attention inthe business and public sphere with the release of models like ChatGPT [4] and DALL-E [5],robust applications within the field of engineering education remain are still emerging [6]. Aspart of the recent popularity of large language models (LLM) there have been increasingconcerns about the ethical ramifications in educational and industry settings. In their analysis ofthe practical ethical dangers of ChatGPT Zhuo et al. [7] outline areas of concern for LLMs as agroup; the risk inherent in small models propagating with increased scale, potential biases withinmodel training data, and the ballooning size of LLMs computational requirements. Theseconcerns limit the number of practitioners that are willing to adopt ML, NN, or LLM tools
Intelligence (AI) applications have become an integral part of our lives, from socialapplications on smartphones to crewless vehicles. However, as they remain in the domain of“computer magic,” these new advancements of knowledge processing and reasoning using AI toolswill not be of a great benefit to humanity, unless a complementary education environment isprovided to help students and communities become involved in this scientific revolution early,ethically, and systematically. Introducing and exploring AI concepts and basics earlier in thestudents’ learning journey will help address the future AI job market needs as well as AI ethicsissues and will open the door for new innovative AI applications in all segments of life. The long-term goal of this
reliance on cloud computing and big data will continuously increase, andnew data-centric technologies and engineering approaches will be developed. Due to this rapidlydeveloping field, there is a need to track these trends and incorporate the corresponding developments intoour current science and engineering curriculum. Besides data science skills already taught in traditionalengineering curricula, such as mathematical, computational, and statistical foundations, the NationalAcademies guide discusses that key concepts in developing data acumen include domain-specificconsiderations and ethical problem-solving. This work-in-progress (WIP) paper will highlight the foundation of a comprehensive study toexplore data science education in two
to have all its undergraduate engineering, computer science, and cybersecurity degrees to be accredited by ABET (Accreditation Board for Engineering andTechnology). Pursuant to this goal, a capstone project course was added to the updatedcurriculum of the BSCS degree. Even though the six Educational Student Outcomes (ESOs)prescribed by ABET [6] are addressed by the core courses in the curriculum, adding a capstoneproject course to the core curriculum brings together all the six ESOs in one course in a polishedand refined manner for students to see the relationship among all six ESOs. The capstonespecifically focuses on ESO #3 (communication skills), ESO #4 (legal and ethical principles), andESO #5 (teamwork). The foundational block in the
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
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
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
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
, 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
education.Chatbots may struggle to handle complex or ambiguous questions from students and may lack thehuman touch and empathy that teachers provide. Additionally, chatbots require constant updatingand maintenance to keep up with the curriculum and standards. There are also ethical and privacyconcerns regarding the data that chatbots collect and use [15]. Furthermore, chatbots may not beaccessible or affordable for all students and schools, and current chatbot technologies might notbe readily accessible for people with disabilities [16]. Since Chatbots are trained based oninformation on the internet or human-curated content, they may carry the same biases as those ofthe original authors [17]. This paper details a framework to tackle a few of these