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Reimagining and rethinking engineering education

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A new report from MIT puts a spotlight on worldwide trends in the changing landscape of engineering education, pinpoints the current and emerging leaders in the field, and describes some of its future directions.

“Engineers will address the complex societal challenges of the 21st century by building a new generation of machines, materials, and systems. We should fundamentally rethink how we educate engineers for this future,” says Ed Crawley, the Ford Professor of Engineering in the Department of Aeronautics and Astronautics and faculty co-director of the New Engineering Education Transformation (NEET) initiative at MIT.

This realization, Crawley says, is what prompted MIT’s engineering faculty to rethink how they were approaching their own offerings on campus, and to launch NEET. “We’re targeting MIT education at the industries of the future rather than industries of the past,” says Anette “Peko” Hosoi, associate dean of engineering and Crawley’s co-lead at NEET; Hosoi is also the Neil and Jane Pappalardo Professor of Mechanical Engineering.

While their on-campus pilot was at the design stage, Crawley decided to take a broader, benchmarking view. “I knew from my five years as founding president of Skoltech in Moscow that there were examples of educational innovation scattered across the world,” he says, “but these distributed developments are difficult to identify and learn from.”

Until now. Crawley and his colleagues in the NEET program have just released “Global state of the art in engineering education.” The report, authored by Ruth Graham, is a global review of cutting-edge practice in engineering education. It is informed by interviews with 178 thought leaders with knowledge of and experience with world-leading engineering programs, combined with case studies from four different universities. The report paints a rich picture of successful innovation in engineering education as well as some of its opportunities and challenges.

The study identifies institutions considered to be the current leaders in engineering education; Olin College and MIT were cited by the majority of experts who were consulted, along with Stanford University, Aalborg University in Denmark, and Delft University of Technology (TU Delft) in the Netherlands. Outside of the U.S. and northern Europe, the only university among the top 10 cited for their educational leadership was the National University of Singapore (NUS).

“The profile of the emerging leaders is very different,” Graham notes. “While they include universities in the U.S. and Europe — Olin College, Iron Range Engineering, and University College London are among the most frequently cited universities –  thought leaders identified emerging leaders from across the world, such as Singapore University of Technology and Design (SUTD), Pontifical Catholic University of Chile (PUC), NUS (Singapore), and Charles Sturt University (Australia).” (The report includes case studies of four of the emerging leaders: SUTD, UCL, Charles Sturt, and TU Delft.)

The study attributes this contrast to a range of sources. For one, Graham notes, “Many political leaders outside of the U.S. are making major investments in engineering education as an incubator for the technology-based entrepreneurial talent that will drive national economic growth.”

The report also identifies some key challenges facing engineering education, and in some cases higher education as a whole. These include aligning the goals of national governments and higher education, delivering student-centered learning to large student cohorts, and setting up faculty appointment and promotion systems that better reward high-quality teaching.

According to Graham’s report, three trends are likely to define the future of engineering education. The first is a tilting of the global axis of engineering education leadership so it is less focused on U.S. and northern European institutions. The second is a shift toward programs that integrate student-centered learning with a curriculum oriented to the pressing challenges of the 21st century — societal, environmental, and technological. And the third is the emergence of a new generation of leaders with the capacity to deliver student-centered curricula at scale.

The case studies highlighted in the report include universities that may be paving the way by, for example, achieving curricular coherence and integration through a connective spine of design projects. In the longer-term, the world’s leading engineering programs may be those that blend off-campus personalized learning, accessed online as students need it, with experiential learning both in work-based placements and on campus.

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• Report: "The Global State of the Art in Engineering Education"
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Journal of Engineering Education

Welcome .

Welcome to the Journal of Engineering Education (JEE),  a peer-reviewed international journal published quarterly by the American Society for Engineering Education (ASEE).

Role: The Journal of Engineering Education is more than a place to publish papers—it is a vital partner in the global community of stakeholders dedicated to advancing research in engineering education from pre-college to post-graduate professional education.

Vision:  The Journal of Engineering Education seeks to help define and shape a body of knowledge derived from scholarly research that leads to timely and significant improvements in engineering education worldwide.

Mission:  The Journal of Engineering Education serves to cultivate, disseminate, and archive scholarly research in engineering education.  

Articles published in JEE are now available to ASEE members at  Wiley Online Library  (login required).

Non-members may be able to view articles through their institutional subscriptions.

Prospective authors should consult the journal's  author guidelines .

Authors should avoid predatory journals with similar titles that promise rapid publication with insufficient time for rigorous peer review.

NOTE:  Clicking the guidelines link takes you to JEE's pages on Wiley; it  does not  provide you with member access to JEE papers. You must be  logged in to the ASEE website  for such access.

JEE is listed in the Science Citation Index (categories: Education, Scientific Disciplines; Engineering, Multidisciplinary), and the Social Sciences Citation Index (category: Education, Education Research) by Clarivate and the  Institute of Scientific Information  (ISI) and the tables of contents are reproduced in ISI’s Current Contents/Engineering, Computing and Technology and Current Contents/Social and Behavioral Sciences. JEE is also listed in the EBSCOhost research databases (Education Research Complete™ and Academic Search Complete™) and the Elsevier bibliographic research database, Scopus. JEE is a founding member of the  International Federation of Engineering Education Societies , and the journal is rated A* by the  Australian Research Council .

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Research Publications

Lab spaces and facilities, research areas.

The persistent pursuit of a more inclusive socially connected and scholarly engineering education. In the lab, in the field, and in the classroom, our faculty keep going to show the world what's possible.

Advancing diversity, inclusion, and equity

Advancing diversity, inclusion, and equity.

reframing how we think about diversity, inclusion, and equity and designing improved interventions across all educational levels.

Related Research and Publications

Trends in the underrepresentation of women of color faculty in engineering (2005–2018) Main, J. B., McGee, E. O., Cox, M. F., Tan, L., & Berdanier, C. G. P.; August 2022

Family formation and the career trajectories of women engineering PhDs Joyce B. Main; August 2022

The role of the teaching assistant: Female role models in the classroom Amanda L. Griffith, Joyce B. Main; December 2021

A Sociocultural Learning Framework for Inclusive Pedagogy in Engineering Stephanie Farrell, Allison Godwin, Donna M. Riley; October 2021

Preparing Industry Leaders: The Role of Doctoral Education and Early Career Management Training in the Leadership Trajectories of Women STEM PhDs Joyce B. Main, Yanbing Wang and Li Tan; August 2021

Social justice and inclusion: Women and minorities in engineering  (Video) Donna Riley, Amy Slaton, Alice Pawley; August 2020

Gatekeepers of Engineering Workforce Diversity? The Academic and Employment Returns to Student Participation in Voluntary Cooperative Education Programs Joyce Main, Beata Johnson, Yanbing Wang; June 2020

Digging deeper: qualitative research methods for eliciting narratives and counter-narratives from student veterans Catherine Mobley, Chaterine Brawner, Susan Lord, Joyce Main, Michelle Camacho; July 2019

Beyond pipeline and pathways: Ecosystem metrics Susan Lord, Matthew Ohland, Richard Layton, Michelle Camacho; February 2019

Shifting the "Default": The Case for Making Diversity the Expected Condition for Engineering Education and Making Whiteness and Maleness Visible Alice Pawley; November 2017

Sustainability Goals of Students Underrepresented in Engineering: An Intersectional Study Allison Godwin, Leidy Klotz, Zahra Harari and Geoff Potvin; June 2017

Pushing and pulling Sara: A case study of the contrasting influences of high school and university experiences on engineering agency, identity, and participation Allison Godwin and G. Potvin; November 2016

GLOBAL SEED GRANT: GirlEngage Program in Zimbabwe Jennifer DeBoer, Dhinesh Radhakrishnan, Molly Fitzgerald; July 2020

NSF AWARD:  Collaborative Research: Building Social Infrastructure for Achieving Change at Scale Donna Riley; March 2019

NSF AWARD:  Identifying Marginalization and Allying Tendencies to Transform Engineering Relationships Alice Pawley, Matthew Ohland, Stephanie Zywicki, Darryl Dickerson; September 2019

Defining frameworks, developing methods and designing data infrastructures

defining and setting standards for quantitative and qualitative research methods, working with big and small data, and developing tools that serve our community

Related Research Publications

Development of Global Engineering Competency Scale: Exploratory and Confirmatory Factor Analysis Andrea Mazzurco, Brent Jesiek, Allison Godwin; April 2020

A Size and Scale Framework for Guiding Curriculum Design and Assessment Yi Kong, Kerrie A. Douglas, Kelsey J. Rodgers, Heidi Diefes-Dux, Krishna Madhavan; July 2017

The Power and Politics of Engineering Education Research Design: Saving the ‘Small N’ Amy Slaton, Alice Pawley; June 2017

Bridging the design-science gap with tools: Science learning and design behaviors in a simulated environment for engineering design Jie Chao, Charles Xie, Saeid Nourian, Guanhua Chen, Siobhan Bailey, Molly H. Goldstein, Senay Purzer, Robin S. Adams, M. Shane Tutwiler; May 2017

Identity, Critical Agency, and Engineering: An Affective Model for Predicting Engineering as a Career Choice Allison Godwin, Geoff Potvin, Zahra Hazari, and Robynne Lock; April 2017

Evaluation of current assessment methods in engineering entrepreneurship education Senay Purzer, Nicholas Fila, and Kavin Nataraja; December 2016

A Developmental Model of Research Mentoring Renata A. Revelo, Michael Loui; March 2016

The Multiple-Institution Database for Investigating Engineering Longitudinal Development: An experiential case study of data sharing and reuse Matthew Ohland, Russell Long; Spring 2016

Justifying aggregation with consensus-based constructs: A review and examination of cutoff values for common aggregation indices David Woehr, Andrew Loignon, Paul Schmidt, Misty Loughry, Matthew Ohland; May 2015

The Informed Design Teaching and Learning Matrix David Crismond, Robin Adams; October 2012

Rigorous research in engineering education (PDF Download) Ruth Streveler, Karl Smith; October 2008

Effecting change in engineering education (research to practice)

working with colleagues in other engineering disciplines to connect research findings to classroom practice

Cultures of Engagement and Innovation: Realizing Purdue’s Public Mission of Access and Impact in Engineering Education Robin Adams, Andrew Brightman, Jennifer DeBoer, Leah Jamieson, William Oakes, Donna Riley, Paige Rudin; August 2021

Person or thing oriented: A comparative study of individual differences of first-year engineering students and practitioners Diana N. Bairaktarova, Mary K. Pilotte; February 2020

Breaking the tyranny of office hours: Overcoming professor avoidance Elizabeth Broidy, Elizabeth Wirtz, Angela Goldenstein, Edward J. Berger; March 2019

Impact of the EPICS model for community-engaged learning and design education William Oakes, James Huff, Carla Zoltowski, D Canchi; 2018

Impact of a student affairs-academic partnership on engineering student academic outcomes Edward J. Berger, Julie Caruccio, and Lisa Lampe; February 2018

Mechanical Engineering Research Center (MEERCat) Ed Berger, Jennifer DeBoer; established June 2017

CISTAR NSF Engineering Research Center Monica Cardella, Allison Godwin, Workforce Development Co-Directors; established 2017

Supporting successful teams: Research to practice in capstone courses Matthew W. Ohland, David Giurintano, Brian Novoselich, Patsy Brackin, Shraddha Sangelkar; 2014

2004-2017 Engineering Education Impact Report

Improving pre-college engineering education

Improving pre-college engineering education.

Faculty, staff and students of the INSPIRE research center lead the way in integrating engineering with science, math, and language arts in pre-college classrooms in a way that engages learners and promotes participation of students from groups underrepresented in engineering

Understanding influences on engineering students’ civic engagement in high school Athena Lin, Justin L. Hess; August 2022

The effectiveness of an integrated STEM curriculum unit on middle school students' life science learning Saira Anwar, Muhsin Menekse, Siddika Selcen Guzey, Lynn A. Bryan; February 2022

The honeycomb of engineering framework: Philosophy of engineering guiding precollege engineering education Senay Purzer, Jenny Quintana-Cifuentes, Muhsin Menekse; November 2021

INSPIRE Research Institute for Pre-College Engineering Research Areas Broaden Participation, STEM Integration, Classroom Assessment, Learning in Informal Environments, Student Learning, Student Engagement

Multiple Representations in Computational Thinking Tasks: A Clinical Study of Second-Grade Students Tamara Moore, Sean Brophy, Kristina Tank, Ruben Lopez, Amanda Johnson, Morgan Hynes, Elizabeth Gajdzik; February 2020

Design-based research to broaden participation in pre-college engineering: research and practice of an interest-based engineering challenges framework Avneet Hira and Morgan Hynes; November 2017

The Role of Robotics Teams’ Collaboration Quality on Team Performance in a Robotics Tournament Muhsin Menekse, Ross Higashi, Christian D. Schunn, Emily Baehr; November 2017

NSF AWARD:  Excellence in STEM Teaching in Indiana through Integrating Engineering Practice and Design Principles Lynn Bryan, Jill Newton, Siddika Guzey, Muhsin Menekse, Paul Asunda; July 2018

Understanding and assessing how people learn

Understanding and assessing how people learn.

from difficult technical concepts to teamwork, ethics, entrepreneurship, global competencies, and much more

MIDFIELD: A Resource for Longitudinal Student Record Research Susan M. Lord, Matthew W. Ohland, Marisa K. Orr, Richard A. Layton, Russell A. Long, Catherine E. Brawner, Hossein Ebrahiminejad, Baker A. Martin, George D. Ricco, Leila Zahedi; August 2022

Assessing learning processes rather than outcomes: using critical incidents to explore student learning abroad Kirsten A. Davis, David B. Knight; March 2022

NSF DUE AWARD -  Improving the Problem Solving Skills of Engineering Undergraduate Students by Infusing Engineering Design in Introductory Physics Carina Rebello, N. Sanjay Rebello, Jason Morphew; July 2020

NSF RAPID AWARD - Approaches to Online Implementation and Social Support in Undergraduate Engineering Courses Kerrie Douglas; June 2020

IES AWARD -  Enhancing Undergraduate STEM Education by Integrating Mobile Learning Technologies with Natural Language Processing Muhsin Menekse; August 2018

Cambridge Handbook of Engineering Education Research: Updated Perspectives - Assessment in Engineering Education (Video) Jim Pellegrino, Sean Brophy; July 2020

How Do Different Reflection Prompts Affect Engineering Students’ Academic Performance and Engagement? Muhsin Menekse, Saira Anwar, Zeynep Gonca Akdemir; July 2020

Challenges to assessing motivation in MOOC learners: An application of an argument-based approach Kerrie Douglas, Hillary Merzdorf, Nathan Hicks, Muhammad Ihsanujlhaq Sarfraz, Peter Bermel; February 2020

Human-centeredness in undergraduate engineering students’ representations of engineering design Monica Cardella, William Oakes, Nusaybah Abu Mulaweh, Andrew Pierce; February 2020

Practicing Engineering Ethics in Global Context: A Comparative Study of Expert and Novice Approaches to Cross-Cultural Ethical Situations Qin Zhu, Brent Jesiek; November 2019

Identifying the characteristics of engineering innovativeness Dan Ferguson, Matt Ohland, enay Purzer, K. Jablokow; April 2017

A systematic literature review of US engineering ethics interventions Justin Hess, Grant Fore; April 2017

Learning conceptual knowledge in the engineering sciences: Overview and future research directions RA Streveler, TA Litzinger, RL Miller, PS Steif; January 2013

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Engineering Education Review

About the Journal

 The complex and ever-changing world, as the rapid development of new technologies present unprecedented opportunities and challenges to engineering education, which propels social progress and determines the future of humanity. However, there is not a special review of engineering education journal.

aims and scope

Led by an outstanding Editorial Board of international experts, this journal focuses on professional development, aim to display cutting-edge and topical issues, to lead disciplinary innovation, and to promote academic communications. The journal publishes critical analysis, summary, and evaluation of previous research to expand new perspectives, to guide paradigm shifts in engineering education, and to improve academic discourse and practice systems.

target audience

Experts and scholars engaged in the field of engineering education, teachers and students of primary and secondary schools, universities, researchers in research institutions, educational policy makers and implementers of various countries, etc.

covered disciplines or sub-disciplines （> 10 Hot topics should be listed）

• engineering science education
• engineering technology education
• engineering management education
• engineering culture education
• global trends and frontiers in engineering education
• engineering education strategy research
• reform and practice of engineering education
• comparative analysis of regional engineering education
• interdisciplinary engineering education
• soft science research in engineering education.

other topics related with engineering education.

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Engineering education review launched the first issue and debuted on world engineers convention 2023.

Arranged by Dr. Marlene Kanga, president of the WFEO (2017-2019), chairman of the WEC 2019, and led by Prof. Gong Ke, president of the WFEO (2019-2021), chairman of the China National Committee of WFEO, our Journal- Engineering Education Review (EER) announced the launch of the first issue at WEC 2023!

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The journal is committed to publish high-quality articles systematically reviewing research progress and achievements, define the education development process, inspire academic innovation, and build a high-level international platform of academic communications for experts and scholars dedicated in the disciplinary field of engineering education worldwide.

ISSN: 2959-6890 (online)

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Comparing First-Year Engineering Student Conceptions of Ethical Decision-Making to Performance on Standardized Assessments of Ethical Reasoning

• Original Research/Scholarship
• Open access
• Published: 04 June 2024
• Volume 30 , article number  23 , ( 2024 )

Cite this article

You have full access to this open access article

• Richard T. Cimino   ORCID: orcid.org/0000-0003-4171-4133 1 ,
• Scott C. Streiner 2 ,
• Daniel D. Burkey 3 ,
• Michael F. Young 4 ,
• Landon Bassett 3 &
• Joshua B. Reed 5  

The Defining Issues Test 2 (DIT-2) and Engineering Ethical Reasoning Instrument (EERI) are designed to measure ethical reasoning of general (DIT-2) and engineering-student (EERI) populations. These tools—and the DIT-2 especially—have gained wide usage for assessing the ethical reasoning of undergraduate students. This paper reports on a research study in which the ethical reasoning of first-year undergraduate engineering students at multiple universities was assessed with both of these tools. In addition to these two instruments, students were also asked to create personal concept maps of the phrase “ethical decision-making.” It was hypothesized that students whose instrument scores reflected more postconventional levels of moral development and more sophisticated ethical reasoning skills would likewise have richer, more detailed concept maps of ethical decision-making, reflecting their deeper levels of understanding of this topic and the complex of related concepts. In fact, there was no significant correlation between the instrument scores and concept map scoring, suggesting that the way first-year students conceptualize ethical decision making does not predict the way they behave when performing scenario-based ethical reasoning (perhaps more situated). This disparity indicates a need to more precisely quantify engineering ethical reasoning and decision making, if we wish to inform assessment outcomes using the results of such quantitative analyses.

Avoid common mistakes on your manuscript.

Introduction

Psychologists, ethicists and educators have been creating scenario-based instruments to assess moral development and ethical reasoning since at least the 1970s. Beginning with the Defining Issues Test (DIT) (Rest et al., 1974 ), Moral Judgment Interview (MJI) (Colby et al., 1987 ), and the updated form of the DIT—the DIT-2 (Rest et al., 1999 ), these instruments have been modeled to varying degrees on Kohlberg’s theory of moral development (Kohlberg & Hersh, 1977 ), which was conceived as a graduated scale of stages and levels: stages 1–2 (preconventional level), stages 3–4 (conventional level), and stages 5–6 ( postconventional level ). The DIT-2 and similar instruments are designed to test the general population and have been applied to a variety of age groups and education levels. Within the past decade and a half, analogous instruments have been developed to assess distinct populations (Borenstein et al., 2008 , 2010 ; Canny & Bielfeldt, 2016 ; Stransky et al., 2023 ). Of particular interest to our research is the engineering education-centric test called the Engineering Ethical Reasoning Instrument (EERI) (Zhu et al., 2014 ). Modeled on the DIT-2, the EERI was developed specifically to assess “individual ethical decision-making of engineering students in project-based design teams” (Zhu et al., 2014 ). Notably, the term ethical decision-making in the context of the EERI’s development is considered essentially synonymous with (or at least highly correlated to) ethical reasoning , though an individual student’s ability to connect these two concepts is an open question, one which is investigated in this paper. For this work, we define ethical reasoning as the active process of wrestling with an ethical dilemma: i.e., analyzing potential solutions, weighing their impacts on stakeholders, etc. When faced with an ethical dilemma and actually making a choice , we term it ethical decision-making. Naturally, ethical decision-making can be influenced by ethical reasoning, and as such the two concepts are linked. However, these concepts are not identical. The decision process reflects both the internal reasoning of the students and the nature of the environment (a situated, interactive, emergent view of ethical decision making). Furthermore, we posit that what these tests measure is not identical with most actual decision-making behavior as it occurs in lived experience, where individuals are plunged into complex, time-sensitive ethical situations in which personal risks and shared risks are in opposition, and decisions are often made based on incomplete knowledge and imperfect information (what they would do). In such situations, timely decisions are more likely to be made using intuition, self interests, and accumulated prior experience (Dreyfus & Dreyfus, 2004 ). Rather, these tests measure the abstract responses of individuals who are given time and opportunity to wrestle with issues and make well-thought-out decisions (what a reasonable, ethical person would do) at their leisure.

Using the EERI as a Measure of Ethical Reasoning

The EERI has been used in numerous educational contexts to assess the ethical reasoning of engineering students, most frequently at the first-year undergraduate (Cimino & Streiner, 2018 ) and graduate levels (Hess et al., 2016 ; Kisselburgh et al., 2016 ). Research has focused primarily on the sensitivity of the instrument to engineering ethics education interventions in the short term (usually one semester) and is frequently paired with the DIT-2. The comparative research has focused on the relationship between population and P (Kohlbergian postconventional thought) and N2 (a mixture of the P score and the extent to which personal interest (I) and maintains norms (M) scores are eschewed) scores finding that in general, older and more experienced engineering students who take the EERI tend to score higher on the EERI than they do on the DIT-2, and when comparing scores pre- to post, the changes in N2 scores on the EERI tend to be larger and are more likely to be positive than the DIT-2 (Hess et al., 2016 ; Kisselburgh et al., 2016 ). This is attributed primarily to the more highly contextualized nature of the EERI, i.e., that when (mature) engineering students are faced with engineering ethics problems, they are more aware that it is best to take a principled perspective than an emotive or normative one. The reasons why this might be the case are complex and may have a lot to do with the differing sense of moral agency students feel in an engineering setting (such as those present in the EERI) versus more general settings (Cimino et al., 2022 ). Conversely, studies among first-year undergraduate students have presented evidence indicating ethics education might temporarily shift engineering students’ mindsets towards more conventional reasoning, i.e., lower P and N2 scores from pre to post (Cimino & Streiner, 2018 ). This situation may be the logical consequence of the juxtaposition of inexperienced engineering students—who are already more likely to be “conventional” thinkers than their graduate-level counterparts—with an ethics education environment where the students are learning to recognize and apply engineering codes of ethics for the first time. However, it is worth noting that in all cases above, the absolute value of the changes observed in DIT-2 or EERI scores assessed in pre-post fashion tend to be very small relative to the prevailing norms (Dong, 2009 ).

Concept Maps as an Additional Assessment Tool

As discussed above, the DIT-2 and EERI are useful for evaluating a student’s ethical reasoning, both as a baseline measure and as a change-over-time measure. Yet, there is another critical piece to this learning puzzle: assessing prior knowledge related to ethics and ethical decision-making more broadly. Student-generated concept maps on ethical decision-making provide one such complementary measurement to ethical reasoning (i.e., comparing depth of ethical concept knowledge to ethical reasoning ability). Concept maps are tools “for people of all ages and all domains of knowledge to express their conceptual understanding about a topic” (Cañas et al., 2013 ). Concept maps have been found to be a useful tool for measuring conceptual knowledge on a topic of interest, as well as how that knowledge can change through instruction. Previous studies have utilized student-generated concept maps in areas such as engineering entrepreneurial mindset (Martine et al., 2019 ), sustainability knowledge (Watson et al., 2014 ), global workforce perceptions (Streiner et al., 2016 ), among others (Tan et al., 2017 ). Concept maps allow students to add any sub-concepts and make connections they deem relevant without prior guidance. This makes concept maps an ideal complementary assessment tool for investigating students’ conceptions of ethical decision-making.

Statement of Intent

To date there has not been enough data collection using the EERI for any educational group to develop norms like those of the DIT-2, meaning that the values of the scores this instrument produces are not yet necessarily characteristic of particular educational groups (unlike the DIT-2, for which stable norms exist for all college education levels). For these reasons, the EERI can, and probably should continue to be paired with other instruments when assessing ethical reasoning until more data have been collected (Kisselburgh et al., 2016 ). Therefore the goal of this paper is to characterize the baseline ethical reasoning skills of first year (FY) undergraduate engineering students using both the DIT-2 & EERI instruments and baseline prior concept-knowledge in ethical decision-making using concept maps. It was hoped that this study will contribute to our overall picture of the ethical reasoning and ethical concept-knowledge of FY engineering students as a population. Furthermore, this study seeks to characterize the extent to which these disparate instruments correlate with one another, and to assess the relevance of the concept map as a tool for assessing ethics concept knowledge. This paper reports the findings from the DIT-2, EERI, concept maps, and their statistical relationship among first-year engineering students during their first academic year (Fall 2020–Spring 2021) of engineering education at the University of Connecticut (UConn), University of Pittsburgh (Pitt), and Rowan University (Rowan) as part of a larger project that investigated the effects of game-based instruction in engineering ethics education in the first year. We hope that in addition to helping build a body of literature that discusses alternative forms of assessment in engineering ethics, that it provides insights into the multifaceted nature of assessing ethical interventions, especially those rooted in active learning.

Research Questions and Hypotheses

This paper explores the topics above by addressing the following research questions:

What are the baseline P/N2 scores of FY undergraduate engineering students who respond to the DIT-2/EERI, and how do they compare to the extant literature data for undergraduate students?

What is the nature of the relationship between ethical reasoning and ethical decision-making concept knowledge among FY engineering students?

It was hypothesized that baseline DIT-2 and EERI P/N2 scores of FY undergraduate engineering students would mirror those of the prevailing norms and existing small-scale studies, respectively. For students whose DIT-2/EERI scores reflected more postconventional levels of moral development and more “sophisticated” ethical reasoning skills, it was hypothesized that they would likewise have more detailed concept maps surrounding ethical decision-making (i.e., higher traditional and holistic scores), reflecting a deeper level of understanding of this topic.

Context of Study: Ethics Instruction Through Playful Learning

While it is not the goal of this paper to assess the effects of ethics instruction on instrument scores, it is still important to discuss the educational context in which this study was undertaken. Details of the ethics instruction framework and the educational contexts in which the instruments were deployed are described below.

Educational Framework

Our framework for understanding all our playful learning activities in the classroom, as well as the ethical decision-making of engineers in authentic real-world settings, draws on the frameworks of embodied cognition (e.g., Barsalou, 2010 ; Muller, 2021 ), situated cognition (Brown et al., 1989 ; CTGV, 1990 ), and situated learning (e.g., Lave & Wenger, 1991 ). A situated cognition view of ethical decision-making also draws on the ecological psychology of Gibson ( 1986 ) and Dreyfus’ ethics of situated involvement, in which acting ethically is an acquired activity ( 2004 ). To understand behavior as “situated” is to reject a cognitivist description of thinking and knowing as storage and retrieval of concepts and schemas that reside in representational neural structures apart from the rest of our bodies, and adopts a dynamic description of knowing (and decision-making) as an emergent interaction between an intentional agent and an information-rich environment. Concepts then are indexical, taking on meaning only in the context in which they are used for intentional acts (see Shaw, 2001 ).

In our project this theoretical framework of embodied situated ethical decision making linked to several educational interventions designed to engage first-year engineers, in large lecture settings, in playful activities designed to make their learning more active. Our interventions used game mechanics and formats to capture student interest, engage them in peer interactions, and induce them to individually and collaboratively make decisions about engineering ethics topics by playing cards, predicting what other freshman classes might have decided, and to vote on how a choose-your-own Mars adventure would proceed week-to-week. These activities were specifically designed to alter student expectations about what they would be doing in a large lecture classroom, and to perhaps suspend their primary goals of achieving high grades, in favor of winning a game or enacting an interesting (funny, clever, creative) game strategy. This was intended to create a game situation, that while not authentic for the lived-in world of practicing engineers, might become an engaging situation in which students could explore their personal situated ethical decision making.

Educational Contexts

At the University of Connecticut, three different game-based ethics education interventions were implemented in a first-year Foundations of Engineering course, which included students from all engineering disciplines except the computing majors. In the first intervention, students engaged weekly with an ethically-situated, narrative, choose-your-own adventure game that asked them to engage with an engineering contextualized story and then make ethically relevant decisions as well as respond to reflection questions. Students’ individual responses were aggregated and the decision with the most support was used to determine the direction of the story in the following week’s narrative. This activity took place over approximately twelve weeks of the Spring ‘21 semester. The other two interventions were an ethically situated card game and an ethically situated board game. Each was played in a single class period in week 9 and week 10 of the course.

Students at the University of Pittsburgh were exposed to the choose-your-own-adventure game across a 1 week period in a Spring ‘21 FY engineering course focused on computer programming. Students were asked to complete the game (and story) individually and at their own pace. Additionally, professional (and academic) integrity modules were included throughout the semester covering topics such as professionalism, academic dishonesty, and engineering ethical codes.

Finally, students at Rowan University completed all three game-based interventions (choose-your-own-adventure, ethically situated card game, and the ethically situated board game) across a subset of sections of a Spring ‘21 FY engineering course. The choose-your-own adventure game was implemented in a similar way as at the University of Connecticut.

Data Collection: Defining Issues Test 2 (DIT-2) and the Engineering Ethical Reasoning Instrument (EERI)

To prevent survey fatigue and to ensure a roughly equal distribution of tests across the three institutions, the EERI was implemented at both the University of Connecticut and Rowan University, and the DIT-2 was implemented at both the University of Pittsburgh and Rowan University. The EERI resulted in a total of 425 students responding and the DIT-2 resulted in a total of 440 students responding. In all cases, students only took a single test regardless of their institution. The demographic distribution of these samples in terms of institution and self-reported sex is provided below (see Table  1 ). Ethical reasoning based on sex/gender/identity is not a main variable in this study, and as such this data is reported only for comparison with earlier studies, where modern notions of gender identity were not explicitly solicited (see Results and Discussion below).

Data Collection: Concept Map Implementation and Assessment

University of Connecticut and Rowan University students were first given instruction in how to construct a concept map using the CMap software (Novak & Cañas, 2006 ) on a general topic to avoid bias and with the goal of ensuring familiarity with creating concept maps. Students were then asked to create their own concept map with the prompt “ethical decision-making” as their topic, with an allowance of 15–20 min. There were a total of 232 responses (198 at University of Connecticut and 34 at Rowan University), of which 225 were “usable” [i.e., created viable concept maps that could be measured using traditional scoring (Watson et al., 2016 )]. The completed maps were first analyzed to quantify their level of complexity and sophistication by looking at the number of terms included, the number of hierarchies (levels of terms), and connections between them, termed “traditional scoring”. This traditional scoring analysis first appeared in the authors’ prior work (Reed et al., 2021 ), and is presented here for the purposes of comparison with the new analysis, termed “holistic scoring” (Besterfield-Sacre et al., 2004 ).

Traditional scoring gives a concept map point values for the number of concepts (breadth of knowledge), number of hierarchies, the number of levels in the highest hierarchy (depth of knowledge), and the number of crosslinks (connectedness of knowledge). These components are detailed in Fig.  1 and through Eq.  1 .

Breakdown of Concept Map (adapted from Watson et al., 2016 )

NC = Number of concepts, NCL = Number of crosslinks, HH = Highest level of hierarchy.

For Fig.  1 example (5 (NC)-3(NCL)) + 2(HH) × 5 + 3(NCL) × 10.

2 + 10 + 30 = 42.

In contrast, the holistic scoring method utilized a research-based Integrated Rubric for Scoring Concept Maps (IRSCM) to score based on comprehension, correctness, and organization (Besterfield-Sacre et al., 2004 )—see Table  2 . The IRSCM has been shown to be useful in capturing students’ conceptualizations of subject areas and can serve as an alternative to traditional scoring (Watson et al., 2016 ). As Besterfield-Sacre et al. ( 2004 ) write, comprehensiveness is used to determine the breadth and depth of students’ knowledge of a topic and how well they define the subject matter more broadly. Organization examines how students connect concepts and the logical approach for portraying these concepts. Correctness evaluates misconceptions students may have and the level of accuracy of the included concepts. Each rubric item was rated on a three-point scale (with 1 being low and 3 being high) and half-point scores were allowed.

The holistic scoring process started with two raters receiving instructions on how to assess concept maps using the IRSCM. First, the raters scored the same 5% of the concept maps (chosen randomly) and scores were compared. The intraclass correlation coefficient (ICC) was next calculated to determine interrater agreement. When the agreement was considered “good” (i.e. above 0.75) (Koo & Li, 2016 ), the maps were scored with remaining discrepancies being discussed amongst the research team in order to finalize the score. The raters were then given equal shares of the next 45% of the concept maps to be scored separately. The raters were then given the remaining 5% to score, share, and when reliability was strong enough, they finalized the scores in the same manner as above. More specifically, comprehensiveness was assessed based on the inclusion of sub-concepts that were included in an “expert concept map” (see Fig.  2 ). This was developed using a modified Delphi technique in which the research team (all who have taught, researched, and/or engaged in ethics education for several years) generated a list of concepts related to ethical decision-making and created a draft concept map together. This concept map was reviewed and revised by a Ph.D. trained ethics education consultant and sent back to the research team. This process was iterated several times until a final “expert concept map” was determined for use with the IRSCM. Organization was evaluated based on the types of connections students were making and whether they branched out linearly or utilized loops. Correctness was scored based on whether the concepts and connections between them were logical.

Expert Concept Map Developed via Modified Delphi Technique

Qualifications and Limitations

While the absolute quantities of student respondents in this study are substantial, it is also important to make note of several qualifying and limiting factors within the experimental design. Notably, all three of the universities involved in this study are major R1 universities in the Northeastern United States with diverse student populations, and the courses in which the students took the three assessments were all two-semester first-year undergraduate introductory engineering design course sequences: one lab based (Rowan University) and others lecture based (University of Connecticut, Pittsburgh). In most instances, the data collection was performed by a PI who also taught the course, though in some cases additional volunteer instructors were involved as well—particularly at Rowan University. While the students in all cases were provided with a brief video training on concept map creation, there was natural variability in the relative emphasis instructors placed on the concept map assignment. Likewise, this study also took place during the height of the COVID-19 pandemic, with Fall’20 courses being largely synchronous online, and Spring’21 courses a vacillating mixture of face-to-face and synchronous online instruction. As such, student engagement and persistence were somewhat lower than expected in a typical year. Finally, it is important to state that the EERI is still in the process of validation, though notably this study took place after several recent changes were implemented to improve the test’s validity after partial confirmatory factor analysis (Odom, 2020 ; Odom & Zoltowski, 2019 ). As such, the absolute numerical values of the present EERI test scores may not be directly comparable to prior published work. Likewise, EERI response data has not yet been benchmarked to the extent that the DIT-2 has, and so it is not currently possible to tell whether the test is sensitive to education level in a similar manner as the DIT-2.

Results and Discussion

Assessment of ethical reasoning using eeri and dit-2.

The mean of the DIT-2 P and N2 scores were compared to the DIT-2 norms of first-year college students generated by the University of Alabama’s Center for the Study of Ethical Development, presented in Table  3 . The DIT-2 norms represent collected responses from 652 diverse data sets from 2005 to 2009 that contain students from many different majors, disciplines, and areas of study (Dong, 2009 ). The student scores from the present study were statistically greater than the DIT-2 norms for first-year students (Dong, 2009 ). The EERI statistics are also compared to the pretest scores of a previous study of first year engineering students at Rowan University in Table  3 (Cimino & Streiner, 2018 ) in which FY engineering students in the same course as the present study took the DIT-2 or the EERI in a pre-post fashion, with a traditional set of ethics interventions in between. In that small-scale study, it was found that there was no statistically significant change in P/N2 scores from pre-to-post, signaling that these instruments may not have the resolution to detect changes in ethical reasoning across a single semester for the FY population (or in the worst case, that the ethics interventions were not capable of shifting student behavior towards postconventional reasoning). Like with the DIT-2, both the P and N2 student scores of the EERI are slightly higher but generally consistent with the previous study.

The EERI and DIT-2 scores were then disaggregated into groups based on self-reported sex. Females scored significantly higher on both the P and N2 scores for the DIT-2 than did males, which is in line with previous research (Bebeau, 2002 ; Bielby et al., 2011 ; Maeda et al., 2009 ). Females scored significantly higher on both the P and N2 scores for the EERI as well, but with a lower effect size. The difference in ethical reasoning between male and female students that is found to be significant for both P and N2 scores of the DIT-2 is consistent with previous research. In particular, it has been previously found that females both within and outside of the field of engineering score significantly higher on the DIT-2 than do males (Bebeau, 2002 ; Bielby et al., 2011 ; Maeda et al., 2009 ). Likewise, in previous research using the EERI, females scored consistently higher than males, but this difference was not statistically significant (Zhu et al., 2015 ). However, the current study found that females scored significantly higher on both the P and N2 measures for the EERI. It is worth noting here also that the scores of the EERI in the current study align closely with the post -scores of higher-educated engineering students assessed in another unrelated study (Kisselburgh, 2016 ). However, as mentioned above in the Limitations, it is impossible to draw any firm conclusions about this observation since the EERI itself is not yet sufficiently benchmarked to allow direct comparison among students at different education levels.

Concept Map Scoring

The concept maps that the first-year engineering students created in their respective courses were scored both through the process of traditional scoring and holistic scoring. Traditional scoring was accomplished using the CMapParse program and the scores were then compiled in SPSS Statistics (Watson et al., 2018 ). Traditional scoring found the number of concepts, number of hierarchies, highest level of hierarchy, number of crosslinks, and the total traditional score using the previously described variables (Table  4 ). The results of the traditional scoring were published in the authors’ previous work (Reed et al., 2021 ) and are reproduced below.

The descriptive statistics in Table  4 display a large variation between students’ traditional scores and the associated variables (Traditional Score = 49.15 ± 39.40). Comparing the Number of Concepts to the other score variables (especially the Number of Crosslinks) it was found that students focus more on the concepts known (16.3), but rarely show how those concepts are interrelated to each other with crosslinks (1.77). Crosslinks are the weakest area of the concept maps with 68.9% having less than 2 crosslinks. Learning research has demonstrated that knowledge is not just about concept retrieval, but specifically drawing the connections between concepts (Rittle-Johnson, 2006 ; Star, 2005 ), and as such, these results are suggestive of a population which has limited reflexive knowledge of ethical decision-making. Such a population could be ripe for influence using tools to develop reflexive principlism such as those espoused by (Beever & Brightman, 2016 ).

The concept maps were next divided up into quarters based on their traditional scores to explore the nature of the differences between the highest and lowest scoring maps (i.e., where is the biggest gap in terms of traditional scoring variables). Figure  3 , reproduced from (Reed et al., 2021 ) illustrates two representative concept maps—one with a low traditional score from the lowest quartile (the bottom 25% of scores) and another with a high traditional score from the highest quartile (the top 25% of scores). Comparing the maps in Fig.  3 , it is easy to see many of the differences between these groups: top-quartile maps have more concepts and a denser looking map with a higher number of cross-links, as well as more hierarchies that go to deeper levels.

Example of bottom quartile map (left—Traditional Score = 9 pts) and top quartile map (right—Traditional Score = 110 pts). Figure reproduced from (Reed et al., 2021 )

Table 5 shows a more precise picture of how the average bottom quartile map compares to the average top quartile map. The coefficient of variation (CV) is the ratio of the standard deviation to the mean and was used to more easily compare the dispersion of data between the different variables. The top quartile maps had twice as many concepts, on average, as bottom quartile maps and likewise maintained a similar CV. Despite there being almost no difference in the number of hierarchies between the two quartiles, the top quartile maps illustrated that these individuals can draw deeper connections between associated concepts in ethical decision-making than bottom quartile individuals, with over twice as many levels of hierarchy as those of the bottom quartile. In fact, the bottom quartile maps do not include a single cross link. Furthermore, the average total scores between top and bottom quartiles are vastly different, with the highest scoring maps being almost five times higher than the low scoring maps. However, the CV in top quartile maps is almost double that of the bottom quartile, due to a small number of very high scores. Overall, the bottom quartile maps were more consistent in their map construction with lower variation, but top quartile maps had higher scores across the board, implying that top quartile individuals are in general substantially more capable of identifying ethical decision-making concepts and drawing connections between associated concepts than bottom quartile individuals.

The holistic scoring statistics also provided insight into the distribution of comprehension about ethical decision-making and concept organization among first-year students, resulting in an average total score of 5.40 out of 9.00 (see Table  6 ). The average comprehension and organization scores of the concept maps (1.60 and 1.77, respectively) were the weakest areas, with average correctness scores being somewhat higher. The low organization scores again exemplified the lack of crosslinks that show the interrelation of concepts. The low average comprehension score showed that in general first-year engineering students have a novice’s understanding of ethics prior to formal ethics education. While the average correctness score was higher than the others (2.03 out of 3), there was clearly still room for improvement. Taken together with the traditional scoring, these holistic scores start to paint a picture for how first-year engineering students initially approach ethical reasoning and ethical decision-making. While they may understand many concepts associated with ethics in general , they may not fully comprehend the relationships between these concepts or how they might weigh into their own ethical decisions in context (Detterman & Sternberg, 1993 ). This showcases the need for instructors to focus on the interrelation of topics in the engineering ethics classroom which can lead to a deeper understanding of ethics and ethical reasoning (Gauthier, 2013 ). Case studies and similar strategies, such as role-playing games based in case studies, have been shown to reinforce connections in many topics in engineering ethics such as analyzing situations, considering outcomes, acknowledging biases and values, implementing codes of ethics, and promoting an ethic of care (Hess & Fore, 2018 ; Loendorf, 2009 ). As such, the authors’ educational approach, incorporating context-rich role playing scenarios (Streiner et al., 2021 ), have the potential for such reinforcement.

Relationship Between Conceptualizations of Ethical Decision-Making (Concept Maps) and Performing Ethical Reasoning (DIT-2/EERI)

The results of the EERI and DIT-2 assessments suggest that engineering students come into their first-year engineering program with a level of ethical reasoning comparable to the population norm at this level of education. Furthermore, the concept map data indicates that they do not have as rigorous an understanding of ethical decision-making as more experienced engineering professionals (the authors). At a deeper level, it was also observed that first-year students do not fully understand the relationships between many of the concepts that they do know in ethics and ethical decision-making. This observation may be the product of students who are drawing more on their experiences of normative social ethics or personal ethics (Abaté, 2011 ) rather than professional ethics (Harris et al., 1996 ). These normative social and personal conceptions of ethics are often instilled within people from a young age by the people and culture surrounding them (Abaté, 2011 ), and as such become second nature, resulting in a diverse range of emotive, instinctive or intuitive responses to common ethical scenarios (Sadler & Zeidler, 2005 ). Professional ethics, however, are the agreed-upon standards that guide those who work in a specific field (Harris et al., 1996 ). It is logical that students at this level would react to a situation in engineering by drawing upon more normative social and personal experiences/instincts, but not professional ones, due to their relative inexperience. Notably, engineering ethics codes are a major part of first-year engineering ethics education, and so recognition of the professional dimensions of ethics would be expected to change post-intervention. Yet, none of this discussion precludes the fact that first-year engineering students do often have their own preconceived notions of what an engineer is “supposed” to do in a given situation (Cimino et al., 2022 ) regardless of whether these opinions concur with actual professional codes (Davis, 1999 ). However, when students are asked to express their knowledge on ethical decision-making and the concepts that guide them, they may lack the ability to reflexively draw the connections between these concepts. If this ethical decision-making knowledge is successfully introduced to the students, their comprehension of professional ethics within engineering may be greatly improved. Growing this relationship between common/personal ethics and professional ethics is something that engineering education curricula should be striving for when producing professional engineers that live up to the standards set by the NSPE.

Correlation of DIT-2/EERI Scores and Concept Map Scores

To investigate the extent to which there is a correlation between conceptualizations of ethical decision-making (concept maps) and performing ethical reasoning (EERI or DIT-2), Spearman rank correlations were determined between the DIT-2 and Concept Map Scores, and between the EERI scores and the Concept map scores for each individual who had successfully completed both assessments (n = 54)—Tables 7 and 8 below. Spearman Rank Correlation assesses how well the relationship between two variables can be described using a monotonic function. Spearman correlations of + 1 or − 1 indicate perfect monotonicity (a strong correlation in either increasing (+ 1) or decreasing (− 1) monotonic trend) and a value near zero indicates no correlation (i.e., the two variables are orthogonal). Comparing the DIT-2 and EERI to the Concept Map scores, the total correlation scores for both traditional and holistic scoring systems indicate essentially no correlation, with no Spearman’s |ρ|≥ 0.2. This result is very interesting from the viewpoints of both educators and education assessment—namely that performance on the DIT-2 or EERI is likely not an indicator of concept map score, therefore implying that a first-year engineering student’s ability to perform ethical reasoning—on the EERI or DIT-2 test at least—is not well-informed by their abstract understanding of ethical decision-making concepts prior to formal ethics education .

Conclusions

In this study, the baseline ethical reasoning capability, as gauged by the DIT-2 & EERI, was measured for a large group (N DIT-2  = 440, N EERI  = 425) of first year engineering students. In answer to RQ1: the baseline DIT-2 P/N2 scores of first-year engineering students are largely indistinguishable from the general population at this level of education. Likewise, EERI P/N2 scores, which in general are numerically larger by about 20 points than DIT-2 scores, are also similar to those previously determined in a small scale study on first-year engineers (where the EERI showed negligible change pre-to-post intervention (Cimino & Streiner, 2018 ). When asked to complete Concept Maps on ethical decision-making, a large variation was found in traditional scores (Traditional Score = 49.15 ± 39.40), with students focusing heavily on concepts known, while not recognizing the links between concepts. In holistic terms, comprehension and organization scores of the concept maps were weak (both < 2 out of 3), with average correctness being moderate (~ 2 out of 3). The low organization scores are in a large part due to the lack of crosslinks that illustrate the interrelation of concepts.

Perhaps the most surprising and interesting result of this study is in regard to the nature of the relationship between ethical reasoning and ethical decision-making concept knowledge among FY engineering students (RQ2). It has been found that FY engineering student concept maps generally have no bearing whatsoever on student DIT-2/EERI scores. The near-zero correlations of DIT-2 and EERI scores with concept map parameters suggest knowing about ethical concepts and performing ethical reasoning in ethical dilemmas may draw on different cognitive and emotional skills and information, and perhaps rely on different thought processes as well. This would not be surprising from a situated cognition framework. Since the situated view would contend that both ethical knowledge and ethical decision-making emerge within context, when the context changes from brief scenarios to the concept mapping task (without applied context), the situated thinking that emerges would be different. We would further contend that ethical decision-making in richly contextualized scenarios (such as immersive virtual reality or enacted role playing) would be equally different, but yet have greater invariance with real-world engineering decision-making than either the concept mapping task or the text-based scenarios task.

When asked to produce concept maps without a scenario context, students may not be using purely logical conceptual reasoning and may not even be aware of the reasoning they are using to construct the abstract concept maps. Instead, they may be relying on thought processes used in their personal lives (normative social and personal conceptions of ethical behavior), as well as their preconceived notions of how an engineer should perceive and act as a professional. Equally plausible is the possibility that they may not be applying reasoning at all—rather, they may be making judgements intuitively or instinctively, without recourse to reason. An additional factor that cannot be overlooked is that of response bias, i.e., they may be performing the task with the intentions of typical classroom assignments, seeking to produce the instructor-approved “correct” concept map response. A situated cognitive view would suggest that professional engineering practitioners would typically be influenced more by industry and societal norms including codes of ethics than they would be by personal ethics from outside their work context. This would be determined as much by the context of the decision as it would be by the engineer’s abstract knowledge and prior experiences.

We would suggest then that “engineering ethical reasoning” describes tasks in which (future) engineers are asked to draw from abstract concepts of ethical principles and apply them from a third-person perspective to one or more imaginary scenarios (as in the DIT-2 and EERI). Likewise “ethical decision-making knowledge” would describe what students produce on tasks like our concept mapping assignment, in a context that lacks any details of an applied engineering authentic context(s). Finally, we would describe our playful learning approaches (Streiner et al., 2021 ) that attempt to establish realistic contexts that situate students as engineering professionals making authentic ethical decisions, as “richly situated ethical decision-making”. We posit that such “richly situated ethical decision-making” most closely resembles real-world behavior from an ecological psychology perspective, wherein behavior emerges in context as an interaction of an intentional agent and an information-rich environment.

Based on our current work, several areas of inquiry arise for potential future study. In particular, the observed differences in concept maps and DIT-2/EERI scores from pre to post must be investigated with regard to specific ethics education interventions. Likewise, the effects of the ethics interventions on the instrument scores and concept maps could be investigated by employing qualitative methods such as discussion groups, interviews, think-alouds etc. The results of which could then inform traditional and alternative pedagogies, such as playful learning, to incorporate situated, authentic and contextually rich ethical decision-making strategies that support agency and experience for undergraduate engineering students.

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Acknowledgements

The authors wish to acknowledge the National Science Foundation under award numbers 1934707 and 2211320.

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Cimino, R.T., Streiner, S.C., Burkey, D.D. et al. Comparing First-Year Engineering Student Conceptions of Ethical Decision-Making to Performance on Standardized Assessments of Ethical Reasoning. Sci Eng Ethics 30 , 23 (2024). https://doi.org/10.1007/s11948-024-00488-y

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Engineering is a wide field of study that is divided into various branches such as Civil, Electrical, Mechanical, Electronics, Chemical, etc. Basically, each branch has thousands of engineering research topics to focus on. Hence, when you are asked to prepare an engineering research paper or dissertation for your final year assignments, you might experience difficulties with identifying a perfect topic. But hereafter, you need not worry about topic selection because to make the topic selection process easier for you, here we have suggested some tips for choosing a good engineering research topic. Additionally, we have also shared a list of the best 150+ engineering research paper topics on various specializations. Continue reading this blog to get exclusive ideas for engineering research paper writing.

Engineering Research Paper Topic Selection Tips

When it comes to research in the field of engineering, identifying the best engineering research topic is the first step. So, during that process, in order to identify the right topic, consider the following tips.

• Choose a topic from the research area matching your interest.
• Give preference to a topic that has a large scope to conduct research activities.
• Pick a topic that has several reference materials and evidence supporting your analysis.
• Avoid choosing an already or frequently discussed topic. If the topic is popular, discuss it from a different perspective.
• Never choose a larger topic that is tough to complete before the deadline.
• Finalize the topic only if it satisfies your academic requirements.

List of the Best Engineering Research Topics

Are you searching for the top engineering project ideas? Would you have to complete your academic paper on the best engineering research topic? If yes, then take a look below. Here, we have suggested a few interesting engineering topics in various disciplines that you can consider for your research or dissertation.

Mechanical Engineering Research Topics

• How does the study of robotics benefit from a mechanical engineering background?
• How can a new composite substitute reduce costs in large heat exchangers?
• Which will become the predominant energy technology this century?
• Why structural analysis is considered the foundation of mechanical engineering?
• Why is cast iron used in the engines of large ships?
• What is the finite element approach and why is it essential?
• Why is the flow of fluids important in mechanical engineering?
• What impact does mechanical engineering have in the medical field?
• How do sports incorporate mechanical engineering theories?
• What is the process of thermal heat transfer in machines?
• How can solar panels reduce energy costs in developing countries?
• In what ways is mechanical engineering at the forefront of the field?
• How do various elements interact differently with energy?
• How can companies improve manufacturing through new mechanical theories?

Additional Research Paper Topics on Mechanical Engineering

• Power generation: Extremely low emission technology.
•   Rail and wheel wear during the presence of third-body materials.
•  Studying the impact of athletic shoe properties on running performance and injuries
• Evaluating teeth decay using patient-specific tools
•   Nanotechnology.
• Describe the newly developed methods and applications in Vibration Systems
• Perspective or general Commentaries on the methods and protocols relevant to the research relating to Vibration Systems
• Software-related technology for Visibility of end-to-end operations for employee and management efficiencies
• What should be the best strategies to apply in the planning for consumer demand and responsiveness using data analytics
• Analysis of the monitoring of manufacturing processes using IOT/AI
• Critical analysis of the advancing digital manufacturing with artificial intelligence (AI) and machine learning (ML) Data Analytics
• Pyrolysis and Oxidation for Production and Consumption of Strongly Oxygenated Hydrocarbons as Chemical Energy Carriers: Explain
• Explore the most effective strategies for fatigue-fracture and failure prevention of automotive engines and the importance of such prevention
• Explore the turbomachinery performance and stability enhancement by means of end-wall flow modification
• Production optimization, engine performance, and tribological characteristics of biofuels and their blends in internal combustion engines as alternative fuels: Explain

Civil Engineering Research Topics

• The use of sustainable materials for construction: design and delivery methods.
• State-of-the-art practice for recycling in the construction industry.
• In-depth research on the wastewater treatment process
• Building Information Modelling in the construction industry
• Research to study the impact of sustainability concepts on organizational growth and development.
• The use of warm-mix asphalt in road construction
• Development of sustainable homes making use of renewable energy sources.
• The role of environmental assessment tools in sustainable construction
• Research to study the properties of concrete to achieve sustainability.
• A high-level review of the barriers and drivers for sustainable buildings in developing countries
• Sustainable technologies for the building construction industry
• Research regarding micromechanics of granular materials.
• Research to set up remote sensing applications to assist in the development of sustainable construction techniques.
• Key factors and risk factors associated with the construction of high-rise buildings.
• Use of a single-phase bridge rectifier
• Hydraulic Engineering: A Brief Overview
• Application of GIS techniques for planetary and space exploration
•   Reengineering the manufacturing systems for the future.
• Production Planning and Control.
•   Project Management.
•   Quality Control and Management.
•   Reliability and Maintenance Engineering.

Environmental Engineering Research Paper Topics

• Design and development of a system for measuring the carbon index of energy-intensive companies.
• Improving processes to reduce kWh usage.
• How can water conductivity probes help determine water quality and how can water be reused?
• A study of compressor operations on a forging site and mapping operations to identify and remove energy waste.
• A project to set up ways to measure natural gas flow ultrasonically and identify waste areas.
• Developing a compact device to measure energy use for a household.
• What are carbon credits and how can organizations generate them?
• Production of biogas is from organic coral waste.
• Analyzing the impact of the aviation industry on the environment and the potential ways to reduce it.
• How can voltage reduction devices help organizations achieve efficiency in electricity usage?
• What technologies exist to minimize the waste caused by offshore drilling?
• Identify the ways by which efficient control systems using information systems can be introduced to study the energy usage in a machining factory.
• The process mapping techniques to identify bottlenecks for the supply chain industry.
• Process improvement techniques to identify and remove waste in the automotive industry.
• In what ways do green buildings improve the quality of life?
• Discussion on the need to develop green cities to ensure environmental sustainability
• Process of carbon dioxide sequestration, separation, and utilization
• Development of facilities for wastewater treatment

Read more topics: Outstanding Environmental Science Topics for You to Consider

Electrical Engineering Research Topics

• Research to study transformer losses and reduce energy loss.
• How does an ultra-low-power integrated circuit work?
• Setting up a control system to monitor the process usage of compressors.
• Integration of smart metering pulsed outputs with wireless area networks and access to real-time data.
• What are the problems of using semiconductor topology?
• Developing effective strategies and methodical systems for paying as-you-go charging for electric vehicles.
• A detailed review and investigation into the key issues and challenges facing rechargeable lithium batteries.
• Trends and challenges in electric vehicles technologies
• Research to investigate, develop and introduce schemes to ensure efficient energy consumption by electrical machines.
• What is meant by regenerative braking?
• Smart charging of electric vehicles on the motorway
• Research to study metering techniques to control and improve efficiency.
• Develop a scheme to normalize compressor output to kWh.
• Research to introduce smart metering concepts to ensure efficient use of electricity.
• What is the most accurate method of forecasting electric loads?
• Fundamentals of Nanoelectronics
• Use of DC-to-DC converter in DC (Direct Current) power grid
• Development of Microgrid Integration

Electronics and Communications Engineering Research Topics

• Developing the embedded communication system for the national grid to optimize energy usage.
• Improvement of inter-symbol interference in optical communications.
• Defining the boundaries of electrical signals for current electronics systems.
• The limitation of fiber optic communication systems and the possibility of improving their efficiency.
• Gaussian pulse analysis and the improvement of this pulse to reduce errors.
• A study of the various forms of errors and the development of an equalization technique to reduce the error rates in data.
• Realizing the potential of RFID in the improvement of the supply chain.
• Design of high-speed communication circuits that effectively cut down signal noise.
• Radiation in integrated circuits and electronic devices.
• Spectral sensing research for water monitoring applications and frontier science and technology for chemical, biological, and radiological defense.

Computer and Software Engineering Research Topics

• How do businesses benefit from the use of data mining technologies?
• What are the risks of implementing radio-controlled home locks?
• To what extent should humans interact with computer technologies?
• Are financial trading systems operating over the web putting clients at risk?
• What challenges do organizations face with supply chain traceability?
• Do chatbot technologies negatively impact customer service?
• What does the future of computer engineering look like?
• What are the major concepts of software engineering?
• Are fingerprint-based money machines safe to use?
• What are the biggest challenges of using different programming languages?
• The role of risk management in information technology systems of organizations.
• In what ways does MOOD enhancement help software reliability?
• Are fingerprint-based voting systems the way of the future?
• How can one use an AES algorithm for the encryption of images?
• How can biological techniques be applied to software fault detection?

Read more: Creative Capstone Project Ideas For Students

Network and Cybersecurity Engineering Research Topics

• Write about Cybersecurity and malware connection.
• How to detect mobile phone hacking.
• Discuss Network intrusion detection and remedies.
• How to improve network security using attack graph models.
• Explain Modern virus encryption technology.
• Investigate the importance of algorithm encryption.
• Discuss the role of a firewall in securing networks.
• Write about the global cybersecurity strategy.
• Discuss the Privacy and security issues in chatbots.
• Write about Cloud security engineering specifics

Industrial Engineering Research Paper Topics

• The application of lean or Six Sigma in hospitals and services-related industries.
• The use of operation research techniques to reduce cost or improve efficiency.
• Advanced manufacturing techniques like additive manufacturing.
• Innovation as a Complex Adaptive System.
• CAD-based optimization in any manufacturing environment.
• Gap analysis in any manufacturing firm.
• The impact of 3D printing in the manufacturing sector.
• Simulating a real-life manufacturing environment into simulating software
• The rise of design and its use in the developing world.
• Building a network-based methodology to model supply chain systems.
• Risk optimization With P-order comic constraint
• Technology and its impact on mass customization
• How project management becomes more complex with disparate teams and outsourced functions?
• Scheduling problem for health care patients.

Biomedical Engineering Research Ideas

• How does the use of medical imaging help patients with higher risks?
• How can rehabilitation techniques be used to improve a patient’s quality of life?
• In what ways can biomaterials be used to deliver medications more efficiently?
• What impact does medical virtual reality have on a patient’s care?
• What advancements have been made in the field of neural technology?
• How does nanotechnology pave the way for further advancements in this field?
• What is computational biology and how does it impact our lives?
• How accurate are early diagnosis systems in detecting heart diseases?
• What does the future hold for technology-fueled medications?
• What are the guiding principles of biomedical engineering research?

Read more: Top Biology Research Topics for Academic Writing

Chemical Engineering Research Topics

• How can epoxy resins withstand the force generated by a firing gun?
• The use of software affected design aspects in chemical engineering.
• What challenges are there for biochemical engineering to support health?
• The advancements of plastic technology in the last half-century.
• How can chemical technologies be used to diagnose diseases?
• What are the most efficient pathways to the development of biofuels?
• How can charcoal particles be used to filter water in developing countries?
• Increased production of pharmacy drugs in many countries.
• How do complex fluids and polymers create more sustainable machinery?

Miscellaneous Engineering Research Ideas

• Sensing and controlling the intensity of light in LEDs.
• Design and development of a pressure sensor for a solar thermal panel.
• Development of microsensors to measure oil flow rate in tanks.
• How can organizations achieve success by reducing bottlenecks in the supply chain?
• Research to identify efficient logistics operations within a supply chain.
• Developing frameworks for sustainable assessments taking into account eco-engineering measures.
• Research to identify process improvement plans to support business strategies.
• What can engineers do to address the problems with climate change?
• The impact of training on knowledge performance index within the supply chain industry.
• Research to introduce efficiency within information systems and support the timely transfer of knowledge and information.

Out of the 150+ engineering research paper topics and ideas suggested in this blog, choose any topic that is convenient for you to conduct research and write about. In case, you have not yet identified a good topic for your engineering research paper, reach out to us immediately.

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Development of revolutionary color-tunable photonic devices

A team at Pohang University of Science and Technology (POSTECH), spearheaded by Professor Su Seok Choi and Ph.D. candidate Seungmin Nam from the Department of Electrical Engineering, has developed a novel stretchable photonic device that can control light wavelengths in all directions. This pioneering study was published in Light: Science & Applications on May 22.

Structural colors are produced through the interaction of light with microscopic nanostructures, creating vibrant hues without relying on traditional color mixing methods. Conventional displays and image sensors blend the three primary colors (red, green, and blue), while structural color technology leverages the inherent wavelengths of light, resulting in more vivid and diverse color displays. This innovative approach is gaining recognition as a promising technology in the nano-optics and photonics industries.

Traditional color mixing techniques, which use dyes or luminescent materials, are limited to passive and fixed color representation. In contrast, tunable color technology dynamically controls nanostructures corresponding to specific light wavelengths, allowing for the free adjustment of pure colors. Previous research has primarily been limited to unidirectional color tuning, typically shifting colors from red to blue. Reversing this shift -- from blue to red, which has a longer wavelength -- has been a significant challenge. Current technology only allows adjustments towards shorter wavelengths, making it difficult to achieve diverse color representation in the ideal free wavelength direction. Therefore, a new optical device capable of bidirectional and omnidirectional wavelength adjustment is needed to maximize the utilization of wavelength control technology.

Professor Choi's team addressed these challenges by integrating chiral liquid crystal elastomers (CLCEs) with dielectric elastomer actuators (DEAs). CLCEs are flexible materials capable of structural color changes, while DEAs induce flexible deformation of dielectrics in response to electrical stimuli. The team optimized the actuator structure to allow both expansion and contraction, combining it with CLCEs, and developed a highly adaptable stretchable device. This device can freely adjust the wavelength position across the visible spectrum, from shorter to longer wavelengths and vice versa.

In their experiments, the researchers demonstrated that their CLCE-based photonic device could control structural colors over a broad range of visible wavelengths (from blue at 450nm to red at 650nm) using electrical stimuli. This represents a significant advancement over previous technologies, which were limited to unidirectional wavelength tuning.

This research not only establishes a foundational technology for advanced photonic devices but also highlights its potential for various industrial applications.

Professor Choi remarked, "This technology can be applied in displays, optical sensors, optical camouflage, direct optical analogue encryption, biomimetic sensors, and smart wearable devices, among many other applications involving light, color, and further broadband electromagnetic waves beyond visible band. We aim to expand its application scope through ongoing research."

• Medical Technology
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• Flexible-fuel vehicle

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Materials provided by Pohang University of Science & Technology (POSTECH) . Note: Content may be edited for style and length.

Journal Reference :

• Seungmin Nam, Wontae Jung, Jun Hyuk Shin, Su Seok Choi. Omnidirectional color wavelength tuning of stretchable chiral liquid crystal elastomers . Light: Science & Applications , 2024; 13 (1) DOI: 10.1038/s41377-024-01470-w

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