individual student needs, and enhance accessibil- solution that utilizes an SLM to manage sensitive studentity. However, as GenAI systems become more integrated into data within higher education institutions. By processing datahigher education, concerns about data privacy, security, and locally, the SLM can scrub personal identifiers and createregulatory compliance are becoming increasingly critical [3]. prompts that maintain student privacy before interacting with Higher education institutions process vast amounts of sen- a generic LLM like ChatGPT. For instance, when a counselorsitive student data, including academic records, behavioral aims to develop a student improvement plan, they input
course [2] O. Vinogradov, “Fundamentals of kinematics and dynamics of machinesI plan to have students measure kinematics using video analysis and mechanisms.” CRC press, 2000.or accelerometers, similar to [7] and kinetics using load cells, [3] M. Bedillion, R. Raisanen, and M. Nizar, “Improving Transitionsand compare their experimental data to results obtained using Between Sophomore Dynamics and Junior Dynamic Systems Courses”. ASEE Annual Conference & Exposition, June 2014, pp. 24-725.simulations and hand calculations. Again, the biggest constraint [4
communication amongoffers specialized programs that integrate AI into engineering team members. At MIT’s Computer Science and Artificial Intelligence students to verify and critically evaluate AI outputs rather thanLaboratory (CSAIL), researchers have developed an AI as- accepting them at face value.sistant that functions as a team coordinator, managing bothhuman and AI agents to ensure task and goal alignment[18]. V. C ONCLUSIONThis system actively monitors team members’ actions, infers The increasing role of AI in engineering education presentstheir plans, and assesses mutual understanding based on pre- a unique opportunity to enhance career competencies, partic
about the features used in the dataset. Theseexplored various methods, from behavioral to neurological features include age, gender, ethnicity, jaundice history,approaches, highlighting gaps in early diagnosis and autism diagnosis, country of residence, prior use of the app,personalized intervention plans. They also discussed the questionnaire results, age description (age range),importance of integrating AI-driven systems to enhance the relationship of the respondent to the participant, and theeffectiveness of ASD treatments. The authors emphasized class/target indicating whether the participant is at risk ofthat future research should focus on creating tailored having ASD. Each row
, no. 1, p. 2232134, Dec. 2023, doi: Joiner, “Case study of virtual reality sepsis 10.1080/10872981.2023.2232134. management- instructional design and ITEM [32] Z. Tacgin, “Immersive virtual reality as an action: outcomes,” J. Vis. Commun. Med., vol. 46, no. 3, pp. measuring approach and learning status of learners after 168–177, Jul. 2023, doi: planning myVOR.,” Educ. Media Int., vol. 57, no. 4, pp. 10.1080/17453054.2023.2280611. 353–371, Dec. 2020, doi:[22] Y. Jeong, H. Lee, and J.-W. Han, “Development and 10.1080/09523987.2020.1848509. evaluation of virtual
mechanisms, are planned. Future System Using Arduino UNO R3 and DHT11 Sensor," in 2020 17th International Computer Conference on Wavelet Active Mediaenhancements will focus on machine learning, weather Technology and Information Processing (ICCWAMTIP), Chengdu,forecasting, and solar-powered off-grid functionality. China, 2020.Future work will focus on enhancing system intelligence [9] Q. Qi and G. J. Brereton, "Mechanisms of removal of micron-sized particles by high-frequency