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Analyzing Feedback of an AI tool for formative feedback of Technical Writing abilities

Conference Session: Computers in Education Division (COED) Track 2.B
Collection: 2025 ASEE Annual Conference & Exposition
Authors: Sean P Brophy, Purdue University at West Lafayette (COE); Fadhla Binti Junus, Purdue Engineering Education
Tagged Divisions: Computers in Education Division (COED)

environments for higher education students studying computer programming. She is particularly interested in investigating students’ programming learning processes, exploring methods to simplify programming instruction, examining theoretical foundations for effective instructional design, and integrating artificial intelligence technologies to facilitate peer-like knowledge construction. ©American Society for Engineering Education, 2025 Analysing Feedback of an AI Tool for Formative Feedback on Technical Writing AbilitiesAbstractThis Full paper describes the use and validation of feedback provided by an AI tool to supportstudents’ technical writing abilities. The project is part of a

Relevance Score: 1.4830836

Assessing Communication Skills Across Upper-Level CS Courses

Conference Session: Computers in Education Division (COED) Track 6.B
Collection: 2025 ASEE Annual Conference & Exposition
Authors: Ryan Edward Dougherty, United States Military Academy; Maria R. Ebling, United States Military Academy
Tagged Divisions: Computers in Education Division (COED)

follow-oncourses in our CS curriculum: a similar writing assignment in an Operating Systems (OS)course, and both written reports and formal presentations in a two-semester capstone course.We found that participation in ToC had a significant effect on the OS course’s outcomes,and similarly was a significant predictor for those of the capstone courses. OS course par-ticipation was an accurate predictor of capstone course performance, and similarly the firstsemester of capstone accurately predicted the second. Additionally, we found that peer re-viewing in ToC predicted OS writing performance and that the final ToC presentation waspredictive of capstone’s presentation scores. These results suggest that specific elements ofprior instruction for

Relevance Score: 0.05006227

Enhancing Learning and Instruction through Structured Reflection in Pair Programming: A Feedback-Driven Approach in Computer Science Education

Conference Session: Computers in Education Division (COED) Track 3.E
Collection: 2025 ASEE Annual Conference & Exposition
Authors: Oyku Eren Ozsoy, Embry-Riddle Aeronautical University - Prescott; Luis Felipe Zapata-Rivera, Embry-Riddle Aeronautical University
Tagged Topics: Diversity
Tagged Divisions: Computers in Education Division (COED)

, loops, and functions. Additionally, itaddresses the need for improvements in course design, instructional effectiveness, and theinstructor’s professional growth. The study employs qualitative and quantitative data collectioninvolving two-course sections with a diverse group of students, engaging in 75-minute pairprogramming sessions where they alternate roles as driver (who writes the code) and navigator(who reviews and guides). The C programming language is used to facilitate collaboration andreal-world skill development. The unique aspect of this study is the structured reflection processapplied after each pair programming session. Students were asked to answer three questions: (1)what they learned, (2) what areas they needed more practice

Relevance Score: 0.030503262

In the Age of LLMs, Is Dual-Submission Homework Dead?

Conference Session: Computers in Education Division (COED) Track 2.D
Collection: 2025 ASEE Annual Conference & Exposition
Authors: Edward F. Gehringer, North Carolina State University at Raleigh; Madhur Dixit, North Carolina State University at Raleigh; Kavya Lalbahadur Joshi
Tagged Topics: Diversity
Tagged Divisions: Computers in Education Division (COED)

,providing detailed solutions by the instructor, and then asking students to write reflections on themistakes made in their original submissions. There are various grading options, such as gradingonly the reflection or grading the homework lightly and the reflection more heavily.For the first submission, it is typical to have students submit just the answers to the homework.Often the feedback on the first submission consists of “light grading,” for completion or effort.The methodology relies upon instructors having a detailed solution set, with more extensiveexplanations than would normally be provided. Since homework problems can be reusedsemester after semester, the methodology can justify the extra effort on the part of the coursestaff.Across all

Relevance Score: 0.028553065

Student Perspectives on the Benefits and Risks of AI in Education

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)

assignments,” which “is a serious risk.” The specific practice ofstudents who ”copy and paste writing assignments from AI chatbots like Chat GPT and hand it inas their own original work” was repeatedly highlighted as problematic. Many participants framedthese behaviors within ethical and institutional contexts, noting that such actions ”are not only inviolation of the school’s honor code, but also unethical and unfair to their peers.” Interestingly, acounterbalancing concern also emerged—that legitimate student work might be incorrectly flaggedas AI-generated, with one participant noting they had ”already seen...peers...who do produce workthat is entirely their own being falsely accused of submitting AI generated work.” Table 2

Relevance Score: 0.028249264

Filling in the Missing Piece: Integrating Storage into CompOrg Courses

Conference Session: Computers in Education Division (COED) Track 3.A
Collection: 2025 ASEE Annual Conference & Exposition
Authors: Xiangqun Zhang, Syracuse University; Ziyang Jiao, Syracuse University; Farzana Rahman, Syracuse University; Bryan Kim, Syracuse University
Tagged Divisions: Computers in Education Division (COED)

American Association of Colleges and Universities to develop effective pedagogy in undergraduate computer science (CS) education. She is the winner of the NCWIT Extension Services (NCWIT ES-UP) award, ABI Systers PIO (Pass-It-On) award, Google ExploreCSR Award, and NCWIT educator award. She published numerous peer-reviewed articles in venues, including the Special Interest Group of the Association of Computing Machinery (ACM SIGCSE), IEEE RESPECT, and IEEE Frontiers in Engineering Education, American Society for Engineering Education (ASEE) conference. She has received funding from different funding agencies research and mentoring initiatives directed toward developing effective pedagogy in undergraduate computer

Relevance Score: 0.025328858

Enhancing Engineering Learning through MathCAD

Conference Session: Computers in Education Division (COED) Track 4.A
Collection: 2025 ASEE Annual Conference & Exposition
Authors: Xiuhua Si, California Baptist University; Keith Hekman, California Baptist University; Jinxiang Xi
Tagged Divisions: Computers in Education Division (COED)

Paper ID #47485Enhancing Engineering Learning through MathCADDr. Xiuhua Si, California Baptist University Dr. Xiuhua (April) Si is a Professor of aerospace and mechanical engineering at California Baptist University. Her broad research interests include engineering education, thermal fluid science, and composite materials application. She has published over fifty peer-reviewed journal and conference papers and had multiple presentations at engineering conferences and meetings.Dr. Keith Hekman, California Baptist University Dr. Keith Hekman is a full professor in Mechanical Engineering. He has been at California Baptist

Relevance Score: 0.025237583

A Framework for Hybrid Human-AI Learning: Insights from Liberal Education Courses in Lebanon

Conference Session: Computers in Education Division (COED) Track 4.B
Collection: 2025 ASEE Annual Conference & Exposition
Authors: Reine Azzi, Lebanese American University
Tagged Divisions: Computers in Education Division (COED)

will beshared in the study) also expose students to another aspect of the pedagogical framework: Amindful awareness of the AI Usability Spectrum. For instance, while Bloom’s revised taxonomyis instrumental in the creation of Human-AI learning outcomes and course content, theframework also encourages faculty to reflect upon the AI Usability Spectrum. To maintainacademic integrity and embrace the full use of Human-AI learning, faculty can engage studentsin the learning process, determining the ‘right’ amount of AI usage for every task. This practiceincludes breaking down tasks into categories pertaining to writing, critical thinking, and researchwhile classifying AI use into low, medium, and high intensity. This interactive processintroduces

Relevance Score: 0.024607506

Integration of Conversational Agents into Learning Management Systems: A Systematized Literature Review

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)

, enhancing intrinsicmotivation.Social Constructivist Phase: The final phase integrates social learning, where studentscollaborate and engage in discussions and group activities. This phase uses the social features ofthe LMS to enrich learning through peer interactions and community feedback, solidifying theknowledge constructed in earlier phases.MethodsTo address the research questions, we will use a systematized literature review according to thePRISMA framework as proposed by [8]. Therefore, the stages are the following. First, we foundalternative terms used for chatbots and Learning Management Systems and formed queries forour searches in the databases. Next, we consulted the databases ERIC, Compendex, INSPEC,Scopus, Web of Science, and ACM

Relevance Score: 0.019984003

BOARD # 79: Student-led VR Content Creation for Engaging Engineering Learning

Conference Session: Computers in Education Division (COED) Poster Session (Track 1.A)
Collection: 2025 ASEE Annual Conference & Exposition
Authors: Nicholas Cameron Amely, California State University, Fresno; Wei Wu, California State University, Fresno; Jesus Leyva, California State University, Fresno
Tagged Divisions: Computers in Education Division (COED)

evaluation andlearning assessment with peer students in ECE. As a proof of concept, this paper explored howstudent-led development of VR content and experience might offer a solution to a commonobstacle faced by many STEM educators who are interested in exploring VR, which is the lackof readily adoptable VR content. This study contributes to better understanding the role andimpacts of learner-as-creator/co-creator in engaging student learning in educational technology-integrated learning environments.1. Introduction & backgroundThe objective of this study was to explore student-led development of virtual reality (VR)applications as an alternative solution to enhance student learning and engagement in the field ofelectrical and computer

Relevance Score: 0.019976776

BOARD # 93: WIP: Investigating the Role of Augmented Reality Science Applications as a Supportive Tool for Facilitating Collaborative Learning in Elementary Classrooms

Conference Session: Computers in Education Division (COED) Poster Session (Track 1.A)
Collection: 2025 ASEE Annual Conference & Exposition
Authors: MALEK EL KOUZI, Queen's University; Omar I.M Bani-Taha, Carleton University; Richard Reeve, Queen's University
Tagged Divisions: Computers in Education Division (COED)

. The research shows that using AR and gamificationimproves young children's learning, especially in alphabet writing [14]. Also,Thompson et al. conducted a comprehensive, multi-year study to identify andcharacterize educational Augmented Reality environments suitable for students ofvarious ages and skill levels. Throughout the research, the students, parents, andteachers actively collaborated to plan, construct, and enhance six AR prototypes. Basedon their student’s positive outcomes, these kinds of software can be used in classrooms.[15]. Students need to be active participants in their learning, fully engaged inexploring the various aspects of 21st-century education. Moreover, there is a necessityto enhance the demanded qualifications

Relevance Score: 0.019738756

BOARD # 89: WIP: Developing an Instrument to Understand Engineering Student uses of Digital External Resources from Solution Manuals to Generative AI

Conference Session: Computers in Education Division (COED) Poster Session (Track 1.A)
Collection: 2025 ASEE Annual Conference & Exposition
Authors: Christopher Allen Calhoun, University of Cincinnati; David Reeping, University of Cincinnati; Siqing Wei, University of Cincinnati; Aarohi Shah, University of Cincinnati
Tagged Divisions: Computers in Education Division (COED)

focus of the literature. Within the first monthsof its launch, it was found that ChatGPT could pass law school exams, though it only managed aC+ [20]. This is just one example of the deluge of papers describing how large language modelscan perform reasonably well on traditional examinations (e.g., [21], [22], [23], [24], [25]). Thesemodels are trained using large and diverse sets of writing and employ statistical procedures topredict a response to a statement or question, which can lead to surprising coherence and theappearance of analytical reasoning.In STEM fields, where communication is less in written short responses and more often acombination of diagrams and equations, generative AI tools have seen uneven success in problem-solving. For

Relevance Score: 0.019462332

BOARD # 98: WIP: Understanding Patterns of Generative AI Use: A Study of Student Learning Across University Colleges

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

Relevance Score: 0.019130316

Development of a Cost-Effective Kit for an International Learning Experience in the Context of Generative Artificial Intelligence

Conference Session: Computers in Education Division (COED) Track 4.D
Collection: 2025 ASEE Annual Conference & Exposition
Authors: Carlos Sotelo, Tecnologico de Monterrey, School of Engineering and Sciences; David Sotelo, Tecnologico de Monterrey, School of Engineering and Sciences; Erick Ramírez-Cedillo, Tecnologico de Monterrey, School of Engineering and Sciences; Félix Martínez-Jiménez, Tecnologico de Monterrey, School of Engineering and Sciences; Ana I. Benavides Lahnstein, Manchester Metropolitan University; Alison Buxton, University of Sheffield
Tagged Topics: Diversity
Tagged Divisions: Computers in Education Division (COED)

students’knowledge, skills, and attitudes. While these assessments might contribute to achieving learningobjectives, the development of thinking, problem-solving skills, and student motivation shouldbe explored as an extracurricular activity rather than an assignment that takes place in aclassroom environment.Augmented reality (AR) is a technology that overlays virtual objects in the real-worldenvironment, which enhances users’ engagement [6]. This technology has been applied toencourage critical thinking in learners of different ages [7-9]. Through the Assemblr Eduplatform, it is shown in [7], that English writing skills are improved. Similarly, in [8], ARtechnology is used to facilitate collaborative learning in science education, while in [9], it

Relevance Score: 0.018938046

A Review of the State of Integrated Engineering Frameworks and Outcome Dimensions

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)

the learning side by developing an Integrated Engineering foundational course withwhat the authors call a “combination of variation theory and capability theory, content framed interms of threshold concepts, and delivery using cooperative peer learning method[s]” (p. 1) [9].Lin and Low have recently proposed an Integrated Engineering Education Alignment Model forIndustry 4.0. The authors report that the integrated alignment model nurtures synergy amongEngineering Education activities such as applied learning, applied research, and continuouseducation training (CET) programs to share a common Industry 4.0 vision with diversestakeholder groups such as students, faculty, industry partners, and recipients of CET programs.The authors use the

Relevance Score: 0.01869604

A Survey of Task Planning: Pre- and Post-Assessment of a Project Management Activity in the Computer Science Senior Capstone

Conference Session: Computers in Education Division (COED) Track 6.C
Collection: 2025 ASEE Annual Conference & Exposition
Authors: Aimee Allard, North Carolina State University at Raleigh
Tagged Divisions: Computers in Education Division (COED)

Paper ID #48079A Survey of Task Planning: Pre- and Post-Assessment of a Project ManagementActivity in the Computer Science Senior CapstoneAimee Allard, North Carolina State University at Raleigh Dr. Aimee Allard is a member of the Senior Design Center faculty in the Department of Computer Science at NC State. As the Communications Coordinator and an instructor in Senior Design, she works with students on writing- and communications-based milestones: task planning, documentation, reports, design strategies, presentations, and more. She is passionate about Senior Design because not only do students gain real-world experience

Relevance Score: 0.018409126

From Mathematical Theory to Engineering Application: An Undergraduate Student’s Research Journey

Conference Session: Computers in Education Division (COED) Track 5.C
Collection: 2025 ASEE Annual Conference & Exposition
Authors: Tony Malayil, Florida Atlantic University; Daniel Raviv, Florida Atlantic University; Juan David Yepes, Florida Atlantic University
Tagged Topics: Diversity
Tagged Divisions: Computers in Education Division (COED)

in which students learn about academic writing and out-of-classroom research with a professor. As a result, the program significantly prepared the student prior to joining a research group, helping eliminate his “fear” of research. Universities that have and encourage students to join such programs can strengthen the abilities of their students [3]. • Active recruitment by peers: The student was recruited into the lab by one of its undergraduate researchers. The researcher recognized their interest in computer vision and believed they would be a strong candidate to join. • Professor mentorship: Once accepted into the lab, the professor explained computer vision using one of the field's

Relevance Score: 0.01814435

FORE: A Student-Centered Framework for Accessible Robotics Education through Simulation and Interactive Learning

Conference Session: Computers in Education Division (COED) Track 4.C
Collection: 2025 ASEE Annual Conference & Exposition
Authors: Hossein Jamali, University of Nevada, Reno; Andrew L DeBolt; Henry Dalton, University of Nevada, Reno; Jenavieve K Layosa, University of Nevada, Reno; Ilana Rose Macy; Ponkoj Chandra Shill, University of Nevada, Reno; David Feil-Seifer, University of Nevada, Reno; Frederick C Harris, University of Nevada, Reno; Sergiu Dascalu, University of Nevada, Reno; Rui Wu, East Carolina University
Tagged Divisions: Computers in Education Division (COED)

Paper ID #47284FORE: A Student-Centered Framework for Accessible Robotics Educationthrough Simulation and Interactive LearningHossein Jamali, University of Nevada, Reno Hossein Jamali is a PhD student at the University of Nevada, Reno, focusing on Human-Computer Interaction, Artificial Intelligence, and Cloud Computing. His research encompasses a range of interdisciplinary topics, including AI-driven recommender systems and resource management algorithms. Hossein has authored several peer-reviewed papers in leading conferences and journals and has actively contributed to advancing AI and optimization techniques. His work

Relevance Score: 0.017876692

BOARD # 71: Integrating Machine Learning into Middle and High School Curricula using Alzheimer's Disease Prediction Models

Conference Session: Computers in Education Division (COED) Poster Session (Track 1.A)
Collection: 2025 ASEE Annual Conference & Exposition
Authors: Tayo Obafemi-Ajayi, Missouri State University; Naomi L Dille, Missouri State University; Dhanush Bavisetti, Missouri State University; Sherrie Ilene Zook
Tagged Divisions: Computers in Education Division (COED)

were able to complete all activities due to absences. The class meets 5 days per weekfor 90 minutes each day. Algebra 1A is an almost exclusively freshman class consisting of mainly low achievingmath students who were deemed to require extra time to master concepts. Those passing Algebra 1A move on to Table 1: High School Standards encoded using Scratch Programming. Teaching Standards Application in Scratch Hacker name: use variables to learn how to 6.EE.B.6 Use variables to represent numbers and write expressions use the various blocks in Scratch to create a when

Relevance Score: 0.01778367

BOARD # 76: Pedagogical Agents in the age of Generative Artificial Intelligence: Opportunities and Challenges in K-12 STEM Education.

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

Relevance Score: 0.016929382

Exploring Student Use of an ACT-based Mobile Application and its Impact on Reducing Procrastination

Conference Session: Computers in Education Division (COED) Track 6.C
Collection: 2025 ASEE Annual Conference & Exposition
Authors: Yiqing Li, University of California, San Diego; Jiaen Yu, University of California, San Diego; U Lam Lou, University of California, San Diego; Dingyi Yu, University of California, San Diego; Michael Levin, Utah State University; Korena S Klimczak, Utah State University; Soohyun Nam Liao, University of California, San Diego
Tagged Divisions: Computers in Education Division (COED)

were transcribed and then analyzed usingthematic analysis.The results of this study provide insights into students’ perceptions on ClearMind with respect toTAM’s core constructs: perceived usefulness, perceived ease of use, and social influence. Theparticipants found ClearMind both useful and easy to use, and were willing to continue using itand recommending it to their peers. They also identified some opportunities for improvementsuch as fostering positive emotions and better organizing the content.Our user study results imply that ClearMind is an accessible yet helpful mental health resourcefor students. This highlights ClearMind’s potential for broader adoption. Future work involves alarge-scale quantitative study to assess ClearMind’s

Relevance Score: 0.01665932

The Role of Artificial Intelligence in Advancing Student Success: Perspectives from Three Land Grant Institutions

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)

usingAI towards decision making in admissions, financial aid, finance, scheduling and humanresources. Within the classroom, there are opportunities for advanced AI models to aid in theteaching enterprise (with faculty/department chair oversight). Furthermore, autonomous robotsmay play a role in services such as libraries, dining halls and facilities and operations.Within STEM disciplines, there are additional opportunities and challenges associated with usingAI tools [17]. Doors are opened to facilitate teaching and learning through simulations as well asin providing personalized tutoring/instruction. Concerns arise from the impact on the learningprocess when tools like ChatGPT can compose text to be used to write essays, conduct

Relevance Score: 0.01660523

BOARD # 77: Perception of the Impact of Generative Artificial Intelligence on Education

Conference Session: Computers in Education Division (COED) Poster Session (Track 1.A)
Collection: 2025 ASEE Annual Conference & Exposition
Authors: Hannah Oluwatosin Abedoh, Morgan State University; Blessing Isoyiza ADEIKA, Morgan State University; Pelumi Olaitan Abiodun, Morgan State University; Oludare Adegbola Owolabi P.E., Morgan State University; Abiola Olayinka Ajala, Morgan State University; OLUWATOYOSI OYEWANDE, Morgan State University
Tagged Topics: Diversity
Tagged Divisions: Computers in Education Division (COED)

enables the creation of personalized learning content, automated feedback, and real-timeacademic support. A notable example is OpenAI’s ChatGPT, a large language model trained togenerate human-like text responses, assisting students and educators in various academic tasks,including writing, coding, and content summarization [4]. While several generative AI models,such as Google Bard and Anthropic's Claude, offer similar capabilities, ChatGPT is known for itswidespread adoption in educational contexts, its advanced natural language processingcapabilities, and its frequent integration into learning management systems and academicworkflows. These factors position ChatGPT as a leading AI tool in education, making it an idealcase for examining the

Relevance Score: 0.013901666

Exploring Student Self-Efficacy in AI Through Model Building Artifacts

Conference Session: Computers in Education Division (COED) Track 4.E
Collection: 2025 ASEE Annual Conference & Exposition
Authors: Gabriella Marie Haire, University of Florida College of Education; Pavlo Antonenko; Christine Wusylko, University of Florida; STEPHANIE KILLINGSWORTH, University of Florida; Brian Abramowitz, University of Florida; Jeremy A. Magruder Waisome, University of Florida
Tagged Topics: Diversity
Tagged Divisions: Computers in Education Division (COED)

participantsto have direct manipulation and feedback.The program encouraged participants to have an active role in their learning, which follows aconstructivist approach to teaching and facilitation. The summer program began with participantslearning about datasets through the use of iNaturalist when visiting a garden anda museum.They also completed teamwork and planning activities. After this, more scientific discussionsbegan with the use of a peanut butter and jelly recipe writing activity, which served as a segueinto a discussion about algorithms and the importance of data in training AI models. From there,GTM was introduced using the example of shark teeth and three classes: cutting teeth, graspingteeth, and crushing teeth. Computer vision was

Relevance Score: 0.013736291

Experiences Using Live Streaming as an Informal Learning Tool in the Formal Classroom

Conference Session: Computers in Education Division (COED) Track 3.E
Collection: 2025 ASEE Annual Conference & Exposition
Authors: Ella Kokinda, Clemson University; D. Matthew Boyer, Clemson University; Paige Rodeghero, Clemson University
Tagged Divisions: Computers in Education Division (COED)

that enable participation from diverse andunderrepresented learners [10, 11]. Structural barriers to computing education include access,lack of engaging content, and shortage of role models and peer networking [11, 12, 13, 14, 15].Outside of structural barriers, social and societal barriers like misconceptions and perceptions ofthe field of computing, and stereotypes of the practitioners and working environments withincomputing [11, 16, 17, 18].Prior work has shown that formal engineering and science curricula alone cannot begin to closethe gaps and barriers seen in computing education [19]. In addition, learning outside of the formalclass has been shown to benefit those who are underrepresented in STEM [20]. Knowing this,there have been many

Relevance Score: 0.013527176

Embodied Sensors and Digital Twins as an Introduction to Microprocessor Programming for Middle and High School Non-CS Majors

Conference Session: Computers in Education Division (COED) Track 4.D
Collection: 2025 ASEE Annual Conference & Exposition
Authors: Leslie Bondaryk, The Concord Consortium; Aaron Kyle, Duke University; Ido Davidesco, University of Connecticut; Chad Dorsey; Bianca Montrosse-Moorhead, University of Connecticut
Tagged Topics: Diversity
Tagged Divisions: Computers in Education Division (COED)

, University of ConnecticutChad DorseyBianca Montrosse-Moorhead, University of Connecticut Bianca Montrosse-Moorhead, Ph.D., is a Professor of Research Methods, Measurement, and Evaluation at the University of Connecticut, where she also directs the Partnership for Evaluation and Educational Research (PEER) lab. As Co-Editor-in-Chief of New Directions for Evaluation and internationally recognized evaluation scholar, Bianca has dedicated her career to bridging the space between evaluation theory, research, and practice. Her scholarship encompasses a broad spectrum of contributions, from evaluating various educational and social programs using diverse methodologies to enhancing the professional training of evaluators