (c) shareable ideals, and (d) full reciprocity (Rest et al., [<reflink idref="bib62" id="ref47">62</reflink>]). Reflexive principlism also emphasizes ethical principles, or shared norms, which ground ethical judgment and ethical reciprocity through full evaluation of stakeholder perspectives, each essential for advanced ethical reasoning. These four ethical principles, beneficence, nonmaleficence, respect for autonomy, and justice, are core to the approach of principlism that has become the central ethical training framework for the medical profession through the seminal work of Beauchamp and Childress ([<reflink idref="bib6" id="ref48">6</reflink>]) on biomedical ethics.</p> <p>Similarly, Beever and Brightman ([<reflink idref="bib9" id="ref49">9</reflink>]) have argued for the application of a principlist approach to ethical reasoning in engineering. They developed an approach, reflexive principlism, which includes iteration as a central component. They argued that reflexive principlism would be effective in engineering because of its close relation with other modes of advanced ethical reasoning and its alignment with problem‐solving approaches in engineering design. They proposed that iterative analysis of multiple cases with students reflectively evaluating the four principles with existing ethics codes and within contexts of the specific cases would create an opportunity to develop an advanced mode for reasoning through ethical dilemmas. With repeated practice over time, this approach to ethical reasoning would have the potential to become reflexive (i.e., habitual, instinctive) for the engineer, who would, therefore, more likely apply the approach in new situations and ethical challenges.</p> <p>Reflexive principlism applies four interrelated components of a reasoning process to arrive at an optimal ethical decision: identifying and specifying the four ethical principles in the context of the technical details of the case; identifying and considering the varied value perspectives of all stakeholders directly or indirectly related to the case; balancing all four principles while simultaneously reflecting on one's decisions in light of other normative judgments, professional ethical codes, and existing regulations; and justifying an optimal ethical decision based on a comprehensive analysis.</p> <p>The reflexive aspect emphasizes the habitual application of this approach over time through a series of varied cases. It facilitates critical reflection on and attunement of one's own views and values with the perspectives of others through activities such as interactive group decision‐making, especially those which include all the stakeholders potentially impacted by the implementation and outcomes of any decision. Further, Beever and Brightman ([<reflink idref="bib9" id="ref50">9</reflink>]) posited, and as we test in this study, this approach will enhance a reasoner's ethical sensitivity and judgment, thereby moving learners beyond their immature or conventional stages of reasoning as they internalize this systematic approach to ethical reasoning.</p> <hd id="AN0134931137-6">Perspective‐taking and advanced ethical reasoning</hd> <p>We argue that perspective‐taking works most effectively in tandem with a coherent ethical reasoning approach such as reflexive principlism. In a principlistic approach, if the reasoner lacks a holistic social‐moral perspective, the specification of the principles will be inaccurate, as they will lack a broader context. Beauchamp ([<reflink idref="bib5" id="ref51">5</reflink>]) provides a concise overview of this "four principles" approach based on respect for autonomy, nonmaleficence, beneficence, and justice in health care ethics.</p> <p>Beneficence requires an estimation of the overall good of a decision. A valid and accurate evaluation of overall goodness considers the perspectives of all stakeholders as well as a consideration of what "good" means to them. We can make the same argument for nonmaleficence, the counterpart of beneficence. Likewise, respect for autonomy is dependent on an accurate understanding of others' perspectives, which can be achieved to some extent through empathic perspective‐taking. As Beauchamp ([<reflink idref="bib5" id="ref52">5</reflink>]) explained, "To respect an autonomous agent is to recognize with due appreciation that person's capacities and perspectives, including his or her right to hold certain views, to make certain choices, and to take certain actions based on personal values and beliefs" (p. 4). Lastly, to effectively employ and evaluate justice requires a similar act of decentering to identify, explore, and empathize with the perspectives of others.</p> <p>The development of a tendency to take the perspective of another, that is, a "socio‐moral perspective" (Kohlberg, [<reflink idref="bib45" id="ref53">45</reflink>], p. 173), is an essential and aligned process of ethical reasoning development. In Kohlberg's framework, specifically, one advances from a "concrete individual perspective" aligned with preconventional thinking to a "member‐of‐society perspective" aligned with conventional thinking to a "prior‐to‐society perspective" aligned with postconventional thinking (p. 177). Postconventional reasoners seek to incorporate the complexity inherent in the wide array of stakeholder values and potential conflicts as they rationalize the best method for navigating ethical encounters.</p> <p>Scholars have argued that empathy is a core component of ethical reasoning (Hoffman, [<reflink idref="bib37" id="ref54">37</reflink>]; Oxley, [<reflink idref="bib57" id="ref55">57</reflink>]). More specifically, Hoffman argues that empathic perspective‐taking is a necessary component of advanced ethical decision‐making. It enables the ethical sensitivity that works in conjunction with ethical reasoning to enable one to imagine and comprehend another's worldview with some level of accuracy, a condition necessary for ethical decision‐making. A tendency to act in this manner is necessary, albeit insufficient by itself, for ethical reasoning in the context of engineering (Hess, Beever, et al., [<reflink idref="bib33" id="ref56">33</reflink>]). Thus, we share the view that among advanced reasoners, ethical principles and perspective‐taking operate in a reflective manner, with perspective‐taking informing principle specification and the principles guiding empathic perspective‐taking (Gibbs, [<reflink idref="bib28" id="ref57">28</reflink>]; Hess, Beever, et al., [<reflink idref="bib33" id="ref58">33</reflink>]; Hoffman, [<reflink idref="bib37" id="ref59">37</reflink>]).</p> <hd id="AN0134931137-7">Facilitating advanced reasoning through a SIRA framework</hd> <p>Given the complex nature of ethical development, it is difficult to develop approaches for enhancing or achieving the developmental processes of ethical decision‐making as evidenced by the limited body of work exploring this area in engineering education (examples of effective approaches include Borenstein et al., [<reflink idref="bib11" id="ref60">11</reflink>]; Drake et al., [<reflink idref="bib23" id="ref61">23</reflink>]; Loui, [<reflink idref="bib47" id="ref62">47</reflink>]; Wilson, [<reflink idref="bib83" id="ref63">83</reflink>]). According to Perry ([<reflink idref="bib60" id="ref64">60</reflink>]), to grow or develop, the learner must develop tools or a framework to cope with and work through complexity. This process requires that contradictions become explicit and that learners internalize the tools and values needed to reconcile contradictions. Likewise, Kohlberg ([<reflink idref="bib45" id="ref65">45</reflink>]) recognized development as a social process that requires working through moral problems. Hence, practicing ethical reasoning leads to the possibility for developmental advancement, although it does not ensure it.</p> <p>We designed the SIRA pedagogical framework to challenge and support students' use of reflexive principlism in the development of advanced reasoning in their analysis of ethical issues. We designed each of SIRA's core components and stages with the end objective of achieving an increased level of reflexive and postconventional moral thinking. Specifically, to develop reflexive responding among students, we relied on the theory of repeated practice for enhanced learning (Brown, Roediger, & McDaniel, [<reflink idref="bib13" id="ref66">13</reflink>]; Einstein & McDaniel, [<reflink idref="bib24" id="ref67">24</reflink>]; Karpicke & Roediger, [<reflink idref="bib42" id="ref68">42</reflink>]). To that end, students worked through four case studies over the course of a semester, each of which included appropriate levels of scaffolding and various modes of interactivity with other students, stakeholders, and experts offering technical and ethical opinions along with numerous required stages for reflective analysis including a final meta‐reflection. The SIRA pedagogical framework provides a structure to guide students through identifying, specifying, and balancing normative principles and justifying an optimal ethical decision. Table 1 provides an overview of the SIRA framework, including the learning types and core components of this six‐stage framework.</p> <p>SIRA pedagogical framework</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Stage #: Learning type</th><th align="left">Stage 1: Establishing knowledge</th><th align="left">Stage 2: Perspective‐taking</th><th align="left">Stage 3: Compare and contrast</th><th align="left">Stage 4: Inducing conflict</th><th align="left">Stage 5: Decision making and justification</th><th align="left">Stage 6: Meta‐reflection</th></tr></thead><tbody valign="top"><tr><td>Content</td><td>Case scenario, facts, and expert information</td><td>Self and other stakeholder perspectives</td><td>Comparing perspectives and principles</td><td>Expert ethical and technical opinions</td><td>Debate; Justification</td><td>Reflection on reasoning process</td></tr><tr><td>Delivery</td><td>Multimedia (video, images, or text)</td><td>Online posts</td><td>In‐class and online posts and responses</td><td>Multimedia (video, audio, or text)</td><td>In‐class discussion; Group case report</td><td>Written responses</td></tr><tr><td>Activity</td><td>Watching and reading</td><td>Reflective writing and reading</td><td>Moderated discussion</td><td>Listening and reading</td><td>Moderated discussion; Collaborative writing</td><td>Reflective writing</td></tr><tr><td>Scaffolding</td><td>Hard</td><td>Hard</td><td>Soft</td><td>Hard</td><td>Hard and soft</td><td>Hard</td></tr><tr><td>Interactivity</td><td>Low</td><td>Medium</td><td>High and medium</td><td>Medium</td><td>High</td><td>Low</td></tr><tr><td>Reflective analysis</td><td>Low</td><td>Medium</td><td>Medium</td><td>Medium</td><td>Medium</td><td>High</td></tr></tbody></table> </ephtml> </p> <p>202491003 Adapted from Kisselburgh et al. ([<reflink idref="bib44" id="ref69">44</reflink>]).</p> <p>While there are many similarities between SIRA and existing approaches for teaching ethics to engineers (Davis, [<reflink idref="bib20" id="ref70">20</reflink>]; Jones, [<reflink idref="bib40" id="ref71">40</reflink>]; Van De Poel & Royakkers, [<reflink idref="bib80" id="ref72">80</reflink>]; Whitbeck, [<reflink idref="bib82" id="ref73">82</reflink>]), we argue that SIRA is more expansive, particularly when integrated with reflexive principlism. Specifically, SIRA is distinct from other step‐based approaches commonly used in engineering curricula to analyze ethical case studies or vignettes given its nonlinearity. We paired SIRA with the reflexive principlism approach for a combined emphasis on ethical principles, their specification, their negotiation in situ among peers in a social setting, and repeated individual and group reflection on the process. In short, we designed the stages of the SIRA framework to help students internalize a mode of ethical reasoning rather than explore inconsistencies among normative ethical theories. For example, Davis ([<reflink idref="bib20" id="ref74">20</reflink>]), who uses Kantian‐ and utilitarian‐based step‐wise reasoning models, has participants respond to vignettes, utilizes discussion prompts to explore inconsistencies and challenges, and contrasts these frameworks with virtue‐based and social‐justice oriented theories, among others. While interactivity, scaffolding, and reflection are arguably components of each of these steps, SIRA requires each of them. We describe the grounding of each component in learning theory below.</p> <hd id="AN0134931137-8">Scaffolding</hd> <p>Scaffolding refers to the tools and resources provided to the learner to support the developmental learning process (Strobel & Idan, [<reflink idref="bib74" id="ref75">74</reflink>]). Hard scaffolds are consistent structures such as glossaries, reflection questions, additional expert information, and textual guides that instructors design in anticipation of expected obstacles to learning. Soft scaffolding refers to the types of dynamic and situation‐specific support provided by instructors that are tailored to individuals and groups (Brush & Saye, [<reflink idref="bib14" id="ref76">14</reflink>]; Saye & Brush, [<reflink idref="bib68" id="ref77">68</reflink>]). The intent of scaffolding is to support the learner in the early stages of complex problem‐solving with resources that, over time, become increasingly less necessary as the learner develops more advanced skills and confidence (Saye & Brush, [<reflink idref="bib69" id="ref78">69</reflink>]). This is a critical element for encouraging students to become independent learners and to reflexively raise their level of reasoning toward a postconventional stage/schema.</p> <p>We provided hard scaffolds for numerous activities throughout our pedagogical framework, including the establishment of knowledge (Stage 1), consideration of stakeholder perspectives (Stages 2 and 5), exploration of inconsistencies (Stage 4), and principle specification (Stages 5 and 6). One of our core goals was to prompt students to think from an other‐oriented perspective (Hoffman, [<reflink idref="bib37" id="ref79">37</reflink>]) rather than from the self‐oriented perspective. We designed prompts toward this end to promote ethical reasoning development in two unique ways. First, we selected prompts that could make stakeholders' values more salient to the learner with the intention of alleviating potential inhibitors to development (i.e., students' escape into commitment where the student relies solely on their own values; see Perry ([<reflink idref="bib60" id="ref80">60</reflink>])). For a learner to develop empathic perspective‐taking tendencies for others, the reasoner must be sensitive to the needs of key stakeholders, include these while specifying ethical principles, and commit to responding to those needs while making decisions. Second, we included structured activities (i.e., perspective‐taking) which we believed would stimulate a macroethical perspective (Herkert, [<reflink idref="bib31" id="ref81">31</reflink>]; Rest et al., [<reflink idref="bib62" id="ref82">62</reflink>]) that would translate into more effective decision‐making and justification (Stage 5).</p> <hd id="AN0134931137-9">Interactivity</hd> <p>Although the principlist approach of Beauchamp and Childress ([<reflink idref="bib6" id="ref83">6</reflink>]) has been implemented primarily as an individual reasoning approach, we designed several interactive dialogic components of SIRA to support an increased level of diverse perspective‐taking. We anticipated that more diverse perspective‐taking would require enhanced specification and balancing of ethical principles and, thus, lead to the overall development of more advanced ethical reasoning. This approach was based on the cognitive‐affective theory of learning with media (Moreno & Mayer, [<reflink idref="bib50" id="ref84">50</reflink>]; Moreno & Valdez, [<reflink idref="bib51" id="ref85">51</reflink>]). The staged framework of interactivity begins in Stage 1 where individuals acquire case‐specific facts (low interactivity). These are followed by Stage 2 perspective‐taking activities that include online postings and asynchronous discussions through which students compare and contrast perspectives of peers (medium interactivity). Stage 3 involves a facilitated discussion in the classroom (high interactivity) or alternatively, a recording of such a discussion for students to watch and discuss through online posts (medium interactivity). Stage 4 challenges students' perspectives by presenting contrasting opinions or facts; here, students again post online asynchronously (medium interactivity). In Stage 5, expert insights and opinions were dialogically engaged through student debate (high interactivity).</p> <p>In an interim implementation (Group 2 of the study intervention, described later), we added a third element of interactivity that challenged students to generate and justify an ethical solution as part of a small group of three to five students to facilitate deeper engagement with the complexity of the cases, peer perspectives, and individual values.</p> <hd id="AN0134931137-10">Reflective analysis</hd> <p>Reflective analysis (RA) was intended as a supportive form of experiential learning targeted toward professional development and actual practice (Osterman & Kottkamp, [<reflink idref="bib56" id="ref86">56</reflink>]; Thompson & Pascal, [<reflink idref="bib77" id="ref87">77</reflink>]). This component of SIRA involved thinking about the relationships and conflicts between value claims and perspectives, both personal and professional. RA can be a challenging process requiring intense scrutiny of one's own views and how they are situated within the views and opinions of others, particularly professional experts, and within the reality of actual experiences, demanding work that is "most successful as a collaborative effort" (Osterman & Kottkamp, [<reflink idref="bib56" id="ref88">56</reflink>], p. 2). This learning method has been applied effectively in other fields of professional practice such as medicine (Kim, [<reflink idref="bib43" id="ref89">43</reflink>]; Maudsley & Strivens, [<reflink idref="bib49" id="ref90">49</reflink>]) and social work (Boud, [<reflink idref="bib12" id="ref91">12</reflink>]).</p> <p>SIRA incorporates RA by requiring students to iteratively specify and balance principles; interact with peers and with stakeholder perspectives; and consider professional codes, regulations, and expectations, evoking a metalevel of RA through a final stage of individual reflection on one's overall reasoning process. Specifically, the reflective component of SIRA led students participating in this study through (a) identification of relevant facts, stakeholders, contextual issues, core ethical principles, and moral assumptions (Stages 2–5); (b) application of reflexive principlism by comparing ethical principles, stakeholder needs, and professional codes (Stages 3–5); (c) collaboration with others to negotiate, debate, and eventually offer a defensible and ethically valid decision (Stage 5); and (d) a meta‐reflection activity following each case where students reflected on their specification and application of the principles to the case context (Stage 6).</p> <hd id="AN0134931137-11">RESEARCH DESIGN AND METHODS</hd> <p></p> <hd id="AN0134931137-12">Learning context</hd> <p>We implemented and tested the reflexive principlism approach integrated within the SIRA learning framework across five semesters as part of a one‐credit graduate‐level course on engineering ethics. We introduced the approach and framework through an initial learning module, followed by four case study modules representing ethics cases over a range of engineering disciplines. We posited that this approach would lead to a higher level of ethical reasoning and perspective‐taking based on evaluations before and after completing the learning modules.</p> <hd id="AN0134931137-13">Participant overview</hd> <p>In total, 72 students (33 females, 46%; 39 males, 54%; ages 20–39 years) participated in this study between 2013 and 2015. A small portion of students were non‐U.S. citizens (<emph>n</emph> = 15, 21%), and a small portion reported a primary language other than English (<emph>n</emph> = 18, 25%). We divided the participants into three groups, with Group 1 students completing the ethics course in 2013, Group 2 in 2014 or 2015, and Group 3 serving as the comparison group. Table 2 provides an overview of the participant demographics from Group 1, Group 2, and the Comparison Group. Because of missing data, not all items total the sample size (e.g., we only had citizenship information for 12 of the 14 students in the Comparison Group).</p> <p>Demographic characteristics of participants</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left" /><th align="left">Group 1</th><th align="left">Group 2</th><th align="left">Comparison Group</th></tr></thead><tbody valign="top"><tr><td>Sample size</td><td>29</td><td>%</td><td>29</td><td>%</td><td>14</td><td>%</td></tr><tr><td>Gender</td><td>Female</td><td>17</td><td>59</td><td>9</td><td>31</td><td>7</td><td>50</td></tr><tr><td>Male</td><td>12</td><td>4</td><td>20</td><td>69</td><td>7</td><td>50</td></tr><tr><td>Engineering major</td><td>Biomedical</td><td>18</td><td>62</td><td>18</td><td>62</td><td>5</td><td>36</td></tr><tr><td>Other<xref ref-type="fn" rid="jee20249-note-0002" /></td><td>11</td><td>38</td><td>11</td><td>38</td><td>8</td><td>57</td></tr><tr><td>Citizenship</td><td>United States</td><td>24</td><td>83</td><td>22</td><td>76</td><td>9</td><td>64</td></tr><tr><td>Non‐United States</td><td>5</td><td>17</td><td>7</td><td>24</td><td>3</td><td>21</td></tr><tr><td>Primary language</td><td>English</td><td>21</td><td>72</td><td>21</td><td>72</td><td>11</td><td>79</td></tr><tr><td>Other</td><td>8</td><td>28</td><td>8</td><td>28</td><td>2</td><td>14</td></tr><tr><td>Participation mode</td><td>Hybrid</td><td>5</td><td>17</td><td>11</td><td>38</td><td>n/a</td><td>n/a</td></tr><tr><td>Online only</td><td>24</td><td>83</td><td>18</td><td>62</td><td>n/a</td><td>n/a</td></tr></tbody></table> </ephtml> </p> <ulist> <item>202490001 <emph>Note</emph>. Group 1 included students in a 2013 engineering education course; Group 2 included students in a 2014 or 2015 course.</item> <item>202490002 Other engineering majors included civil, electrical/computer, engineering education, industrial, materials science, and mechanical.</item> </ulist> <p>Students in Groups 1 and 2 enrolled in the engineering ethics course offered through a School of Biomedical Engineering, a course required for Master's‐level biomedical engineering students' degrees. Hence, the majority of Group 1 and 2 students were biomedical engineering majors (<emph>n</emph> = 36). Other academic areas of study included civil, electrical/computer, industrial, and mechanical engineering. Both distance and on‐campus students in this study participated in the course during the Spring 2013, Spring 2014, and Spring 2015 semesters, and only distance students participated in the course during the Summer 2013 and 2014 semesters. Hence, most students participated in an online format (<emph>n</emph> = 42) rather than in the in‐class/hybrid format (<emph>n</emph> = 16). The primary distinction between the online‐only and hybrid modes of participation was that the latter participated in a weekly facilitated group discussion, whereas the former watched recorded discussions and posted online responses to it. A comparison of student experiences based on their participation in these formats was conducted, the results indicating no differences in the ethical reasoning changes between the groups (Hess et al., [<reflink idref="bib35" id="ref92">35</reflink>]).</p> <p>While the experiences of Groups 1 and 2 students were similar in many respects, several changes in the intervention led to our decision to analyze these groups separately. Specifically, we implemented the following four changes in 2014 for Group 2:</p> <p></p> <ulist> <item> We shifted delivery of the learning materials from the GlobalHub™ Learning Management System to Pearson OpenClass, as the latter provided such additional features as an integrated player for scaffolding materials as students viewed recorded discussions.</item> <p></p> <item> While refining the cases and their content, we added case videos, including animated videos on reflexive principlism that compared this approach with utilitarianism and deontology.</item> <p></p> <item> For each case study or module, students completed a small group case report in which three to five students worked through and justified their proposed resolution to the case‐specific ethical challenge.</item> <p></p> <item> We added the IRI to our set of evaluation instruments to ascertain changes in students' self‐reported empathic tendencies.</item> </ulist> <p>To provide a basis for comparison, we collected comparative data from engineering students enrolled in four graduate seminars offered at the same university. We recruited these students through an email distributed by the instructors of the graduate seminars, and respondents were compensated with a $40 Amazon gift certificate after completing the second of the two evaluation sessions at the end of the semester. Comparison Group participants were current graduate students in a biomedical, civil, electrical/computer, engineering education, materials science, or nuclear engineering program. This sample was comparative demographically to the course participants in residency, although slightly more likely to be native English speakers and female, and less likely to be biomedical engineering majors. Furthermore, we conducted a series of independent samples <emph>t</emph>‐tests to determine if precourse responses to the survey constructs across groups were significantly different, these analyses indicating that precourse responses across all groups on all constructs were not significantly different. (These results are reported in Section 5.1.)</p> <hd id="AN0134931137-14">Research procedures</hd> <p>Participants completed precourse assessments during the first week of the course prior to the delivery of any learning material and postcourse assessments during the final week following the completion of all activities. The precourse measures included two ethical reasoning instruments, the Defining Issues Test 2 (DIT2, Rest et al., [<reflink idref="bib63" id="ref93">63</reflink>]) and the EERI (Zhu et al., [<reflink idref="bib84" id="ref94">84</reflink>]). Taken together, the average completion time for these instruments was approximately 45 min. In addition, students in Group 2 completed a 5‐ to 10‐min measure of empathic tendencies, the IRI (Davis, [<reflink idref="bib21" id="ref95">21</reflink>]). To analyze changes in ethical reasoning and self‐reported empathic tendencies, we conducted a set of comparative tests to determine whether there were statistically significant changes between the prescores and postscores. As a final component of this investigation, we analyzed correlations between students' empathic tendencies and ethical reasoning scores.</p> <hd id="AN0134931137-15">Defining Issues Test 2</hd> <p>The DIT2 (Rest et al., [<reflink idref="bib63" id="ref96">63</reflink>]) presents five ethical scenarios or challenges. In each, respondents rank 12 issues using a set of criteria such as "Great," "Much," "Some," "Little," or "No" to indicate how important they perceived each issue for their decision. Next, the respondents selected and rank‐ordered four of the 12 issues they perceived as most important. The ethical challenges in DIT2 scenarios deal with stealing from a rich man during a famine, whether to report a dated story that could hurt a political candidate's reputation, a school board meeting, drug dosage prescriptions for a dying cancer patient, or political demonstrations against oil companies.</p> <p>The DIT2 results that we report in this study include (a) the P‐score, which reflects an individual's capacity for postconventional moral reasoning, and (b) the N2 score, which measures an individual's affinity for postconventional reasoning along with their rejection of preconventional or personal interest schema. This score is measured by adjusting the P‐score based on the "participants' ability to discriminate between [postconventional] items and lower stage [personal interest] items" (Thoma, [<reflink idref="bib75" id="ref97">75</reflink>], p. 80). These scores provide quantitative measures of the level of moral judgment of the respondents, where higher N2 and P‐scores reflect a greater propensity for postconventional ethical reasoning.</p> <hd id="AN0134931137-16">Engineering ethical reasoning instrument</hd> <p>The second ethical reasoning instrument we utilized was a short form of the recently developed EERI (Zhu et al., [<reflink idref="bib84" id="ref98">84</reflink>]). Although markedly like the DIT2, the EERI instrument evaluates ethical reasoning with respect to engineering‐specific ethical challenges (Titus et al., [<reflink idref="bib78" id="ref99">78</reflink>]; Zhu et al., [<reflink idref="bib84" id="ref100">84</reflink>]). As with the DIT2, respondents identify how important they perceive a set of issues in response to each ethical challenge or scenario. For each scenario, respondents specify their perception of the importance of 14 statements of reasoning (responses include "Great," "Much," "Some," "Little," and "No") and then select and rank order the four most important items.</p> <p>The four EERI scenarios utilized in this study include the design of a racing go‐cart for differently abled children, housing quality and city planning, distribution of governmental funds for a flood‐control system, the installation and security of a server with personal information, and reporting findings from a water quality test tied to a large local employer.</p> <hd id="AN0134931137-17">Interpersonal reactivity index</hd> <p>As an additional measure to evaluate ethical reasoning, we explored changes in respondents' self‐reported empathic tendencies by utilizing the IRI (Davis, [<reflink idref="bib21" id="ref101">21</reflink>]). This instrument provides a multidimensional approach for evaluating empathy through four empathy constructs: (a) perspective‐taking (the tendency to consider another's viewpoint), (b) fantasy (the tendency to project oneself into the shoes of fictitious characters), (c) empathic concern (the tendency to have other‐oriented feelings of concern or sympathy), and (d) personal distress (the tendency to become anxious in emotional or tense interpersonal situations). The IRI includes 28 items with seven items loading onto each construct.</p> <hd id="AN0134931137-18">RESULTS</hd> <p></p> <hd id="AN0134931137-19">Precourse comparisons</hd> <p>To ascertain whether ethical reasoning scores of groups were significantly different at the time of the pretest, we conducted a series of independent samples <emph>t</emph>‐tests comparing precourse responses across groups on the EERI and DIT2 constructs. In each instance, we first checked Levene's test for equality of variances. In all instances, we assumed equal variances except for the EERI precourse scores for Group 1 versus the Comparison, <emph>F</emph> = 4.535, <emph>p</emph> < 0.05. Through this analysis, we did not find any significant differences in precourse responses on any of the survey constructs as seen in Table 3.</p> <p>Comparison of precourse responses across groups</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Group</th><th align="left">Group 1 versus Group 2</th><th align="left">Group 1 versus Comparison</th><th align="left">Group 2 versus Comparison</th></tr><tr><th align="left"><italic>t</italic></th><th align="left"><italic>p</italic> (two‐tailed)</th><th align="left"><italic>t</italic></th><th align="left"><italic>p</italic> (two‐tailed)</th><th align="left"><italic>t</italic></th><th align="left"><italic>p</italic> (two‐tailed)</th></tr></thead><tbody valign="top"><tr><td>EERI N2</td><td>−0.606</td><td>0.547</td><td>0.707</td><td>0.483</td><td>0.323</td><td>0.749</td></tr><tr><td>EERI P</td><td>−1.196</td><td>0.237</td><td>0.831<xref ref-type="fn" rid="jee20249-note-0003" /></td><td>0.417</td><td>0.164</td><td>0.871</td></tr><tr><td>DIT2 N2</td><td>−0.974</td><td>0.334</td><td>0.097</td><td>0.924</td><td>−0.731</td><td>0.469</td></tr><tr><td>DIT2 P</td><td>−1.107</td><td>0.273</td><td>0.454</td><td>0.652</td><td>−0.453</td><td>0.653</td></tr></tbody></table> </ephtml> </p> <p>202490003 Equal variances not assumed.</p> <hd id="AN0134931137-20">Changes in ethical reasoning with general moral dilemmas via the DIT2</hd> <p>As an initial strategy to evaluate the effect of the intervention on students' ethical reasoning changes, we utilized the DIT2. The results indicated that Group 1 participants' precourse N2 responses (<emph>M</emph> = 41.0; <emph>SD</emph> = 14.4) were below those of Group 2 (<emph>M</emph> = 44.7, <emph>SD</emph> = 14.5). While this trend held postcourse, the gap between Group 1 (<emph>M</emph> = 41.9, <emph>SD</emph> = 15.7) and Group 2 (<emph>M</emph> = 42.7, <emph>SD</emph> = 16.0) decreased. The Comparison Group's precourse N2 scores (<emph>M</emph> = 41.4, <emph>SD</emph> = 11.9) were between those of Groups 1 and 2 although their final average score (<emph>M</emph> = 41.8, <emph>SD</emph> = 12.6) was below both groups' scores. These trends held for the P‐score. We present both the P‐scores and N2 scores as scholars have used the former longer. However, we emphasize the N2 score in the discussion as the DIT2 designers consider it the more valid measure (Rest et al., [<reflink idref="bib63" id="ref102">63</reflink>]). Table 4 provides an overview of the DIT2 precourse, postcourse, and difference scores for each group.</p> <p>Defining Issues Test 2 (DIT2) descriptive statistics</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Group</th><th align="left">Statistic</th><th align="left">Prescore</th><th align="left">Postscore</th><th align="left">Difference</th></tr><tr><th align="left"><italic>M</italic></th><th align="left"><italic>SD</italic></th><th align="left"><italic>M</italic></th><th align="left"><italic>SD</italic></th><th align="left"><italic>M</italic></th><th align="left"><italic>SD</italic></th></tr></thead><tbody valign="top"><tr><td><p>Group 1</p><p>(<italic>n</italic> = 29)</p></td><td>N2</td><td>41.0</td><td>14.4</td><td>41.9</td><td>15.7</td><td>0.93</td><td>12.8</td></tr><tr><td>P</td><td>37.6</td><td>16.5</td><td>38.6</td><td>17.2</td><td>1.03</td><td>14.0</td></tr><tr><td><p>Group 2</p><p>(<italic>n</italic> = 29)</p></td><td>N2</td><td>44.7</td><td>14.5</td><td>42.7</td><td>16.0</td><td>−1.97</td><td>12.9</td></tr><tr><td>P</td><td>42.5</td><td>17.2</td><td>41.0</td><td>18.7</td><td>−1.45</td><td>16.2</td></tr><tr><td><p>Comparison</p><p>(<italic>n</italic> = 14)</p></td><td>N2</td><td>41.4</td><td>11.9</td><td>41.8</td><td>12.6</td><td>0.36</td><td>15.5</td></tr><tr><td>P</td><td>40.0</td><td>16.1</td><td>38.7</td><td>13.7</td><td>−1.29</td><td>18.0</td></tr></tbody></table> </ephtml> </p> <p>We conducted a series of comparison tests to ascertain if the pre‐/postscores were significantly different. For each test, the null hypothesis was that N2 and P difference scores would not be significantly different from zero. The alternative hypothesis was that, for each group, the differences scores would be significantly different from zero.</p> <p>As a first step, we calculated the Shapiro–Wilk statistic (Shapiro & Wilk, [<reflink idref="bib72" id="ref103">72</reflink>]) for the difference scores for each measure. For the Comparison Group, the N2 difference score distribution was approximately nonnormal (<emph>W</emph> = 0.83; <emph>p</emph> < 0.05). The data were approximately normal for all other measures, supporting the use of parametric testing (see Table 5). Second, we implemented a Bonferroni adjustment to establish a more stringent alpha level to help avoid Type 1 errors. We divided an alpha of 0.05 by the number of comparisons for each group, that is, two, establishing an alpha of 0.025 as the threshold for significance.</p> <p>Defining Issues Test 2 (DIT2) independent samples t‐test results</p> <p> <ephtml> <table><thead valign="bottom"><tr><th>Group</th><th align="left">Statistic</th><th align="left">Normality tests</th><th align="left">95% CI</th><th align="left"><italic>t</italic>‐test results</th></tr><tr><th align="left"><italic>W</italic></th><th align="left"><italic>p</italic> (two‐tailed)</th><th align="left">Lower</th><th align="left">Upper</th><th align="left"><italic>t</italic>‐stat.</th><th align="left"><italic>p</italic> (two‐tailed)</th><th align="left"><italic>d</italic></th></tr></thead><tbody valign="top"><tr><td><p>Group 1</p><p>(<italic>n</italic> = 29)</p></td><td>N2</td><td>0.99</td><td>1.00</td><td>−3.92</td><td>5.78</td><td>0.39</td><td>0.70</td><td>0.09</td></tr><tr><td>P</td><td>0.99</td><td>0.97</td><td>−4.29</td><td>6.36</td><td>0.40</td><td>0.69</td><td>0.09</td></tr><tr><td><p>Group 2</p><p>(<italic>n</italic> = 29)</p></td><td>N2</td><td>0.97</td><td>0.65</td><td>−6.86</td><td>2.93</td><td>−0.82</td><td>0.42</td><td>−0.18</td></tr><tr><td>P</td><td>0.97</td><td>0.58</td><td>−7.61</td><td>4.71</td><td>−0.48</td><td>0.63</td><td>−0.11</td></tr><tr><td><p>Comparison</p><p>(<italic>n</italic> = 14)</p></td><td>N2</td><td>0.83</td><td>0.01</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>P</td><td>0.94</td><td>0.47</td><td>−11.68</td><td>9.11</td><td>−0.27</td><td>0.79</td><td>−0.12</td></tr></tbody></table> </ephtml> </p> <p>202490004 <emph>Note</emph>. <ephtml> <math display="inline" overflow="scroll" altimg="urn:x-wiley:10694730:media:jee20249:jee20249-math-0001" xmlns="http://www.w3.org/1998/Math/MathML"><mi mathvariant="normal">d</mi><mo>=</mo><msub><mi mathvariant="normal">M</mi><mn>1</mn></msub><mo>−</mo><msub><mi mathvariant="normal">M</mi><mn>2</mn></msub><mo>/</mo><mrow><mo stretchy="true">(</mo><msqrt><mo>(</mo><msup><mrow><mi mathvariant="normal">S</mi><msub><mi mathvariant="normal">D</mi><mn>1</mn></msub></mrow><mn>2</mn></msup><mo>+</mo><msup><mrow><mi mathvariant="normal">S</mi><msub><mi mathvariant="normal">D</mi><mn>2</mn></msub></mrow><mn>2</mn></msup><mo>)</mo></msqrt><mo>/</mo><mn>2</mn><mo stretchy="true">)</mo></mrow><mo>.</mo></math> </ephtml></p> <p>Finally, we conducted a series of paired samples <emph>t</emph>‐tests to evaluate pre‐/postscores on the DIT2 constructs for the normally distributed measures. These analyses revealed no significant changes for Group 1, Group 2, or the Comparison Group on any DIT2 measure. The largest change by magnitude was Group 2's N2 score which decreased from prescore (<emph>M</emph> = 44.7, <emph>SD</emph> = 14.5) to postscore (<emph>M</emph> = 42.7, <emph>SD</emph> = 16.0). Although this change was not significant, <emph>t</emph>(<reflink idref="bib28" id="ref104">28</reflink>) = −0.82, <emph>p</emph> = 0.42 (two‐tailed), it exhibited a small effect size (<emph>d</emph> = −0.18) using Cohen's ([<reflink idref="bib16" id="ref105">16</reflink>]) suggested thresholds (i.e., <emph>d</emph> > 0.20 indicates small effect, <emph>d</emph> > 0.50 = moderate effect, and <emph>d</emph> > 0.80 indicates large effect). Table 5 summarizes these results.</p> <hd id="AN0134931137-21">Changes in ethical reasoning with engineering‐specific cases via the EERI</hd> <p>As a second strategy to determine the effect of the intervention on students' ethical reasoning development, we applied the EERI. Group 1's precourse N2 responses (<emph>M</emph> = 41.0; <emph>SD</emph> = 18.1) were below those of Group 2 (<emph>M</emph> = 43.7; <emph>SD</emph> = 15.7). While this trend held for postcourse scores, the difference between the scores of Group 1 (<emph>M</emph> = 49.5; <emph>SD</emph> = 22.4) and Group 2 (<emph>M</emph> = 54.2; <emph>SD</emph> = 18.7) increased. Further, the Comparison Group's precourse N2 scores (<emph>M</emph> = 45.6; <emph>SD</emph> = 24.5) were above those of Groups 1 and 2 although their final average score (<emph>M</emph> = 49.6; <emph>SD</emph> = 23.9) was between the two. These trends were similar for the P‐score, with some slight differences; for example, the difference scores for Groups 1 and 2 were almost identical, and the final P‐score of the Comparison Group was between those. Table 6 summarizes these results.</p> <p>Descriptive statistics from the Engineering Ethical Reasoning Instrument</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Group</th><th align="left">Statistic</th><th align="left">Prescore</th><th align="left">Postscore</th><th align="left">Difference</th></tr><tr><th align="left"><italic>M</italic></th><th align="left"><italic>SD</italic></th><th align="left"><italic>M</italic></th><th align="left"><italic>SD</italic></th><th align="left"><italic>M</italic></th><th align="left"><italic>SD</italic></th></tr></thead><tbody valign="top"><tr><td><p>Group 1</p><p>(<italic>n</italic> = 29)</p></td><td>N2</td><td>41.0</td><td>18.1</td><td>49.5</td><td>22.4</td><td>8.5</td><td>19.4</td></tr><tr><td>P</td><td>38.5</td><td>15.6</td><td>46.1</td><td>20.0</td><td>7.6</td><td>18.0</td></tr><tr><td><p>Group 2</p><p>(<italic>n</italic> = 29)</p></td><td>N2</td><td>43.7</td><td>15.7</td><td>54.2</td><td>18.7</td><td>10.5</td><td>20.1</td></tr><tr><td>P</td><td>43.6</td><td>16.7</td><td>51.1</td><td>20.9</td><td>7.5</td><td>22.1</td></tr><tr><td><p>Comparison</p><p>(<italic>n</italic> = 14)</p></td><td>N2</td><td>45.6</td><td>24.5</td><td>49.6</td><td>23.9</td><td>4.0</td><td>32.7</td></tr><tr><td>P</td><td>44.6</td><td>25.4</td><td>47.7</td><td>19.8</td><td>3.1</td><td>29.7</td></tr></tbody></table> </ephtml> </p> <p>To test whether pre/post differences were significant for any group on any variable, we conducted a series of comparison tests using the same procedures as those for the DIT2 analysis. Prior to comparative testing, we calculated the Shapiro–Wilk statistic (Shapiro & Wilk, [<reflink idref="bib72" id="ref106">72</reflink>]) for the difference scores for each measure to determine the appropriateness of utilizing parametric testing. For Groups 1 and 2, these findings indicated the data distribution was approximately normal (see Table 7) although the P difference score distribution of the Comparison Group was approximately nonnormal (<emph>W</emph> = 0.86, <emph>p</emph> < 0.05).</p> <p>Results from the Engineering Ethical Reasoning Instrument independent samples t‐test</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Group</th><th align="left">Statistic</th><th align="left">Normality tests</th><th align="left">95% CI</th><th align="left"><italic>t</italic>‐test results</th></tr><tr><th align="left"><italic>W</italic></th><th align="left"><italic>p</italic> (two‐tailed)</th><th align="left">Lower</th><th align="left">Upper</th><th align="left"><italic>t</italic>‐stat.</th><th align="left"><italic>p</italic> (one‐tailed)</th><th align="left"><italic>d</italic></th></tr></thead><tbody valign="top"><tr><td><p>Group 1</p><p>(<italic>n</italic> = 29)</p></td><td>N2</td><td>0.96</td><td>0.33</td><td>1.10</td><td>15.86</td><td>2.35</td><td>0.013</td><td>0.59</td></tr><tr><td>P</td><td>0.98</td><td>0.76</td><td>0.79</td><td>14.45</td><td>2.29</td><td>0.015</td><td>0.60</td></tr><tr><td><p>Group 2</p><p>(<italic>n</italic> = 29)</p></td><td>N2</td><td>0.97</td><td>0.43</td><td>2.87</td><td>18.16</td><td>2.82</td><td>0.005</td><td>0.86</td></tr><tr><td>P</td><td>0.98</td><td>0.77</td><td>−0.90</td><td>15.93</td><td>1.83</td><td>0.039</td><td>0.56</td></tr><tr><td><p>Comparison</p><p>(<italic>n</italic> = 14)</p></td><td>N2</td><td>0.96</td><td>0.76</td><td>−14.90</td><td>22.90</td><td>0.46</td><td>0.327</td><td>0.23</td></tr><tr><td>P</td><td>0.86</td><td>0.03</td><td>–</td><td>–</td><td>–</td><td>–</td><td>–</td></tr></tbody></table> </ephtml> </p> <p>202490005 <emph>Note</emph>. We did not report results for the Comparison Group on the P‐score due to the approximately nonnormal distribution of participant responses on this statistic.</p> <p>Then, we conducted a paired‐samples <emph>t</emph>‐test for each group on each normally distributed score to determine whether there were statistically significant differences between prescores and postscores. Table 7 summarizes these results. The Group 1 EERI N2 score significantly increased from prescore (<emph>M</emph> = 41.0, <emph>SD</emph> = 18.1) to postscore (<emph>M</emph> = 49.5, <emph>SD</emph> = 22.4), <emph>t</emph>(<reflink idref="bib28" id="ref107">28</reflink>) = 2.35, <emph>p</emph> = 0.013 (one‐tailed), with a medium effect size (<emph>d</emph> = 0.59); and the Group 1 P‐score significantly increased from prescore (<emph>M</emph> = 38.5, <emph>SD</emph> = 15.6) to postscore (<emph>M</emph> = 46.1, <emph>SD</emph> = 20.0), <emph>t</emph>(<reflink idref="bib28" id="ref108">28</reflink>) = 2.29, <emph>p</emph> = 0.015 (one‐tailed) with a medium effect size (<emph>d</emph> = 0.60). Likewise, Group 2's EERI N2 score significantly increased from prescore (<emph>M</emph> = 43.7, <emph>SD</emph> = 15.7) to postscore (<emph>M</emph> = 54.2, <emph>SD</emph> = 18.7), <emph>t</emph>(<reflink idref="bib28" id="ref109">28</reflink>) = 2.82, <emph>p</emph> < 0.01 (one‐tailed), and exhibited a large effect size (<emph>d</emph> = 0.86). While not significant at an alpha threshold of 0.025, Group 2's EERI P‐score increased from prescore (<emph>M</emph> = 43.6, <emph>SD</emph> = 16.7) to postscore (<emph>M</emph> = 51.1, <emph>SD</emph> = 20.9), <emph>t</emph>(<reflink idref="bib28" id="ref110">28</reflink>) = 1.83, <emph>p</emph> = 0.039 (one‐tailed), and exhibited a moderate effect size (<emph>d</emph> = 0.56). The Comparison Group did not show significant changes on the N2 score from prescore (<emph>M</emph> = 45.6, <emph>SD</emph> = 24.5) to postscore (<emph>M</emph> = 49.6, <emph>SD</emph> = 23.9), <emph>t</emph>(<reflink idref="bib13" id="ref111">13</reflink>) = 0.46, <emph>p</emph> = 0.327, although it exhibited a small effect size (<emph>d</emph> = 0.23). This study used Cohen's ([<reflink idref="bib16" id="ref112">16</reflink>]) criterion for effect sizes. These findings suggest that the intervention had a strong impact on students' ethical reasoning development, specifically in responding to engineering‐specific ethical scenarios.</p> <p>As a final step, we examined whether the difference scores of Groups 1 or 2 were significantly different from those of the Comparison Group. We implemented a series of independent samples <emph>t</emph>‐tests rather than multivariate analyses (i.e., MANCOVA) as we hypothesized that the results from Groups 1 and 2 would be significantly different from the Comparison Group's. However, we did not hypothesize that the difference scores for Groups 1 and 2 would be different. The alternative hypothesis was that the difference scores would be approximately equal.</p> <p>Levene's <emph>t</emph>‐test for equality of variances between groups indicated that the precourse score variances of the Comparison Group were approximately equal to those from both Groups 1 and 2, with one exception: the variances between the precourse P‐scores for Group 1 and the Comparison Group were approximately nonequal (<emph>F</emph> = 4.54, <emph>p</emph> < 0.05). Due to this finding, we compared only the N2 difference scores. Next, we conducted a series of independent samples <emph>t</emph>‐tests to determine whether students' EERI N2 precourse responses were approximately equal. The results of this analyses indicated that these responses were not significantly different for Group 1 versus the Comparison Group, <emph>t</emph>(<reflink idref="bib41" id="ref113">41</reflink>) = 0.32, <emph>p</emph> = 0.75 (two‐tailed) or Group 2 versus the Comparison Group, <emph>t</emph>(<reflink idref="bib41" id="ref114">41</reflink>) = 0.71, <emph>p</emph> = 0.48 (two‐tailed).</p> <p>An independent‐samples <emph>t</emph>‐test indicated no significant difference in the difference scores (i.e., postscore minus prescore) for Group 1 (<emph>M</emph> = 8.5, <emph>SD</emph> = 19.4) and the Comparison Group (<emph>M</emph> = 4.0, <emph>SD</emph> = 32.7), <emph>t</emph>(<reflink idref="bib41" id="ref115">41</reflink>) = 0.56, <emph>p</emph> = 0.58 (two‐tailed). The magnitude of the differences in the means (<emph>M</emph><subs><emph>D</emph></subs> = 4.5, 95% CI = −11.57 to 20.54) was very small (<emph>d</emph> = 0.17). A second independent‐samples <emph>t</emph>‐test indicated no significant difference in the difference scores for Group 2 (<emph>M</emph> = 10.5, <emph>SD</emph> = 20.1) and the Comparison Group (<emph>M</emph> = 4.0, <emph>SD</emph> = 32.7), <emph>t</emph>(<reflink idref="bib41" id="ref116">41</reflink>) = 0.807, <emph>p</emph> = 0.42 (two‐tailed) although these difference scores (<emph>M</emph><subs><emph>D</emph></subs> = 6.52, 95% CI = −9.79 to 22.82) exhibited a small effect size (<emph>d</emph> = 0.24). These results suggest that the intervention was more effective at enhancing students' ethical reasoning in engineering‐specific scenarios compared to graduate‐level students who were not part of the intervention but who participated in discipline‐specific seminars.</p> <hd id="AN0134931137-22">Changes in empathic tendencies</hd> <p>To evaluate the connection between empathy and ethical reasoning, we examined the effect of the intervention on the development of the students' empathic tendencies. We used the IRI (Davis, [<reflink idref="bib21" id="ref117">21</reflink>]), in which students self‐report their responses on a 5‐point Likert‐type scale ranging from 1, "Does Not Describe Me Well," to 5, "Describes Me Very Well," on four subscales. Since we introduced the IRI partway through the research project, we do not have IRI data for Group 1. In addition, one of the Comparison participants did not complete this portion of the survey. Table 8 summarizes these statistics.</p> <p>Descriptive statistics from the Interpersonal Reactivity Index</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Group</th><th align="left">Statistic</th><th align="left">Prescore</th><th align="left">Postscore</th><th align="left">Diff. scores</th></tr><tr><th align="left"><italic>M</italic></th><th align="left"><italic>SD</italic></th><th align="left"><italic>M</italic></th><th align="left"><italic>SD</italic></th><th align="left"><italic>M</italic></th><th align="left"><italic>SD</italic></th></tr></thead><tbody valign="top"><tr><td><p>Group 2</p><p>(<italic>n</italic> = 29)</p></td><td>Fantasy</td><td>3.29</td><td>0.58</td><td>3.28</td><td>0.64</td><td>−0.02</td><td>0.54</td></tr><tr><td>Perspective‐Taking</td><td>3.53</td><td>0.65</td><td>3.82</td><td>0.58</td><td>0.29</td><td>0.52</td></tr><tr><td>Empathic Concern</td><td>3.60</td><td>0.65</td><td>3.81</td><td>0.63</td><td>0.21</td><td>0.51</td></tr><tr><td>Personal Distress</td><td>2.56</td><td>0.62</td><td>2.31</td><td>0.65</td><td>−0.24</td><td>0.43</td></tr><tr><td><p>Comparison</p><p>(<italic>n</italic> = 13)</p></td><td>Fantasy</td><td>3.03</td><td>0.68</td><td>3.25</td><td>0.61</td><td>0.22</td><td>0.48</td></tr><tr><td>Perspective‐Taking</td><td>3.54</td><td>0.56</td><td>3.55</td><td>0.71</td><td>0.01</td><td>0.48</td></tr><tr><td>Empathic Concern</td><td>3.68</td><td>0.79</td><td>3.65</td><td>0.73</td><td>−0.03</td><td>0.38</td></tr><tr><td>Personal Distress</td><td>2.53</td><td>0.58</td><td>2.67</td><td>0.55</td><td>0.14</td><td>0.44</td></tr></tbody></table> </ephtml> </p> <p>202490006 <emph>Note</emph>. Responses were on a five‐point Likert‐type scale where 1 = strongly disagree and 5 = strongly agree.</p> <p>To test whether pre‐/postscores were significantly different for either group, we conducted a series of comparison tests. For each test, the null hypothesis was that students' difference scores on each IRI subscale would not be significantly different from zero, with the alternative hypothesis being that the differences would be significantly greater than zero. We implemented a Bonferroni adjustment, dividing an alpha of 0.05 by the number of comparisons for each group (four), establishing an alpha of 0.0125 as the threshold for significance. Next, we calculated the Shapiro–Wilk statistics (Shapiro & Wilk, [<reflink idref="bib72" id="ref118">72</reflink>]) for the difference scores for each measure. For Group 2, the data distributions for Fantasy (<emph>W</emph> = 0.86, <emph>p</emph> < 0.01) and Empathic Concern (<emph>W</emph> = 0.85, <emph>p</emph> < 0.01) were approximately nonnormal. Based on these results, we used nonparametric testing procedures to compare these pre/post responses.</p> <p>Two paired‐samples <emph>t</emph>‐tests were conducted to evaluate the changes between prescores and postscores for the normally distributed IRI constructs of Group 2, the results indicating that this Group exhibited a significant increase in Perspective‐Taking from prescore (<emph>M</emph> = 3.53; <emph>SD</emph> = 0.65) to postscore (<emph>M</emph> = 3.82; <emph>SD</emph> = 0.58), <emph>t</emph>(<reflink idref="bib29" id="ref119">29</reflink>) = 3.00, <emph>p</emph> < 0.05 (two‐tailed) with a medium effect size (<emph>d</emph> = 0.67). Group 2 showed a significant decrease in Personal Distress from prescore (<emph>M</emph> = 2.56; <emph>SD</emph> = 0.62) to postscore (<emph>M</emph> = 2.31; <emph>SD</emph> = 0.65), <emph>t</emph> = −3.05, <emph>p</emph> < 0.01, with a medium effect size (<emph>d</emph> = −0.53). For the nonnormally distributed IRI constructs of Empathic Concern and Fantasy, we conducted Wilcoxon Signed Ranks tests. These analyses indicated that the median Empathic Concern responses for Group 2 participants did not exhibit a significant difference from prescore (<emph>M</emph><subs><emph>D</emph></subs> = 3.57) to postscore (<emph>M</emph><subs><emph>D</emph></subs> = 3.86), <emph>z</emph> = −2. 02, <emph>p</emph> = 0.04, although it showed a moderate effect size (<emph>r</emph> = 0.38) using Cohen's ([<reflink idref="bib16" id="ref120">16</reflink>]) criteria of 0.3 = medium effect (we calculated <emph>r</emph> by dividing <emph>z</emph> by the square root of <emph>n</emph>).</p> <p>Next, we conducted a series of paired samples <emph>t</emph>‐tests to determine if the Comparison Group exhibited significant changes on any of the IRI constructs. While no result were significant at an alpha threshold of 0.0125, the Comparison Group exhibited a small effect size (<emph>d</emph> = 0.48) on the Fantasy subscale when comparing prescore (<emph>M</emph> = 3.03, <emph>SD</emph> = 0.68) and postscore (<emph>M</emph> = 3.25, <emph>SD =</emph> 0.61) responses, <emph>t</emph>(<reflink idref="bib12" id="ref121">12</reflink>) = 1.68, <emph>p</emph> = 0.06 (one‐tailed). Table 9 summarizes these results. These data suggest that the intervention had a strong impact on students' empathic dispositions as measured by the IRI, including their tendency to take others' perspectives and their tendency toward becoming anxious in tense interpersonal situations. Rephrased in positive terms, this latter finding suggests that Group 2 students had enhanced emotion regulation skills (i.e., the ability to manage emotions during stressful encounters; see Eisenberg & Spinrad, [<reflink idref="bib25" id="ref122">25</reflink>]) following the intervention.</p> <p>Results from the Interpersonal Reactivity Index independent samples t‐test</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Group</th><th align="left">Statistic</th><th align="left">95% CI</th><th align="left"><italic>t</italic>‐test or Wilcoxon results</th></tr><tr><th align="left">Lower</th><th align="left">Upper</th><th align="left"><italic>t</italic>‐stat. (or Z)</th><th align="left"><italic>p</italic> (one‐tailed)</th><th align="left"><italic>d</italic></th></tr></thead><tbody valign="top"><tr><td><p>Group 2</p><p>(<italic>n</italic> = 29)</p></td><td>Fantasy</td><td>–</td><td>–</td><td>−0.30<xref ref-type="fn" rid="jee20249-note-0008" /></td><td>0.381</td><td align="left" /></tr><tr><td>Perspective‐Taking</td><td>0.09</td><td>0.49</td><td>3.00</td><td>0.003<xref ref-type="fn" rid="jee20249-note-0007" /></td><td>0.67</td></tr><tr><td>Empathic Concern</td><td>–</td><td>–</td><td>−2.02<xref ref-type="fn" rid="jee20249-note-0008" /></td><td>0.022</td><td align="left" /></tr><tr><td>Personal Distress</td><td>−0.41</td><td>−0.08</td><td>−3.05</td><td>0.003<xref ref-type="fn" rid="jee20249-note-0007" /></td><td>−0.53</td></tr><tr><td><p>Comparison</p><p>(<italic>n</italic> = 13)</p></td><td>Fantasy</td><td>−0.07</td><td>0.51</td><td>1.68</td><td>0.06</td><td>0.48</td></tr><tr><td>Perspective‐Taking</td><td>−0.28</td><td>0.30</td><td>0.08</td><td>0.47</td><td>0.02</td></tr><tr><td>Empathic Concern</td><td>−0.26</td><td>0.20</td><td>−0.31</td><td>0.38</td><td>−0.06</td></tr><tr><td>Personal Distress</td><td>−0.12</td><td>0.41</td><td>1.16</td><td>0.13</td><td>0.35</td></tr></tbody></table> </ephtml> </p> <ulist> <item>202490007 * <emph>p</emph> < 0.0125 (note that Bonferonni adjustments were implemented to determine the appropriate alpha threshold, calculated by dividing 0.05 by 4, the total number of comparisons per group).</item> <item>202490008 a Wilcoxon signed ranks tests were performed to compare response changes for Group 1's Fantasy and Empathic Concern responses as participants' response distributions were approximately nonnormal; hence, these data represent Wilcoxon Z‐stats rather than <emph>t</emph>‐stats.</item> </ulist> <p>As a final step, two independent samples <emph>t</emph>‐tests were conducted to determine whether the difference scores of Group 2 were significantly different from those of the Comparison Group for Perspective‐Taking or Personal Distress. As we conducted two tests, we implemented the Bonferroni adjustment and used an alpha threshold of 0.025 for significance. These analyses indicated that Personal Distress difference scores were significantly different between Group 2 (<emph>M</emph> = −0.24, <emph>SD</emph> = 0.43) and the Comparison Group (<emph>M</emph> = 0.14, <emph>SD</emph> = 0.44), <emph>t</emph>(<reflink idref="bib40" id="ref123">40</reflink>) = 2.70, <emph>p</emph> = 0.011 (two‐tailed), with a large effect size (<emph>d</emph> = 0.87). While difference scores for Perspective‐Taking between Group 2 (<emph>M</emph> = 0.29, <emph>SD</emph> = 0.52) and the Comparison Group (<emph>M</emph> = 0.01, <emph>SD</emph> = 0.48) were not significantly different, <emph>t</emph>(<reflink idref="bib40" id="ref124">40</reflink>) = 1.64, <emph>p</emph> = 0.109 (two‐tailed), this comparison exhibited a medium effect size (<emph>d</emph> = 0.56). Despite the small sample size of the groups, these results suggest that the intervention was more impactful in the development of emotion regulation and perspective‐taking tendencies for course participants compared with graduate‐level engineering students who did not participate in the intervention, albeit the effect size for perspective‐taking was small.</p> <hd id="AN0134931137-23">Correlational analysis</hd> <p>Lastly, we investigated the relationship between postcourse scores for empathic tendencies as measured by the IRI and ethical reasoning as measured by the EERI and DIT2 using Pearson product–moment correlation (Cohen et al., [<reflink idref="bib17" id="ref125">17</reflink>]). In addition, as a check for relations between the DIT2 and EERI, we computed the correlations between prescore and postcore responses for all students. Prior to testing, we tested for violations of the assumptions of normality, linearity, and homoscedasticity using both the Group 2 students (<emph>n</emph> = 29) and the Comparison Group students (<emph>n</emph> = 13). As we were testing 16 relationships, we flagged correlations as significant only at the 0.01 level to help mitigate the likelihood of committing a Type 1 error.</p> <p>At an alpha of 0.01, using Pearson product–moment correlation coefficients, we found one significant relationship. Table 10 summarizes these results. The EERI N2 score exhibited a moderate (i.e., <emph>r</emph> > 0.30), positive relationship with Perspective‐Taking (<emph>r</emph> = 0.397, <emph>p</emph> < 0.01). The EERI P‐score also showed a moderate, positive, albeit nonsignificant relationship with Perspective‐Taking (<emph>r</emph> = 0.366). All other EERI and IRI correlations except for Fantasy exhibited a small effect size (i.e., <emph>r</emph> > 0.10), while the DIT2 N2 score exhibited small, positive correlations with Personal Distress (<emph>r</emph> = 0.253) and Fantasy (<emph>r</emph> = 0.213). The DIT2 P‐score exhibited similar results, but also showed a small, positive correlation with Perspective‐Taking (<emph>r</emph> = 0.184). Taken together, these findings suggest that fostering students' perspective‐taking tendencies may simultaneously increase their ethical reasoning ability to a moderate extent, specifically as one reasons through engineering‐specific ethical scenarios. However, these findings indicate only the existence of potential relationships between variables, but they do not provide any indications of causality.</p> <p>Correlations between the empathy and ethical reasoning instruments</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left">Perspective‐Taking</th><th align="left">Fantasy</th><th align="left">Empathic Concern</th><th align="left">Personal Distress</th></tr></thead><tbody valign="top"><tr><td>EERI‐N2</td><td>0.397<xref ref-type="fn" rid="jee20249-note-0011" /></td><td>−0.005</td><td>0.178</td><td>0.174</td></tr><tr><td>EERI‐P</td><td>0.366</td><td>−0.074</td><td>0.107</td><td>0.118</td></tr><tr><td>DIT2‐N2</td><td>0.073</td><td>0.213</td><td>−0.001</td><td>0.253</td></tr><tr><td>DIT2‐P</td><td>0.184</td><td>0.174</td><td>0.040</td><td>0.260</td></tr></tbody></table> </ephtml> </p> <ulist> <item>202490009 Data are the postcourse responses for Group 2 and the Comparison Group.</item> <item>202490010 <emph>n</emph> = 42.</item> <item>202490011 * <emph>p</emph> < 0.01 (two‐tailed).</item> </ulist> <hd id="AN0134931137-24">DISCUSSION</hd> <p>This section is divided into three parts. First, we discuss this study in relation to existing engineering ethics interventions. Second, we discuss considerations for evaluating ethical reasoning. Finally, we discuss the findings pertaining to changes in empathic tendencies and the relationship between empathic tendencies and ethical reasoning.</p> <hd id="AN0134931137-25">Situating ethics in engineering curricula</hd> <p>Ethics continues to be required in the accreditation of engineering programs (ABET, [<reflink idref="bib1" id="ref126">1</reflink>]). Yet, how ethics is integrated into the engineering curriculum continues to be widely varied in terms of goals, pedagogical strategies, and methods of evaluation (Haws, [<reflink idref="bib30" id="ref127">30</reflink>]; Hess & Fore, [<reflink idref="bib34" id="ref128">34</reflink>]). This study investigated reflexive principlism, an ethical reasoning approach developed specifically for preparing engineering students to analyze ethical issues (Beever and Brightman [<reflink idref="bib9" id="ref129">9</reflink>]).</p> <p>We posited that the effective training and application of this ethical reasoning approach require grounding in a pedagogical framework based on relevant learning theory. To this end, we created and implemented the pedagogical framework, SIRA, which includes the three core components of scaffolding, interactivity, and reflective analyses. To ascertain the effectiveness of this integrated approach, we evaluated quantitative changes in ethical reasoning and empathic tendencies.</p> <p>Importantly, while our study focused on one skill and several dispositional tendencies, we recognize that there are other critical aspects essential to an optimized ethics education for engineering students. For example, other educators might seek to foster an ethic of care (Gilligan, [<reflink idref="bib29" id="ref130">29</reflink>]; Pantazidou & Nair, [<reflink idref="bib58" id="ref131">58</reflink>]) or to integrate micro‐ and macroethical concerns (Herkert, [<reflink idref="bib31" id="ref132">31</reflink>]; Thoma & Dong, [<reflink idref="bib76" id="ref133">76</reflink>]). Our attempt in this research project was to examine the impact of one ethical reasoning approach integrated into a pedagogical framework on the development of students' ethical reasoning abilities and empathic tendencies.</p> <hd id="AN0134931137-26">Evaluating ethical reasoning</hd> <p>Previous research using the DIT2 has found changes in ethical reasoning development based on multiple educational strategies and various age ranges (Rest et al., [<reflink idref="bib62" id="ref134">62</reflink>]). Rest et al. argued that environments that seek to foster student intellectual development, in general (such as college), have the additive effect of enhancing students' moral judgment. Bebeau ([<reflink idref="bib7" id="ref135">7</reflink>]) also found that "when dealing with mature adults with considerable intellectual ability, learning often moves quickly, and gains following 20–30 hours of personalised [sic] instruction (augmented by reading, writing and role‐playing) are marked" (p. 288). These findings align with Kohlberg's ([<reflink idref="bib45" id="ref136">45</reflink>]) assertions that ethical development continues throughout one's life span, as well as Perry's ([<reflink idref="bib60" id="ref137">60</reflink>]) intellectual/ethical developmental framework that focuses solely on the developmental progression of undergraduate students. Thus, since ethical reasoning can be developed and evaluated, we scholars continue to investigate how this is best accomplished in the engineering curriculum.</p> <p>Our study evaluated the impact of situating the ethical reasoning approach of reflexive principlism within the SIRA pedagogical framework as part of an introductory graduate‐level engineering ethics course. To evaluate the impact of the intervention, we applied a series of psychometric instruments, with the findings providing some evidence that this integrated approach improved ethical reasoning, specifically when students responded to engineering‐specific problems. After the intervention, the ethical reasoning levels of the engineering students were significantly advanced based on the EERI N2 scores with a moderate effect size. However, changes as evidenced by the DIT2 scores were not significant. In addition, the ethical reasoning scores of the course participants increased significantly more than the graduate student peers (the Comparison Group) who participated in departmental seminars that included an ethics lecture, a trend found in the EERI scores but not the DIT2.</p> <p>These different findings from the DIT2 and the engineering‐specific EERI indicate that evaluation instruments utilized to measure ethical reasoning can have varying results. Prior to this study and based on the literature, we anticipated that the contextualized nature of the EERI would be more sensitive to evaluating ethical reasoning with engineering students as they are responding to engineering‐specific issues, and we found this result here. However, we did not expect the DIT2 instrument to yield results that were not significant.</p> <p>Importantly, the EERI and DIT2 present different contextual foci in their scenarios, a situation which may have impacted reasoning responses. We anticipated that the application of reflexive principlism would lead to the development of more advanced (postconventional) reasoning regardless of the case context. However, as the DIT2 results were not positive, the level of student engagement with and familiarity of these short assessments might have a more significant impact on the measurements than has previously been recognized. For example, reasoning about whether Heinz should steal a drug for his ailing wife or Mustaq Singh should steal food from a hoarder, two cases presented in the DIT2, could be less engaging to engineering students than reasoning about the quality of housing or water quality testing, two cases presented in the EERI. It is possible that the latter are more relevant or even important for engineers to consider since they are engineering‐specific problems, whereas the former may be less familiar and engaging to engineers. In light of this potential limitation of the DIT2 and of single instrument studies, we have developed and are in the ongoing process of validating a new instrument, the ethics transfer case (Hess et al., [<reflink idref="bib32" id="ref138">32</reflink>]), targeted at measuring the ability to transfer skills from reflexive principlism to a new engineering specific case study.</p> <p>However, another explanation may be that the DIT2 and EERI are measuring and activating ethical reasoning schema in a distinct manner. Specifically, cases presented in the DIT2 represent general moral dilemmas, whereas the EERI cases are engineering‐specific. As we consider the reflexive principlism approach that students applied to engineering‐specific problems, students may not apply the same ethical reasoning schema to general moral problems. In other words, students may apply the ethical reasoning skills gained through the course to highly contextualized engineering cases from the EERI but not to cases involving more general moral issues from the DIT2. Hence, the ethical reasoning measured by the EERI might be more domain‐specific or engineering‐specific and less transferrable to ethical reasoning in generalized cases as reflected in the DIT2 scores.</p> <p>While these considerations may help explain, to some extent, why findings were significant for one instrument but not the other, as with validity of any instrument (Douglas & Purzer, [<reflink idref="bib22" id="ref139">22</reflink>]) we also recognize that establishing validity of the EERI is ongoing whereas the application of the DIT2 has a storied history. Expert review and focus groups contributed to the development of the instrument (Zhu et al., [<reflink idref="bib84" id="ref140">84</reflink>]) and its construct validity. In addition, the developers of the EERI have calculated coefficient alpha reliabilities on the current version using more than 800 participants. According to Zhu et al. ([<reflink idref="bib84" id="ref141">84</reflink>]), "the estimated reliability of the ratings across the six scored scenarios ranged from 0.72 to 0.85, except for one scenario which had an estimated reliability of 0.565" (p. 9).</p> <p>As a study‐specific validation check post hoc, we computed the correlations between the EERI and DIT2 constructs both pre‐ and postcourse (see the Appendix). In short, these correlation analyses indicated that the DIT2 and EERI constructs were significantly related for both N2 and P constructs. For the EERI and DIT2 N2 scores measuring one's affinity for postconventional reasoning and rejection of preconventional reasoning (Rest et al., [<reflink idref="bib63" id="ref142">63</reflink>]), we found correlations of 0.531 and 0.530 pre‐ and postcourse, respectively. Similar correlation patterns emerge if we analyze correlations by group (see the Appendix). Notably, perfect correlations would indicate that the EERI and DIT2 measure the same phenomena, whereas these significant correlations indicate that the instruments are measuring strongly related phenomena.</p> <p>Finally, we note that the EERI is but one engineering‐specific ethics evaluation instrument and that others may be preferable depending on the alignment between the instrumentation and the learning goals of any specific course (e.g., the ESIT; Borenstein et al., [<reflink idref="bib11" id="ref143">11</reflink>]). Future research exploring the differences between the EERI, other engineering instruments, and the DIT2 may further elucidate the similarities and distinctions between the numerous instruments. We also want to emphasize the limitations of relying solely on quantitative measures of ethical reasoning as a single test, especially one that captures a response only through a mark on an evaluation scale, as such an approach is likely to provide only a limited evaluation of complex phenomena.</p> <hd id="AN0134931137-27">Empathic tendencies and ethical reasoning</hd> <p>We used the IRI (Davis, [<reflink idref="bib21" id="ref144">21</reflink>]) to measure changes in empathic tendencies, the results indicating that the learning intervention contributed to an increase in perspective‐taking and a decrease in personal distress. In other words, the tendency of the engineering students to consider others' perspectives (in general) and their tendency toward emotion regulation when considering challenging ethical concerns both increased. While perspective‐taking was a targeted aspect of this learning intervention as the SIRA framework distributed perspective‐taking prompts in multiple stages, we were uncertain if and how other related empathic tendencies would change. Hence, the large decrease in personal distress was unexpected. Here, we offer a few explanations for these findings.</p> <p>First, the interactive components of the course enabled students not only to consider but also to internalize others' perspectives. This dual process has been called moral imagination (Johnson, [<reflink idref="bib39" id="ref145">39</reflink>]), or the process of blending "reason and emotion through attending to what is taken for granted, what is left out of a situation, how possibilities could be otherwise envisioned" (Tuana, [<reflink idref="bib79" id="ref146">79</reflink>], p. 375). Zoltowski, Oakes, and Cardella ([<reflink idref="bib85" id="ref147">85</reflink>]) described two types of experiences that prompted students' advancement to higher or more comprehensive levels of human‐centered design, categorizing the most comprehensive category as "empathic design" (p. 41). To advance to this level, students tended to have had either "critical" or "immersive" experiences (p. 49). Critical experiences represent the equivalent of an "a‐ha" moment, where one realizes that his or her own way of thinking may need revision or expansion. While the nature of these experiences can be highly variable, the sharing (i.e., giving and receiving) of diverse perspectives is one of the most common avenues (Hess, Strobel, & Brightman, [<reflink idref="bib36" id="ref148">36</reflink>]). Likewise, Zoltowski et al. ([<reflink idref="bib85" id="ref149">85</reflink>]) characterized immersive experiences in terms of engagement with stakeholders. Often this engagement involved informal interactions which, we would suspect, provided student designers with the opportunity to develop a more comprehensive and empathic understanding of the user through listening.</p> <p>Second, openness to other ways of knowing may be especially challenging for engineers. Openness and fully listening require a decentering of the rational isolated decision‐maker. We propose that multiple course activities related to perspective‐taking, decision‐making, inducing conflict, and reflection may have prompted students to be more open in this respect. As Penny ([<reflink idref="bib59" id="ref150">59</reflink>]) describes, the engineering worldview is "quintessentially reductive and deterministic" (p. 37), meaning that engineers tend to believe that phenomena can be studied outside of their given context and that mechanistic modes of reasoning can be utilized to arrive at a valid answer. Similarly, Leydens and Lucena ([<reflink idref="bib46" id="ref151">46</reflink>]) argued, "A significant amount of their [engineering students'] academic training foregrounds methods of problem solving that marginalize the human component and that reduce complexity and ambiguity to more manageable assumptions and equations" (p. 372). We posit that enabling students to clearly see and experience disagreements, ambiguities, and social complexity, all while simultaneously trying to address ethical issues, led them to question some of their own implicit biases or values that may be generally unquestioned by students in engineering curricula.</p> <p>Third, we posited that a structured ethical reasoning approach would provide students with a systematic mode for exploring others' thoughts and feelings. Further, we purposefully integrated reflexive principlism due to its similarity to other engineering‐specific modes of learning with which engineering students would be familiar. In other words, students utilized systematic methods (e.g., identify, specify) and normative principles (e.g., beneficence, justice) to imaginatively enter the minds of and think from the perspectives of imagined stakeholders. The results of the correlation analysis among the DIT2/EERI and IRI constructs supported our hypothesis. Specifically, the strongest correlations were between perspective‐taking and ethical reasoning as evaluated by the EERI, a relationship that supports Kohlberg's ([<reflink idref="bib45" id="ref152">45</reflink>]) conceptualization of social perspective‐taking development as paralleling ethical reasoning development. However, we caution overemphasizing these findings, as we did not find significant correlations between perspective‐taking measures and the DIT2 measures.</p> <p>Fourth, the changes in personal distress indicate that students were less prone to distress after the educational intervention. Importantly, empathic distress was essential to Hoffman's ([<reflink idref="bib37" id="ref153">37</reflink>]) framework of moral development as he argued that distress invokes a salience effect, which in turn may prompt action. However, as he cautioned, too much distress may generate "empathic over‐arousal" whereby one effectively turns inward rather than considering the needs or perspective of another (p. 198). Hoffman further argued, "Individual differences in empathic over‐arousal may be due to difference in empathic tendency, the ability to help, and the ability to regulate one's emotions" (p. 203). Emotion regulation itself is a complex phenomenon (Eisenberg & Spinrad, [<reflink idref="bib25" id="ref154">25</reflink>]). However, our results suggest that this intervention enabled students to regulate their emotions while engaging with challenging uncertainty. For example, our approach guided students as they imaginatively reasoned from the point of view of various stakeholder perspectives that may (and likely did) conflict. Further, it provides a common vernacular and base for reasoning among and collaboratively with peers who might also disagree with one another, despite their collective attempt to respond to a complex and potentially sensitive ethical issue.</p> <p>Finally, the perspective‐taking prompts might have been emotionally powerful for some students, an engagement that may have generated the moderate (albeit, nonsignificant) changes in empathic concern that we found. While emotional engagement was not an a priori outcome or learning objective of the intervention, we posit that it was a necessary component for engaging students in the class exercises and debates. As Newberry ([<reflink idref="bib55" id="ref155">55</reflink>]) argued, ethics education that focuses on the development of intellectual knowledge but is not emotionally engaging runs the risk of being "a superfluous academic exercise" (p. 347). As we cursorily revisit student responses to postcourse interviews, we also see ample evidence of student emotional engagement. As one student described their experience when reasoning through a case that involved the distribution of pediatric heart valves, "I think in taking the perspective of a parent or someone like that, [imagined the parent perspective] 'Hey, my child needs a valve,' [laughs], that made it, those perspectives were stronger, I think. 'Hey, this is my son. They're gonna get what they need. I don't care about what valves.'" This quote highlights not only emotional engagement but also the overlap between empathic concern and perspective‐taking, and their potential role in the student's own ethical reasoning process.</p> <hd id="AN0134931137-28">CONCLUSION</hd> <p>There is a need for a coherent approach to and framework for developing ethical reasoning and empathic perspective‐taking among engineering students. In addition, an appropriate assessment strategy is essential for developing and evaluating the impact of such an approach. Currently, engineering education scholars use several methods to measure the impact of the various approaches to ethics education in engineering, with DIT2 being one of the most widely applied. Reflexive principlism grounded in the SIRA framework is the pedagogical approach that we implemented and tested in this study. While we found enhancements in ethical reasoning using the EERI as well as a decrease in personal distress and increase in perspective‐taking via the IRI, we emphasize that these quantitative measures of ethical reasoning and empathic tendencies provide only a partial explanation of the full impact of such a learning intervention. For example, this analysis does not highlight qualitative changes, nor does it directly measure the qualitative influences of scaffolding, interactivity, and reflective analysis. As we have previously done and continue to do, we encourage educators to also consider qualitative strategies for discerning factors that contribute to changes in students' ethical reasoning and empathic development.</p> <hd id="AN0134931137-29">LIMITATIONS AND FUTURE RESEARCH</hd> <p>We recognize that this study has several limitations. First, our sample size of participants was small. Larger samples could reveal relationships among the factors considered that were not evident in our findings and would allow for predictive analyses rather than the correlation analyses reported here. We also acknowledge that while our approach to measuring ethical reasoning includes two instruments, both measures are drawn from cognitive models of moral judgment based on Kohlbergian and neo‐Kohlbergian theory. Kohlberg's six‐stage theory of moral development has been criticized for its overemphasis on the ethic of justice to the exclusion of the ethic of care, as an ethic of care presents a less androcentric view of moral judgment with added emphasis on relationality (Gilligan, [<reflink idref="bib29" id="ref156">29</reflink>]; Jorgensen, [<reflink idref="bib41" id="ref157">41</reflink>]).</p> <p>Some scholars have also suggested that the DIT2 instrument and, by extension, the EERI assess only moral judgment, and that Rest et al.'s ([<reflink idref="bib62" id="ref158">62</reflink>]) four‐component model of ethical reasoning includes other factors associated with moral behavior not evaluated by these instruments (Huff & Frey, [<reflink idref="bib38" id="ref159">38</reflink>]). For example, Clarkeburn ([<reflink idref="bib15" id="ref160">15</reflink>]) developed the Ethical Sensitivity Test in Science (TESS) to measure ethical sensitivity, or the ability to interpret the presence of ethical issues in a situation although not necessarily to reason through them. This instrument was built on the earlier work of Bebeau and Brabeck ([<reflink idref="bib8" id="ref161">8</reflink>]), who found that sensitivity shows only a moderate relationship with reasoning and vice versa. Others have encouraged a move beyond cognitive models that focus primarily on individual cognition, judgments, and decision‐making, and do not emphasize the communicative, social, and cultural elements of ethical decision‐making processes (Reynolds, [<reflink idref="bib65" id="ref162">65</reflink>]). We are sensitive to this ongoing dialogue, and we do not suggest that Kohlbergian models of ethical development are superior to others. Rather, as we emphasized throughout, sensitivity and empathy are essential to <emph>any</emph> type of moral or ethical reasoning, especially reflexive principlism, and we encourage ethics educators and researchers to actively engage these tensions. For example, we have developed and are continuing to revise an Ethics Transfer Case assessment tool that captures changes in application of the core components of reflexive principlism, including identification, specification, perspective‐taking, justification, and reflectivity (Hess et al., [<reflink idref="bib32" id="ref163">32</reflink>]).</p> <p>Finally, we recognize that other situational or individual variables may influence the outcomes of ethics interventions and should be considered for optimizing ethics education in engineering. Specifically, we recognize that factors related to individual characteristics, other formal curricular experiences, co‐curricular experiences, and institutional culture all may factor into students' ethical development (Finelli et al., [<reflink idref="bib27" id="ref164">27</reflink>]). Although we did not capture this complexity in this study, as one means to address a potential confounding variable, our team previously tested whether participation in the hybrid versus the online only mode might have impacted results immediately (Hess et al., 2016). Interestingly, while these comparisons indicated that the type of participation did not affect students' ethical reasoning development, we found that the hybrid group who participated in at least one in‐class lecture exhibited higher levels of satisfaction with course components, especially those involving interactivity, than the online participants.</p> <hd id="AN0134931137-30">ACKNOWLEDGMENTS</hd> <p>This work was made possible by the National Science Foundation (Grant No. 1237868) as part of the Ethics Education in Science and Engineering Program. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.</p> <hd id="AN0134931137-31">APPENDIX</hd> <p>This section supplements the associated text in Section 6 and serves as a study‐specific validation check. We report correlations between the EERI and DIT2 constructs both precourse (Table A1) and postcourse (Table A2).</p> <p>Pearson product‐moment correlations of DIT2 and EERI constructs: Precourse</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left" /><th align="left">All (<italic>n</italic> = 72)</th><th align="left">Group 1 (<italic>n</italic> = 29)</th><th align="left">Group 2 (<italic>n</italic> = 29)</th><th align="left">Comparison (<italic>n</italic> = 14)</th></tr><tr><th align="left">DIT2</th><th align="left">DIT2</th><th align="left">DIT2</th><th align="left">DIT2</th></tr><tr><th align="left">N2</th><th align="left">P</th><th align="left">N2</th><th align="left">P</th><th align="left">N2</th><th align="left">P</th><th align="left">N2</th><th align="left">P</th></tr></thead><tbody valign="top"><tr><td>EERI</td><td>N2</td><td align="left">0.531<xref ref-type="fn" rid="tfn2" /></td><td>0.541<xref ref-type="fn" rid="tfn2" /></td><td align="left">0.429</td><td>0.400</td><td align="left">0.553<xref ref-type="fn" rid="tfn2" /></td><td>0.609<xref ref-type="fn" rid="tfn2" /></td><td align="left">0.770<xref ref-type="fn" rid="tfn2" /></td><td>0.710<xref ref-type="fn" rid="tfn2" /></td></tr><tr><td>P</td><td align="left">0.425<xref ref-type="fn" rid="tfn2" /></td><td>0.489<xref ref-type="fn" rid="tfn2" /></td><td align="left">0.350</td><td>0.387</td><td align="left">0.409</td><td>0.522<xref ref-type="fn" rid="tfn2" /></td><td align="left">0.623</td><td>0.597</td></tr></tbody></table> </ephtml> </p> <p>1 <emph>n</emph> = 72 (Groups 1, 2, and the Comparison combined).</p> <p>2 Significant relationship at <emph>p</emph> < 0.01.</p> <p>Pearson product–moment correlations of DIT2 and EERI constructs: Postcourse</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left" /><th align="left">All (<italic>n</italic> = 72)</th><th align="left">Group 1 (<italic>n</italic> = 29)</th><th align="left">Group 2 (<italic>n</italic> = 29)</th><th align="left">Comparison (<italic>n</italic> = 14)</th></tr><tr><th align="left">DIT2</th><th align="left">DIT2</th><th align="left">DIT2</th><th align="left">DIT2</th></tr><tr><th align="left">N2</th><th align="left">P</th><th align="left">N2</th><th align="left">P</th><th align="left">N2</th><th align="left">P</th><th align="left">N2</th><th align="left">P</th></tr></thead><tbody valign="top"><tr><td>EERI</td><td>N2</td><td align="left">0.530<xref ref-type="fn" rid="tfn4" /></td><td>0.530<xref ref-type="fn" rid="tfn4" /></td><td align="left">0.525<xref ref-type="fn" rid="tfn4" /></td><td>0.460</td><td align="left">0.530<xref ref-type="fn" rid="tfn4" /></td><td>0.605<xref ref-type="fn" rid="tfn4" /></td><td align="left">0.586</td><td>0.580</td></tr><tr><td>P</td><td align="left">0.404<xref ref-type="fn" rid="tfn4" /></td><td>0.493<xref ref-type="fn" rid="tfn4" /></td><td align="left">0.360</td><td>0.437</td><td align="left">0.431</td><td>0.518<xref ref-type="fn" rid="tfn4" /></td><td align="left">0.451</td><td>0.564</td></tr></tbody></table> </ephtml> </p> <ulist> <item>3 <emph>n</emph> = 72 (Groups 1, 2, and the Comparison combined).</item> <item>4 Significant relationship at <emph>p</emph> < 0.01.</item> </ulist> <ref id="AN0134931137-32"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref4" type="bt">1</bibl> <bibtext> Funding information National Science Foundation, Grant/Award Number: 1237868</bibtext> </blist> </ref> <ref id="AN0134931137-33"> <title> REFERENCES </title> <blist> <bibtext> ABET. 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H ess is the Assistant Director of the STEM Education Innovation and Research Institute and an Adjunct Assistant Professor of STEM Education Research in the Department of Technology Leadership and Communication at Indiana University–Purdue University Indianapolis, IN;.</p> <p>J. B eever is an Assistant Professor of Ethics and Digital Culture in the Department of Philosophy at the University of Central Florida, Orlando, FL;.</p> <p>C. B. Z oltowski is an Assistant Professor of Engineering Practice in the Schools of Electrical and Computer Engineering and (by courtesy) Engineering Education at Purdue University, West Lafayette, IN;.</p> <p>L. K isselburgh is a Visiting Lecturer in the Center for Entrepreneurship and a Faculty Fellow in the Center for Education and Research in Information Assurance and Security (CERIAS) at Purdue University, West Lafayette, IN;.</p> <p>A. O. B rightman is the Assistant Head for Academic Affairs and an Associate Professor of Engineering Practice in the Weldon School of Biomedical Engineering at Purdue University, West Lafayette, IN;.</p> </aug> <nolink nlid="nl1" bibid="bib54" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib10" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib66" firstref="ref3"></nolink> <nolink nlid="nl4" bibid="bib31" firstref="ref7"></nolink> <nolink nlid="nl5" bibid="bib73" firstref="ref8"></nolink> <nolink nlid="nl6" bibid="bib19" firstref="ref9"></nolink> <nolink nlid="nl7" bibid="bib18" firstref="ref10"></nolink> <nolink nlid="nl8" bibid="bib53" firstref="ref11"></nolink> <nolink nlid="nl9" bibid="bib44" firstref="ref13"></nolink> <nolink nlid="nl10" bibid="bib64" firstref="ref14"></nolink> <nolink nlid="nl11" bibid="bib28" firstref="ref15"></nolink> <nolink nlid="nl12" bibid="bib45" firstref="ref16"></nolink> <nolink nlid="nl13" bibid="bib60" firstref="ref17"></nolink> <nolink nlid="nl14" bibid="bib71" firstref="ref18"></nolink> <nolink nlid="nl15" bibid="bib62" firstref="ref19"></nolink> <nolink nlid="nl16" bibid="bib26" firstref="ref20"></nolink> <nolink nlid="nl17" bibid="bib23" firstref="ref24"></nolink> <nolink nlid="nl18" bibid="bib27" firstref="ref25"></nolink> <nolink nlid="nl19" bibid="bib48" firstref="ref26"></nolink> <nolink nlid="nl20" bibid="bib52" firstref="ref27"></nolink> <nolink nlid="nl21" bibid="bib67" firstref="ref28"></nolink> <nolink nlid="nl22" bibid="bib70" firstref="ref29"></nolink> <nolink nlid="nl23" bibid="bib29" firstref="ref31"></nolink> <nolink nlid="nl24" bibid="bib41" firstref="ref32"></nolink> <nolink nlid="nl25" bibid="bib84" firstref="ref40"></nolink> <nolink nlid="nl26" bibid="bib78" firstref="ref41"></nolink> <nolink nlid="nl27" bibid="bib21" firstref="ref44"></nolink> <nolink nlid="nl28" bibid="bib61" firstref="ref45"></nolink> <nolink nlid="nl29" bibid="bib81" firstref="ref46"></nolink> <nolink nlid="nl30" bibid="bib37" firstref="ref54"></nolink> <nolink nlid="nl31" bibid="bib57" firstref="ref55"></nolink> <nolink nlid="nl32" bibid="bib33" firstref="ref56"></nolink> <nolink nlid="nl33" bibid="bib11" firstref="ref60"></nolink> <nolink nlid="nl34" bibid="bib47" firstref="ref62"></nolink> <nolink nlid="nl35" bibid="bib83" firstref="ref63"></nolink> <nolink nlid="nl36" bibid="bib13" firstref="ref66"></nolink> <nolink nlid="nl37" bibid="bib24" firstref="ref67"></nolink> <nolink nlid="nl38" bibid="bib42" firstref="ref68"></nolink> <nolink nlid="nl39" bibid="bib20" firstref="ref70"></nolink> <nolink nlid="nl40" bibid="bib40" firstref="ref71"></nolink> <nolink nlid="nl41" bibid="bib80" firstref="ref72"></nolink> <nolink nlid="nl42" bibid="bib82" firstref="ref73"></nolink> <nolink nlid="nl43" bibid="bib74" firstref="ref75"></nolink> <nolink nlid="nl44" bibid="bib14" firstref="ref76"></nolink> <nolink nlid="nl45" bibid="bib68" firstref="ref77"></nolink> <nolink nlid="nl46" bibid="bib69" firstref="ref78"></nolink> <nolink nlid="nl47" bibid="bib50" firstref="ref84"></nolink> <nolink nlid="nl48" bibid="bib51" firstref="ref85"></nolink> <nolink nlid="nl49" bibid="bib56" firstref="ref86"></nolink> <nolink nlid="nl50" bibid="bib77" firstref="ref87"></nolink> <nolink nlid="nl51" bibid="bib43" firstref="ref89"></nolink> <nolink nlid="nl52" bibid="bib49" firstref="ref90"></nolink> <nolink nlid="nl53" bibid="bib12" firstref="ref91"></nolink> <nolink nlid="nl54" bibid="bib35" firstref="ref92"></nolink> <nolink nlid="nl55" bibid="bib63" firstref="ref93"></nolink> <nolink nlid="nl56" bibid="bib75" firstref="ref97"></nolink> <nolink nlid="nl57" bibid="bib72" firstref="ref103"></nolink> <nolink nlid="nl58" bibid="bib16" firstref="ref105"></nolink> <nolink nlid="nl59" bibid="bib25" firstref="ref122"></nolink> <nolink nlid="nl60" bibid="bib17" firstref="ref125"></nolink> <nolink nlid="nl61" bibid="bib30" firstref="ref127"></nolink> <nolink nlid="nl62" bibid="bib34" firstref="ref128"></nolink> <nolink nlid="nl63" bibid="bib58" firstref="ref131"></nolink> <nolink nlid="nl64" bibid="bib76" firstref="ref133"></nolink> <nolink nlid="nl65" bibid="bib32" firstref="ref138"></nolink> <nolink nlid="nl66" bibid="bib22" firstref="ref139"></nolink> <nolink nlid="nl67" bibid="bib39" firstref="ref145"></nolink> <nolink nlid="nl68" bibid="bib79" firstref="ref146"></nolink> <nolink nlid="nl69" bibid="bib85" firstref="ref147"></nolink> <nolink nlid="nl70" bibid="bib36" firstref="ref148"></nolink> <nolink nlid="nl71" bibid="bib59" firstref="ref150"></nolink> <nolink nlid="nl72" bibid="bib46" firstref="ref151"></nolink> <nolink nlid="nl73" bibid="bib55" firstref="ref155"></nolink> <nolink nlid="nl74" bibid="bib38" firstref="ref159"></nolink> <nolink nlid="nl75" bibid="bib15" firstref="ref160"></nolink> <nolink nlid="nl76" bibid="bib65" firstref="ref162"></nolink>
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  Data: Enhancing Engineering Students' Ethical Reasoning: Situating Reflexive Principlism within the SIRA Framework
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  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Hess%2C+Justin+L%2E%22">Hess, Justin L.</searchLink><br /><searchLink fieldCode="AR" term="%22Beever%2C+Jonathan%22">Beever, Jonathan</searchLink><br /><searchLink fieldCode="AR" term="%22Zoltowski%2C+Carla+B%2E%22">Zoltowski, Carla B.</searchLink><br /><searchLink fieldCode="AR" term="%22Kisselburgh%2C+Lorraine%22">Kisselburgh, Lorraine</searchLink><br /><searchLink fieldCode="AR" term="%22Brightman%2C+Andrew+O%2E%22">Brightman, Andrew O.</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Journal+of+Engineering+Education%22"><i>Journal of Engineering Education</i></searchLink>. Jan 2019 108(1):82-102.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Wiley Periodicals, Inc. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA
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  Label: Peer Reviewed
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  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 21
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2019
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  Label: Sponsoring Agency
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  Data: National Science Foundation (NSF)
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  Label: Contract Number
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  Data: 1237868
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  Label: Document Type
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  Data: Journal Articles<br />Reports - Research
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  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Engineering+Education%22">Engineering Education</searchLink><br /><searchLink fieldCode="DE" term="%22Ethical+Instruction%22">Ethical Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Thinking+Skills%22">Thinking Skills</searchLink><br /><searchLink fieldCode="DE" term="%22Instructional+Effectiveness%22">Instructional Effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22Empathy%22">Empathy</searchLink><br /><searchLink fieldCode="DE" term="%22Perspective+Taking%22">Perspective Taking</searchLink><br /><searchLink fieldCode="DE" term="%22Graduate+Students%22">Graduate Students</searchLink><br /><searchLink fieldCode="DE" term="%22Teaching+Methods%22">Teaching Methods</searchLink>
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  Data: <searchLink fieldCode="SU" term="%22Interpersonal+Reactivity+Index%22">Interpersonal Reactivity Index</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1002/jee.20249
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1069-4730
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Background: Educating engineers to reason through the ethical decisions they encounter when developing or implementing new technologies is a critical challenge. However, engineering educators have not widely adopted a framework for preparing engineering students to analyze ethical issues. Purpose/Hypothesis: We developed and tested an approach for enhancing the ethical reasoning of engineering students. This approach integrates reflexive principlism, an ethical reasoning approach, within a structured learning framework, scaffolded, interactive, and reflective analysis, or SIRA. We hypothesized that students' ethical reasoning abilities and empathic perspective-taking tendencies would increase. Design/Method: We implemented and tested the integrated approach over five semesters with graduate-level engineering students through a quasi-experimental, controlled research design. We measured changes in ethical reasoning using the Engineering Ethical Reasoning Instrument (EERI) and the Defining Issues Test 2 (DIT2) and empathic tendencies using the Interpersonal Reactivity Index (IRI). We examined relationships among measures through correlation analysis. Results: The EERI instrumentation indicated that the approach significantly increased the ethical reasoning abilities of graduate-level engineering students. However, the DIT2 findings did not indicate change. The IRI indicated perspective-taking tendencies were enhanced and personal distress tendencies were reduced. Postcourse correlational data indicated moderate relationships between perspective-taking and ethical reasoning as measured by the IRI and the EERI indexes. Conclusions: This study provides a theoretical approach for developing ethical reasoning and empathic perspective-taking among graduate-level engineering students. It also provides a theoretical framework, a pedagogical approach, and evaluation methods that others may utilize.
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  Data: As Provided
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  Label: Entry Date
  Group: Date
  Data: 2020
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1254180
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1254180
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    Identifiers:
      – Type: doi
        Value: 10.1002/jee.20249
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 21
        StartPage: 82
    Subjects:
      – SubjectFull: Engineering Education
        Type: general
      – SubjectFull: Ethical Instruction
        Type: general
      – SubjectFull: Thinking Skills
        Type: general
      – SubjectFull: Instructional Effectiveness
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      – SubjectFull: Empathy
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      – SubjectFull: Perspective Taking
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      – SubjectFull: Graduate Students
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      – SubjectFull: Teaching Methods
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      – SubjectFull: Interpersonal Reactivity Index
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      – TitleFull: Enhancing Engineering Students' Ethical Reasoning: Situating Reflexive Principlism within the SIRA Framework
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            NameFull: Hess, Justin L.
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            NameFull: Zoltowski, Carla B.
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            NameFull: Brightman, Andrew O.
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