their work. This is especially important if we consider the required balance between teaching and other academic expectations. For example, the input of a second instructor during highly technical sessions might not be as beneficial as their contribution during a more open-ended discussion session. Examples of open-ended discussions are semester project presentations, review of quality assurance and quality control in the design and construction process, and during studio sessions when students are working on both the aspects of design and construction.Discussion and Future Directions The experiences the authors provide in the paper echo previous research in terms ofcompatibility between
to understand the role of properties in engineering design. Properties are then measured in the lab. Towards the end of the course, the students perform a design project that involves identifying an engineering problems and measuring relevant properties for engineering design. The students submit oral and written reports.Course Goals: Upon completion of the course, a student should: 1. Understand the importance of units and dimensions, 2. Understand and apply the uniqueness of biological materials, 3. Comprehend the general categories, definitions, and measurement methods of engineering properties, and 4
college studentsdescribe experiencing moderate to high stress levels [1], [2]. As students are busy and feelingoverwhelmed, they have limited structured opportunities for reflecting on and developing theirpurpose and professional identities. In STEM environments, students may find that they do notfit into a predominant narrative of just “being good at math” and thus lack an adequatejustification for entering an engineering field. Similarly, they may find that they areunderrepresented demographically, underresourced compared to some peers, or unsure how theybelong in general, even if they are interested in their field of study. These students may find itdifficult to feel comfortable taking advantage of opportunities available to them on campus
Scholarship of Teaching and Learning,” International Society for the Scholarship of Teaching and Learning (ISSOTL), 2022. https://issotl.com/ (accessed Dec. 09, 2022).[6] P. Young, “Generic or discipline‐specific? An exploration of the significance of discipline‐specific issues in researching and developing teaching and learning in higher education,” Innov. Educ. Teach. Int., vol. 47, no. 1, pp. 115–124, Feb. 2010, doi: https://doi.org/10.1080/14703290903525887.[7] A. Jenkins, “Discipline‐based educational development,” Int. J. Acad. Dev., vol. 1, no. 1, pp. 50–62, 1996, doi: 10.1080/1360144960010106.[8] S. V. Chasteen and R. Chattergoon, “Insights from the Physics and Astronomy New Faculty Workshop: How do new physics
management. Moreover, PBL contributes to increased student engagement in classes [20].The acquiring technical knowledge can be effectively accomplished through PBL, emphasizingthat the use of this strategy encompasses both soft skills and technical proficiency. According to Silveira et al. [5], PBL has the following structure (Chart 1): Chart 1 – Project Based Learning steps. Step 1 Receive or choose the project theme. Collect facts to understand the proposed project (initial research) and formulate 2 the problems. 3 Create ideas to develop or elaborate the project. 4 Learn the content necessary to achieve it. Discuss solution proposals and project implementation
Artificial Intelligence (AI)The advent and evolution of Artificial Intelligence (AI) has revolutionized multiple industries,altering how tasks are executed and managed [1]. AI, characterized by its ability to simulatehuman intelligence processes, has seen significant advancements over the past few decadesparticularly with the development of Large Language Models (LLMs) like the GPT(Generative Pre-trained Transformer) series [2]. The emergence of ChatGPT, a variant of theGPT series known for its conversational capabilities, exemplifies the growing prominence ofAI in everyday applications, becoming almost synonymous with accessible AI [3]. From basicmachine learning algorithms to more complex neural networks, AI's capabilities haveexpanded due to its
technical challenges ofcommunications time delay, real world error and uncertainty, and network infrastructuredescribed here exemplify how postgraduate educational goals can be achieved through remote,collaborative-faculty-student project-based learning that can have broader impact for lab andproject work.IntroductionCOVID-19 changed abruptly the way in which higher education was delivered by faculty andreceived by students, moving from in-person to remote learning. In particular, the change hasbeen significant for postgraduate education where more than 1 million students are international 2 .By moving to a distributed classroom with students located around the world, teaching challengesfor both faculty and students have been many, such as dealing
that women, students from groups historically underrepresented inSTEM, and first-generation college students are more drawn to fields that they perceive asaltruistic and can lead to careers in which they can help others [7], [8], [9], [10], [11], [12], [13].Therefore, by using this project to situate MSE as a field in which students could impact theircommunities, we hope to increase interest in MSE. Finally, there is evidence to support thatcampus-related projects improve student outcomes by providing real-world experience [14],[15], [16], and can also provide a benefit to the university [17].In this work, we seek to understand the impacts of a campus-focused design project on students’1) sense of belonging in the field of MSE, 2) sense of
the primary cognitive determinant ofwhether or not an individual will attempt a given behavior. Bandura22 identified four sources ofinformation that shape self-efficacy: (1) performance accomplishments, (2) vicarious experience,(3) verbal persuasion, and (4) physiological and affective states.Robert Lent23 and his associates expanded on general self-efficacy theory to develop a SocialCognitive Career Theory (SCCT), a “conceptual framework aimed at understanding the processesthrough which people develop educational/vocational interests, make career-relevant choices, andachieve performances of varying quality in their educational and occupational pursuits” (p. 62). Inaddition to highlighting cognitive-person variables, such as self-efficacy
interaction,stability of the platform and customer support. To quantify this broader spectrum of the qualityand effectives of hybrid courses, future work will also include a a Hybrid Course Maturity Model(HCMM) which includes quality and quantity ratings in the following areas : (1) recordedlectures (2) discussion forums (3) online quizzes (4) online worked-out homework (5) onlinehomework submission and grading (6) student polls/feedback (7) online course shell design andease of use (8) technical support and (9) LMS platform stability. Coupling this with theknowledge of trends in student use of technology (especially Smartphones) should provide addedinsight aimed at improving the effectiveness of hybrid STEM courses.References:Naseer, M. (2012
engineering withmarginalized identities navigate their workplace cultures, specifically looking at howthey can authentically be themselves. The data shown within this presentation werecollected as part of a larger NSF-funded study qualitatively assessing themanifestation of racism within the technology industry.From literature, we know that Black engineers leave their workplaces at a higher ratethan White engineers. This is largely due to the toxic workplace environments definedby White men that are unwelcoming for minoritized people [1], [2]. With this work,we intend to understand their experiences and combat racism in tech. The narrativesshared by the participants will provide a depiction of what is occurring in tech. Theintention of this is to
action-oriented entrepreneurial mindset inengineering, science, and technical undergraduates. Some skills often associated with theentrepreneurial mindset are effective communication (written, verbal, and graphical), teamwork,ethics and ethical decision-making, customer awareness, persistence, creativity, innovation, timemanagement, critical thinking, global awareness, self-directed research, life-long learning,learning through failure, tolerance for ambiguity, and estimation.1, 2, 3, 4, 5, 6 In 2010, KEENspecifically outlined seven student outcomes pertaining to the entrepreneurial mindset.7 Astudent should be able to: 1. Effectively collaborate in a team setting (teamwork) 2. Apply critical and creative thinking to ambiguous problems
way to learn and grow that is reciprocal but asymmetrical [1].These attributes are found in the recent working definition of mentorship proposed by theNational Academies of Science, Engineering, and Medicine [3] and prescribed by the M360project: “Mentorship is a professional, working alliance in which individuals work together over time to support the personal and professional growth, development, and success of the relational partners through the provision of career and psychosocial support.” [3, p. 37].The benefits of faculty receiving mentorship are well documented and include increasedproductivity, career satisfaction, career success, organizational commitment, and general well-being [13], [14]. Comparatively, little
approach that centers teaching and learningaround projects. Students gain knowledge and skills by working autonomously for an extendedperiod of time to investigate, explore, and respond to an authentic and complex question, problem,or challenge [1], [2]. Students’ work generally culminates in realistic and concrete products andartifacts [3]. PBL is based on the constructivism learning approach, which supports that idea thatpeople construct knowledge based on their experiences and their drive to understand thoseexperiences by imbuing them with meaning and connecting them to prior knowledge [4]. In hiswidely-cited meta-analysis of PBL, Thomas outlines five criteria that help distinguish PBL fromproject work in general [2]: • Centrality: In PBL
and TAs) may interface with EM in their teaching roles (Table1). We also added three case scenario questions influenced partially by the KEEN framework [18] as well as a promptsoliciting feedback (Table 1). Finally, three open-ended prompts were custom-generated but created directly fromeach of the 3Cs of the framework - curiosity, connections, and creating value. These three open-ended prompts werethe same for both Spring 2021 and Autumn 2021 iterations (Table 1). Table 1: Modifications to pilot modules between iterations. Spring 2021 Autumn 2021 Trainee Population UTAs in the First-Year
, and talent development for future generations of STEMM professionals [10, p. 1].Atkins and colleagues [11] explain that even though mentorship has been prioritized by severalacademic programs to increase the diversity and support of these future leaders, an in-depthunderstanding of mentorship within these contexts remains limited.Within engineering and computing graduate education, research on mentorship as a tool tobroaden the participation of underrepresented students is scarce. As the demographics in theUnited States diversifies, there is a need for an “attitudinal, behavioral, and cultural adjustments”within the graduate education system [14, p. 970]. Departments and graduate programs are beingencouraged to shift to a more student
(DTLab).DTLab is also supported by Amazon Web Services and aims to accelerate public sectorinnovation in Germany, helping government, education, and nonprofits tackle some of the mostpressing challenges in delivering a wide range of citizen services. In this document, we will usethe terms DxHub and DTLab to refer to the two specific centers, and the general phrase digitalinnovation centers (DICs) to include both.Our external collaborator for this project is the Global Program for Safer Schools (GPSS) of theWorld Bank. The World Bank is an international organization (IO) that provides financialproducts and technical assistance to member countries in the developing world to addressdevelopment challenges with innovative and cross-cutting solutions
the written genres common in both academia and industry.Yet, much of the efforts of both researchers and practitioners on how to support student writinghave been centered around those at the undergraduate level, with very few studies focusing onhow engineering programs may support writing skills within doctoral education (Berdanier,2019; Cox, 2011; Gassman et al., 2013). This finding suggests a movement of engineeringdepartments—and higher education institutions in general—to expect students to be fullyapprenticed into academic and professional writing of their field upon beginning their doctoralstudies, even though the written genres that these students encounter in doctoral programs maydiffer greatly from those required in earlier degrees.1
student’s schedule.Universities generally staff career services offices for their students, offering a host of resourceson finding internships, writing resumes and cover letters, and practicing effective interviewstrategies. However, nearly 40% of students never even visit their universities’ career servicesoffices [1]. Disseminating useful information on career and professional development, therefore,must occur through the individual department. And, the timing of such exposure should be suchthat the student can contextualize any career advice received; giving students advice in interviewstrategies, for example, when they are in the midst of finding internships is more effective thanadvice given pre-college, which is naturally proffered in the
students did not respond tothe interview request. Thirty-three interviews were conducted over the program period.Participants Thirty-one students most recently were transfers from tribal or community colleges andtwo students most recently had attended a four-year university or college. Demographics ofprogram participants are in Table 1, and majors are listed in Table 2.Table 1: Demographics of interview participants, n=33 Gender Underrepresented First-generation Age at transfer minority in STEM college status Male Female Yes No Yes No <22 22 or
as new evidence-based approaches toteaching become more widespread in the STEM community. Although many of these techniqueshave been gaining traction in most STEM disciplines [1, 2], the rate of adoption in the areas ofComputer Science (CS), Information Technology (IT), and Software Engineering (SE) is less thanexpected [3]. The increasing number of students entering undergraduate programs in CS/IT/SE[4] requires that the introduction of these evidence-based approaches be adopted at a faster rate.This is particularly true for students entering SE programs given that the effective developmentof software applications requires the use of a wide range of skills, including both technical andnon-technical skills [5, 6]. The technical skills needed
interviews with early-career scholars explored thispreference for using general search tools in more depth and pointed to the appreciation of GoogleScholar’s natural fit in researchers’ workflows, allowing them to seamlessly open the full-text ofsources, as well as to link to sources for easy sharing (Ince et al., 2018). While our participantsalso liked the easy-to-use features of Google Scholar and Google, even more important to themwas the consistent identification of relevant sources and access to the most recently availableresearch.Our participants’ non-use of engineering databases like Engineering Village/Compendex andeven multidisciplinary tools like Web of Science, despite our regular promotion of these tools ininstruction sessions and
also highlighted the widespread optimism for the future of OER [6].OER in Engineering:Given the decentralized nature of creating and hosting OER, it is challenging to quantify theexact number produced. One of the most commonly used reference libraries, The Open TextbookLibrary [7], lists a total of 1,361 resources as of Jan 1, 2024. As seen in Figure 1, most OERshave been written for the Humanities, followed by the Natural and Social Sciences. WhileComputer Science has 116 developed OER, other Engineering & Technology branches have onlydeveloped 70 OER. Furthermore, 48 of the OER in Engineering & Technology have been writtenfor either general Engineering & Technology or Electrical Engineering. This leaves only 22 OERin the Open
-Sacre, & McGourty, 2005). According to ABET’s EC2000 standards, the new generation ofengineers is expected to possess deep technical knowledge in their field of study as well asprofessional skills, such as communicating effectively, working in teams, solving unstructuredproblems, and an awareness of ethical and contextual considerations in engineering (Lattuca,Terenzini, & Volkwein, 2006). The NAE believes engineers need to be flexible, resilient,creative, empathetic, and have the ability to recognize and seize opportunities (NAE, 2002;Sheppard, Pellegrino, & Olds, 2008) How can entrepreneurship education lead to these learning outcomes? Mostentrepreneurship-related activities students participate in are experiential in
-efficacy responses were focused on what they were able to accomplish in terms oftheir writing and technical research skills and their capabilities for conducting research: “…yes, I’ve learned a lot of new things in respect to my research work um so I can say I’ve made a, a lot of progress in a way of learning so specifically I’ve uh I’ve improved with my data analysis data analysis skills in Excel and using this data uh I can… I’ve improved in that I’ve also improved in my general writing and presenting my arguments umm compared to where I started on my research (inaudible word) and where I started on this particular project I can, personally I can see improvements in my in my, in my writing and in
has a high percentageof first-generation college students, with approximately 46% of the student populationidentifying as such.The overall student population is 3% American Indian/Alaskan Native, 3% Black/AfricanAmerican, and 25% Hispanic/Latinx with 64% of the students identifying as female and 36%male. The demographics of the students within engineering college (also housing informatics andapplied sciences) are very similar to the overall university except a slightly lower percentage ofHispanic/Latinx students at 21% and a starkly different divide among genders with 21% ofstudents identifying as female and 79% male. Table 1 indicates that representation within theengineering college by different demographics has been consistent between 2011
than the previous semester. This proved positive because 1)students developed a closer working relationship and 2) tasks could be more specifically assigned,creating a better isolation, which was one of the goals in this semester. In the future, the numberof students (and faculty) will remain similarly small to ensure similar success.In addition to the technical and on-demand tasks, the co-op also helped to set-up documentationand code-sharing policies, which will provide invaluable for the next generation ofparticipants.4.4.1 What Needed Improvement?In this semester, the largest issue was an unforeseen shift in the final goals. The dual paths - theoriginal bike system and the additional portable exercise system - created a more difficult
institutional review board protocolIRB-FY2017-169. There was one student who did not consent to participate in this part of theproject; he did not sign a follow up consent form.Description of the Program and ParticipantsTo give context to the experiences of students with disabilities, Table 1 shows the demographicsof all 25 students participating in the summer REU program in two cohorts. Of these students 13majored in mechanical engineering, seven in biomedical engineering, three in computer science,one in physics, and one general engineering. Two students were rising sophomores, 14 studentswere rising juniors, and nine students were rising seniors. Table 1: REU Cohort Demographics Female
Paper ID #26534Provoked Emotion in Student Stories of Motivation Reveal Gendered Percep-tions of What It Means to be Innovative in EngineeringProf. Barbara A. Karanian, Stanford University Barbara A. Karanian, Ph.D. , Lecturer, formerly visiting Professor, in the School of Engineering, in the Mechanical Engineering Design Group at Stanford University. Barbara’s research focuses on four ar- eas: 1)grounding a blend of theories from social-cognitive psychology, engineering design, and art to show how cognition affects design; 2) changing the way people understand the emotion behind their work with the intent to do
students or failure in other contexts such as academics in general), for the purposes ofthis study, the literature reviewed only relates to the study of failure by engineering students inan entrepreneurial context. Figure 1: Intersection of the discipline areas to be targeted by the systematic review.The primary research question is broken down into several sub-questions: 1) What theoreticalframeworks are used to study entrepreneurial failure in this literature?, 2) How has failure beendefined, operationalized, and measured?, 3) What are the research questions that are used tostudy failure?, and 4) What are the research methods that are used to study failure?Methods:Inclusion criteria and search strategyThe process of conducting the