Conference Session

Computing and Information Technology Division (CIT) Technical Session 7

Collection

2025 ASEE Annual Conference & Exposition

Authors

Yu-Zheng Lin, The University of Arizona; Karan Patel, The University of Arizona; Ahmed H Alhamadah, The University of Arizona; Sujan Ghimire, The University of Arizona; Jesus Pacheco; Banafsheh Saber Latibari, The University of Arizona; Soheil Salehi, The University of Arizona; Pratik Satam, University of Arizona

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology Division (CIT)

Inspection Training Group 1 (w/o Adaptive Mechanism) Group 2 (w/ Adaptive Mechanism) Participants 22 6 Samples 82 72 Statistic Time Taken (s) Hits Percentage Time Taken (s) Hits Percentage x) Mean (¯ 68.93 78 % 48.94 83 % Standard Deviation (σ) 34.93 17 % 23.89 14 % Minimum Value (xmin ) 27.00 25 % 10.00 50 % Maximum Value (xmax ) 208.00 100

Conference Session

Computing and Information Technology Division (CIT) Poster Session

Collection

2025 ASEE Annual Conference & Exposition

Authors

Yug Patel, Missouri University of Science and Technology; Sanjana Shangle, University of Texas at Dallas; Asir Abrar, Missouri University of Science and Technology; Venkata Sriram Siddhardh Nadendla, Missouri University of Science and Technology; K Krishnamurthy, Missouri University of Science and Technology

Tagged Divisions

Computing and Information Technology Division (CIT)

consolidate all data into a database for comprehensiveanalysis.CASE STUDY: GENERATED PILOT EXPERIMENTS AND DATA COLLECTION PLANThe testbed has been validated by generating three pilot experiments. These pilot experimentsare designed using parameters depicted in figures 4 and 5 for both N -back tasks and MOT taskrespectively. Each of these pilot experiments comprises of R runs, where each run contains T trialsand each trial has S sub-trials. The participant performs any given task once in every sub-trial. Inthe case of both N -back pilot experiments, we chose R = 3, T = 9 and S = 20. Furthermore,the value of N is also varied randomly between 1 and 3 (i.e. N = 1 for low workload, N = 2 formedium workload, and N = 3 for high workload) across trials to

Conference Session

Computing and Information Technology Division (CIT) Poster Session

Collection

2025 ASEE Annual Conference & Exposition

Authors

Utsab Khakurel, Howard University; Danda B Rawat, Howard University

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology Division (CIT)

(Figure 27) represents a male passenger who survived despite gender being a negativefactor in the model’s prediction. His high Pclass and fare ($35.5) played a crucial role inincreasing his survival probability. The cumulative SHAP value graphs (Figs. 28, 29) furtherhighlight these trends by selecting the few vital causes from the trivial many, showing thatinstance 3’s survival was driven by gender, wealth, and class, aligning with historical data where75% of women survived compared to only 19% of men. On the other hand, instance 55 survivedsolely due to his high social class, with gender contributing the least to his survival.3 Evaluation and FindingsIn this section, we evaluate the effectiveness of the DARE-AI labs through surveys conducted

Conference Session

Computing and Information Technology Division (CIT) Technical Session 7

Collection

2025 ASEE Annual Conference & Exposition

Authors

Ismael Villegas Molina, University of California, San Diego; Audria Nikitza Montalvo, University of California, San Diego; Benjamin Ochoa, University of California, San Diego; Paul Denny, University of Auckland; Leonard Porter, University of California, San Diego

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology Division (CIT)

resource for NNES studentsin computer science education, providing tailored support that enhances their learning experience and overcomes languagebarriers. R EFERENCES [1] V. Agarwal, Y. Chuengsatiansup, E. Kim, Y. LYu, and A. G. Soosai Raj, “An analysis of stress and sense of belonging among native and non-native english speakers learning computer science,” in Proceedings of the 53rd ACM Technical Symposium on Computer Science Education-Volume 1, 2022, pp. 376–382. [2] S. Alaofi and S. Russell, “A validated computer terminology test for predicting non-native english-speaking cs1 students’ academic performance,” in Australasian Computing Education Conference, 2022, pp. 133–142. [3

Conference Session

Computing and Information Technology Division (CIT) Technical Session 8

Collection

2025 ASEE Annual Conference & Exposition

Authors

Juan Felipe Calderón, Universidad Andres Bello, Viña del Mar, Chile; Matias Isaac Vargas

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology Division (CIT)

flexibility engine within the LMSand adjustments to the underlying framework to facilitate adaptability in the dynamic assignmentof materials, tasks, and evaluations, utilizing a more extensive cluster model encompassing abroader spectrum of student characteristics.References[1] S. Park, “Analysis of Time-on-Task, Behavior Experiences, and Performance in Two Online Courses With Different Authentic Learning Tasks,” The International Review of Research in Open and Distributed Learning, 2017, doi: 10.19173/irrodl.v18i2.2433.[2] Z. Zen, Reflianto, Syamsuar, and F. Ariani, “Academic Achievement: The Effect of Project-Based Online Learning Method and Student Engagement,” Heliyon, 2022, doi: 10.1016/j.heliyon.2022.e11509.[3] S. B

Conference Session

Computing and Information Technology Division (CIT) Poster Session

Collection

2025 ASEE Annual Conference & Exposition

Authors

Mengyuan Liu, Northeastern University; Jeongkyu Lee, Northeastern University

Tagged Divisions

Computing and Information Technology Division (CIT)

will enable students to visually exploreand interact with muscle segmentation processes, including keypoint selection, boundarytracking, and 3D reconstruction. This hands-on approach aims to foster a deeper, more intuitiveunderstanding of the algorithm’s functionality and its practical application in real-world medicalimaging scenarios.AcknowledgmentThis project was funded in part by the Northeastern TIER 1 seed grant.References [1] J. Zhu, B. Bolsterlee, B. V. Chow, C. Cai, R. D. Herbert, Y. Song, and E. Meijering, “Deep learning methods for automatic segmentation of lower leg muscles and bones from mri scans of children with and without cerebral palsy,” NMR in Biomedicine, vol. 34, no. 12, p. e4609, 2021. [2] R. Ni, C. H. Meyer, S. S

Conference Session

Computing and Information Technology Division (CIT) Technical Session 4

Collection

2025 ASEE Annual Conference & Exposition

Authors

Jason M. Keith, Iowa State University of Science and Technology; Amin Amirlatifi, Mississippi State University; Sudip Mittal, Mississippi State University; Subash Neupane, Mississippi State University; HIMANSHU TRIPATHI, Mississippi State University

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology Division (CIT)

cybersecurity and digital forensics). Further iterations of the chatbot will focus onimproving its ability to facilitate collaborative learning, assist with project-based assessments,and provide actionable feedback to students and instructors.References[1] Maderer, J. “Artificial Intelligence Course Creates AI TeachingAssistant,”https://news.gatech.edu/news/2016/05/09/artificial-intelligence-course-creates-ai-teaching-assistant, May 2016, accessed January 2025.[2] Chopra, S., Gianforte, R., and Sholar, J. “Meet Percy: The CS 221 Teaching AssistantChatbot,” ACM Transactions on Graphics, Vol. 1 (1), December 2016.[3] Lluna, A. P. “Creation and Development of an AI Teaching Assistant,” Master’s Thesis,Universitat Politecnica de Catalunya, 2017/2018.[4

Conference Session

Computing and Information Technology Division (CIT) Technical Session 6

Collection

2025 ASEE Annual Conference & Exposition

Authors

Gabriel Eduardo Prieto, Florida International University; Neila Bennamane, Florida International University; Agoritsa Polyzou, Florida International University; Peter J Clarke, Florida International University

Tagged Divisions

Computing and Information Technology Division (CIT)

described in Section 3.1. The extra credit points from SEP-CyLE were computed as apercentage ratio of the student(s) with the highest number of virtual points. The student(s) withthe most virtual points received 3% extra credit course points.The grades for each course project deliverable consist of four components: presentation (21%),demonstration (12.6%), documentation (50.4%), and peer evaluation (16%). The peer evaluationconsists of the members of a team grading each other using a peer evaluation rubric provided bythe instructor. The rubric includes four criteria: Helping - assistance provided by a team memberto other team members, Participating - contribution and attendance by a team member at teammeetings, Questioning - the level at which the

Conference Session

Computing and Information Technology Division (CIT) Technical Session 10

Collection

2025 ASEE Annual Conference & Exposition

Authors

Donggil Song, Texas A&M University; ANNE LIPPERT, Prairie View A&M University

Tagged Divisions

Computing and Information Technology Division (CIT)

with validity and reliability checks [10], which is based onFischer, Bruhn, Gräsel and Mandl [11]’s framework. For example, the Evaluating category ismeasured on a scale from 1 (Minimally determined the significance or relevance of informationneeded for the writing task) to 5 (Completely determined the significance or relevance ofinformation needed for the writing task). When scoring student work in this category, studentsreceive high scores if they identify and articulate the most relevant and significant informationfor their argument. For instance, when discussing a principle of network security, one studentcorrectly highlighted the most relevant and significant aspect: “… confidentiality can beachieved through encryption, access controls

Conference Session

Computing and Information Technology Division (CIT) Poster Session

Collection

2025 ASEE Annual Conference & Exposition

Authors

Hyeree Cho, Purdue Polytechnic Institute, Purdue University – West Lafayette; Woongbin Park, Purdue University at West Lafayette

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology Division (CIT)

without thedominance of societal biases.References[1] T. Camp, W. R. Adrion, B. Bizot, S. Davidson, M. Hall, S. Hambrusch, E. Walker and S. Zweben, “Generation CS: The growth of computer science,” ACM Inroads, vol. 8, no. 2, pp. 44–50, May 2017. [Online]. Available: https://doi:10.1145/3084362. [Accessed Jan 14, 2025].[2] T. G. Zimmerman, D. Johnson, C. Wambsgans and A. Fuentes, “Why latino high school students select computer science as a major,” ACM Trans. Comput. Educ., vol. 11, no. 2, pp. 1–17, Jul. 2011. [Online]. Available: https://doi:10.1145/1993069.1993074. [Accessed Jan 14, 2025].[3] S. R. Roy, “Educating Chinese, Japanese, and Korean international students: Recommendations to American professors

Conference Session

Computing and Information Technology Division (CIT) Technical Session 10

Collection

2025 ASEE Annual Conference & Exposition

Authors

Abdulmalek Al-Gahmi, Weber State University

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology Division (CIT)

models throughout theentire semester in a production setting is outlined. Such models and processes can be crucial forhigher education institutions in providing timely support to struggling students, therebyimproving learning outcomes and student retention.Bibliography[1] R. Umer, A. Mathrani, T. Susnjak and S. Lim, "Mining Activity Log Data to Predict Student'sOutcome in a Course," in Proceedings of the 2019 International Conference on Big Data andEducation, New York, NY, USA, 2019.[2] S. V. Goidsenhoven, D. Bogdanova, G. Deeva, S. v. Broucke, J. D. Weerdt and M. Snoeck,"Predicting Student Success in a Blended Learning Environment," New York, NY, USA:Association for Computing Machinery, 2020.[3] P. Shayan and M. v. Zaanen, "Predicting Student

Conference Session

Computing and Information Technology Division (CIT) Technical Session 4

Collection

2025 ASEE Annual Conference & Exposition

Authors

Claire Han; Abel Andres Reyes-Angulo, Michigan Technological University; Sidike Paheding, Fairfield University

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology Division (CIT)

flexible choice for applicationslike cookie classification and wildcard matching in cybersecurity.3.3.3 Flan-T5Flan-T5 is an enhanced version of the T5 model that incorporates instruction fine-tuning 15 . By training on a mixture of tasks phrasedas instructions, Flan-T5 improves its ability to follow task descriptions and generalize to new tasks. This makes Flan-T5 particularlyeffective in zero-shot and few-shot learning scenarios, where the model needs to perform well on tasks it has not explicitly beentrained on. In the context of identifying wildcard matches in cookies, Flan-T5’s improved understanding of instructions can lead tomore accurate and reliable classification results.4 Results4.1 Experimental SetupThe experimental

Conference Session

Computing and Information Technology Division (CIT) Technical Session 8

Collection

2025 ASEE Annual Conference & Exposition

Authors

Juan Felipe Calderón, Universidad Andres Bello, Viña del Mar, Chile; Marco Aguilera; Martin Ignacio Gil; Maria Elena Truyol, Universidad Andres Bello, Santiago, Chile; Danilo Leal, Universidad Andres Bello; Claudia Bascur, Universidad Andres Bello, Santiago, Chile

Tagged Divisions

Computing and Information Technology Division (CIT)

in education andopens the door to new opportunities for personalization and adaptability in virtual environments.Integrating advanced technologies with robust pedagogical approaches is essential to transformteaching and learning in the digital age.References[1] S. Martín, E. López-Martín, A. Moreno-Pulido, R. Meier, and M. Castro, “A Comparative Analysis of Worldwide Trends in the Use of Information and Communications Technology in Engineering Education,” Ieee Access, 2019, doi: 10.1109/access.2019.2935019.[2] O. Kuzu, “Digital Transformation in Higher Education: A Case Study on Strategic Plans,” Vysshee Obrazovanie v Rossii = Higher Education in Russia, 2020, doi: 10.31992/0869-3617-2019-29-3- 9-23.[3] B. R. Aditya

Conference Session

Computing and Information Technology Division (CIT) Technical Session 2

Collection

2025 ASEE Annual Conference & Exposition

Authors

Prarthona Paul, University of Toronto; Chirag Variawa, University of Toronto

Tagged Divisions

Computing and Information Technology Division (CIT)

education, ultimately preparing students for a rapidly evolvingtechnological landscape.References[1] M. R. Chavez, T. S. Butler, P. Rekawek, H. Heo and W. L. Kinzler, "Chat Generative Pre-trained Transformer: why we should embrace this technology," American Journal of Obstetrics and Gynecology, vol. 228, no. 6, pp. 706-711, 2023.[2] G. Debjania and J.-B. Souppeza R. G., "Generative AI In Engineering Education," in UK and Ireland Engineering Education Research Network Annual Symposium, Belfast, 2024.[3] A. Johri, A. S. Katz, J. Qadir and A. Hingle, "Generative artificial intelligence and engineering education," Journal of Engineering Education, vol. 112, no. 3, p. 572–577, 2023.[4] D. De Silva, O. Kaynak, M. El-Ayoubi, N. Mills, D

Conference Session

Computing and Information Technology Division (CIT) Technical Session 8

Collection

2025 ASEE Annual Conference & Exposition

Authors

Danushka Bandara, Fairfield University; Djedjiga Belfadel, Fairfield University

Tagged Divisions

Computing and Information Technology Division (CIT)

, limiting insights into how undergraduate students orthose in other disciplines might experience redesigned assessments. The short-term focus of the studyalso means that long-term impacts on learning and skill retention remain unexplored. Additionally,studies could examine the impact of redesigned assessments on instructor workload, studentengagement, and equity and accessibility, ensuring that innovative assessment practices benefit alllearners.ReferencesAnthropic. (2024). Claude [Large language model]. https://www.anthropic.com/Google. (2024). Gemini [Large language model]. https://gemini.google.com/Huang, A. Y. Q., Lu, O. H. T., & Yang, S. J. H. (2023). Effects of artificial intelligence–enabledpersonalized recommendations on learners

Conference Session

Computing and Information Technology Division (CIT) Technical Session 5

Collection

2025 ASEE Annual Conference & Exposition

Authors

Caroline Crockett, University of Virginia

Tagged Divisions

Computing and Information Technology Division (CIT)

and curriculum developers select the correct learning goals and activities for theirspecific student population.References [1] S. Isaac Flores-Alonso, N. V. M. Diaz, J. Kapphahn, et al., “Introduction to AI in under- graduate engineering education,” in 2023 IEEE Frontiers in Education Conference (FIE), College Station, TX, USA: IEEE, Oct. 18, 2023, pp. 1–4, ISBN: 9798350336429. DOI: 10.1109/FIE58773.2023.10343187. [2] S. Khorbotly, “Machine learning: An undergraduate engineering course,” in 2022 ASEE Illinois-Indiana Section Conference Proceedings, Anderson, Indiana: ASEE Conferences, Apr. 2022, p. 42 132. DOI: 10.18260/1-2--42132. [3] R. DeMara, A. Gonzalez, A. Wu, et al., “A crcd experience: Integrating machine learning

Conference Session

Computing and Information Technology Division (CIT) Technical Session 5

Collection

2025 ASEE Annual Conference & Exposition

Authors

James Weichert, Virginia Polytechnic Institute and State University; Hoda Eldardiry, Virginia Polytechnic Institute and State University

Tagged Divisions

Computing and Information Technology Division (CIT)

. For example, Scenario 3 on‘general-purpose’ AI is inspired by the EU AI Act’s requirement [28] that proprietors of ‘generalpurpose’ AI systems report details about model architecture and training processes to national AIauthorities. Each scenario, along with the proposed AI regulations that Congress can vote on, aredescribed in Appendix B. To start the game, only members of Evil Inc. are told internal companyinformation that motivates their lobbying efforts. For example: “Evil Inc.’s large language modelis only successful because its model architecture is kept a secret, so Evil Inc. should preventCongress from requiring the disclosure of any model architecture information.” Each round, EvilInc. members decide how to distribute a limited

Conference Session

Computing and Information Technology Division (CIT) Technical Session 1

Collection

2025 ASEE Annual Conference & Exposition

Authors

Mudasser Fraz Wyne, National University; Alireza Farahani, National University; Lu Zhang, National University

Tagged Divisions

Computing and Information Technology Division (CIT)

Conference Session

Computing and Information Technology Division (CIT) Technical Session 1

Collection

2025 ASEE Annual Conference & Exposition

Authors

Christopher Freeze, The University of Oklahoma

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology Division (CIT)

many as possible rather than to screen [out allbut the best academic students].” Towhidi and Pridmore’s (2023) research underscores the finding that incorporatingindustry certifications is not considered a panacea while Ouh and Shim (2021) explained thatintegrating certifications into a curriculum required an intentional, purposeful, and well-thought-out approach that benefited students, faculty, and industry and, as such, the public. Further,industry organizations regularly seek well-rounded employees of which certifications are simplyone part of the whole. For example, Tran et al. (2023) identified three hiring criteria amongorganizations seeking to hire cybersecurity graduates: 1) an academic degree, 2) professionalcertification(s

Conference Session

Computing and Information Technology Division (CIT) Poster Session

Collection

2025 ASEE Annual Conference & Exposition

Authors

Amanda Nicole Smith, University of Florida; Sage Bachus, University of Florida; Ashish Aggarwal, University of Florida

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology Division (CIT)

. Communications in Computer and Information Science, H. Florez and H. Astudillo, Eds. Springer, Cham, 2025, vol. 2237, accessed: 21-Oct-2024. [Online]. Available: https://doi.org/10.1007/978-3-031-75147-9 4 [3] K. Shah, P. Lee, D. Barretto, and S. N. Liao, “A qualitative study on how students interact with quizzes and estimate confidence on their answers,” in Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education V. 1, ser. ITiCSE ’21. New York, NY, USA: Association for Computing Machinery, 2021, p. 32–38. [Online]. Available: https://doi.org/10.1145/3430665.3456377 [4] S. N. Liao, “Early identification of at-risk students and understanding their behaviors,” Ph.D. dissertation, UC San

Conference Session

Computing and Information Technology Division (CIT) Technical Session 7

Collection

2025 ASEE Annual Conference & Exposition

Authors

Christine Allain Roach, Texas A&M University

Tagged Divisions

Computing and Information Technology Division (CIT)

. Kay, "Review: Exploring the use of video podcasts in education: A comprehensive review ofthe literature," Computers in Human Behavior, 2012.[3] N. I. Scagnoli, J. Choo, and J. Tian, "Students' insights on the use of video lectures in onlineclasses," British Journal of Educational Technology, 2019.[4] M. E. Haagsman et al., "Pop-up Questions Within Educational Videos: Effects on Students'Learning," Journal of Science Education and Technology, 2020.[5] N. Singh, S. Getenet, and E. Tualaulelei, "Examining students' behavioral engagement in lecturevideos with and without embedded quizzes in an online course," ASCILITE Publications, 2023.[6] E. Jung and G. Snow, "Using Panopto In-Video Quizzes for Online Education," eLearn, 2023.[7] N. Mirriahi et

Conference Session

Computing and Information Technology Division (CIT) Technical Session 5

Collection

2025 ASEE Annual Conference & Exposition

Authors

Neda Farahmandi, University of Massachusetts Dartmouth; Ashok Patel, University of Massachusetts Dartmouth

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology Division (CIT)

Conference Session

Computing and Information Technology Division (CIT) Technical Session 10

Collection

2025 ASEE Annual Conference & Exposition

Authors

Nikunja Swain, South Carolina State University; Biswajit Biswal, South Carolina State University; Janmejay Mohanty, South Carolina State University

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology Division (CIT)

]. Available: https://www.cyberseek.org/heatmap.html[6] M. Ismail, N. T. Madathil, M. Alalawi, S. Alrabaee, M. A. Bataineh, S. Melhem, and D. Mouheb, “Cybersecurity activities for education and curriculum design: A survey,” Computers in Human Behavior Reports,Volume 16, 2024, 100501,ISSN 2451-9588, https://doi.org/10.1016/j.chbr.2024.100501.[7] N. A. A. Rahman, I. H. Sairi, N. A. M. Zizi, & F. Khalid, “The Importance of Cybersecurity Education in School,” International Journal of Information and Education Technology, Vol. 10, No. 5, May 2020.[8] SIDDHANT MISHRA (2024). Integrating Cybersecurity Education into the Curriculum: Best Practices and Implementation Challenges. [Online] Available: https://www.researchgate.net

Conference Session

Computing and Information Technology Division (CIT) Poster Session

Collection

2025 ASEE Annual Conference & Exposition

Authors

Marjan Asadinia, California State University, Northridge; Sherrene Bogle, California Polytechnic State University Humboldt ; Rowena Quinn

Tagged Divisions

Computing and Information Technology Division (CIT)

expressed in this paper are those of the authors anddo not necessarily reflect the views of the NSF.References [1] A. Ehrmann, T. Blachowicz, G. Ehrmann, and T. Grethe, “Recent developments in phase- change memory,” Applied Research, Jun. 2022, doi: https://doi.org/10.1002/appl.202200024. [2] R. Azevedo, J. D. Davis, K. Strauss, P. Gopalan, M. Manasse, and S. Yekhanin, “Zombie memory: Extending memory lifetime by reviving dead blocks,” in Proceedings of the Inter- national Symposium on Computer Architecture (ISCA), 2013. [3] H. Luo et al., “Write Energy Reduction for PCM via Pumping Efficiency Improvement,” ACM Transactions on Storage, vol. 14, no. 3, pp. 1–21, Aug. 2018. [4] J. Fan, S. Jiang, J. Shu, Y. Zhang, and W. Zhen

Conference Session

Computing and Information Technology Division (CIT) Technical Session 3

Collection

2025 ASEE Annual Conference & Exposition

Authors

Mahima Agumbe Suresh, San Jose State University

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology Division (CIT)

objectives mapped to eachquestion. Occassionaly, if the questions were phrased in a confusing manner, thresholds werereduced. Overall, the cutoffs were consistent with traditional grading letter grade cutoffs.Programming exams contained specifications similar to lab assignments (as described below),with tasks summing up to particular letter grades.Example specifications for a lab assignmentTask 1. Padovan Sequence:[LP] Part 1: In a file called Padovan.txt, write the pseudocode to recursively compute the nthPadovan number . A padovan number is an extension to the Fibonacci series that is defined by therelation: P(n) = P(n-2) + P(n-3). P(0)=P(1)=P(2)=1. Clearly state your base case(s).[LP] Part 2: Implement the pseudocode in a function called unsigned

Conference Session

Computing and Information Technology Division (CIT) Technical Session 7

Collection

2025 ASEE Annual Conference & Exposition

Authors

Ashish Kharel, The University of Toledo; Ahmad Y Javaid, The University of Toledo; Quamar Niyaz, Purdue University Northwest; Sidike Paheding, Fairfield University; Devinder Kaur, The University of Toledo

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology Division (CIT)

? What are some challenges of implementing secure embedded systems? How confident are you in your ability to identify and fix vulnerabilities in embedded system s/w? How confident are you in your ability to secure embedded systems from cyberattacks?Knowledge What aspects of cybersecurity for embedded systems do you feel most comfortable with?Improvement What aspects of cybersecurity for embedded systems do you feel least comfortable with? How can this lab be improved to help students learn more about cybersecurity for embedded systems? (Only Post-Lab Survey) 2. Reading Material:  Purpose: The reading material titled "Cybersecurity Fundamentals for Embedded Systems" is provided

Conference Session

Computing and Information Technology Division (CIT) Technical Session 3

Collection

2025 ASEE Annual Conference & Exposition

Authors

Nestor L. Osorio, Northern Illinois University; Abul K. M. Azad, Northern Illinois University

Tagged Divisions

Computing and Information Technology Division (CIT)

scholarly production: How great is the impact?" Scientometrics, vol. 105, pp. 1809–1831, 2015.7. R. Thomopoulos, S. Destercke, B. Charnomordic, I. Johnson, and J. Abécassis, "An iterative approach to build relevant ontology-aware data-driven models," Information Sciences, vol. 221, pp. 452-472, 2013.8. N.F. Noy and D.L. McGuinness, "Ontology development 101: A guide to creating your first ontology," Stanford University, 2001. [Online]. Available: https://corais.org/sites/default/files/ontology_development_101_aguide_to_creating_your_fir st_ontology.pdf9. A.L.A. Menolli, H.S. Pinto, S.S. Reinehr, and A. Malucelli, "An incremental and iterative process for ontology building," in ONTOBRAS, Proceedings of the 6th Seminar on Ontology

Conference Session

Computing and Information Technology Division (CIT) Technical Session 3

Collection

2025 ASEE Annual Conference & Exposition

Authors

Roberto Patricio Carú, Universidad Andres Bello; Juan Felipe Calderón, Universidad Andres Bello, Viña del Mar, Chile

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology Division (CIT)

points, with Group 1's average being5.81 and Group 2's being 4.91. This indicates that, on average, Group 1 achieved higher gradesthan Group 2.Applying ANOVA to compare performance (final grade) between Group 1 and Group 2 yieldsan F-statistic value of 116.8963 and a p-value of approximately 7.411684e-13. The p-value isextremely low (much lower than any standard significance threshold, such as 0.05), indicating astatistically significant difference between the two groups' final grades. This suggests thatacademic performance (measured by final grade) significantly differs between Group 1 andGroup 2.Analysis of Students' Work ExperienceBoth groups belong to the evening session, mainly consisting of students working during the day.Additionally

Conference Session

Computing and Information Technology Division (CIT) Technical Session 6

Collection

2025 ASEE Annual Conference & Exposition

Authors

Derin Cayir, Florida International University; Mark Allen Weiss, Florida International University; Selcuk Uluagac, Florida International University

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology Division (CIT)

smart home networks. In NDSS, 2022. [8] Leonardo Babun, Amit Kumar Sikder, Abbas Acar, and A Selcuk Uluagac. The truth shall set thee free: Enabling practical forensic capabilities in smart environments. In NDSS, 2022. [9] Derin Cayir, Reham Mohamed, Riccardo Lazzeretti, Marco Angelini, Abbas Acar, Mauro Conti, Z Berkay Celik, and Selcuk Uluagac. Speak up, i’m listening: Extracting speech from zero-permission vr sensors. In NDSS, 2025.[10] H. Maenpaa, S. Varjonen, A. Hellas, S. Tarkoma, and T. Mannisto. Assessing iot projects in university education - a framework for problem-based learning. In 2017 IEEE/ACM 39th International Conference on Software Engineering: Software Engineering Education and Training Track (ICSE-SEET

Conference Session

Computing and Information Technology Division (CIT) Technical Session 2

Collection

2025 ASEE Annual Conference & Exposition

Authors

Peng Li, East Carolina University; Sohan Gyawali, East Carolina University

Tagged Divisions

Computing and Information Technology Division (CIT)

programmingassignments," Computer Science Education, vol. 15, no. 2, pp. 83–102, 2005. doi:10.1080/08993400500150747.[2] C. Douce, D. Livingstone, and J. Orwell, "Automatic test-based assessment of programming:A review," Journal on Educational Resources in Computing (JERIC), vol. 5, no. 3, pp. 4–es,2005. doi: 10.1145/1163405.1163409.[3] P. Li and L. Toderick, "An automatic grading and feedback system for e-learning ininformation technology education," in Proc. 2015 ASEE Annu. Conf. & Expo., Seattle, WA,USA, 2015, pp. 26.179.1–26.179.11. [Online]. Available: https://peer.asee.org/23518[4] C. L. Hull, "Simple trial and error learning: A study in psychological theory," PsychologicalReview, vol. 37, no. 3, pp. 241–256, 1930. doi: 10.1037/h0073614.[5] S. H