Google(previously Conversational Writing assistance, content generation, Q&A DeepMindBard)Perplexity Conversational Information retrieval, Q&A, search assistance Perplexity AIClaude Conversational Writing assistance, summarization, Q&A Anthropic Content generation, summarization, chatbotLlama Conversational Meta integrationJasper Jasper AI(previously
study was to answer the question: Does theuse of the GraySim CPU simulator improve student learning? We use student performance on anexam as our measure of student learning. We collected exam responses from two sample groups:a group of students who did not have access to GraySim while taking OS and a group who did.We conducted a two-proportion z-test [14] for each tested scheduling policy: FIFO, RR withquantum q = 2, STCF, and MLFQ. (Note that SJF was not tested on the exam.) We used twohypotheses for each scheduling policy, where X is FIFO, RR, STCF, and MLFQ: • H0 : The students’ performance with the X scheduling policy with access to GraySim is the same as the students’ performance before using the simulator. • H1 : The students
that staff are comfortable negotiating appropriate recognition for their participation in any published output from the research that is conducted. References[1] W. A. Townsend et al., “A competency framework for librarians involved in systematic reviews,” J. Med. Libr. Assoc., vol. 105, no. 3, Jul. 2017, doi: 10.5195/jmla.2017.189.[2] Q. E. Wafford and L. C. O’dwyer, “Adopting a toolkit to manage time, resources, and expectations in the systematic review process: A case report,” J. Med. Libr. Assoc., vol. 109, no. 4, pp. 637–642, 2021, doi: 10.5195/jmla.2021.1221.[3] S. K. D. Smith, K. Burton, and S. Carroll, “Acting in self-defense: The creation of an online systematic review tutorial to assist
ofapproaches are used in a complementary manner, with both strong theoreticalfoundations and a focus on practical application. The course employs a combination ofoffline lectures, MOOC viewing, site visits, Q&A interactions, and group discussionsand presentations, integrating theory with practice and fostering ample interactionbetween teachers and students. In terms of course assessment, a multi-dimensionalapproach is adopted, with both the transmission of knowledge and the cultivation ofabilities moving in the same direction. The assessment method combines formativeassessment, group discussions, and a final paper.Methods: A combination of interviews and questionnaires was used. We conductedinterviews with all students enrolled in the course and
politicization of trans identity: an analysis of backlash, scapegoating, and dog-whistling from Obergefell to Bostock. Lanham: Lexington Books, 2022.[3] S. G. Horne, M. McGinley, N. Yel, and M. R. Maroney, “The stench of bathroom bills and anti-transgender legislation: Anxiety and depression among transgender, nonbinary, and cisgender LGBQ people during a state referendum.,” J. Couns. Psychol., vol. 69, no. 1, pp. 1–13, Jan. 2022, doi: 10.1037/cou0000558.[4] E. J. Meyer, “Sex, Gender, and Education Research: The Case for Transgender Studies in Education,” Educ. Res., vol. 51, no. 5, pp. 315–323, Jun. 2022, doi: 10.3102/0013189X211048870.[5] C. M. Keegan, “Against Queer Theory,” TSQ Transgender Stud. Q., vol. 7, no. 3, pp. 349
thatthey all found and read the example that contained the solution and formula, however none ofthem used it in their final answer.Student A arrived at a correct answer using a while statement to force the minimum valuerequired for part B. Student Q quickly skims through the examples, including the one with theformula, but their final answer did not attempt to specify bounds and simply used f = rand().Student J found the example with the formula early in their documentation use and took aconsiderable amount of time to read through the example. However, this student continued toswap back and forth between the problem and the documentation as shown in Figure 3. Duringthis period, the student searched the following terms “random decimal”, “random
problems given in Figs. 1a, 1b & 1c as developed in Blackboard (instructor view) – Dynamics of MachinesFigure 1d shows the Question Set as developed in Blackboard. There are two question sets: Q 1has two problems out of which one will be delivered to a student and Q 2 has only one problemthat will be delivered to every student. One might ask why not put two problems in Q 2 too, onefor each of the alternate problems (given in Fig. 1a & 1b)? The answer lies in the wayBlackboard works. If there are two problems in question set 2 one for each problem in questionset 1, then those may (or will) be mismatched as there is no control over which problem(s) aregiven from the set. It is quite possible that all students may get the same problem in
assignments to help prepare students for some of the Regular, content in the upcoming lectures, which contain about 5 questions based on deliberate assigned reading excerpts, videos, and/or audio demonstrations. practice 2. Weekly homework assignments to provide regular practice and interaction with course content. 1. Q&A with online tool, e.g., TopHat, to gauge content comprehension and encourage active participation with content; encourages participation from students who prefer not to speak up in class; allows for more think time. 2. Collaborative learning activities with clear, written instructions. Opportunities
clarified, and students' questions wereaddressed.The first assignment, released in week ten, focused on guiding students to study and understandthe API 6A standard. Design teams were given two weeks to complete it. The API Specification6A document was provided, and students were required to review and comprehend the relevantsections related to API flange design.In the first Q&A session, a schematic of a typical bolted-flange-gasket assembly, as shown inFigure 2, was discussed. Students were guided to understand its structure and working principle.They were also directed to gather three specific pieces of information: (1) a list of materials for 6the flange, gasket, and bolts, (2) the dimensions of
, lately the radio and communication systems have been moving away from electronics-based hardware to software defined radio (SDR) platforms [1-3], and the pricing of such platformsbecame very accessible for individuals and educational settings. While top performance SDRplatforms such as the Universal Software Radio Peripheral (USRP) [4] are still expensive and areusually considered for research purposes, the price range of under $50 for an RTL-SDR [5] is veryaffordable for a student or any individual who wants to experiment with radio receivers. RTL-SDRis a USB device using the Realtek RTL2832U chipset, which allows the device to convert receivedradio frequency (RF) signals to a stream of in-phase/quadrature (I/Q) samples that can be processedon
, we must look atthe past," a one-hour tech elective course in a General Engineering program was designed togive students the opportunity to examine historical cases and learn modern tools, equippingthem for the workplace in the AI era.This paper presents a dual-pronged approach used to achieve these goals: (A) studying historicaltechnology and business cases, and (B) learning how to use powerful AI tools such as ChatGPT. (A) Learning from History: In small, randomly assigned groups, students were asked to watch episodes of the documentary series The Men Who Built America and read selected articles from the book Inspiring Technology: 34 Breakthroughs. They then presented their findings to the entire class and engaged in Q
the steps of how the AI assistant is created, deployed, andupdated. Please note that the developer aspect of the AI tool is out of the scope of this study, thuswill not be discussed; instead, we will focus on the application of this tool. The basic steps are the same regardless of the choice of an AI tool (Figure 2.). Thestarting point is the Knowledge Base, i.e. materials that contain information that are relevant toMETM faculty’s teaching success; this consists of the Faculty Handbook, and additional Q&Adocument created based on some commonly raised questions by new faculty members. Figure 2. Process to create the AI Assistant. Figure 3 is a screenshot of what Google NotebookLM can offer with free
), floating-point (Zfh/F/D/Q),atomic (A), and bit manipulation (B) extensions. Wally supports the RVI20U32, RVI20U64, andRVA22S64 RISC-V profiles and can boot Linux with privilege modes and virtual memory andcan run on an FPGA. The textbook can be used to teach courses in computer architecture, SoCdesign, design verification, embedded systems, or a subset of these in theory, practice, or both.We describe two types of courses we taught using a draft version of this textbook: asenior/master’s level course that focused on all stages of SoC design and a second course taughtat the sophomore/junior level that focused on computer architecture and processor design only.These courses used the labs, exercises, and Wally SoC that accompany the textbook. We
-581.[7] D. Li, E. Milonas and Q. Zhang. “Converging Paths in Divergent Systems: A Comparative Analysis of Data Science Education Strategies in China and the United States.” 2024 Frontiers in Education(FIE), IEEE, Washington, DC. October 13-16, 2024.[8] Vinay, B. (2024). “Data Scientist Competencies and Skill Assessment: A Comprehensive Framework.” International Journal of Data Scientist (IJDST) Volume 1, Issue 1, January- June 2024, pp. 1-11. Available: https://iaeme.com/MasterAdmin/Journal_uploads/IJDST/VOLUME_1_ISSUE_1/IJDST_ 01_01_001.pdf[9] Tang, Rong & Lim, Watinee. (2016). “Data science programs in U.S. higher education: An exploratory content analysis of program description
. García Clemente, M. Gil Pérez, and G. Martínez Pérez, "SafeMan: A unified framework to manage cybersecurity and safety in manufacturing industry," Software: Practice and Experience, vol. 51, no. 3, pp. 607-627, 2021.[16] C. W. J. Lim, K. Q. Le, Q. Lu, and C. H. Wong, "An overview of 3-D printing in manufacturing, aerospace, and automotive industries," IEEE potentials, vol. 35, no. 4, pp. 18-22, 2016.[17] A. Jandyal, I. Chaturvedi, I. Wazir, A. Raina, and M. I. U. Haq, "3D printing–A review of processes, materials and applications in industry 4.0," Sustainable Operations and Computers, vol. 3, pp. 33-42, 2022.[18] S. W. Kim, J. H. Kong, S. W. Lee, and S. Lee, "Recent advances of artificial
.2006.11.005.[5] C. R. Starr, “I’m not a science nerd! STEM stereotypes, identity, and motivation amongundergraduate women,” Psychol. Women Q., vol. 42, no. 4, pp. 489–503, 2018, doi:10.1177/0361684318793848.
Paper ID #46783BOARD # 409: NSF LSAMP: 2-Year Institution STEM Faculty and StaffPerceptions of the KS-LSAMP ProjectDr. Lydia Yang Yang, Kansas State University Dr. Lydia Yang is an Associate Professor of Quantitative Educational Research Methodology at College of Education, Kansas State University. She received her Ph.D. in Curriculum and Instruction from Florida International University. Her research interest include quantitative educational research design and statistical analyses, Q methodology, and broadening participation in STEM fields.Craig Wanklyn P.E., Kansas State UniversityDr. Amy Rachel Betz, Kansas State
agreeReferencesBorrego, M., Knight, D. B., Gibbs Jr, K., & Crede, E. (2018). Pursuing graduate study: Factorsunderlying undergraduate engineering students' decisions. Journal of Engineering Education,107(1), 140-163.Gilmartin, S. K., Thompson, M. E., Morton, E., Jin, Q., Chen, H. L., Colby, A., & Sheppard, S.D. (2019). Entrepreneurial intent of engineering and business undergraduate students. Journal ofEngineering Education, 108(3), 316-336.Lattuca, L., Terenzini, P., Knight, D., & Ro, H. K. (2014). 2020 Vision: Progress in preparingthe engineer of the future.Lee, W. C., Hall, J. L., Godwin, A., Knight, D. B., & Verdín, D. (2022). Operationalizing andmonitoring student support in undergraduate engineering education. Journal of
for the Change to Last. Lioncrest Publishing, 2020.[3] J. P. Kotter, Leading Change, 1R ed. Boston: Harvard Business Press, 2012.[4] J. Herron, Feeling and Personhood. Thousand Oaks, CA: Sage, 1992.[5] J. Herron, Cooperative Inquiry: Research into the human condition. Thousand Oaks, CA: Sage, 1996.[6] L. Alcántara, S. Hayes, and L. Yorks, Collaborative inquiry in action. San Francisco: Jossey- Bass, Wiley, 2009.[7] T. L. Renshaw, A. C. J. Long, and C. R. Cook, “Assessing adolescents’ positive psychological functioning at school: Development and validation of the Student Subjective Wellbeing Questionnaire,” Sch. Psychol. Q. Off. J. Div. Sch. Psychol. Am. Psychol. Assoc., vol. 30, no. 4, pp. 534–552, Dec. 2015, doi: 10.1037
onSemiconductor Processing and Metrology Techniques. Another objective is to enhance their careerreadiness through elevator pitch interview sessions and resume preparation. We plan to increasethe number of scholars involved and expand access to university-wide the resources. For futureresearch, we will explore the broader impact of learning teams as cooperative learning, role ofnear-peer graduate mentors in improving self-efficacy, as well as well as the impact of careercompetency.AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Award No.2030861.References[1] “College Navigator - Polk State College,” Ed.gov, 2022.https://nces.ed.gov/collegenavigator/?q=Polk+State+College&s=all&id=136516#retgrad
students’ overall experience with gamification throughout the course, determine whichelements were most/least effective, and analyze the impact on collaboration, competition, andstress levels. Students were also asked about the perceived impact on learning outcomes, andunderstanding of course material. Suggestions for improving gamification in future courses werecollected in the survey as well.General Overview of Gamification PlatformsTwo platforms were used in the five courses by three instructors in Fall 2024: Kahoot! [10] andMentimeter [11]. Kahoot! featured competitive quizzes with real-time leaderboards and prizeoptions for top performers, fostering engagement and competition. Mentimeter enabledinteractive polling and anonymous Q&A
practices and prevention against futuredata-related incidents. Students can use classification models and/or regression models in thistask.The midterm assessments have been conducted to monitor the students’ progress andperformance, followed by an immediate adjustment of the instructor’s intervention as needed.For example, from the tests, class discussion, and midterm exam, students in CS413/CS520demonstrated weaker understanding on some concepts and skills such as using Python packagesin model training & fitting. The instructor added in-class lab times to reinforce the relatedconcepts and office hours after class for Q&A. In addition, the data on student projectcompletion rate, exit survey and final exam were collected to evaluate and
TransboundaryCompetence", Journal of Cleaner Production, 49, pp. 123~133. (14)Lattuca, L. R., Voigt, L. J. and Fath, K. Q., 2004, "Does Interdisciplinarity Promote Learning?Theoretical Support and Researchable Questions", Review of Higher Education, 28(1), pp. 23~48. (15)Ming, X., van der Veen, J. and MacLeod, M., 2024, "Competencies in InterdisciplinaryEngineering Education: Constructing Perspectives On Interdisciplinarity in a Q-Sort Study", EuropeanJournal of Engineering Education, pp. 1~22. (16)Quelhas, O. L. G. C., Lima, G. B. A., Ludolf, N. V., Meiri N O, M. J., Abreu, C., Anholon, R.,Vieira Neto, J. and Rodrigues, L. S. G., 2019, "Engineering Education and the Development ofCompetencies for Sustainability", International Journal of Sustainability in
.2022.3166478[12] C.H. Godoy, Jr, “A Review of Augmented Reality Apps for an AR-Based STEM EducationFramework”, Southeast Asian Journal of STEM Education, Vol 3, No. 1, Jan. 2022, doi:10.48550/arXiv.2203.07024[13] M. W. McColgan, G. E. Hassel, and K. Pashayi, “MSM Framework: AR Model of the Forceon a Charge Moving in a Magnetic Field”, 2024 PERC Proceedings [Boston, MA, July 10-11,2024], edited by Q. X. Ryan, A. Pawl, and J. P. Zwolak, doi:10.1119/perc.2024.pr.McColgan[14] M. W. McColgan, G. E. Hassel, N. C. Stagnitti, J. W. Morphew, and R. S. Lindell,“Augmented Reality to Scaffold 2D Representations of 3D Models in Magnetism”, 2023 PERCProceedings [Sacramento, CA, July 19-20, 2023], edited by D. L. Jones, Q. X. Ryan, and A.Pawl, doi:10.1119/perc.2023
/. Accessed: Sep. 20, 2022.[8] A. Sirinterlikci, Z. Czajkiewicz, J. Doswell, and N. Behanna, "Direct and indirect rapid tooling," in 2009Rapid/3D Scanning Conf., Chicago, IL, 2009.[9] "ExOne S-Max Review, an Industrial 3D Printer (Binder Jetting)–Aniwaa," Aniwaa, [Online]. Available:https://www.google.com/search?q=https://www.aniwa.com/product/. Accessed: Sep. 20, 2022.[10] "3D Materials & Binders–ExOne," ExOne, [Online]. Available:https://www.google.com/search?q=https://www.exone.com/en-US/sand-casting. Accessed: Sep. 20, 2022.[11] A. Sirinterlikci, O. Uslu, N. Behanna, and M. Tiryakioglu, "Preserving historical artifacts through digitizationand indirect rapid tooling," Int. J. Mod. Eng., vol. 10, no. 2, pp. 42–48, 2010.[12] "Formlabs Rigid 10K
program events. Recurring school information sessions, featuring guest lectures and Q&A sessions with professionals from medical and science fields, will be held every two months for grades 6-8 to ensure sustained exposure and engagement. Key stakeholders, including the researchers, Ascension Foundation, participating schools, and educational partners such as Meharry Medical College, will support the program’s implementation and evaluation. The anticipated outcomes of this study will highlight the influence of early exposure to healthcare and STEM on shaping students’ long-term aspirations. By tracking their progress, the research will pinpoint which program interventions are most effective in fostering sustained
), 284.14. Trucchia, A., Meschi, G., Fiorucci, P., Gollini, A., and Negro, D. (2022). Defining wildfire susceptibility maps in Italy for understanding seasonal wildfire regimes at the national level. Fire, 5(1), 30.15. Wu, T., He, S., Liu, J., Sun, S., Liu, K., Han, Q. L., and Tang, Y. (2023). A brief overview of ChatGPT: The history, status quo and potential future development. IEEE/CAA Journal of Automatica Sinica, 10(5), 1122-1136.16. Zhao, Q., Yu, L., Li, X., Peng, D., Zhang, Y., and Gong, P. (2021). Progress and trends in the application of Google Earth and Google Earth Engine. Remote Sensing, 13(18), 3778.