Displaying results 31 - 60 of 138 in total
Insights into Faculty's use of Generative Artificial Intelligence systems in Engineering Classrooms.
- Conference Session
- Faculty Development: Grading and Artificial Intelligence
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Azadeh Hassani, University of Nebraska - Lincoln; Tareq Daher, University of Nebraska - Lincoln; Guy Trainin, University of Nebraska Lincoln; Jordan M Wheeler, University of Nebraska - Lincoln
- Tagged Topics
- Diversity
- Tagged Divisions
- Faculty Development Division (FDD)
. The Chronicle of Higher Education has observed, One year after its release, ChatGPT has pushed higher education into a liminal place. Colleges are still hammering out large-scale plans and policies governing how generative AI will be dealt with in operations, research, and academic programming. But professors have been forced more immediately to adapt their classrooms to its presence. Those adaptations vary significantly, depending on whether they see the technology as a tool that can aid learning or as a threat that inhibits it [11]. Faculty perspectives and responses are particularly critical in professional programs suchas engineering, medicine, and teacher preparation, where the rapid integration
- Conference Session
- Panel: AI and Engineering Technology Education: What, Why, How?
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- Meenakshi Narayan, Miami University; Lokesh Kumar Saharan, Gannon University
- Tagged Topics
- Diversity
- Tagged Divisions
- Engineering Technology Division (ETD)
Reshaping Engineering Technology Education: Fostering Critical Thinking through Open-Ended Problems in the Era of Generative AIAbstractAcademic integrity breaches and plagiarism existed long before the rise of Generative Artificialintelligence (G-AI), where students used paid online tutoring platforms like Chegg to obtain helpwith homework assignments, take-home exams, and course projects. Additionally, G-AIplatforms such as ChatGPT provide students with immediate support in understanding conceptsand improving problem-solving abilities. However, it also opens up possibilities for students toimproperly use the technology for homework and exams. This necessitates a revision in howeducators design curricula and
- Conference Session
- Engineering Management Division (EMD) Technical Session 2
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- Sakhi Aggrawal, Purdue University ; Paul J. Thomas
- Tagged Topics
- Diversity
- Tagged Divisions
- Engineering Management Division (EMD)
quantitative data.Concurrently, qualitative data was thematically analyzed to gain insights into usage andperceptions surrounding AI.Results: The study revealed a growing trend among project management professionals inleveraging AI tools for a variety of tasks, including project planning, task assignment, tracking,and crafting emails, reports, and presentations. A strong correlation was observed betweenfamiliarity with ChatGPT and its likely usage in project management tasks. While someparticipants found AI tools convenient and efficient, they were frustrated with potentialinaccuracies and the need for specific input prompts. Overall, industry professionalsdemonstrated the usage of AI in project management, with a notable emphasis on taskautomation
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- 2024 ASEE North East Section
- Authors
- Abdullah Aldwean, University of Bridgeport ; Dan Tenney, University of Bridgeport
- Tagged Topics
- Diversity
mechanism called attention [18].Despite the LLM technical characteristics and sophisticated capabilities, the introduction ofconversational-based models such as ChatGPT has established a new paradigm in human-AIinteraction. The wide adoption and the fast diffusion of these models reflect a deep interest in AIbased products by users. According to the OpenAI company, the ChatGPT has 100 millionweekly active users [15].Efficient evaluation is a crucial step in ensuring the applicability of LLMs in the healthcaresector. While automated evaluation methods are more cost and time-efficient, human evaluationremains the golden standard for determining the safety and usefulness of LLM in healthcare.Experts-based evaluation is critical in a sensitive domain
- Collection
- 2025 ASEE -GSW Annual Conference
- Authors
- Rojan Shrestha, The University of Texas at Arlington
- Tagged Topics
- Diversity
and scipy (version 1.7.1) for statistical computations. IEEE Open Journal of the Communications Society, vol. 4, pp. 2952 2971, 2023, doi: 10.1109/OJCOMS.2023.3320646.tools such as Large Language models like ChatGPT are being The sentiment analysis component utilized multiple indicators A moderate positive correlation was observed between self-reported AI [3] Li Y, Wang C, Cao Y, et al. Human pose estimation based in-home lower body rehabilitation system[C]//2020implemented in educational institutions to provide personalized learning
- Conference Session
- Transformative and Just Futures in Engineering (Equity, Culture & Social Justice in Education Division ECSJ Technical Session 11)
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Nadia N. Kellam, Arizona State University
- Tagged Topics
- Diversity
- Tagged Divisions
- Culture & Social Justice in Education Division (EQUITY), Equity
disrupt inequities. Manywidely used AI tools, such as ChatGPT, are trained on massive proprietary datasets controlled byprivate corporations, raising questions about data security, bias, and accessibility. These concernsare particularly pressing in education, where AI’s role in student and faculty interactions must becritically examined. Without transparent and equitable governance, AI risks reinforcing existingpower imbalances rather than dismantling them.By centering only on the technical aspects of AI, we risk unintended consequences that reinforcesystemic inequities, creating outcomes that disproportionately harm marginalized groups. Someresearchers are exploring ethics, bias, and social responsibility regarding AI [5]. In this practicepaper
- Conference Session
- Biomedical Engineering Division (BED) Postcard Session (Best of WIPs)
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Nathan Hyungsok Choe, The George Washington University; Chanyee Hong; Hyeyeon Lim
- Tagged Topics
- Diversity
- Tagged Divisions
- Biomedical Engineering Division (BED)
al.emphasized that utility value and self-efficacy are essential in shaping the learning outcomes ofengineering students, highlighting the importance of integrating practical applications into thecurriculum to enhance students' perceived utility value [3]. In the context of using large languagemodel (LLM) like ChatGPT in engineering education, the utility value can significantlyinfluence how students perceive and utilize these tools. Recent studies have explored the impactof LLM on students' perception of utility value in using AI tools. For instance, Rosenzweig et alexamined the effectiveness of utility value interventions in online math courses and found thatsuch interventions significantly increased students' perceived utility value and
- Conference Session
- Track 4: Technical Session 5: Impact of Generative AI Technologies on Blind and Visually Impaired Students: A Case Study
- Collection
- 2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)
- Authors
- Lance Leon Allen White, Texas A&M University; Sara Amani, Texas A&M University; Trini Sofia Balart, Texas A&M University; Amanda Kate Lacy; Gene Sung-Ho Kim, Stanford University; Gibin Raju, Texas A&M University; Karan Watson P.E., Texas A&M University; Kristi J. Shryock, Texas A&M University
- Tagged Topics
- 2025 CoNECD Paper Submissions, Diversity
of Blind and Visually Impaired Students and the Impact of Generative AI: A NarrativeAbstractThe advent of Generative AI (GenAI) in our society has taken root so deeply that simple Googlesearches invoke a GenAI response attempting to synthesize a simplified summary for a user.Incidentally, these GenAI systems like ChatGPT from OpenAI, LLaMA from Meta, Geminifrom Google, and Copilot from Microsoft are all largely text-based large language modelsproviding an increased level of access to people who use screen reading technology to interactwith personal computing systems. This study investigates the impact of GenAI on accessibilityfor blind and visually impaired students, focusing on the experiences of two computing
- Conference Session
- Computers in Education Division (COED) Track 2.D
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Ryan Tsang, University of California, Davis; SYDNEY Y WOOD, University of California, Davis
- Tagged Topics
- Diversity
- Tagged Divisions
- Computers in Education Division (COED)
-dictive power on performance outcomes. Finally, we call for continued empirical research on theefficacy of LLM-based technologies in STEM education and propose future research directions inexploring their impact on teaching and learning.1 IntroductionThe introduction of OpenAI’s ChatGPT in November 2022 [1] triggered an unprecedented surgeof interest in applications of artificial intelligence (AI) based on Large Language Models (LLMs)and their underlying transformer architecture.In particular, LLMs appear to be exceptional in applications that involve human interaction, infor-mation retrieval, and summation, making them an attractive prospect for improving the effective-ness and accessibility of education in the digital age [2, 3, 4]. However
- Conference Session
- Computers in Education Division (COED) Track 2.A
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Jason M. Keith, Iowa State University of Science and Technology; Jason Coleman, Kansas State University; Lis Pankl, Mississippi State University
- Tagged Topics
- Diversity
- Tagged Divisions
- Computers in Education Division (COED)
a growth in academic integrityfilings since the advent of ChatGPT. In fact, [2] points to a Stanford University survey where1/6th of students said they had used ChatGPT on assignments or exams. This article [2] alsopoints towards the issues of hallucinations, where AI focuses on generating text that sounds goodbut may not be scientifically accurate. However, [1] also points to potential efficiencies andutility of AI in higher education, such as teaching ethical use of AI, growth of tutoring/teachingassistants and for operational efficiencies. Auon [3] discussed the impact of AI on the humanexperience in physical (personalized medicine/drug delivery and disease identification),cognitive (increased workplace productivity, focused effort on
- Collection
- 2025 ASEE North Central Section (NCS) Annual Conference
- Authors
- Aniruddha Maiti; Samuel Adewumi; TEMESGEN ALEMAYEHU TIKURE; Zichun Wang; Niladri Sengupta; Anastasiia Sukhanova, Marshall Community & Technical College; Ananya Jana, Marshall University
- Tagged Topics
- Diversity
outputs of bothmodels.For alignment, fuzzy matching techniques were used. These techniques matched sentences be-tween GPT-4o and DeepSeek R1, even when there were minor differences in phrasing. This ap-proach improved the accuracy of mapping and ensured consistency in the processed data. Theresult was a clean and reliable dataset for analysis.5.2. Overall Categorization CoverageWe analyzed the total number of sentences processed and the extent to which GPT-4o and DeepSeekR1 provided category assignments. Table 1 summarizes the categorization coverage across all an-alyzed sentences. ChatGPT DeepSeek Total Sentences 1823 1823
- Conference Session
- ERM Technical Session: Improving Assessment in Engineering Education
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- David Coulter Jangraw, University of Vermont; Anneliese Marie Shoudt; Courtney D Giles, University of Vermont
- Tagged Topics
- Diversity
- Tagged Divisions
- Educational Research and Methods Division (ERM)
hypotheses for future research.A preliminary qualitative analysis of Ticket Home student exit surveys and TA Ticket Homesummaries used ChatGPT to identify common themes. The surveys were first manuallyanonymized by removing names, then entered into ChatGPT with the prompt “Please summarizethese responses to the question: . List the most common themes and how manyresponses mentioned each of them.” While a similar approach has been used successfully forthematic analysis before [20], our approach involves different data and prompts; it shouldtherefore be considered preliminary and subject to a more extensive validation. To assess theapproximate accuracy of this approach, a human rater manually identified the four most commoncodes identified by ChatGPT
- Conference Session
- ENT-1: Innovative Approaches to Student Engagement and Belonging in Engineering
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Andrea T Kwaczala, Western New England University; Andrea Davis, Western New England University; Heidi Ellis, Western New England University
- Tagged Topics
- Diversity
- Tagged Divisions
- Entrepreneurship & Engineering Innovation Division (ENT)
-confidence in their individualskills in oral communication, specifically related to presentations, but these results requireadditional research to confirm these findings.Using AI to Assess Student Outcomes: Co-Pilot and ChatGPT were both used to evaluate pitchtranscripts using the Grading Rubric. The results of AI-evaluations were compared to the facultyevaluations using the same grading rubric. This was limited to transcripts of the pitch as anyonline video-based platform for video analysis was by paid subscription only. In identifyingavailable AI tools, some interesting subscription-based options we discovered. These tools focusspecifically on video analysis of body language and pitch performance, including uSpeek(Sarang, 2023) and Bodha (Cadet
- Conference Session
- AI in the Engineering Management Classroom
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Ekaterina Koromyslova, South Dakota State University; Bishnu karki, South Dakota State University; Prafulla Salunke, South Dakota State University; Carrie Steinlicht, South Dakota State University; Gary Anderson, South Dakota State University
- Tagged Topics
- Diversity
- Tagged Divisions
- Engineering Management Division (EMD)
prompt to AI. Thus, a lack of effective communications skills can compromise thequality of the generated output if the question is not clearly formulated, and the prompts are notrefined or elaborated. Moreover, without an expert to evaluate the generated solution, there is adanger that the solution is based on incorrect or biased information [16]. Unless the decisionmakers are able to critically evaluate the generated solutions, they may make costly mistakes.Farrokhnia, Banihashem, Noroozi, and Wals [17] completed a SWOT analysis of ChatGPT – agenerative AI tool which is commonly used in higher education by instructors and students. Theyidentified the following weaknesses and threats of generative AI: • Lack of deep understanding of the
- Conference Session
- Charting Inclusivity: Advancing Diversity, Equity, and Technology in Engineering and Computing Education
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- Clay Walker, University of Michigan
- Tagged Topics
- Diversity
- Tagged Divisions
- Culture & Social Justice in Education Division (EQUITY), Equity
technology, but also reported theoutputs generated by the algorithm were not sophisticated enough to be useful for completingcoursework. The question of sophistication is difficult to pin down due to the rapid developmentof the technology, for within the first year of public access, the power of widely availablecommercial platforms like ChatGPT have continued to develop in power and sophistication withthe problems of hallucination and accuracy diminishing as many of the algorithms now haveaccess to the internet, thus further edifying the outputs generated by the AI.Despite these nascent discussions of student impacts, one issue missing from conversationsaround GenAI are the impacts they are likely going to have on how students develop
- Conference Session
- Software Engineering Division (SWED) Technical Session #2
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- Maura Lyons, Codio; Elise Deitrick, Codio; Joshua Richard Coughlin Stowell Ball, Codio
- Tagged Topics
- Diversity
- Tagged Divisions
- Software Engineering Division (SWED)
work.Notably, students who were taught how AI works had significantly different views on AI tools’impact on academic integrity concerns.Computing students’ use of Generative AI is growing, and thoughts on academic integrity are farfrom decided – but there does seem to be an opportunity to teach students the variety of ways itcan be used effectively for programming tasks.IntroductionChatGPT, a Generative AI product developed by OpenAI, was released in November 2022 andalmost immediately, its popularity began to surge worldwide, as illustrated by its steep increaseas a search term on Google. Teachers and administrators took notice – “‘plagiarism’ was rankedin two out of the top five related search queries alongside ‘ChatGPT’” [1]. The popularization
- Conference Session
- Biomedical Engineering Division (BED) Poster Session
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Xianglong Wang, University of California, Davis; Tiffany Marie Chan, University of California, Davis; Angelika Aldea Tamura, University of California, Davis
- Tagged Topics
- Diversity
- Tagged Divisions
- Biomedical Engineering Division (BED)
], rapidimprovement in the performance of these products, as reflected by one faculty’s experience ofPerplexity AI scoring 80% on their multiple choice-based engineering quiz, accentuated the needfor BME educators and students to improve AI literacy and cultivate responsible use of AI.ML algorithms are computer programs that improve their performance with more experience(data) [8]. Therefore, problems in the data used to train ML algorithms, such as demographicbiases, can be reflected in the performance of ML algorithms. In a BME context, GPT-4, whichpowers ChatGPT and Perplexity AI, showed strong ethnic biases when assigning medicalconditions such as HIV/AIDS [9], while GPT-4 and Gemini (also powers AI-enabled notebook,NotebookLM) showed negative perception
- Conference Session
- Student Success in ET
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- Kenan Baltaci, University of Wisconsin, Stout; Monika Herrmann, University of Wisconsin, Stout; Ahmet Turkmen
- Tagged Topics
- Diversity
- Tagged Divisions
- Engineering Technology Division (ETD)
Critical EngagementIn this study, students were invited to participate in a survey to share their experiences using AItools during one semester in four courses. Thirty-five (35) Computer and Electrical Engineering(CEE) students at the University of Wisconsin-Stout responded to the survey describing their useof AI tools such as ChatGPT in their studies. The group included 15 sophomores and 20 seniorsenrolled in 4 different CEE courses titled “CEE-215 Electronics”, “CEE-405 Capstone I:Computer Engineering Design”, “CEE-410 Capstone II: Computer Engineering Design”, and“CEE-355 Applied Electromagnetics”. The survey featured nine questions, seven using a Likertscale to measure students' opinions about AI tools in their education. The Likert scale
- Conference Session
- First-Year Programs Division (FPD) Technical Session 4: Fostering Belonging - Identity, Self-Efficacy, and Retention
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Brian Patrick O'Connell, Northeastern University; Kathryn Schulte Grahame, Northeastern University; Richard Whalen, Northeastern University; Constantine Mukasa, Northeastern University; Susan F Freeman, Northeastern University
- Tagged Topics
- Diversity
- Tagged Divisions
- First-Year Programs Division (FPD)
using ChatGPT for high-level analysis. Datasets weremanually formatted to ensure consistent wrangling by the AI, using standardized key phrases andstructured formatting to enhance the AI's ability to parse and interpret the information accurately. Thisstudy implemented a simplistic segmentation, considering each sentence as a single statement, toimprove reliability and repeatability. This process was systematically repeated and refined by utilizingsubsets of the data with established qualities until preprocessing consistently achieved accurate parsingfollowing emerging best practices [23].Throughout the analysis, refinements were made to prompts and categorizations, ensuring alignmentwith the nuances of each reflection. Reanalysis occurred in
- Conference Session
- Computers in Education Division (COED) Track 2.A
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Griffin Pitts, University of Florida; Viktoria Medvedeva Marcus, University of Florida; Sanaz Motamedi, University of Florida
- Tagged Topics
- Diversity
- Tagged Divisions
- Computers in Education Division (COED)
ChatGPT [1], Google’s Gemini [2],and Microsoft’s Copilot [3] have gained widespread student adoption due to their free access andease of use. This expansion has occurred amid varying acceptance [4–6] and trust [7] in digitallearning technologies across student populations through the COVID-19 pandemic and into thepresent day. Approximately one-third (35.4%) of students reported regular usage of ChatGPT,while 47% expressed concern about AI’s impact in education [8]. Additionally, 60% reported thattheir instructors or schools had not yet provided guidelines for ethical or responsible AI tool use [8].As students increasingly use available online AI assistants, researchers have concurrently devel-oped specialized educational AI tools designed
- Conference Session
- Computers in Education Division (COED) Poster Session (Track 1.A)
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Daniel Kane, Utah State University; Wade H Goodridge, Utah State University; Linda Davis Ahlstrom, Utah State University; Oenardi Lawanto, Utah State University; Michaela Harper, Utah State University; Cassandra J McCall, Utah State University
- Tagged Topics
- Diversity
- Tagged Divisions
- Computers in Education Division (COED)
publications have been recognized by leading engineering education research journalsat both national and international levels. Dr. McCall has led several workshops promoting the inclusionof people with disabilities and other minoritized groups in STEM. She holds B.S. and M.S. degrees incivil engineering with a structural engineering emphasis. ©American Society for Engineering Education, 2025 WIP: Understanding Patterns of Generative AI Use: A Study of Student Learning Across University CollegesIntroductionDue to the relatively recent introduction of AI to academia, facilitated by the development andrelease of popular generative AI systems such as ChatGPT, few studies have examined theeffects of AI use on
- Conference Session
- Student Engagement in Construction Education
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- Hariharan Naganathan, Wentworth Institute of Technology; John Cribbs Ph.D., Wentworth Institute of Technology
- Tagged Topics
- Diversity
- Tagged Divisions
- Construction Engineering Division (CONST)
, software, andtools can positively impact construction projects by increasing productivity, improving safetyrates, and increasing the success rate of winning construction projects and bids. Interestingly, evenArtificial Intelligence (AI) has made its way into the construction industry, with tools likeChatGPT being utilized to realign project schedules and improve overall project efficiency .Researchers have used ChatGPT to explore integration with digital twins for healthcare, writingmanuscripts, and adapting classroom education to achieve student learning outcomes [18]-[20]. Itis worth noting that tools such as ChatGPT, which have emerged recently as AI-poweredassistants, are still in the process of gathering data to establish their reliability
- Conference Session
- GIFTS II
- Collection
- FYEE 2025 Conference
- Authors
- Osman Sayginer, Temple University; Cory Budischak, Temple University
- Tagged Topics
- Diversity, FYEE 2025
-a = 0.25 -x = 4 ::Numeric Precision:: -x = 0 What is the density of water at room temperature in kg/m³? ::Numeric Precision:: [!Numeric!] [1000+-5] How many km in a marathon? ::Numeric Range:: [!Numeric!] [42.2+-0.1] What is the typical range of efficiency (%) for a modern gas turbine? ::Numeric Range:: [!Numeric!] [30 40] Normal body temp in Celsius? [!Numeric!] [36.5 37.5]Figure 2. Example of an input prompt used to generate quiz questions (left) and the resultingoutput generated by ChatGPT (right).Preliminary Results and DiscussionInitial trials
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- Engineering Ethics Division (ETHICS) Technical Session - Ethics education methodologies and interventions
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Robyn Mae Paul, University of Calgary
- Tagged Topics
- Diversity
- Tagged Divisions
- Engineering Ethics Division (ETHICS)
ethics in engineering education. Science and Engineering Ethics, 10(2), 343–351. https://doi.org/10.1007/s11948-004-0030-8Paul, R. M., Hugo, R., & Falls, L. C. (2015). International expectations of engineering graduate attributes. 11th International CDIO Conference.Piers, C. (2024, February 7). Even ChatGPT Says ChatGPT Is Racially Biased. Scientific American. https://www.scientificamerican.com/article/even-chatgpt-says-chatgpt-is- racially-biased/Riley, D. (2012). Aiding and ABETing: The Bankruptcy of Outcomes-based Education as a Change Strategy. 2012 ASEE Annual Conference & Exposition Proceedings, 25.141.1- 25.141.13. https://doi.org/10.18260/1-2--20901Ross, S. R. (2019). Supporting your
- Conference Session
- Computing and Information Technology Division (CIT) Technical Session 4
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Jason M. Keith, Iowa State University of Science and Technology; Amin Amirlatifi, Mississippi State University; Sudip Mittal, Mississippi State University; Subash Neupane, Mississippi State University; HIMANSHU TRIPATHI, Mississippi State University
- Tagged Topics
- Diversity
- Tagged Divisions
- Computing and Information Technology Division (CIT)
Education, 2025 Barkplug 2.0 and Beyond: a Chatbot for Assisting Students in High DFW CoursesAbstractHigher education continues to respond to the challenges and opportunities presented by artificialintelligence (AI) and large language models (LLM) such as ChatGPT. In our prior work weintroduced a chatbot that used AI and LLM to recruit prospective students, assist current studentswith academic advising (course selection, changing majors) and student affairs (directingstudents to university resources regarding the campus community, housing and dining, studentorganizations, mental health and more). Towards the promotion of student success initiatives wereport in this work our formulation of course specific teaching
- Conference Session
- WIP Poster Session: Emerging Research and Practices in Pre-College Engineering Education
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Syeda Fizza Ali, Texas A&M University; Ayaan Sunil Rege, The Hill School; Susanna Angela Ponniah, The Hill School; Hoda Ehsan, The Hill School ; Saira Anwar, Texas A&M University
- Tagged Topics
- Diversity
- Tagged Divisions
- Pre-College Engineering Education Division (PCEE)
developing systemscapable of performing tasks that usually require human intelligence, including learning,reasoning, and decision-making [21]. Generative AI (Gen-AI) is a subset of AI thatspecializes in creating human-like content, including text, images, and audio [22]. With AI'srecent innovations, many have explored its educational applications. Many educatorscurrently utilize AI tools to increase efficiency within the classroom [1]. Two examples ofGen AI tools include 1) ChatGPT, a generative AI chatbot, and 2) Grammarly, an AI-powered writing assistant. Both tools have proven valuable educational assistants [2, 3].GenAI can help educators with tasks like creating assessments and streamliningadministrative tasks and lessons [23, 24]. In the field
- Conference Session
- Design in Engineering Education Division (DEED) Technical Session 1
- Collection
- 2023 ASEE Annual Conference & Exposition
- Authors
- Yun Wang, Undergraduate at University of Illinois Urbana-Champaign; Colin P. Lualdi, University of Illinois Urbana-Champaign; Lawrence Angrave, University of Illinois Urbana-Champaign; Guru Nanma Purushotam
- Tagged Topics
- Diversity
- Tagged Divisions
- Design in Engineering Education Division (DEED)
integrated into ScribeAR butother integration projects are possible. For example, ESPnet [21] is also a common speech to textplatform that is an end-to-end speech processing toolkit. It includes various applications such asspeech recognition, text-to-speech, speech translation, and speech enhancement.Recent advances in Large Language Models will also provide new opportunities for inclusiveconversational approaches. For example, a student project might use the new ChatGPT API thatas of May 2023 is now available as part of Microsoft Azure cloud services, to providesummarization or other textual transformation of a transcript [24]t.8. AcknowledgmentsWe thank the VR@Illinois program and the Department of Physics Graduate Office at theUniversity of
- Conference Session
- ELOS Technical Session 3: Advancing Engineering Competencies: From Labs to Writing
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Dave Kim, Washington State University-Vancouver; Charles Riley P.E., Oregon Institute of Technology; Sean St. Clair P.E., Oregon Institute of Technology; Olusola Adesope, Washington State University
- Tagged Topics
- Diversity
- Tagged Divisions
- Experimentation and Laboratory-Oriented Studies Division (DELOS)
community of practice focusing on engineering lab writing education. Thispaper presents the content, delivery, and results of the professional development workshop onengineering lab writing.2. Workshop Content and DeliveryThe workshop was designed for the participants to conduct the following in a small groupsetting: 1) develop engineering lab report assignments; 2) improve engineering lab reportassessment; 3) guide students in navigating writing with generative AI (ChatGPT-4); and 4) trainlab teaching assistants or lab report graders. Participants accessed the guides (available atengineeringlabwriting.org) to design and develop sample labs, discuss issues related to labwriting and how to deliver lab writing expectations, and provide feedback to
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- AI and Tools for Transdisciplinary Work
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- Elana Goldenkoff, University of Michigan; Erin A. Cech, University of Michigan
- Tagged Topics
- Diversity
- Tagged Divisions
- Liberal Education/Engineering & Society Division (LEES)
education (due to the COVID-19 pandemic) as well as a cohort of students whotook all their classes under standard post-pandemic in-person instructional protocols. The secondinterview period also coincided with launch and subsequent public debates around ChatGPT(OpenAI, San Francisco, USA) and other similar generative AI models.All interviews were conducted by the first author virtually using video conferencing. They wereoffered a $50 gift card as a token of gratitude for their time and participation. The interviewsbegan by gathering information about respondents’ educational and employment history andtheir prior training in ethics and public welfare responsibilities. After asking about theirexperiences in their current master’s program, we asked
- Conference Session
- Computing and Information Technology Division (CIT) Technical Session 7
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Ismael Villegas Molina, University of California, San Diego; Audria Nikitza Montalvo, University of California, San Diego; Benjamin Ochoa, University of California, San Diego; Paul Denny, University of Auckland; Leonard Porter, University of California, San Diego
- Tagged Topics
- Diversity
- Tagged Divisions
- Computing and Information Technology Division (CIT)
Corrected Question P-Value Mean Mean P-Value I use CodeHelp because the professor told us we could use it in the class. 3.80 3.72 0.6615 1.0000 I prefer CodeHelp to ChatGPT because it does not give me the answer directly. 3.56 3.79 0.2056 0.9937 I believe that CodeHelp gives me just enough information to continue my work without