can understand what is appropriate for this this task? working well or not in task? the project. Which of the following tools are more appropriate for this problem? Expected Correct Answers Drones Virtual Reality Programming ChatGPT (+1) Point
mentees and randomly sorting each column independently to create a random butrepresentative set of mentees. The mentees were then manually paired to create the seeds formentoring groups. Sample student data was generated using a combination of generative AI(ChatGPT) and previous student data. Random student names were generated in ChatGPT byasking for a list of 100 random names from all ethnicities in the US with likely ethnicity and genderfor each name (ChatGPT only returned 98 entries). Gender was classified as Man or Woman with2% of the list being randomly classified with a gender of More to account for transgender and non-binary students. Sample student ethnicity was classified as one of: African American/Black, EastAsian/Asian American (e.g
required by employers. As more data and analytical methods becomeavailable, more aspects of the economy, society, and daily life will become dependent on data-driven decision-making. Recognizing this shift, the National Academies of Sciences (2018)emphasizes that academic institutions must prioritize developing "a basic understanding of datascience in all undergraduates" to prepare them for this new era [1]. This is particularly crucial forSTEM graduates, who must develop varying levels of expertise in working with data – the abilityto understand, interpret, and critically evaluate data, as well as to use data effectively to informdecisions. The recent emergence of large language models (LLMs) such as ChatGPT, which arebecoming increasingly
writing In-class activity2.1 Week 1: First In-person Meeting Activity: Setting Up Your Goal2.1.1 Use of MentimeterIn the first in-person class, the course expectations are introduced. A Mentimeter is used to makethe session interactive and engaging. The following questions are asked during the first meeting,allowing students to see their responses in real-time: How are you today? Use one word todescribe how you feel now. How do you rate your current writing skill? (0-100 points). Howmany journal articles (not including conference presentations) have you published so far? Whatare your expectations for this course? Have you used AI (e.g. ChatGPT) in your academic work?Which area(s) do you find challenging when starting to write? How are
construction industry, even fewer studies haveexplored the impact of predictive analytics using large language models (LLM), such asChatGPT or BERT. Yet, the little existing research also points to the need for reskilling theexisting workforce [17,18], albeit unclear on the broad implications beyond direct developmentand interaction of LLMs. Short- and long-term implications of the use of ChatGPT in allindustries are still unclear [18]. However, due to its analytical nature, it might displace differentpositions than those affected by the use of robotics.Moreover, it is clear through the increased use of information technologies that roles related tothis discipline will start to be part of the building process. For example, the centrality of
receive instant feedback about their score but do not have access to thequestion or their answer after they submit it. Students can re-attempt these exam topics infinitetimes; getting a (hopefully) different question each time.Students are free to access their notes and course materials while answering these questions andare encouraged to write and run test code as well. They are allowed to access the Internet ingeneral, however, they are forbidden from using Internet chat sites such as stackoverflow.com orquestion answering sites such as Chegg, CourseHero, or ChatGPT or from communicating withother people using any medium.Exam questions give the students 30 minutes to do problems that would typically take them 5-10minutes on a standard exam
not a definitive and exhaustive list, it is a good starting point andcan be modified to suit the specific needs and context of the partnership. (Note that the rubricwas constructed with the assistance of ChatGPT. Putting a collection of related ideas into astandard format, like a rubric, is one of the tasks that AI seems to do well. We share thisinformation when we share the rubric as an incentive for potential collaborators to improve it.)Workshop PlanThe IEC has developed a broad and very challenging vision of enabling MSIs and their students,staff and faculty to more fully become part of and contribute to the ECE enterprise. To realizethis vision, this workshop brought together IEC Core MSI members with the heads of other ECEdepartments
perceived growth and development of the student. In the latter case, manualcoding of the responses revealed which specific skills were acquired by the student and identifiedby the mentor but not by the student response, leading to a positive score discrepancy, or theareas which mentors identified as having room for improvement, leading to a negative scorediscrepancy.When considering the thematic content of all responses rather than focusing on those whichpresented with score discrepancies, coding and tallying of responses was complemented with theaid of the LLM ChatGPT (OpenAI, CA, USA). The use of LLMs in content analysis has beenpreviously shown to have good agreement with human results [12], [13]. In this study, ChatGPTwas prompted to identify
-5ct7-54du.[13] S. A. Athaluri, S. V. Manthena, V. S. R. K. M. Kesapragada, V. Yarlagadda, T. Dave, and R. T. S. Duddumpudi, “Exploring the Boundaries of Reality: Investigating the Phenomenon of Artificial Intelligence Hallucination in Scientific Writing Through ChatGPT References,” Cureus, Apr. 2023, doi: 10.7759/cureus.37432.[14] A. E. Greene, Writing Science in Plain English, Chicago, IL, USA: The University of Chicago Press, 2013.[15] G. R. Hess and E. N. Brooks, “The Class Poster Conference as a Teaching Tool,” Journal of Natural Resources and Life Sciences Education, vol. 27, no. 1, pp. 155–158, 1998, doi: 10.2134/jnrlse.1998.0155.[16] J. Schimel, Writing Science: How to Write Papers that Get Cited and Proposals
, DOI: 10. 1080/105112506008661663. Fask, A., Englander, F., & Wang, Z. (2014). Do online Exams Facilitate Cheating? An Experiment Designed to Separate Possible Cheating from the Effect of the Online Test Taking Environment. J Acad Ethic, 12:101–112 DOI 10.1007/s10805-014-9207-14. Charlesworth, P., Charlesworth, D.D., & Vician, C. (2006) Students’ Perspectives of the influence of Web- Enhanced Coursework on Incidences of Cheating, Journal of Chemical Education, vol. 83 No.9.5. Chegg Inc., website https://www.chegg.com, accessed on November 4th, 2024.6. ChatGPT 4o, https://chat.openai.com, accessed on November 4th, 2024.7. Coure Hero, website www.coursehero.com, accessed on November 4th, 2024.8. Nader, M
curriculum of our Computer Engineering program and require only basicknowledge of physics and calculus. For Arduino code, templates will be given and explained, soattendees can focus on the key concepts like A/D and D/A conversions, circuit modeling andperformance, feedback control, as well as Proportional-Integral-Derivative (PID) controller.The organizing faculty worked with the recruiting staff and started the preparation in latesummer of 2024. ChatGPT found a name for the workshop as ‘Circuit Breaker: Women inEngineering’; and Nov. 15 was chosen for this half-day hands-on free workshop from 12 to 4pm.We chose Nov. 15 since it was a Friday when community colleges in the area usually don’t offerclasses in the afternoon. Also, the Autumn quarter is
. R. Adapa, and Y. E. V. P. K. Kuchi, “The Power of Generative AI: A Review of Requirements, Models, Input–Output Formats, Evaluation Metrics, and Challenges,” Future Internet, vol. 15, p. 260, 2023, doi: 10.3390/fi15080260.[15] A. K. Y. Chan and W. Hu, “Students’ voices on generative AI: perceptions, benefits, and challenges in higher education,” International Journal of Educational Technology in Higher Education, vol. 20, no. 1, p. 43, 2023, doi: 10.1186/s41239- 023-00411-8.[16] Tlili et al., “What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education,” Smart Learning Environments, vol. 10, no. 1, p. 15, 2023, doi: 10.1186/s40561-023-00237-x.[17] M. S
processing, and transformer architectures and how they fit into larger systems • Generative adversarial networks and survey of AI methods (Bayesian reasoning, genetic algorithms, expert systems) and when they are used • Relationship with signal processing, pattern recognition, and data analytics • Open-source tools, data sourcing, licensing, and rights management • Data cleansing strategies and data cost estimation, including cost of data generation • LLMs, prompt engineering, ChatGPT, and organizational adoption and use • Multi-modal AI, agent-based models, and humanoid robotics • Computing infrastructure for AI, including compute requirements and platform selection • The disruptive impact of AI on the
lives. Thisis especially true now, since the world is in the midst of a number of controversies dealing withbiased data sets for training of neural networks, ChatGPT unfair uses, or the Elon Musk’s call fora moratorium on AI development. Results from this research will be used as preliminary findings while planning large-scale regionalresearch activities related to AI that could be supported by NSF, Amazon Machine LearningUniversity or the Department of Education. A collaborative network consisting of localschoolteachers interested in AI and AI-active university professors will be created to furtherpromote and implement AI in the K-12 curriculum. Partnership modalities with the AI4K12organization will be investigated to improve AI literacy
to the question “Was there anything that you would take away fromthis experience and apply to future projects or group work? If so what?” in the survey wasanalyzed and validated in two ways. Salient themes were identified by the authors and thefrequency of those themes were tabulated to count the number of occurrences specific featureswere identified from students. Responses were coded into the following 8 themes:Communication, assigned roles, motivation, lab skills/course content, collaboration/teamwork,leadership, enjoyment, and delegation/group organization. In addition, the responses were inputinto an artificial intelligence natural language processing tool (ChatGPT, OpenAI) to identifythemes from responses in an unbiased manner. This
learning community of the course? Ex. Engage students with personal knowledge that can enhance class activities like students from various origins or countries who can discuss how climate change is affecting their homes YES or NO Are students required to demonstrate self-reflective processes in evaluating engineering in society? Ex. Require students to express and defend opinions on engineering issues in the news on a regular basis, like the effects of ChatGPT on education YES or NO Are there opportunities for students to demonstrate their ability to integrate multiple values into evaluation and decision making in an engineering context? Ex
students might help to gainmeaningful insight from students’ viewpoints to improve the AI certificate program. Finally, thelow number of student samples and institutional and regional effects may also be considered fora complete study in the future.6. AcknowledgmentThis work was funded and supported by the National Science Foundation (#2051113) andUSDOT Transportation Consortium of the South-Central States (TRAN-SET) (# 21-034, and#21-049) to YFJ.References[1] B. D. Lund and T. Wang, "Chatting about ChatGPT: how may AI and GPT impact academia and libraries?," Library Hi Tech News, 2023.[2] R. R. Murphy, Introduction to AI robotics. MIT press, 2019.[3] K. Siau and W. Wang, "Building trust in artificial intelligence, machine learning, and
activities' interactive nature. They would muchrather engage in these topics in this format rather than write another essay (this isalso becoming tougher with the commercialization of large language models and XAItools like ChatGPT and Bard).We generally use an iterative design process that brings together real-world examplesof the topic we want to discuss with students. We include articles, publications,videos, and other resources to establish the roles and build a conversation. Someroles are designed not to agree with each other – the values of different perspectivesare set up to foster conversation. Ultimately, we hope to facilitate a conversation anddirect students into recognizing the principles at play
level category structure that these options fell intousing ChatGPT and prior research. Categorized Response Developing Options Response Items Situational Judgement Inventory (SJI) 25Finally, we sorted the organized responses into each response option category,making sure that each response option was only one action. Given the varyingdomains of scenarios and relevant responses, some of the scenarios have severalresponse options within the same response option category and/or some responseoption categories are skipped altogether
creating a laboratory course wherestudents learn the applications of AI and get to play and experiment with concepts that they can right away see beingapplied through concepts of simple Calculus and Python programming.Deep Convolution based networks with the Triplet loss were quite successful (e.g., FaceNet) in face recognitionresulting in greater than 99% accuracy on benchmarks such as LFW. With the recent success of Transformer basedNatural Language Processing architectures (e.g., ChatGPT), transformers have been attempted in Computer Visionapplications. They have shown considerable success with better computational efficiency than CNN-basedarchitectures. In this project, we compare the FaceNet and transformer-based architecture for face
prompts in LLMs (ChatGPT, Bard and Hugging Face)These modules include lecture notes, practice problems, and quizzes. The learners can completethese modules at their own pace. The course instructor acts as the facilitator and provides help asneeded.The modules can be accessed at https://skills.yourlearning.ibm.com/. Students need to createaccounts to log in and sign up a module to see the module content. The login screen is shown inFigure 2: Figure 2 – Log in options Analysis of Course Survey Results Student Surveys A. Cybersecurity (Fall 2024, Sample Size N = 88)The Cybersecurity module was infused to six sections of CS 150 course during
Using Instructor-Specified Criteria, “ Advances in Engineering Education, 2(1), 1-28, 2010.[10] Loughry, M. L., et. al., “Development of a Theory-Based Assessment of Team MemberEffectiveness,” Educational and Psychological Measurement, 67, 505-524, 2007.[11] Loignon, A. C., et. al., “Facilitating Peer Evaluation in Team Contexts: The Impact ofFrame-of-Reference Rater Training,” Academy of Management Learning & Education, 16(4),562-578, 2017.[12] CATME, “CATME Terms Student Dictionary,” https://info.catme.org/student/student-help/catme-terms-student-dictionary/, [Accessed Jan. 12, 2025].Note: ChatGPT was used in this manuscript to check grammar and spelling; (GPT-4o). OpenAI,https://chat.openai.com/chat. [Accessed Jan. 20, 2025]Appendix A
personalexperience relating to one of the topics covered in the course materials. The second high contextquestion was a fill in the gap series of questions in which they needed to identify the name of theconcept or equation after providing a description of a real-case scenario. See Figure 1. To deterstudents from copying or collaborating with others, a total of three different exam versions werereleased and the included numeric problems were not previously published so they coul d not befound online. ChatGPT had not been released yet so it had no effect on this investigation, but itwould need to be addressed for future applications.Figure 1. Excerpt from a fill-in-the gap question series to identify the name of the concept orequation by providing them a
in freshman information processing and the rise in Using academic resources both fall outside of the 2 sigma bands starting the Fall of 2022. Since ChatGPT was introduced in November 2022, this decrease is likely not due to AI usage. The COVID-19 pandemic effect, on the other hand, matches the timing. The national trends mentioned in sections IV.A.1 and 2 above support this theory. However, whether this is the true cause needs further research. Further, the rise in Using academic resources may be happening in compensation for the dropping Information Processing skill. Again, to establish if this is the case, will need further research. 2
Improving Decisions in Engineering Education Agents and Systems (IDEEAS) Lab, a group that uses multi-modal data to characterize, understand, a ©American Society for Engineering Education, 2023 Pushing Ethics Assessment Forward in Engineering: NLP-Assisted Qualitative Coding of Student ResponsesAbstractRecent headlines have featured large language models (LLMs), like ChatGPT, for their potentialimpacts throughout society. These headlines often focus on educational impacts and policies. Weposit that LLMs have the potential to improve instructional approaches in engineering education.Thus, we argue that as an engineering education community, we should aim to leverage LLMs tohelp resolve
more learner-centered and focusedon formative feedback rather than summative evaluation [1].As the world of technology continues to advance, a shift and embracement of new assessmentmethods is appropriate and necessary. For example, as of early 2022, the New York Timesreported that universities are now having to change the way they are teaching and assessingstudents because of the widespread availability of A.I. Chatbots such as ChatGPT [12]. WithinIE at Minnesota State University, Mankato, differential methods of assessment have beenemployed for over a decade and we want to share our experiences with oral exams to supportothers in embracing the changing world, better preparing engineering students for their futurepositions.Overview of
they can right away see being applied through concepts ofsimple Calculus and Python programming.Deep Convolution-based networks with the Triplet loss were quite successful (e.g., FaceNet) inface recognition, resulting in greater than 99% accuracy on benchmarks such as LFW. With therecent success of transformer-based Natural Language Processing architectures (e.g., ChatGPT),transformers have been attempted in Computer Vision applications. They have shown considerablesuccess with better computational efficiency than CNN-based architectures. In this project, wecompared the FaceNet and transformer-based architecture for face recognition. We also providedan insightful understanding of the face recognition process, its limitations, and future
University of Hong Kong, "InnoShow," in Tam Wing Fan Innovation Wing 2023. [Online]. Available: https://innoacademy.engg.hku.hk/innoshow/[24] Innovation Academy, Faculty of Engineering, the University of Hong Kong, "From Ground to Air," in Tam Wing Fan Innovation Wing 2023. [Online]. Available: https://innoacademy.engg.hku.hk/20231106_workshop/[25] Innovation Academy, Faculty of Engineering, the University of Hong Kong, "Build Your IoT Smark Clock," in Tam Wing Fan Innovation Wing 2023. [Online]. Available: https://innoacademy.engg.hku.hk/iotclock/[26] Innovation Academy, Faculty of Engineering, the University of Hong Kong, "Unleash Creativity with Generative AI through Open AI Engine and ChatGPT - Build Your Personalized
the assistance of ChatGPT. We include this information when we share therubric as an incentive for potential collaborators to improve it.) Asset Driven Equitable Partnerships – ADEP in Practice (WIP)References [1] Connor, K. A., & Goodnick, S. M., & Klein, M., & Sullivan, B. J., & Kelly, J. C., & Leigh-Mack, P., & Abraham, S., & Janowiak, J., & Alvarado, S., & Andrei, P., & Scales, W. A., & Wilson, T., & Lagunas, Y. (2023, June), Board 78: ADEP: Asset-Driven Equitable Partnerships (WIP) Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1- 2—42939 [2] National Academies of Sciences, Engineering