Conference Session

Computers in Education Division (COED) Track 4.C

Collection

2025 ASEE Annual Conference & Exposition

Authors

Safia Malallah, Kansas State University; Ejiro U Osiobe; Lior Shamir, Kansas State University; David S. Allen, Kansas State University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

critical aspects necessary to create virtual worlds that are engaging, inclusive,and developmentally appropriate for young children. These elements are: Engagement andMotivation (EM), Collaboration and Teamwork (CT), Creativity and Problem-Solving (CPS),Communication and Interaction (CI), Inclusivity, Accessibility, and Age-Appropriate (IAA),Design and Environment (DE), Data Security and Privacy (DSP), Safety and TechnicalSecurity (STS), Evaluation and Feedback (MEF), Cultural Responsiveness (CRR), CommunityBuilding (CB), Facilitation and Educator Tools (FET), Ethics, Empathy, and Decision-Making(EDM) [4]. This paper uses these elements to develop the virtual world environment in Roblox.Table. 1 Elements for Virtual World [4]. The VW integrates

Conference Session

Computers in Education Division (COED) Track 6.D

Collection

2025 ASEE Annual Conference & Exposition

Authors

Mitchell Gerhardt, Virginia Polytechnic Institute and State University; Andrew Katz, Virginia Polytechnic Institute and State University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

by incorporating social justice, ethics,problem definitions, and professional development considerations, many still rely on technically-focused a developed during the Cold War ([28], as cited in [24]). Robinson [3] analyzedengineering textbooks’ approaches to teaching electrical circuits over about 80 years (1940-2017), focusing on how they present and understand engineering knowledge. Although morerecent textbooks included brief “real-world” applications at the beginnings and ends of chapters,they primarily concentrated on mathematical analysis, problem-solving, and technical details,minimizing theoretical explanations. By contrast, earlier textbooks contained more detailedwritten explanations, emphasized theoretical understanding, and

Conference Session

Computers in Education Division (COED) Poster Session (Track 1.A)

Collection

2025 ASEE Annual Conference & Exposition

Authors

Rawan Adnan Alturkistani, Virginia Tech Department of Engineering Education; Mohammed Seyam, Virginia Polytechnic Institute and State University

Tagged Divisions

Computers in Education Division (COED)

, researchassistance, automated grading, writing coach, make lesson plans, help to make progressreports, also helping the teachers how to teach a subject [76], [77], [78]. Although GenAI is apowerful technology in education, it still needs to be used with extra caution to ensure usingit safely and responsibly. For example, in [70], the article discusses the application ofArtificial Intelligence in online learning and distance education, based on a systematic reviewof empirical studies. The application of AI in these settings has been shown to enhance thelearning experience by personalizing the content, facilitating peer interaction, and providingreal-time feedback. Nevertheless, it also warns of the ethical and legal implications ofwidespread AI use in

Conference Session

Computers in Education Division (COED) Track 3.C

Collection

2025 ASEE Annual Conference & Exposition

Authors

Eric L Brown, Tennessee Technological University; Douglas A. Talbert, Tennessee Technological University; Jesse Roberts, Tennessee Technological University

Tagged Divisions

Computers in Education Division (COED)

syllabi, how manyaddress knowledge unit XXX?” This experiment was conducted by providing up to six individualsyllabi simultaneously (limited by the platforms and their associated context windows). A secondversion of this experiment was conducted by providing a single combined PDF document, whichincluded all 16 syllabi. This document was optimized and text-recognized using Adobe Acrobatto assist with readability by the LLM. The authors used the Policy, Legal, Ethics, and Compliance(PLE) knowledge unit, which was known to be unique to one specific syllabus, where many of theothers could have been generalized. This selection was made to help assess the accuracy of theevaluation. For ease of identification, the single combined document experiment

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

David Reeping, University of Cincinnati; Aarohi Shah, University of Cincinnati

Tagged Divisions

Computers in Education Division (COED)

interdisciplinary engineering projects. Degree: Articulate how diverse perspectives and expertise from multiple disciplines contribute to the richness of ideas generated during brainstorming sessions.7. Behavior: Identify potential barriers to effective brainstorming and propose strategies to overcome them. Conditions: Given examples of common challenges encountered during brainstorming sessions. Degree: Demonstrate awareness of factors such as groupthink, lack of participation, and dominance dynamics, offering solutions to mitigate these obstacles.8. Behavior: Evaluate the ethical implications of design decisions resulting from brainstorming sessions. Conditions: Presented with ethical dilemmas related to engineering design choices. Degree

Conference Session

Teaching with ML and Generative AI

Collection

2024 ASEE Annual Conference & Exposition

Authors

Bobby F Hodgkinson, University of Colorado Boulder; Nathan Eric Whittenburg, University of Colorado Boulder

Tagged Divisions

Computers in Education Division (COED)

ourlearning management system. These achievements paved the way for the initial development ofan AI-based grading assistant. Mindful of the ethical considerations associated with a fullyautomated grader, we focused on creating a tool to assist, rather than replace, humangraders.This AI assistant streamlines the evaluation of group lab reports, traditionally a time-intensivetask in large-scale courses. By uploading nameless lab reports to a LLM through an APIinterface, the system efficiently identifies and highlights segments that align closely with specificrubric items. This process is designed to isolate the most relevant sections of each report,providing a preliminary guide for human graders. The aim is to enhance grading efficiency andconsistency

Conference Session

Computers in Education Division (COED) Track 6.D

Collection

2025 ASEE Annual Conference & Exposition

Authors

Shana Shaw, Texas A&M University; L. Taylor Starr, Texas A&M University; laila badran, Texas A&M University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

technologies toincrease efficiency in their work [29]. Ethical cautions of using AI were prevalent in the literature [19], [20], [23]. Thesecautions involved not only students’ ethical use of AI, privacy concerns, academic quality,quality of the results generated and legal considerations, but a focus on needs for future policy,ethical review, and monitoring in evaluation of AI-generated content. Therefore, cautions shouldbe held at the forefront of future research in engineering education and in the skills developmentof future engineers.DiscussionRQ1: How have engineering educators used generative artificial intelligence (AI) tools toenhance students' proficiency of industry professional skills? As the implementation of AI in engineering

Conference Session

Computers in Education Division (COED) Track 6.D

Collection

2025 ASEE Annual Conference & Exposition

Authors

Bahar Memarian, Arizona State University ; Shawn S. Jordan, Arizona State University

Tagged Divisions

Computers in Education Division (COED)

: Applied behavior 3. Attitudes: Feelings and beliefsFigure 7 presents a word cloud summary of terms associated with competencies used forIntegrated Engineering (a) and a bar graph summary of the dimensions adapted from [2], [3]across the 19 reviewed studies (b). The textual overview of competencies employed (Figure 7a)may suggest the socio-technical-cultural emphasis of competency explanations and how they aredefined with holistic terms such as professional, global, ethical, etc. The codification overview ofcompetencies employed (Figure 7 b) suggests that the most frequent trends are: • 1. Knowledge: Understanding and familiarity with information 2. Skills: Applied behavior and 3. Attitudes: Feelings and beliefs are studied the most

Conference Session

Computers in Education Division (COED) Track 6.A

Collection

2025 ASEE Annual Conference & Exposition

Authors

Abdulrahman AlRabah, University of Illinois at Urbana - Champaign; Zepei Li, University of Illinois at Urbana Champaign; Meredith Blumthal, University of Illinois at Urbana - Champaign; Sotiria Koloutsou-Vakakis, University of Illinois Urbana-Champaign; Volodymyr Kindratenko, University of Illinois Urbana-Champaign; Tomasz Kozlowski, University of Illinois Urbana-Champaign; Abdussalam Alawini, University of Illinois Urbana - Champaign

Tagged Divisions

Computers in Education Division (COED)

student queries and identify usage patterns across courses.For RQ4, we compare student prompts with course syllabi and the university’s student code toidentify and characterize instances of potential policy violations. We use natural languageprocessing (NLP) techniques to classify question types and patterns. This mixed-methodapproach will provide a comprehensive understanding of how students interact with the systemand how it supports their learning. This study aims to provide insights into the role of AI-drivensystems like AI-bot by investigating the different types of questions and their relevance insupporting student learning, while also addressing potential challenges and ethical considerationsin their use.2 Related WorkResearchers have

Conference Session

ML and Generative AI Tools and Policies

Collection

2024 ASEE Annual Conference & Exposition

Authors

Lucas J. Wiese, Purdue University at West Lafayette; Alejandra J. Magana, Purdue University at West Lafayette

Tagged Divisions

Computers in Education Division (COED)

Paper ID #42501A Department’s Syllabi Review for LLM Considerations Prior to University-standardGuidanceLucas J. Wiese, Purdue University at West Lafayette Lucas Wiese is a PhD student in Computer and Information Technology at Purdue University. He studies AI ethics education and workforce development and works in the Research on Computing in Engineering and Technology Education lab (ROCkETEd) and the Governance and Responsible AI Lab (GRAIL).Dr. Alejandra J. Magana, Purdue University at West Lafayette Alejandra J. Magana, Ph.D., is the W.C. Furnas Professor in Enterprise Excellence in the Department of Computer and

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Brayan A Díaz, North Carolina State University; Kevin Han, North Carolina State University

Tagged Divisions

Computers in Education Division (COED)

ethical considerations in working with K-12 studentsand obtaining authorization from school districts to the EDM community. The objectives of the EDM course are to cultivate an environment where students can acquireknowledge and develop skills associated with data science techniques, advanced software usage for dataanalysis, and learning theories and educational practices to interpret and design educational interventions. Considering that it is very likely that participants in an EDM course may come from strong datascience or education backgrounds, there are two considerations to accomplish the learning outcomes ofthe EDM course. First, students must learn concepts and skills that may not be part of their background,such as

Conference Session

Computers in Education Division (COED) Track 6.A

Collection

2025 ASEE Annual Conference & Exposition

Authors

Sujan Poudyal, Cleveland State University

Tagged Divisions

Computers in Education Division (COED)

1, highlight that the bestperformance was achieved with Adam optimizers for 100 epochs. The comparison in Figure 2further confirms that our hybrid model significantly outperformed standalone traditional modelsin terms of classification accuracy.Even though results show how effective our approach is, there are significant ethical concernsraised by using AI to predict students' academic performance, especially with regard to bias andfairness. The OULAD dataset might have inherent biases related to demographics,socioeconomic status, or institutional regulations because it is based on real student records.Machine learning models run the risk of sustaining current educational disparities if these biasesare not addressed properly. A major concern

Conference Session

COED: Computing in K-12 / Early Childhood Education

Collection

2023 ASEE Annual Conference & Exposition

Authors

Safia A. Malallah, Kansas State University; Lior Shamir, Kansas State University; William Henry Hsu, Kansas State University; Joshua Levi Weese, Kansas State University; Salah Alfailakawi, Kansas State University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

clusters; elements with evidence are highlighted in green.Literature Review 1 – Data Science for PreschoolersThe search using IEEE Xplore revealed 86 results, and the ScienceDirect search yielded 65results, with all excluded expected one, which indicated the need for further investigation. Thepaper “Data Science K-10 Big Ideas” provided a comprehensive overview of the fundamentalskills students should learn to become proficient in data science [10]. The paper also outlinedfour key concepts that should be taught in data science curriculum for kindergarten through10th grade, including topics such as data collection and representation, data analysis andinterpretation, and ethical considerations in the use of data. The included paper was developedby

Conference Session

The Best of Computers in Education Division (COED)

Collection

2024 ASEE Annual Conference & Exposition

Authors

Gerald Tembrevilla, Mount Saint Vincent University; Mohosina Jabin Toma, University of British Columbia, Vancouver; Marina Milner-Bolotin, University of British Columbia, Vancouver

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

(reflection-on-action) [11], and improve for future implementations (reflection-for-action) [13]. In addition, during the school practicum, preservice teachers’ ongoing collaborationwith their university practicum advisor, associate teacher, school staff, and fellow preserviceteachers allow preservice teachers to acquire and improve their collective knowledge of thenature of learning, the diverse development of their students (intellectual, physical, social,emotional, etc.), professional, social, legal, and ethical responsibility [12].In the spring of 2020, COVID-19 pandemic brought significant restrictions and changing healthprotocols that lasted until winter 2023. These changes affected many of Canada’s ITE programsand consequently the conduct of

Conference Session

Computers in Education Division (COED) Track 3.D

Collection

2025 ASEE Annual Conference & Exposition

Authors

Friday Emmanuel James, Kansas State University; Joshua Levi Weese, Kansas State University; Russell Feldhausen, Kansas State University; Nathan H Bean, Kansas State University; Michelle Friend, University of Nebraska - Omaha; David S. Allen, Kansas State University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

as they work on programmingtasks. Students with extended error resolution times are perceived to display strugglingbehaviors. By tracking the duration and frequency of error corrections, instructors can gaininsight into students’ debugging strategies.Furthermore, by integrating unit tests with the keystroke analysis, the tool enables theinstructors to dynamically assess code correctness. The pass/fail rates of the unit tests areclear measures of students’ progress.5 Ethical ConsiderationsGiven the focus of this research on student data collection and analysis, the study adheres toestablished ethical guidelines in order to protect the students’ privacy and maintain datasecurity. This research has been approved by our University’s

Conference Session

Computers in Education Division (COED) Track 2.C

Collection

2025 ASEE Annual Conference & Exposition

Authors

Mahmoud K Quweider, The University of Texas Rio Grande Valley; Liyu Zhang, University of Texas Rio Grande Valley; Jorge Castillo, The University of Texas Rio Grande Valley; Ala Qubbaj, The University of Texas Rio Grande Valley

Tagged Divisions

Computers in Education Division (COED)

ethical implications and societal impacts ensures they areprepared to develop responsible and sustainable solutions. With the increasing reliance ontechnology and the internet, protecting sensitive information from cyber threats has become a toppriority for individuals, businesses, and governments alike, and incorporating AI/ML into theprogram empowers students to become future leaders who drive progress in an increasingly digitalworld, with a strong emphasis on the critical field of cybersecurity. Approaching this need to fuseAI/ML in our cybersecurity curriculum starts by identifying the key applications of AI/ML incybersecurity. Once these are identified, we can determine the freshman, sophomore, and juniorcourses that can prepare the students

Conference Session

COED: Online and Remote Learning

Collection

2023 ASEE Annual Conference & Exposition

Authors

Carolyn Kusbit Dunn, East Carolina University; David L. Batts, East Carolina University

Tagged Divisions

Computers in Education Division (COED)

Paper ID #37922Pandemic or Profession? Factors Motivating Students to Pursue an OnlineBachelor’s DegreeDr. Carolyn Kusbit Dunn, East Carolina University Carolyn Kusbit Dunn is an Assistant Professor in the Department of Technology Systems at East Carolina University. Dr. Dunn teaches Technical Writing and Technical Presentations, and centers her research on the pedagogy of technical writing, crisis and risk communication, and the the ethics of crisis and risk communication.Dr. David L. Batts, East Carolina University David Batts, Ed.D., is an assistant professor in the Department of Technology Systems at East Carolina

Conference Session

COED Programming Education 2: Instructional Approaches

Collection

2023 ASEE Annual Conference & Exposition

Authors

Richard Whalen, Northeastern University; Joshua L. Hertz, Northeastern University

Tagged Divisions

Computers in Education Division (COED)

acceptable. Specifically, the emphasis is that Cornerstone is a lens by whichengineering learning can come together to develop practical applications to solving problems.The Cornerstone 1 course focuses on learning the principles of engineering and design; this isaccomplished through active learning in areas such as problem definition, conceptual design,preliminary and detailed design, design communication and implementation, engineering ethics,along with report writing and presentations in relation to projects that students produce in teams.There is a strong emphasis on applying technical knowledge, developing problem-solving anddecision-making skills, and using computer-aided design (CAD) to communicate graphically.Within this course, algorithmic

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)

, the teaching communityhas raised substantial concerns regarding academic integrity, student learning, ethical application, 1and the dynamics of human-AI interaction [4, 5, 6, 7, 8]. While empirical studies on LLM usage ineducation have been conducted in this early stage of adoption, given the current novelty of LLMsin education and the myriad ways they might be incorporated into an educational setting, additionalresearch is crucial for better understanding the short-term and long-term effects of LLM-based AIon teaching and learning in computer science.Due to the relative lack of evidence from early research in this area, we believe the immediate ef-fects of using generative AI in classroom

Conference Session

Computers in Education Division (COED) Track 4.D

Collection

2025 ASEE Annual Conference & Exposition

Authors

James E. Lewis, University of Louisville; Nicholas Hawkins, University of Louisville; Brian Scott Robinson, University of Louisville; Angela Thompson P.E., University of Louisville

Tagged Divisions

Computers in Education Division (COED)

, Tools, & Practice I (ENGR110), and Engineering Methods, Tools, & Practice II (ENGR 111). ENGR 110 is an introductionto the profession and some fundamentals of engineering. ENGR 110 introduces engineeringgraphics, ethics, professionalism, Python programming, teamwork, etc. ENGR 111 is taught in a15,000 𝑓𝑡 2 makerspace, this makerspace is controlled and directed by the SSOE. ENGR 111incorporates application and integration of fundamental engineering skills learned in ENGR 110.ENGR 111 consists of instruction for skills such as teamwork, circuitry, Arduino microcontrollers,three-dimensional graphics, 3D-printing, and technical writing.ENGR 111 includes a semester long team-based Cornerstone project that all student teamscomplete

Conference Session

Computers in Education Division (COED) Poster Session (Track 1.A)

Collection

2025 ASEE Annual Conference & Exposition

Authors

Joel Nirupam Raj; Ashwath Muppa, Thomas Jefferson High School for Science and Technology; Rhea Nirmal; Teo W. Kamath; Achyut Dipukumar; Aarush Laddha; Mihai Boicu, George Mason University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

laboratory conditions, the research aims to provide practical insights for educatorsconsidering these tools. The findings will contribute to broader discussions about technology-enhanced learning and the evolving relationship between artificial intelligence and humaninstruction in technical disciplines.Literature ResearchRecent advances in LLMs have shown their potential to transform educational settings, particularlyin programming courses where timely, detailed feedback is important. Fagbohun et al. [1] statesthat LLMs can automate grading with personalized feedback but that they still require carefulhandling of biases combined with human supervision to ensure that LLMs are fair and efficientand to reduce the occurrence of ethical risks like

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)

engineering (i.e. developing prompts to maximizeoutput accuracy), evaluation of AI responses, and ethical considerations [9-11].Due to its versatile nature, AI has the capacity to be used in nearly every academic discipline,similar to the use of the internet. However, AI may be most effective in fields where students arerequired to complete more ill-defined tasks such as writing lab reports or creative writing [1],[8]. Similarly, AI has been used in marketing and other business fields for content creation, salesoptimization, and for customer service chatbots [12-13]. In science education, the use of AI hasbeen shown to can boost students’ motivation and participation in learning exercises, but it haslimitations regarding complex subjects, and can

Conference Session

ML and Generative AI Tools and Policies

Collection

2024 ASEE Annual Conference & Exposition

Authors

Jason M. Keith, Mississippi State University; Amin Amirlatifi, Mississippi State University; Shahram Rahimi; Subash Neupane, Mississippi State University; Sudip Mittal

Tagged Divisions

Computers in Education Division (COED)

the ethical use of AI. Additionally, faculty hiring trends in STEMfields have brought in faculty who have access to and experience in using “toolboxes” such as AI,machine learning, data science and cybersecurity to enhance their research. Furthermore, to helpcontextualize academic research needs at comprehensive institutions, many university libraries areadding faculty positions with specific aims including data science, copyright / intellectual property;virtual / extended reality and AI / emerging technologies to support research in critical areas suchas autonomy, advanced materials, big data, cultural geography, linguistics, discovery and digitalhumanities.Aside from formulation of the algorithms behind LLM’s [1], a great deal of dialogue

Conference Session

Spotlight on Diverse Learners

Collection

2024 ASEE Annual Conference & Exposition

Authors

Isabella Gransbury, North Carolina State University; Monica M. McGill, Institute for Advancing Computing Education; Leigh Ann DeLyser

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

1 2% 1 2% 1 3% 1 2% Funding 26 52% 21 46% 19 51% 19 46% Language 1 2% 1 2% 1 3% 2 5% Low Study Participation 8 16% 8 17% 8 22% 8 20% Publishing Challenges 6 12% 5 11% 4 11% 5 12% Research Ethics Approval 8 16% 8 17% 4 11% 6 15% Research Interest 7 14% 7 15% 4 11% 7 17% Lack of Admin Training in CER 12 24% 12 26% 11 30% 11 27% Social-Familial Influences 4 8% 3 7% 3 8

Conference Session

Computers in Education Division (COED) Track 5.D

Collection

2025 ASEE Annual Conference & Exposition

Authors

Milad Rezvani Rad, University of Southern Indiana; Ronald Diersing, University of Southern Indiana; Ryan Integlia, University of Southern Indiana; Julian Ly Davis, University of Southern Indiana

Tagged Divisions

Computers in Education Division (COED)

indicates that students perceive significant value in these technologies, underscoring theimportance of ongoing refinement and thoughtful integration of AI into educational contexts.It is also important to recognize potential ethical considerations regarding the use of ChatGPT inan engineering education context, such as how its integration might influence students'independent problem-solving and debugging skills, with respect to MATLAB. To betterunderstand these implications, future surveys could include questions designed to explore students'perspectives on ethical aspects of using AI tools. This approach would support a balanced andthoughtful discussion about the effective and responsible integration of AI in education.There are several possible

Conference Session

Computers in Education Division (COED) Track 2.D

Collection

2025 ASEE Annual Conference & Exposition

Authors

Maryam Khalid Multani, University of Florida; Laura Melissa Cruz Castro, University of Florida

Tagged Divisions

Computers in Education Division (COED)

educational systemscan be optimized. Researchers, including Freeman and Aoki [6], stress the importance ofdesigning conversational agents that are pedagogically effective and that ethical frameworksshould guide their implementation. In their literature review, Freeman and Aoki [6] build on theunderstanding of how to optimize these systems, explores theories that provide a framework forthe use of pedagogical strategies and ethical considerations in deploying these agents.With this context in mind, this study conducts a systematized literature review, focusing on threeresearch questions to address the effective implementation and integration of conversationalagents in current educational hubs (LMS or VLEs) education and current contributions

Conference Session

Computers in Education Division (COED) Track 6.A

Collection

2025 ASEE Annual Conference & Exposition

Authors

Gabriel Beal, zyBooks, A Wiley Brand; Chi Yan Daniel Leung, zyBooks, A Wiley Brand; Joe Mazzone, zyBooks, A Wiley Brand; Chelsea L Gordon, zyBooks, A Wiley Brand; Yamuna Rajasekhar, zyBooks, A Wiley Brand

Tagged Divisions

Computers in Education Division (COED)

=aisel.aisnet.org/ukais2024/19&utm_medium=PDF&utm_campaign=P‬ ‭DFCoverPages.‬‭[33]‬ ‭Callaghan,‬ ‭D.‬ ‭E.,‬ ‭Graff,‬ ‭M.‬ ‭G.,‬ ‭&‬ ‭Davies,‬ ‭J.‬ ‭(2013).‬ ‭Revealing‬ ‭all:‬ ‭misleading‬ ‭self-disclosure‬ ‭rates‬ ‭in‬ ‭laboratory-based‬ ‭online‬ ‭research.‬ ‭Cyberpsychology, Behavior, and Social Networking, 16(9), 690-694.‬‭[34]‬ ‭Simkin,‬ ‭M.‬ ‭G.,‬ ‭&‬ ‭McLeod,‬ ‭A.‬ ‭(2010).‬ ‭Why‬ ‭do‬ ‭college‬ ‭students‬ ‭cheat?.‬ ‭Journal of business ethics, 94, 441-453.‬‭[35]‬ ‭Stone,‬ ‭A.‬ ‭(2023).‬ ‭Student‬ ‭perceptions‬ ‭of‬ ‭academic‬ ‭integrity:‬ ‭a‬ ‭qualitative‬ ‭study‬ ‭of‬ ‭understanding,‬ ‭consequences,‬ ‭and‬ ‭impact.‬ ‭Journal‬ ‭of‬ ‭Academic‬ ‭Ethics, 21(3), 357-375.‬

Conference Session

COED: Spotlight on Diverse Learners

Collection

2023 ASEE Annual Conference & Exposition

Authors

Vijesh J. Bhute, Imperial College London; Ellen Player; Deesha Chadha, Imperial College London

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

received from the Education Ethics Review Process Team prior toconducting this study.Questionnaire 1 was distributed to teaching staff via Teaching and Learning Network on MSTeams. 34 teachers participated in this questionnaire from different departments across theCollege. Questionnaire 2 was distributed to second-, third- and fourth-year undergraduatestudents from the Department of Chemical Engineering who have experience with universitylearning. 55 students (~14.4%) participated in this questionnaire across these three yeargroups. Both questionnaires 1 and 2 were launched at the beginning of the academic year.Questionnaire 3 was distributed to second year undergraduate students in the Department ofChemical Engineering at the end of teaching

Conference Session

COED Programming Education 2: Instructional Approaches

Collection

2023 ASEE Annual Conference & Exposition

Authors

Matthew Morrison, University of Notre Dame

Tagged Divisions

Computers in Education Division (COED)

, capability, and ethical ramifications of a computing device to “think” and“create art” have long been debated by computer scientists, many pioneers in the field will arguethat the process of designing a computer program is similar to composing music or poetry.Donald Knuth begins his magnum opus The Art of Computer Programming with the argumentthat a computer scientist who understands computer programming at several levels of abstractionwill find the process aesthetically pleasing3 “much like composing poetry or music.”3 ProfessorKnuth had three crucial characteristics in common with Ada Lovelace: a strong understanding ofmathematics, a passion for music, and an understanding of the connection between the two.In fact, universities have long observed

Conference Session

Computers in Education Division (COED) Track 3.C

Collection

2025 ASEE Annual Conference & Exposition

Authors

Randy McDonald, Texas A&M University; Salvatore Enrico Paolo Indiogine; Nasiha Lachaud, Texas A&M University; Wei Lu, Texas A&M University; Mohammad Affan Khokhar

Tagged Divisions

Computers in Education Division (COED)

authors [14],[7], [17] who have highlighted their concerns about the potential implications of using AItechnologies like voice cloning to create academic content. While these technologies offersignificant benefits during the content production process, they also raise concerns aboutintellectual property (IP) considerations, authenticity, and the potential for misuse, such as thecreation of deepfakes. Administrators emphasize the need for clear policies and guidelines toaddress these issues, ensuring that both creators' rights and the ethical implications of using AI ineducational content are adequately managed [18].Research QuestionsThe main goal of this study was to contribute to a rapidly growing body of knowledge that couldlead to the