Paper ID #41983Gauging Scholarly Engagement: An Investigation into Topic Popularity withinthe ASEE CIT DivisionDr. Barry M. Lunt, Brigham Young University Dr. Barry Lunt has taught electronics engineering technology, information technology, and cybersecurity at Brigham Young University since 1993 where he now serves as a full professor in the Department of Electrical and Computer Engineering. He has also taught electronics at Utah State University and Snow College. Before academia, he was a design engineer with IBM in Tucson, AZ.Dr. Mudasser Fraz Wyne, National University I hold a Ph.D. in Computer Science, an M.Sc. in
(ICACIT), IEEE, 2019, pp. 1–4.[8] O. Saidani, L. J. Menzli, A. Ksibi, N. Alturki, and A. S. Alluhaidan, “Predicting student employability through the internship context using gradient boosting models,” IEEE Access, vol. 10, pp. 46472–46489, 2022.[9] S. Mchugh, K. Quille, L. Carmody, and K. Nolan, “Developing an On-Campus Internship Model for Computing Students-An Alternative Experiential Learning Pathway,” presented at the Proceedings of the 2022 Conference on United Kingdom & Ireland Computing Education Research, 2022, pp. 1–7.[10] N. Kumar et al., “Factors Affecting the Future Career Pathway Decisions of Lower-income Computing Students,” presented at the 2023 ASEE Annual Conference & Exposition, 2023.[11] İ
, Autonomous Systems, and Control and Automation. Dr. Luo is an IEEE senior member, INFORMS, and ASEE member. Dr. Luo is active nationally and internationally in his research field. He was the Program Co-Chair in 2018 IEEE International Conference on Information and Automation (IEEE-ICIA’2018). He was the Plenary Session Co-Chair in the 2021 and 2019 International Conference on Swarm Intelligence, and he was the Invited Session Co-Chair in the 2017 International Conference on Swarm Intelligence. He was the General Co-Chair of the 1st IEEE International Workshop on Computational Intelligence in Smart Technologies (IEEE-CIST 2015), and Journal Special Issues Chair, IEEE 2016 International Conference on Smart Technologies
instructors. Furthermore, it discusses the challenges associated with working with this inherently unbalanced data. ● It enhances the existing models with new features related to specific course events, such as missing assignments, making late submissions, or failing individual assignments. ● It conducts numerous experiments, training a variety of machine learning models using the augmented data to evaluate their portability and the robustness of their predictions.Data AcquisitionThe data analyzed in this paper comprises 10 required lower-division CS courses taught over aspan of three years, from Spring 2019 to Summer 2022, catering to students pursuing theirassociate CS degrees within the same timeframe. Across these courses
Anwar, Texas A&M University Saira Anwar is an Assistant Professor at the Department of Multidisciplinary Engineering, Texas A and M University, College Station. She received her Ph.D. in Engineering Education from the School of Engineering Education, Purdue University, USA. The Department of Energy, National Science Foundation, and industry sponsors fund her research. Her research potential and the implication of her work are recognized through national and international awards, including the 2023 NSTA/NARST Research Worth Reading award for her publication in the Journal of Research in Science Teaching, 2023 New Faculty Fellow award by IEEE ASEE Frontiers in Education Conference, 2022 Apprentice Faculty Grant
employment in an industry anxious for employees. The UtahDepartment of Workforce job forecasts and other job trends surveys indicate that while thesestudents can earn strong salaries without degrees, their careers will not advance as they wouldwith degrees [5]. Employers are also feeling the disadvantage of too few job candidates with theadequate training provided by a baccalaureate degree [6]. The lack of adequate number ofscholarships in Computer Science and Engineering programs is a significant inhibitor ingraduating and enrolling more students. Program Enrollment Numbers 2017-2018 2018-2019 2019-2020
published papers | Research Project winner! Education: BE in Mechanical Engineering MBA in Information Technology MS in Computer Science (IP) My paper is accepted for 2024 ASEE Southeastern Section Conference, Marietta, GA, March 10 - 12, 2024. Research interests: 1. Meditation 2. Music 3. AI Hackathons: 1. INTEL AI Hackathon FIRST prize Winner! 2. Llama 2 ClarifAI LablabAI hackathon SECOND prize winner! Published papers: Peer-reviewed Published papers: 1. FIE 2023 IEEE conference, Texas, USA: EEG Spectral Analysis and Prediction for Inattention Detection in Academic Domain 2. AIMC 2023, Brighton, UK: Introductory Studies on Raga Multi-track Music Generation of Indian classical music using AI. 3. ASEE
Academy of Sciences, 117(12):6476–6483, 2020. [8] Ang´elica Burbano, Katherine Ortegon, Silvia Guzman, and Henry Arley Taquez Quenguan. Active learning: Faculty mind-sets and the need for faculty development. In 2019 ASEE Annual Conference & Exposition, 2019. [9] Michael Prince. Does active learning work? a review of the research. Journal of engineering education, 93(3): 223–231, 2004.[10] Charles C Bonwell and James A Eison. Active learning: Creating excitement in the classroom. school of education and human development, george washington university, 1991.[11] Jim Eison. Using active learning instructional strategies to create excitement and enhance learning. Jurnal Pendidikantentang Strategi Pembelajaran Aktif (Active
. Zavala, and J. F. Calderón, “Student response to instructional practices (StRIP) survey in engineering classrooms: Validating a Spanish version,” in 2020 ASEE Virtual Annual Conference Content Access, 2020.[5] M. L. Kovarik, J. K. Robinson, and T. J. Wenzel, “Why Use Active Learning? In Active Learning in the Analytical Chemistry Curriculum,” American Chemical Society, 2022, pp. 1–12.[6] L. Deslauriers, L. S. McCarty, K. Miller, K. Callaghan, and G. Kestin, “Measuring actual learning versus the feeling of learning in response to being actively engaged in the classroom,” Proceedings of the National Academy of Sciences, p. 116(39), 2019.[7] H. J. Cho, K. Zhao, C. R. Lee, D. Runshe, and C. Krousgrill, “Active learning
as a software engineer at Sina for one year after I graduated as a master from China Agriculture University in 2009. He received the Best Paper Award from IEEE Edge in 2019.Jin Lu, University of Georgia Jin Lu received his Ph.D. degree in computer science and engineering from the University of Connecticut, USA in 2019. He worked as an assistant professor at the University of Michigan - Dearborn from 2019 to 2023. He is currently an assistant professor at the School of Computing at the University of Georgia. My major research interests include machine learning, data mining, and optimization. I am particularly interested in transparent machine learning models, distributed learning algorithms, optimization and so