critical thinking components, withthe goal of attracting and retaining a more diverse student population.The research hypothesis for this program is that “Positive outcomes can be achieved in anengineering program through strategic curricular and co-curricular modifications that integrateand embrace STEAM program development. Outcomes targeted include innovation, creativity,collegiality, entrepreneurship and broadening of the STEM talent pool [1].”The team has made significant progress in the first and second years of the program [2-3]. TheA+E team has advanced into the third phase (approximately halfway through the three-year award)of the NSF IUSE grant. Notably, the program has reinvigorated the curriculum, including theformation of two new
deconstruct the experience and surface students’ personalvalues among trusted peers.References 1. Planning Committee for the National Summit on Developing a STEM Workforce Strategy, Board on Higher Education and Workforce, Policy and Global Affairs, National Academies of Sciences, Engineering, and Medicine (PC). (2016). Developing a National STEM Workforce Strategy: A Workshop Summary. National Academies Press. 2. The Coalition for Reform of Undergraduate STEM Education (CR). (2014). Achieving Systematic Change: A Source Book for Advancing and Funding Undergraduate STEM Education. Washington, D. C.: The Association of American Colleges and Universities. http://www.aacu.org/pkal/sourcebook3. Kuh, G. D. (2008). High
. Forour project, we define spatial skills or spatial ability as abilities to mentally manipulate 2D and3D objects that one can acquire through formal training [1], [2]. Research in the past decade hasshown that spatial skills can predict STEM success among students, with findings showing thatspatial skills can have a role in increasing the likelihood of obtaining advanced STEM degrees[3]. Sorby and colleagues have also found that improving spatial skills through interventioncourses can impact the introductory STEM course grade performances of students who take theintervention courses [1]. Specifically, the study has shown such impact on grade performance incourses like Physics and Intro to Engineering, in addition to impact on STEM course GPAs [1
often place undue emphasis on the categorization ofknowledge and skills, while not sufficiently addressing the process through which studentsnavigate and act on ethical dilemmas. This, we posit, is an area that needs redefining, given thatethical decision-making is rarely a linear process with single objective “right” answers and ofteninvolves iterative reasoning and interactive engagement with the problem. As such, we havedeveloped a suite of ethics-driven classroom games that have been implemented and evaluatedacross three universities, engaging over 400 first-year engineering students over the past 3 years.Now in the grant’s final year, we are finishing the design of two of the game-based ethicsinterventions to (1) more accurately align with
a Culturally Responsive, Community-Based Fluid Dynamics Mini-Unit for Middle School (poster)IntroductionFundamental engineering concepts, such as those principles governing fluid mechanics inaerospace applications, can be perceived to be too complex to teach to young learners [1] [2].Furthermore, many primary and secondary educators are hesitant to teach engineering, believingthat doing so requires specialized preparation [3]. These views have prevented widespreadadoption of K-12 engineering curricula in the United States [4]. Since interest in STEM subjectspeaks for women and other minoritized populations in middle school [5], the lack of engineeringoutreach at these grade levels has negatively
address climate change. Currently, MiguelAndres is working on a framework to support and conduct undergraduate research. ©American Society for Engineering Education, 2024 WIP: Generative AI to support critical thinking in water resources students Daniel Abril1, Sixto Durán-Ballén1, Miguel Andrés Guerra1* 1 Universidad San Francisco de Quito USFQ, Colegio de Ciencias e Ingenierías, Departamento de Ingeniería Civil, Casilla Postal 17-1200-841, Quito 170901, Ecuador.* Correspondence: Miguel Andrés Guerra, MAGuerra@usfq.edu.ecAbstractIn the realm of water resources education, harnessing the power of artificial intelligence
surveys and focus groupsdiscussions conducted by the external evaluation team, was overwhelmingly positive andhighlighted significant benefits to students’ academic success and their future professionalcareers. This paper also presents the lessons learned that were synthesized using the observationsmade by the project team and evaluation team, and the feedback provided by the students. Theselessons learned can be institutionalized at West Virginia University and elsewhere in highereducation to aid students’ success in their education and future professional careers in thecybersecurity field.1. IntroductionCybersecurity is of crucial importance for protecting the public and private sector companies, aswell as individuals from cyber threats and
attention over the recent decades [1], [2], [3]. Engineering fundamentally revolvesaround tackling intricate challenges, and developing long-term solutions to societal problems.Yet, the effectiveness of these solutions greatly hinges on their ability to encompass a spectrumof perspectives, experiences, and skills from the global community. It falls upon engineeringeducators to foster inclusive environments where every voice matters, diversity is celebrated as adriver of creativity, and fairness guarantees equal access to opportunities for everyone. However,despite efforts to broaden participation and make engineering more equitable and inclusive, westill fall short of attracting and retaining students and faculty members from
: MIDFIELD InstituteThe current team of MIDFIELD researchers continues to support this project, including helpingothers learn to use the database. This has involved developing tutorials and designing andfacilitating the MIDFIELD Institute, an online three-day workshop to help researchers learnabout and use MIDFIELD effectively.We have developed detailed tutorials in R that introduce MIDFIELD, key metrics, and examplescenarios. We have created an R data package, midfielddata, that provides a stratified sample ofMIDFIELD data as a publicly available practice data set [1]. The practice data can be accessedand manipulated using midfieldr, an R package that provides tools for studying MIDFIELDstudent unit record data [2].The third MIDFIELD Institute was
, R. (2020). Who's Learning? Using Demographics in EDM Research. Journal of Educational Data Mining, 12(3), 1-30.Wenger, E. (1998). Communities of practice: Learning, meaning, and identity. Cambridge university press.Wenger, E., McDermott, R. A., & Snyder, W. (2002). Cultivating communities of practice: A guide to managing knowledge. Harvard business press
three campuses which each have large commuter populations, having to work while inschool also reduces the amount of time that students can spend engaged in other activities, suchas networking with peers, attending student organization meetings, or studying in student groups.These campus interactions, whether academic in nature or social, are very important forestablishing community and helping students develop STEM identity and sense of belonging. Infact, networking activities can prove to be more impactful on student success than academicinterventions [1]. Developing a sense of belonging and community within the major is crucialfor retention and academic success, in part because students that are connected to a network ofpeers and faculty are
Exploration to Develop an Engineering Identity in Low-Income StudentsAbstractEast Carolina University (ECU) was funded by a multi-institutional Track 3 S-STEM Grant#1930497 in January 2020. The funds from this grant have been used to recruit and support threecohorts of students at ECU and three partnering community colleges. The project is referred tointernally as the PIRATES project for Providing Inclusive Residential and Transfer EngineeringSupport. In addition to funding scholarships, the research aim of this project uses Lee andMatusovich’s Model of Co-Curricular Support for Undergraduate Engineering Students [1] tostudy best practices in co-curricular support for both students who start their pathway towards
’ PerspectivesIntroductionIn 2022 the Chips and Science Act was passed, which aims to bring more advancedsemiconductor manufacturing back to the US while mitigating supply chain risks andmaintaining US technological and economic leadership. Billions in federal investments as wellas commitments from private companies has revealed the next hurdle; the US is facing a growingworkforce shortage in the semiconductor industry [1] with a projected 67,000 unfilledsemiconductor jobs for technicians, engineers, and computer scientists by 2030 [2]. The shortageof STEM students is a major contributor to the problem. Perhaps even more important is the lackof high school curricula on semiconductors despite almost eighty years of history.To address the problem, we proposed a
attention, particularly inengineering and more broadly STEM [1-17]. Additionally, this is evidenced by a notable rise inthe popularity of the terms “neurodiversity” and “neurodivergent”. Specifically, during thepandemic, “neurodivergent” experienced a remarkable surge surpassing "neurodiversity" insearch frequency [18]. This rapidly increasing interest has not only been noted in the publicsphere, but has also precipitated a wave of academic inquiry, seen in the increasing frequency ofscholarly works focusing on various aspects of neurodiversity. Publications have delved into itsimplications within higher education and theoretical explorations of the concept, showcasing adiversity of terminological use that sometimes conflates or ambiguously employs
. Theinterview questions were designed to explore each participant’s specific major selection process.These questions focus on three overarching themes; participants’ personal experiences of theirmajor, specific factors that influenced their choice, and what sources were used to help informtheir decision. Occasionally, follow-up questions were asked to elicit further details or to clarifyresponses. At the end of each interview, the students were asked if there was any additionalinformation they would like to add about their respective major choice. Table 1. Interview questions broken out by category. a. Personal experience b. Influential factor questions c. Informative source questions
StudentsAbstractThis work in progress (WIP) paper focuses on the development and initial validation of a surveyadapting the three identity scales from Godwin’s (2016)1 Engineering Identity measure –Recognition (R), Interest (I), and Competence (C) - to assess research identity formation indoctoral engineering students. This study is a product of an NSF grant (Award No. 2205033)obtained to apply user experience (UX) methods to investigate the process through whichdoctoral engineering students develop their research identity. This survey was conducted during2022 and 2023 for on-site and online Ph.D. students enrolled in various engineering fields at alarge research university in the United States. In addition to the three identity scales, items fromthe survey
various competencies in undergraduate engineering programs.Gloria J Kim, University of Florida Dr. Gloria Kim is an Assistant Professor of Engineering Education at the University of Florida (UF). She is also an affiliate faculty in UF’s Department of Electrical and Computer Engineering. She received her B.S. in chemistry from Seoul National University, M.S. in biomedical engineering from Johns Hopkins University, and Ph.D. in biomedical engineering from Georgia Institute of Technology. As an instructional associate professor, she was awarded several grants from the National Science Foundation (IUSE Level 1, IRES Track 1, I-Corps, and I-Corps for Learning) as principal investigator. She transitioned to tenure track in
summer and freshman fall/spring/summer semesters)curriculum-based STEM-enrichment program called USTEM. USTEM implements high-impactand proven STEM-enrichment activities, practices, and strategies that have been published in theliterature. The research component studies how an original set of creative video projects (CVPs)influences students’ psychosocial, scholastic, and persistence outcomes. This study entailsrandomizing half of each cohort to participate in USTEM without CVPs (USTEM1) and the otherhalf to participate in USTEM with CVPs (USTEM2). USTEM2 participants produce four CVPs:1) a biography of a STEM scientist, 2) a position statement on a STEM controversy, 3) a tutorialon a STEM topic, and 4) a critique of a STEM peer-reviewed
enrichment programs[1]. Universities also turned to Discord to help engage their students and enhance the onlinelearning environment they provided [2, 3, 4, 5]. As Discord becomes more prominent in students’ day-to-day lives, we should aim toidentify how Discord communities are impacting student success. We have scraped 4 semestersworth of conversational data from a college computer science Discord server to help identifyDiscord impacts on student success. In this work in progress paper, we propose an exploratorystudy to identify how an unofficial departmental computer science Discord server is impactingstudents’ education, relationships, job prospects, and more. We welcome any comments andfeedback from the community before we begin our
. We hope to learn what gaps exist in current TA trainingand open the “black box” of office hours. To collect this data, we are using a self-hosted versionof MyDigitalHand, an automated office hours queuing system. We have modified our instance ofMyDigitalHand to collect additional data to answer our research questions.IntroductionOffice hours provide the backbone of communication between course staff, specifically teachingassistants, and students. As the number of students in programming courses has increased,universities have responded with three main solutions: 1) increase staff sizes by hiring moreTeaching Assistants (TA), 2) use automated feedback systems to take augment instructional staff,and 3) deploy systems designed to support TA
motivation.We have identified the following research questions regarding students in a Discrete Mathclass in an introductory CS sequence:RQ1: Do students’ expectations to do well, value of the course, and time spent studyingcontribute to their course outcome?RQ2: Can students who do not expect to do well in the course when they first enter it, cannevertheless engage in study behaviours that lead to positive course outcomes?2 MethodsWe surveyed students in a Discrete Math course at the University of Illinois Urbana-Champaignthree times during Spring 2022. Survey 1 was used to get information about students’ mo-tivation and belonging as they enter the course in the first week of the semester. Surveys 2and 3 were given in the middle and at the end of
users, in two groups of students—with and without priorknowledge of computer networks. The feedback received from both groups verify theeffectiveness of our design that 87.5% of inexperienced learners found intuitive and simple touse; and 70% of experienced users noted that this design helped them review and deepentheir understanding.1 Literature ReviewMultimedia resources are widely used in modern education and provide innovative andeffective learning experiences. Studies on the cognitive advantages of multimedia ineducation, such as Mayer's cognitive theory of multimedia learning, emphasize its potentialto enhance learning through dual coding and multisensory engagement [1]. Among variousmultimedia methods, 3D interactive animation is
systems as well as WebAssembly, withsmooth operation even on low-power devices such as single-board computers. Additionally, thetool is designed to continue to grow via community-driven support – the project is open-sourceand hosted on GitHub, open to public contributions, and will grow as community members addsupport for additional hardware platforms. Features and documentation that will allow for furthercommunity engagement are underway, and the long-term goal of the project is to become apopular and useful tool among open-source development environments, especially in aneducational setting.IntroductionModern open-source hardware ecosystems such as Adafruit’s Feather boards [1], Sparkfun’sMicroMod boards [2], and Raspberry Pi’s single-board
where knowledge might be transferred between participants. Next, we ask RQ3 ,which aims to classify the types of knowledge being transferred and if the knowledge is relevantto what happens during the stream, unrelated off-topic knowledge, or general programmingknowledge. Finally, using previous data, we ask RQ4 to understand if knowledge transfer helps orharms development activities during a live stream.Background and Related WorkInformal Learning OpportunitiesInformal learning opportunities play a crucial part in knowledge sharing and acquisition inundefined and opportunistic ways and are not motivated or bound by specific curriculum [1, 2].Research suggests that informal learning can be effective when individuals can contextualize andsituate
Datastorm challenges. We also plan to host annual full-day Datastormevents, which should provide visibility and outreach opportunities to other undergraduate studentsat our institution as well as highlight the relevance of the Computer Science program to thegeneral public.IntroductionComputer Science and computing based majors in general suffer from a variety of issues at theuniversity level.One of those issues is high drop out rates. The level of attrition in Computer Science is reportedto be between 9.8% [1] and 28% [2]. This represents both a direct loss in terms of students notcompleting the major as well as an indirect loss in terms of students not encouraged to pursue itbecause of a perceived difficulty given its high withdrawal rates.Figure
senior year, they havemastered the art of designing a logic primitive, e.g., a CMOS inverter or a simple circuit, e.g., afull adder. With this knowledge, they have the foundation to pursue graduate studies in VLSI de-sign, which, depending on the university, includes a course that introduces them to logic synthesisand physical design. This approach to teaching VLSI has a lot of shortcomings: (1) students withthe desire to design a microprocessor from scratch have to delay gratification for several years, (2)students must appreciate and have a strong aptitude for each step of the VLSI design process insequential order, (3) most universities do not offer the full sequence of courses needed, and (4)exposure to skills needed is usually not available
,” because they can provideclinicians with “super-human” capabilities. Another important but less well-known area ofapplication is assistive robotics, which has been advancing, but at a slower pace. The “weak link”in development and adoption of assistive robotics is that for such assistive robots to be effective,they need to interact with, respond to, and adapt to the needs of the human/patient they assist [1].The challenge in the design of assistive robots is in selecting the right degree of realism that isrequired to make the assistant effective and accepted by the user. “Temperament” encapsulatesthis particular trait of how robots present themselves to the user [2]. Ideally assistive robotsshould be able to judge whether their user is introverted
fall 2023 section ofCSC 101 piloted a pre- and post-survey to measure their SoB and ASC. Additionally, studentswere interviewed about their experiences on the CoLT course. This survey will be implemented inthree sections of the CSC 101 course in spring 2024. This paper presents the overall researchdesign and preliminary survey responses from fall 2023. Preliminary results demonstrate a positiveimpact on SoB and ASC for students. These results provide encouraging motivation to furtherinvestigate how CoLTs may impact student retention and academic performance in computingmajors.1. Introduction and BackgroundComputer Science and Computer Programming and Information Systems are complex subjectsthat require critical thinking and problem solving for
game design elements into instruction can have in enhancing students’ under- standing of topics such as SOP minimization and Karnaugh maps. These re- sults highlight the importance of future research investigating the educational benefits of applying game-based learning to other introductory logic design topics. IntroductionWithin the field of education research, there has been a significant amount of research comparinginteractive learning methods to more traditional methods [1]. Interactive learning methods typi-cally involve the application of digital media, such as apps and games, to encourage independent,autonomous learning. Traditional learning methods, on the other hand, involve methods that
Engineering Education. He is also selected as an NSF SIARM fellow for the advanced research methods for STEM education research. Dr. Menekse received four Seed-for-Success Awards (in 2017, 2018, 2019, and 2021) from Purdue University’s Excellence in Research Awards programs in recognition of obtaining four external grants of $1 million or more during each year. His research has been generously funded by grants from the Institute of Education Sciences (IES), the U.S. Department of Defense (DoD), Purdue Research Foundation (PRF), and the National Science Foundation (NSF).Ali Alhaddad, Purdue University, West Lafayette ©American Society for Engineering Education, 2024 Work in progress: A