," International Journal on Interactive Design and Manufacturing (IJIDeM), vol. 3, pp. 147-156, 2009.12. D. A. Schön, "Designing as reflective conversation with the materials of a design situation," Knowledge-based systems, vol. 5, pp. 3-14, 1992.13. J. Jang and C. D. Schunn, "Physical design tools support and hinder innovative engineering design," Journal of Mechanical Design, vol. 134, p. 041001, 2012.14. R. I. Campbell, D. J. D. Beer, L. J. Barnard, G. J. Booysen, M. Truscott, R. Cain, et al., "Design evolution through customer interaction with functional prototypes," Journal of Engineering Design, vol. 18, pp. 617-635, 2008.15. Y.-K. Lim, E. Stolterman, and J. Tenenberg, "The anatomy of prototypes: Prototypes as filters, prototypes
empathetic communication. A systematic review found that simulation-basedinterventions that are both immersive and experiential were the most effective method ofempathic education [32]. In a scoping review of empathy in nursing students, simulationincreased empathy levels and confidence, and is deemed beneficial for enhancing empathyawareness, sensitivity, and decreasing negative emotions [31].Empathy is central to the nursing role, fostering and promoting the therapeutic nurse-patientrelationship. Empathetic nursing care requires self-reflection, mindfulness, giving of oneself, andviewing the patient as a whole. Empathy allows patients to feel validated, understood, andrespected. Collaboration and communication between nursing and engineering is
and in identifying formal evaluation criteria that robustlycapture whether skills have been acquired. Of interest is whether tools can be developed thatprovide more robust formative assessment of a modeling activity. This contrasts with summativeassessment approaches which largely benefits the assessor in reducing grading times byevaluating the result but can miss important tendencies in a student designer that might need tobe corrected. For this to be feasible better metrics that reflect how a modeling activity isprogressing not just with respect to realizing a final shape goal, but also in capturing designintent and meeting best practices is needed. In this paper some of the challenges of evaluating 3DCAD modeling efficacy are explored
commitment to RT transformed into effective RT for communities 5 1.5 RT is not supported nor 2.5 Academic advisors can help students required by academic institutions circumvent institutional barriers to RTRT in Academic Research Program: Student Case Studies in HES @ MinesAs reported in our ASEE 2022 paper [1], graduate students’ journey to RT begins with an in-depth process of formation which includes a self-reflection of their perspectives as historical andsocial agents, extensive critical readings of the history of engineering, development, and the roleof engineers in development. Once they
efforts indiversity, equity, and inclusion were out of his scope. Initially, the researchers felt Omar’sresponses could have fit in broader systemic issues such as greenwashing or performativeallyship [34], [35], but in reflection following the interview process, the researchers felt Omarmight have been uncomfortable, or felt he was being assessed, leading him to look for the “right”answer. However, Omar perceived his work as separate from efforts in diversity or equity, the“science side of things.” Later in the interview, Omar also mentioned that he did not have a lot ofinvolvement with the Center outside of his lab, lab work, and advisor. Omar may not have beenexposed to the importance of inclusive or equitable practices in the way Zenith was
Discovery Channel and other news sources. Hammond is dedicated to diversity and equity, which is reflected in her publications, research, teaching, service, and mentoring. More at http://srl.tamu.edu and http://ieei.tamu.edu. ©American Society for Engineering Education, 2024 Emotionally Intelligent Machines in Education: Harnessing Generative AI for Authentic Human-Machine Synergy in the ClassroomAbstractThis paper delves into the realm of Generative AI (GenAI) infused with Artificial EmotionalIntelligence (AEI) to enhance cooperative and genuine human-machine interplay. It underscoresthe imperative of assimilating AEI in diverse sectors including education
is repeated until one victor emerges. After this, the instructor typicallypresents the true conclusion, which is always an entertaining time—especially if a team wascorrect but was not voted up to the next level.Students are asked to reflect on the experience together in a classroom-wide discussion. Themain takeaways typically regard:• The criticality of due process, the formality of investigations, and the correct handling/ interpretation of evidence.• The power of perception, and how remaining impartial is paramount when the stakes are so high.• The nuance and broadness of engineering as a profession and skillset. Equipment can be very sensitive to small elements, and a broad knowledge base is needed to not only understand the
with the students, but without dictatingtheir activities.In addition to the 2.5 hours described above, students can optionally visit the Wind Tunnel in adifferent room for 30 minutes, which is outside the scope of this paper.Tutors were trained with video footage from previous years and then met with the module leaderfor guidance. A summary of the training follows: Guidance for tutors • Reflect on the purpose of the activity and how students experience it • Students have written guidance and can complete the activity independently • Avoid telling students things directly or giving them instructions • Listen to students, understand their point of view first and use that as a starting point • Be positive and
completed the survey near the end of each school term, with the Winter termsurveys completed in March 2023, and the Spring term surveys completed in June 2023. TheMECH-431 courses were complete by the time the survey was taken by enrolled students, so theywere able to reflect on the course as a whole at the time of completing the surveys.4.1 HypothesisResults are determined in this study by inductive reasoning. Based on the results of the literaturereview, it is clear that some dynamics systems and controls undergraduate laboratory courses atother institutions have effectively employed hands-on laboratory exercises at low cost. Therefore,a reasonable resulting hypothesis is that low cost physical laboratory experiments can beemployed effectively in
both undergraduate and graduateeducation should reflect that change [1], [2], [3]. This commitment to a shift in the educationalapproach within MSE departments is highlighted in the strategic plan of the National Scienceand Technology Council’s Materials Genome Initiative, which posits that the next generation ofthe MSE workforce will need to master three competencies: experimentation, data management,and computation [4].MSE educators have worked to construct educational offerings that develop competencies in theareas identified by the Materials Genome Initiative. Several departments have developedcomputational courses or add-on computational modules for existing courses [5], [6], [7], [8],[9], [10]. However, while inroads have been made in
–student interaction data, where the frequency of online interactions proved to betterindicate student persistence and success than did the length of interactions. And the study by Aguiaret al. (2014) [14] predicted persistence using first‐year engineering students' electronic portfolios,extracting information about their course engagement through their reflections about engineeringadvising, project updates, and engineering exploration throughout the course. Using attributesrelated to student activities such as assignment skips, assessment performance, and video skips andlags to predict student dropout in online courses, while the study by Halawa et al. (2014) [15] wasable to successfully flag 40%–50% of students who dropped out of the course
summarizedmemos. A guiding research question prompted participants to reflect on how they felt others sawthem as engineers. This question was derived from previous work that quantitatively exploredundergraduate engineering identity and recognition beliefs [11] and specifically uses thephrasing “see you as an engineer” to keep questions in the participants’ language [37]. The open-ended nature of the focus groups allowed for follow-up questions and permitted researchers togather rich details about participants’ experiences to go beyond whether they do or do notbelieve others saw them as an engineer and to better explore the qualities of experiences that ledto these beliefs. Questions relevant to this study are presented in Table 1.Table 1: Focus
participants noted that engineering faculty do not havethat knowledge and said, “if you’re gonna teach and assess these things (professional skills)you’re reaching a lot more into social sciences.”LimitationsThis research's findings cannot be generalized to any engineering programs at differentuniversities. Nonetheless, the research process of engaging with faculty can offer valuableinsights into areas for enhancement and collaboration and raise awareness of curricularinitiatives.The study solely reflects faculty perspectives, given their role as gatekeepers determiningsyllabus content and classroom focus. However, it's crucial to incorporate industry and studentperspectives into discussions on professional skill development. Integrating these
similarity. In this design, students are encouraged toexpress their initial perspective on a situation before engaging in modeling, reflecting, anddiscussing their views. These approaches aim to improve their understanding of a givensituation. As for the second aspect, action-based embodied design aims to establish afoundation for mathematical concepts by utilizing students’ natural abilities, with a specificfocus on their adaptable sensorimotor skills. In this design, students utilize technologyinterventions to manipulate objects to reach a specific goal state. We identified three studiesincluded in this systematic review ([18], [20], [41]) that implemented both aspects ofembodied design frameworks.These three studies incorporate game-based play
scholarly pursuits, Ayodeji demonstrates a keen interest in engineering education. He has made significant contributions to his field through a prolific publication record and active participation in academic conferences. Possessing a diverse skill set, including strong communication abilities and analytical proficiency, Ayodeji is also an avid reader and enjoys nature. His trajectory reflects a commitment to continuous growth and making a meaningful impact within engineering and beyond.Dr. Emmanuel Okafor, King Fahd University of Petroleum and Minerals, Saudi Arabia Emmanuel Okafor holds a Ph.D. in Artificial Intelligence from the University of Groningen, Netherlands, specializing in computer vision, machine learning, and
) • Connectivity Problems (17 Voices) • Challenges and Obstacles of Virtuality (15 Voices) • Difficulties with Specific Content (9 Voices) • Personal Factors (6 Voices)Student statements about obstacles to learning during the course reflect an uneven adaptation tovirtual teaching. Challenges are associated with connectivity and understanding specific topics such asmathematics and circuit laws.3) What changes to the course could improve your learning? When analyzing the answers to thisquestion, the following emerging constructs can be seen (71 student voices) • Suggestions to Improve interaction (43 voices) • Request for More Practices and Activities (37 Voices) • Recommendations to Improve Communication (20 Voices)Below is a
questionnaire refers to emotions you may experience as part of this class (EGR 210 - Electric Circuits). It is divided into three sections: (a) your emotions related specifically to testing in this course, (b) your emotions related to Circuits class in general, and (c) your experience as part of the larger Engineering program. Please reflect on your experiences during this semester as you answer the questions below.* Required Unique Identifier 1. Copy and paste the unique identifier you received in your email: *Emotions during Electric Circuits testing and examsAttending college classes can create different feelings. This part of the questionnaire refers specifically to emotionsyou may experience during exams in EGR 210 - Electric Circuits. Before
limitation is mostlikely due to the FPGA’s ability to connect two ALMs during the routing process, where a wirewith a width larger than 1120 cannot be connected between two ALMs. The data we report onlygoes up to a maximum bit-width of 1024, so this limitation is not reflected in our graphs. Also,the Goldschmidt divider has a smaller range than the other dividers because it was not able tosynthesize above a width of 244. This is due to the limited number of DSP blocks.4.1 AreaThe FPGA used in these tests is the 5CGXFC9E7F35C8 from the Cyclone V line. This FPGA ischosen due to its large amount of available ALMs and DSP blocks. The maximum ALMs that ourFPGA has in this study is 113,560. Very few dividers in this study approached this maximumnumber of
standard deviation and the number of participants for each semester. The Likert-scale used in the surveyconcepts across various ranged from "Excellent" (5) to "Poor" (1), enabling participants to rateinstructional delivery formats. The their perceptions regarding the effectiveness of the take-home kits ormodules' effectiveness is widely desk-scale modules in aiding their understanding of theoretical concepts underlying physicochemical phenomena and unit operations.acknowledged among students,reflected in small standarddeviations. Emphasizing the importance of face-to-face components in blended learning, thesemodules received high
to improve student teamwork experience and academic performance in circuits analysis course Proceedings of the 129th American Society for Engineering Education (ASEE) Annual Conference and Exposition, 2022 https://peer.asee.org/40873[34] *S. Claussen, V. Dave. “Reflection and metacognition in an introductory circuits course,” Proceedings of the 124th American Society for Engineering Education (ASEE) Annual Conference and Exposition, Columbus, Ohio, 2017. https://peer.asee.org/28788[35] *B. H. Ferri, D. M. Majerich, N. V. Parrish, A. A. Ferri. “Use of a MOOC platform to blend a linear circuits course for non-majors,” Proceedings of the 121st American Society for Engineering Education (ASEE) Annual Conference and
results from the preceding analysis,including further interpretation of the results, and propose some possible explanations.Beginning with demographic variables, Asian students reported stronger beliefs in the value ofcollaborative learning compared to white students. This may reflect cultural differences inlearning styles, or the value placed on group harmony and collective effort. Additionally,Mechanical Engineering (ME) and Industrial Engineering (IE) students showed lowercollaborative learning beliefs compared to their counterparts in Electrical and ComputerEngineering (ECE). These findings suggest that there may be disciplinary differences in thevalue and integration of collaborative learning in different degree programs.Turning to other
gender choice of “Other”was excluded due to the limited number of degrees awarded, reported only for 2019. Our“Native” category reflects combining the racial reporting options of “American Indian/AlaskaNative” and “Native Hawaiian/Other Pacific Islander.” Similarly, our “Multi” category reflectscombining “Foreign,” “Multiracial,” and “Unknown.” Other racial categories are used asreported by ASEE (e.g., “Asian,” “Black,” “Hispanic,” and “White”). Procedurally, the data was first downloaded into a CSV file. A self-generated Jupyter filewas created to clean the data and create the tidy format [21] XLSX files needed by Tableau forcreating the infographics [11]. Once the charts were styled with shapes, colors, and categorieschosen for visual
-learning systems [21]. To assess students’learning styles, this study used the Visual, Aural, Read/Write, or Kinesthetic (VARK) learningstyles inventory which is a questionnaire consists of 16 items used to assess the respondent’slearning style [21]. The study also used the Dixion scale to measure students’ engagement usingthe adaptive or non-adaptive e-learning system; this scale includes the factors of skills,participation/interaction, performance, and emotion [21]. This study found that students wholearned through the adaptive system learned more, reflected by their engagement scale responsesand overall course outcomes. While this study does not model the relationship between students’learning styles and intentions to use, has a small sample
incorporated into the class to help students toaddress these questions. The lab experimentation provided students with a hands-on opportunity to assess the biological impact of various biomaterials. Through thisexperiment, students gained practical skills in experimental design, data analysis,and interpretation, fostering a deeper understanding of biomaterials beyondtheoretical concepts. The inclusion of ethical considerations in the biomaterialcurriculum was addressed through a debate. This encouraged students to reflect onthe societal implications of biomaterials research, fostering a sense of responsibilityand ethical awareness among future practitioners.The study employed both qualitative and quantitative assessment methods,including pre- and post