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-loop approach is used to manually select/assign the most relevant category forthose students’ responses. The following are the observations found. • For the first question, ‘If you stayed in an engineering or computer science major, what or who influenced your decision to continue?’ Figure 2.4(c) shows that only 7 out of 75 students’ responses (9.33%) are identified, when only using Bandura’s work and a taxonomy, for which the AI model predicted Figure 2.4(c): Predicted Categories for different categories for both Q i #1 the prompts
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program with reflections and messaging through groups that have broadconstituencies. In our case, we began collecting internal data about DEIS through our AMP-UPtask groups. We introduced the concept of A&A–majoritarian individuals advocating forminoritized groups–through grass-roots meetings emphasizing national and campus data andencouraging Q&A and small group breakouts. We encouraged anyone attending a conferencewhere germane workshops were being held to attend those workshops. For example, at oururging, a few faculty attended A&A sessions at a national conference (ASEE), where they heardparticipants from other universities talk about how impactful and valuable the A&A workshopshad been on their campuses. For our faculty, this
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generative AI (many wrote about multiple types of experiences), 5 students mentioned theirexperience using generative AI for schoolwork. Examples included using DALL-E to generateimages when making a zine for a senior English project and generating practice problems forclasses. 4 talked about learning with or about generative AI in out-of-school settings. Forexample, one student had attended a summer program hosted by a university where they codedan AI using Q-learning and Monte Carlo tree search. 3 students used generative AI for theirhobby by setting generative AI up as their opponent for video games or creating stories aboutcharacters for role-playing games. 10 students stated their experiences testing out generative AIon their own or with their
to B and J for participating in this study by sharing your experiences and insights.Thank you to Maryrose Weatherton and Betsy Chesnutt for excellent feedback on the interviewand poem method. Thanks to the engage™ Engineering Fundamentals Program for researchspace and administrative support.References[1] M. E. Brenner, “Interviewing in Educational Research.,” in Handbook of complementary methods in education research, J. L. Green, G. Camilli, and P. B. Elmore, Eds., Lawrence Erlbaum Associates Publishers, 2006, pp. 357–370. Accessed: Jan. 29, 2024. [Online]. Available: https://psycnet.apa.org/record/2006-05382-021[2] M. Q. Patton, “Chapter 8: Qualitative analysis and interpretation,” in Qualitative research and
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reinforcing the status quo. Therefore, theengineering industry should take the students’ concerns as input if the industry wants to worktowards the reframing of engineering as sociotechnical, and the commitment to social justice.References[1] D. M. Hatmaker, “Engineering identity: Gender and professional identity negotiation among women engineers: identity negotiation among women engineers,” Gend. Work Organ., vol. 20, no. 4, pp. 382–396, 2013, doi: 10.1111/j.1468-0432.2012.00589.x.[2] J. Jorgenson, “Engineering selves: negotiating gender and identity in technical work,” Manag. Commun. Q., vol. 15, no. 3, pp. 350–380, 2002, doi: 10.1177/0893318902153002.[3] E. A. Cech, “Culture of disengagement in engineering education?,” Sci. Technol. Hum
morelikely to engage in the epistemic practice, consider problems in context. This supports priorresearch that has shown empathy to be a skilled developed through user-centered engineeringcontexts [33-34]. Similar, the structure and open-ended nature of the kits to align with anengineering design process elicited engagement in particular epistemic practices such asenvisioning multiple solutions. In the context of this study, envisioning multiple solutions weregrounded in the process of sketching which has been shown to promote the development ofinnovative ideas, building upon ideas, and deeper thinking about their solutions [35]. Second, theinclusion of familiar and everyday materials (e.g., q-tips, cotton balls, sandpaper, straws)supported children
, cumulative GPA, number of papers authored (research productivity) , and successfuldegree completion. The results of these studies are not consistent or conclusive, depending asthey do on the type and level of the program, the discipline, the sample size and diversity, andthe statistical methods and controls.However, some general observations can be made based on the literature. Kuncel et al. [33]performed a meta-analysis of nearly 100 studies involving 10,000 students. They reportoperational validities of 0.38 and 0.30, respectively, for the predictive validity of the GRE-V andGRE-Q for masters-level GPAs. For doctoral students, the corresponding values are 0.27 and0.28. They conclude, “The primary implication of these findings is that the evidence
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words, why did we not skip the process of flocculation and go directly to filtering? 7. What additional steps would you take to make the water potable?ENGR 1203Module 6: Life Cycle AssessmentUse the following carbon footprint database to find the kg CO2e/kg for each ingredient.https://apps.carboncloud.com/climatehub/search?q=pizza&market=USA&sort=market%3AdescDeliverables 1. One table showing total kg CO2e/kg for each meal (three rows, one column) 2. Three pie charts, one for each meal, showing what proportion of the total impact is caused by each ingredient 3. One bar graph, showing how the total kg CO2e/kg breaks out by "phase" (agriculture, transportation, etc.) 4. Discussion
scenario-based learning experience. By integrating concepts like supply chain management and integrated circuit manufacturing, the workshop organizers expected it would offer a comprehensive view of how these technologies interact within a broader system, providing participants with a holistic understanding crucial for their roles in defense and national security. 3.2 Learning journeyThe learning journey followed a scaffolded approach, with each innovation concept andtechnology building upon, and incorporating, those priorly introduced. The educational activitiesincluded pre-workshop readings, instructor presentations, interactive lectures, four small-teamsexercises connecting theory and practice, Q&A sessions
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were defined as any software or system that utilizesartificial intelligence techniques to assist with or automate project management tasks. Thisincludes but is not limited to machine learning algorithms, natural language processing,predictive analytics, chatbots, and virtual assistants. Chatbots specifically refer to AI-poweredconversational agents that interact with users via text-based interfaces, while virtual assistantsincorporate both text and voice-based interaction. These definitions were provided toparticipants in Survey Preamble. Table 1. Survey Data Collection Instrument Q# Question Options/Response Type
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available for academic question-and-answer sessions. Some are integrated with learning management systems (e.g., Canvas [24], Moodle [25]). And some are standalone, such as Piazza [27] and Discord [28]. These tools can be used in a moderated or unmoderated fashion in a classroom setting. Messaging from an instructor can reach every student. These collaboration tools do not include any discipline-specific features (e.g., circuit analysis). However, users could post links to circuit examples as part of the Q&A discussion.Compared to the above categories of systems, the key novelty of CATE is the ability to generaterandom circuit topologies and present an analysis in a step-by-step manner. Outside of the abovecategories, one nearest
rethinking the uses of technology in the organizationof information within the Tribe’s world view.ACKNOWLEDGEMENTSJ.M. M.-A. wishes to acknowledge the continuing support, advice, and traditional knowledgeshared with me without which this paper would not exist:Alexander Soto (Tohono O’odham), Director, Labriola National American Indian Data Center,Arizona State University (ASU) Library.Esther Nystrom (Diné), Elder-in-residence, American Indian Student Support Services, ArizonaState University.References:[1] “Kiva.” Oxford English Dictionary. Accessed Jan. 18, 2024. [Online]. Available:https://www.oed.com/search/dictionary/?scope=Entries&q=kiva[2] Artelisa, “Lost Secrets of Chartres Blue? History of color, and why astrology in a church?”[blog post
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