Paper ID #49250The Shift Towards Inclusion and Accessibility: The Impact of Inclusive Designon UX Career PreparationMs. Taylor Mone Smith, University of Texas at Austin Taylor M Smith is a PhD student in the School of Information at The University of Texas at Austin.Dr. Earl W. Huff Jr., University of Texas at AustinHansika Murugu, University of Maryland, College Park Hansika Murugu is a graduate student pursuing a Master of Science in Human-Computer Interaction at the College of Information at University of Maryland, College Park. ©American Society for Engineering Education, 2025 The Shift Towards
-structured interviews with twofemale and two male Korean undergraduates, three core themes emerged: strong personalinterest in computing, influences of parental beliefs and societal norms limiting female students(particularly affecting female students), and utility of major for future career. Findings show thatwhile personal interest is a primary motivator, gender biases and parental beliefs can redirectfemale students from other STEM fields to CS. Additionally, participants cited dissatisfactionwith Korea’s public education system, and freedom and flexibility with U.S. education asreasons for studying abroad. The study underscores the need for reforms in K-12 computer andcareer education and for addressing gender biases to support informed major
intend to pursue this opportunity. Having contributed inthe past to creative scholarship will make these potential students an ideal recruiting pool for theSFS PIs to enlarge their research groups. In this paper we examine through observations two SFSsites, and how students, if given the opportunity, will engage in research activities. For thosestudents that are involved in research, we conducted an interview, capturing their profile, thebenefits they are observing in their professional development, and their intended careers aftercompleting their service commitment. We report on these results and discuss ways to encouragefurther engagement with SFS scholars for research.Keywords – CyberCorps, Cybersecurity, Scholarships for Service, Student
the IBMSkillBuild program. We are thankful to IBM for providing us with this opportunity. IBM SkillsBuild ProgramIBM SkillsBuild is a free education program focused on underrepresented communities in tech,that helps adult learners and high school and university students and faculty, develop valuablenew skills and access career opportunities. The program includes an online platform that iscomplemented by customized practical learning experiences delivered in collaboration with aglobal network of partners.The open version of IBM SkillsBuild is an online platform which offers over 1,000 courses in 20languages on artificial intelligence, cybersecurity, data analysis, cloud computing and manyother technical
1valuable or very valuable for their career” while 65% say “certifications are the best way toprove knowledge and understanding of concepts” (ISC2, 2024, p. 25). This case study intends to relate the intentional steps taken by a major mid-westernuniversity to incorporate the CompTIA Security+ certification exam topics into anundergraduate, junior-level, Foundations of Cybersecurity semester-long course. The programwas the first offering of the class in a new undergraduate degree in cybersecurity. Theundergraduate degree is housed in the university’s Polytechnic Institute. The institute “focuseson high-demand, advanced and applied technology-based education” (OUPI, 2024). Ebneyaminiet al. (2018) explained that the use of a case study was
value students place on external resources. Thefindings highlight the need for better institutional support, mentorship, and career preparation forCS students, particularly those from underrepresented backgrounds. Additionally, this researchlays the groundwork for future studies on the evolving role of external online education inshaping the academic and professional trajectories of CS students.IntroductionIn recent years, the rapid evolution of technology and the growing demand for computer science(CS) professionals have transformed the educational landscape. As universities strive to preparestudents for the dynamic tech industry, gaps in formal education have become increasinglyevident. These gaps—ranging from insufficient mentorship to a
students to tackle complex projects, often involving interdisciplinary applications infields such as medicine, finance, and environmental science. Graduate students also exploreinnovation and entrepreneurship, examining how AI can disrupt industries and create new businessmodels.Integrating AI into Computer Science (CS) and Information Systems (IS) programs enhancesstudent engagement, proficiency learning outcomes, and career readiness and prepares students toleverage AI responsibly and effectively in the global job market. This paper identifies key AI topicsand proposes how they can be seamlessly integrated into undergraduate and graduate curricula tooptimize learning and achieve critical educational outcomes.Keywords: Artificial Intelligence
talentsurge” as well as the training of the federal workforce on “AI issues. . . as well as relevant policy,managerial, procurement, regulatory, ethical, governance, and legal fields.”Our previous research [5] has found that although some students studying AI are interested incareer paths related to AI policy, only a third of students surveyed thought their computer science(CS) courses adequately prepared them for these career options. This conclusion is supported bya review [6] of computing ethics requirements for 250 CS undergraduate programs worldwide,which found that only one third of programs required students to take a computing ethics coursein order to graduate, while nearly one half of programs did not offer any computing-related
impact their learning the most. The priority of the learning environmentamong the online, in-class, and hybrid learning options, participants choices depended on their lifeconditions that relied on having a family, a part time or full-time job, and availability of thecoursework in the associated environmentKeywords: Cybersecurity education, cybersecurity learning factors, cybersecurity learningenvironments, online learning, in-person learning, hybrid learning, professor, social media, self-study. 1 1. Introduction.Cybersecurity careers are continuing to increase with the demand rate increasing over time. Theanalysis presented in the Cybersecurity
learntechnical writing and that their beliefs are influenced by assessment practices. They believe thattechnical writing is important for their careers and they want to learn technical writing incomputer science courses, however, they perceive that technical writing is not assessed often ordeeply enough and shared that course assessment practices affect the learning activities that theyprioritize.2 IntroductionCommunication skills are integral to professional computer scientists’ success [1], [2], [3]. Thesecommunicative skills and competencies are usually integrated into program learning outcomes,which are assessed via students’ course work; recently, assessment in post-secondary computerscience programs is shifting towards the heavier use of
their 21st century skills with all itemsaveraging above 4.0. They strongly believed in their ability to set their own learning goals, workwith students from different backgrounds and respect the differences of their peers, makechanges when things do not go as planned and produce high quality work.Career Readiness: Students expressed great confidence in their career readiness skills with eachcompetency averaging above 4.0.Persistence: When indicating their intentions to persist in their degree and career, students werevery positive with all items averaging above 4.0 in 2022 and all above 3.75 in 2023. Theystrongly believed they would complete their degree in their current major (M=5.0 in 2022 andM=4.67 in 2023), get a job in the field major (M
Internet of Things, and engineering education. She has published in several peer-reviewed conferences and journals and has been a program committee member at several conferences. ©American Society for Engineering Education, 2025 Active Learning and Specifications Grading for Undergraduate Algorithms and Data Structures coursesAbstractAlgorithms and Data Structures are core concepts taught in all computing undergraduateprograms. It is important to ensure that student activities in the class lay the foundation andprepare them for future courses and career. In addition, assessment should allow for students todevelop a growth mindset. The course may benefit with a grading system can be
from Carnegie Mellon University. He received US National Science Foundation CAREER Award, US Air Force Office of Sponsored Research’s Summer Faculty Fellowship, and Google’s ASPIRE Research award in security and privacy, inter alia. He is an expert in the areas of cybersecurity and privacy. He has hundreds of publications in the most reputable venues as well as numerous patents. His research has been funded by numerous government agencies and industry. He has chaired/served on the of top-tier security conferences, e.g., NDSS, USENIX, ACM CCS, IEEE SP, and serving as the deputy editor in-chief of IEEE TIFS and associate editor of Elsevier COMNET journals. More information can be obtained from http://nweb.eng.fiu.edu
completed a master’s program in Cognitive Science at SNU.ANNE LIPPERT, Prairie View A&M University ©American Society for Engineering Education, 2025 Work in Progress: Improving Engineering Students’ Writing Skills Through a Text Visualization ToolIntroductionDue to the importance of communication skills in the professional engineering field, engineeringcourses have incorporated writing and communication into their curricula [1]. Writing is amultifaceted process requiring critical thinking [2], creativity [3], and synthesis of ideas [4]. Forengineers in research careers, writing activates the cognitive and social processes, allowingstudents aiming for various engineering roles to contribute
flexibility allows learners to progress at their ownpace while accommodating varied schedules. Moreover, virtual learning enables real-timefeedback and peer interactions, essential for mastering intricate OOP concepts.With the primary objective of designing a flexible OO programming course for engineeringstudents that incorporates multiple learning paths based on profile characterization, this paperaims to address the following question: What are the student profiles in an OOP programmingcourse for an online engineering career? To this end, unsupervised learning techniques, such asclustering, were employed to categorize students based on patterns of LMS use behavior andacademic performance associated with an existing instructional design for an
Studies: A Systematic Literature Review.46. Board 150: Systematic Review of the Design Fixation Phenomenon at the K-12 Engineering Education (Other).47. Board 165: K-12 STEM Teachers’ Perceptions of Artificial Intelligence: A PRISMA-tic Approach (Work-in-Progress).48. An Ecosystem Analysis of Engineering Thriving with Emergent Properties at the Micro, Meso, and Macro Levels.49. Unmasking Cognitive Engagement: A Systematized Literature Review of the Relationships Between Students’ Facial Expressions and Learning Outcomes.50. A Systematized Literature Review on Workforce Development Programs for Engineering Graduate Students.51. A Systematized Literature Review of Mental Health and Racial Battle Fatigue in Early- Career Black
, BAE, Raytheon etc.) and private Foundations. Dr. Rawat is the recipient of the US NSF CAREER Award, the US Department of Homeland Security (DHS) Scientific Leadership Award, Presidents’ Medal of Achievement Award (2023) at Howard University, Provost’s Distinguished Service Award 2021, Researcher Exemplar Award 2019 and Graduate Faculty Exemplar Award 2019 from Howard University, the US Air Force Research Laboratory (AFRL) Summer Faculty Visiting Fellowship 2017, Outstanding Research Faculty Award (Award for Excellence in Scholarly Activity) at GSU in 2015, the Best Paper Awards (IEEE CCNC, IEEE ICII, IEEE DroneCom and BWCA) and Outstanding PhD Researcher Award in 2009. He has delivered over 100 Keynotes and
, “Learning two programming languages in one semester does not adversely affect undergraduate biomedical engineering student performance,” presented at the 2017 ASEE Annual Conference & Exposition, Jun. 2017. Accessed: Jul. 17, 2024. [Online]. Available: https://peer.asee.org/learning-two- programming-languages-in-one-semester-does-not-adversely-affect-undergraduate-biomedical-engineering- student-performance[12] R. Rybarczyk and L. Acheson, “Integrating A Career Preparedness Module into CS2 Curricula Through The Teaching C++ and Java Side-by-Side,” in Proceedings of the 49th ACM Technical Symposium on Computer Science Education, Baltimore Maryland USA: ACM, Feb. 2018, pp. 592–597. doi: 10.1145/3159450.3159552.[13] C. L. Resch
, academic planning, and career pathways. Through these info sessions, students receive essential counseling and advisement, equipping them with the knowledge and tools to make informed decisions regarding their educational futures. Moreover, these gatherings provide a platform for students to interact with academic advisors and current students, further demystifying the transfer process and alleviating any associated anxieties. The sessions were offered to students from both CSULA and ELAC, ensuring that prospective transfer students had access to accurate and relevant information regardless of where they were in their academic journey.2.5 Challenge 5: (Both pre- and post-transfer) Lack of community support
. Suining He received the NSF CAREER Award in 2023, Google Research Scholar Program Award and NVIDIA Applied Research Accelerator Program Award in 2021, and two UConn Research Excellence Program (REP) Awards in 2022 and 2020, and held the Google PhD Fellowship in Mobile Computing in 2015, HKUST School of Engineering (SENG) PhD Research Fellowship Award in 2015–2016, and Hong Kong Telecom Institute of Information Technology (HKTIIT) Post-Graduate Excellence Scholarship in 2016. His scholarly works appear in WWW, SenSys, UbiComp, INFOCOM, TKDE, and TMC, and received the IEEE MASS Best Paper Runner-up Award in 2020 and IEEE RTSS Outstanding Paper Award in 2021. He was ranked among the Stanford’s World’s Top 2
. Möhring, and J. Váncza, “Artificial Intelligence in manufacturing: State of the art, perspectives, and future directions,” CIRP Annals, vol. 73, no. 2, pp. 723–749, 2024, doi: 10.1016/j.cirp.2024.04.101.[8] S. J. Russell and P. Norvig, Artificial intelligence: a modern approach. Pearson, 2016.[9] L. Da Xu and L. Duan, “Big data for cyber physical systems in industry 4.0: a survey,” Enterp Inf Syst, vol. 13, no. 2, pp. 148–169, Feb. 2019, doi: 10.1080/17517575.2018.1442934.[10] Z. Slimi, “Systematic Review: AI’s Impact on Higher Education - Learning, Teaching, and Career Opportunities,” Tem Journal, 2023, doi: 10.18421/tem123-44.[11] A. T. Capinding, “Development and Validation of Instruments for Assessing the