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1. Experts' and novices' perspectives on the priority of affective dimensions in civil engineering: A mixed methods study

   London, J; Christina, L. A.; Borders, J; Perry, L; Ayer, S; Wu, W. (January 2020, IJEE International Journal of Engineering Education)

   null (Ed.)

   Although some have called for engineering curricula that fully integrates learning in the head (cognitive), hand (skill), and heart (affective) domains, others acknowledge the difficulty of overhauling existing curriculum to adequately prioritize the ''heart''. The opinions of experts are often consulted to inform curricular changes, but this is rarely compared to the opinions of novices. There is a need for a better understanding of both experts' and novices' perspectives on the role of the ''heart'' in engineering education and in engineering work. With an emphasis on civil engineering, this study uses a convergent parallel mixed methods research design and Shulman's Three Apprenticeships framework to investigate expert and novice perspectives on the priority of affective constructs in undergraduate education and their approach to designing facilities for users with needs different from their own. Data was collected from civil engineering experts and novices at an annual regional civil engineering-focused conference. Results suggest experts and novices may have different perspectives on which values should be emphasized earlier versus later in civil engineering education. Implications of the results from this study suggest that while many values should be emphasized in engineering education, it might be important for educators to emphasize certain values (e.g., compassion) earlier rather than later to assist in the development of a well-rounded engineer. 

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2. Human Expertise and AI in Civil Engineering: Competencies for Responsible Engineering Practice

   Volpe, E; Simmons, D R; Beddoes, K (September 2025, Annual Conference of the European Society for Engineering Education (SEFI))

   As artificial intelligence (AI) rapidly evolves, its integration into civil engineering presents both significant opportunities and challenges. Through a qualitative analysis of interview, survey, and reflection journal data, this study explores the perspectives of early-career civil engineers regarding the current and potential roles of AI in engineering practice. While AI is seen as a valuable tool for automating routine tasks and enhancing efficiency, concerns persist about its reliability, ethical implications, and potential overreliance. Participants emphasized the importance of maintaining human oversight, with AI serving as an aid rather than a replacement for engineering judgment. The study identifies key competencies essential for engineers to effectively and ethically integrate AI, including AI literacy, critical thinking, ethics, and cybersecurity awareness. As AI continues to influence the field, it is crucial to equip engineers with these competencies through education and ongoing professional development. The paper offers recommendations for integrating responsible AI practices into engineering education and the workplace, highlighting the need for continuous training in both technical skills and ethical decision-making. This research contributes to the growing literature on responsible AI integration, providing insights that can guide the future workforce in navigating the complexities of AI-enhanced engineering practices. 

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3. Investigating the Effect of Engineering Undergraduates’ Writing Transfer Modes on Lab Report Writing in Entry-level Engineering Lab Courses

   Riley, Charles E.; Kim, Dave; Lulay, Ken; Lynch, John D.; St.Clair, Sean (June 2021, 2021 ASEE Annual Conference Proceedings)

   Engineering undergraduates are exposed to a variety of writing curricula, such as first-year-composition courses, in their early program of study; however, they have difficulties meeting the expectations of writing in early engineering courses. On the other hand, instructors in entry-level engineering lab courses struggle to instruct lab report writing due to a wide range of student writing backgrounds and pressure to focus on technical content. When using the lens of learning transfer theories, which describe the processes and the effective extent to which past experiences affect learning and performance in a new situation, we can classify engineering students in three writing transfer modes: 1) concurrent transfer, which occurs when a rhetorically-focused technical writing class is taken concurrently or prior to engineering labs in the major; 2) vertical transfer, which occurs when a rhetorically-focused general education writing class is taken prior to engineering labs in the major; and 3) absent transfer, which occurs when no rhetorically-focused writing class exists (rather literature-focused) or writing-intensive courses are not required in the general education curriculum. This study aims to investigate how the engineering sophomore’s past writing experience, specifically in collegiate writing or writing-across-the-curriculum courses, affects their engineering lab report writing. Lab reports from four sophomore engineering courses (1 civil, 2 electrical, 1 general engineering) across three institutions collected for analysis consisted of two sets: the sample sets in early labs (for example, Lab 1) and in later labs (for example, the last lab) of the courses. A total of 46 reports (22 early and 24 later) were collected from 22 engineering sophomores during AY2019-2020. Four engineering faculty (1 civil, 1 electrical, and 2 mechanical engineering) developed a rubric based on lab report writing student outcomes, which are aligned with the existing outcomes such as ABET outcomes and the student outcomes from the Council of Writing Program Administrators (WPA). The data suggest that the greatest writing gains in a first lab course are made by vertical transfer students, while concurrent transfer students enter with skills developed in prior writing coursework. The largest improvements among the three transfer modes were found in the student outcomes related to lab data presentation, analysis, and interpretation. In these outcomes, the concurrent transfer students had relatively high scores for both early and later reports, while the vertical transfer students improved their scores from relatively low in early reports to meet expectations in later reports. Absent transfer students demonstrated inconsistent outcomes and deserve greater study with more data than was available for this study. 

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4. What should we do with Emotion AI? Towards an Agenda for the Next 30 Years

   https://doi.org/10.1145/3678884.3689135  

   Andalibi, Nazanin; Stark, Luke; McDuff, Daniel; Picard, Rosalind; Gratch, Jonathan; Howell, Noura (November 2024, ACM)

   What should we do with emotion AI? Should we regulate, ban, promote, or re-imagine it? Emotion AI, a class of affective computing technologies used in personal and social computing, comprises emergent and controversial techniques aiming to classify human emotion and other affective phenomena. Industry, policy, and scientific actors debate potential benefits and harms, arguing for polarized futures ranging from panoptic expansion to complete bans. Emotion AI is proposed, deployed, and sometimes withdrawn in collaborative contexts such as education, hiring, healthcare, and service work. Proponents expound these technologies’ benefits for well-being and security, while critics decry privacy harms, civil liberties risks, bias, and shaky scientific foundations, and gaps between technologies’ capabilities and how they are marketed and legitimized. This panel brings diverse disciplinary perspectives into discussion about the history of emotions—as an example of ’intimate’ data—in computing, how emotion AI is legitimized, people’s experiences with and perceptions of emotion AI in social and collaborative settings, emotion AI’s development practices, and using design research to re-imagine emotion AI. These issues are relevant to the CSCW community in designing, evaluating, and regulating algorithmic sensing technologies including and beyond emotion-sensing. 

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5. Investigating the Effect of Engineering Undergraduates’ Writing Transfer Modes on Lab Report Writing in Entry-level Engineering Lab Courses

   Riley, Charles; Kim, Dave; Lulay, Ken; Lynch, John D.; St. Clair, Sean (July 2021, ASEE Annual Conference proceedings)

   Engineering undergraduates are exposed to a variety of writing curricula, such as first-year-composition courses, in their early program of study; however, they have difficulties meeting the expectations of writing in early engineering courses. On the other hand, instructors in entry-level engineering lab courses struggle to instruct lab report writing due to a wide range of student background in writing. When using the lens of learning transfer theories, which describe the processes and the effective extent to which past experiences affect learning and performance in a new situation, we can classify engineering students in three writing transfer modes: 1) concurrent transfer, which occurs when a rhetorically-focused technical writing class is taken concurrently or prior to engineering labs in the major; 2) vertical transfer, which occurs when a rhetorically-focused general education writing class is taken prior to engineering labs in the major; and 3) absent transfer, which occurs when no rhetorically-focused writing class exists (rather literature-focused) or writing-intensive courses are not required in the general education curriculum. This study aims to investigate how the engineering sophomore’s past writing experience affects their engineering lab report writing. Lab reports from four sophomore engineering courses (1 civil, 2 electrical, 1 general engineering) across three institutions collected for analysis consisted of two sets: the sample sets in early labs (for example, Lab 1) and in later labs (for example, the last lab) of the courses. A total of 46 reports (22 early and 24 later) were collected from 22 engineering sophomores during AY2019-2020. Four engineering faculty (1 civil, 1 electrical, and 2 mechanical engineering) developed a rubric based on lab report writing student outcomes, which are aligned with the existing outcomes such as ABET outcomes and the student outcomes from the Council of Writing Program Administrators (WPA). Data collected via early-later lab reports show that student outcomes related to writing conventions were scored high regardless of the transfer modes. The largest variations among three transfer modes were found in the student outcomes related to lab data presentation, analysis, and interpretation. In these outcomes, the concurrent transfer students had relatively high scores for both early and later reports, while the vertical transfer students improved their scores from relatively low in early reports to high in later reports. This research results show that the area of writing knowledge that has been most influenced by their writing curricula prior to sophomore engineering lab courses is disciplinary meaning-making through presenting, analyzing, and interpreting lab data for the technical audience. 

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