Systems), Advisor for Engineers Without Borders (EWB) Purdue and CE 4 ©American Society for Engineering Education, 2024 Lessons Learned through Multi-Year Team Teaching of an Engineering Course for Pre- College StudentsABSTRACTTeam teaching or co-teaching has been present in the K-12 systems for decades and has recentlybecome more common in higher education. Team teaching has been proven effective inimproving student’s knowledge of the subject, increasing student satisfaction due to greaterinstructor support, and increasing positive perceptions associated with the course [1], [2]. Studiesalso suggest that team teaching can enhance instructors’ professional development by providinga
: delayed enrollment into college, part-time enrollment, financialindependence, full-time employment while enrolled in college, have dependents, is a singleparent, and/or did not receive a standard high school diploma [1][2]. NCES also includesstudents over the age of 24 as one of the characteristics of NTS [2].NTS population is increasing as students are attending college on a part-time basis and are takingup part-time or full-time jobs. From 2010 to 2017, part-time student attendance increased from37.7% to 38.9%, and a projected 39.6% growth by 2028 [3]. In 2020, 40% of undergraduatestudents who were attending college on a full-time basis were also employed full-time, indicatinga considerable NTS population [4].NTS make up over 50% of the
Engineering Education, 2024 Lessons Learned: Faculty Development Book Club to Promote Reflection among Engineering Faculty on Mental Health of StudentsIntroductionIt is a real difficult challenge walking through this world full of monsters when our own bodies and minds can be monstrous. - Sarah Rose CavanaghIn universities around the U.S., mental health issues are on the rise [1], [2], [3]. College studentsare at increased mental health risks due to major mental health problems manifesting during earlyadulthood [4], and significant life changes (e.g., changes in independence, environment, and socialsupport, academic pressures/competition) [5], [6]. While
. Farmers are providedwith water level visualization tools accessible on mobile devices that provide a comprehensibleoverview of the water levels over a period of time. As well, intelligent notifications alert farmers toany anomalies or failures, enabling quick intervention to minimize downtime and prevent cropdamage. Future expansion options for this solution are discussed, such as integration of weatherforecasts and live weather data and sensors' deployment in fuel reservoirs to ensure the pump canrun optimally.Key words: IoT, LoRa, Sensors, Smart Agriculture, Water Management 1. IntroductionThe rising prevalence of Internet of Things (IoT) devices is reshaping industries [1]. One keyadvantage is enhanced efficiency and automation, as IoT
theoreticalconcepts in practice.1. IntroductionThe use of hands-on learning devices is a well-accepted instruction method in the active learningdomain [1-6]. It allows students to engage directly with the subject matter which enhancesunderstanding, retention, knowledge, and skills. In addition, hands-on devices provideopportunities to apply theoretical concepts in real-world scenarios that help students bridge thegap between theory and practice, allowing learners to develop practical skills and gain valuablereal-life experiences. Moreover, hands-on projects often involve tackling real-life problems thatnurture critical thinking, problem-solving, and decision-making skills as learners navigate throughobstacles and seek innovative solutions. Furthermore, hands
; teaching ES technical conventions; and building capacityfor project management and project documentation. Engineering students become more accuratein their evaluations of Technical Writing (TW), and better able to distinguish effective andineffective TW after working with these tools. Lastly, teaching students to use ML writing toolsallow engineering educators to effectively promote these learning outcomes in novel ways, whilesupporting professional preparation.1. BackgroundMany higher education institutions are penalizing or restricting students’ use of ArtificialIntelligence (AI) tools at the same time that professors and STEM practitioners are leveragingthem in practical ways. As higher education seeks to identify, control, and in some
al. (2005), ethical leadership refers to “the demonstration ofnormatively appropriate conduct through personal actions and interpersonal relationships, andthe promotion of such conduct to followers through two-way communication, reinforcement, anddecision-making” (p. 120). The researchers developed and validated a ten-item scale to measureethical leadership, which is shown in Table 1. The scale relies on data reported by a followerabout their perceptions of a leader’s commitment to ethics. Table 1: Ethical Leadership Scale My leader conducts his or her personal life in an ethical manner. My leader defines success not just by results but also the way that they are obtained. My leader listens to what employees have to say. My leader
studies [1-3]. Yet, the opportunities to develop, sustain, and grow one’sengineering identity are not uniformly distributed across students enrolled in engineering programs, nor evenamong those select students offered the opportunities to participate in mentored engineering researchinterventions [4]. Indeed, engineering students from underrepresented and structurally marginalized groups may have feweraccess points to engage with engineering peers, mentors, and professionals prior to and during their collegiatestudies [5-7]. These challenges can compound for students who may be underrepresented on multipledimensions in this field, seeing their personal identities reflected less often in their intended engineering careers(e.g., gender, sexuality
mechanical engineering courses with sustainability and the percentage ofBachelor’s degrees earned by females when relationships were explored within single states andeither public or private institutions. This preliminary work suggests that sustainability may helpattract and retain female students to mechanical engineering, sparking interest in future research.IntroductionMechanical engineers can play an important role in contributing to a sustainable future [1, 2].Key concepts in sustainability include environmental impacts (over the cradle to grave lifecycleincluding greenhouse gas emissions, natural resource conservation, pollution minimization,energy issues), societal impacts (poverty alleviation, safety), and economics. Many institutionsoffer
extends beyond examining conventional forms of peermentoring by examining the work of peer mentors supporting students’ work in a first-yearengineering design course based in a makerspace classroom. The problems students solve in themakerspace classroom-based course typically have a wide array of possible solutions, whichdiffers from many problems students solve in traditional courses with peer mentor support.Further, students in the makerspace classroom-based course are also expected to work in teams,which adds another layer of complexity to the role of the peer mentors working in the course.Review of LiteratureSocial SkillsSocial skills are critical for the success of professional engineers [1, 2]. Because the developmentand expressions of
individualism andexceptionalism through the interdisciplinary and theoretical lens of Critical Race Theory andCritical Whiteness Studies has highlighted the ways Whiteness has flourished, particularly inengineering, and helped support these two pillars of Whiteness. Thus, through a historicallycontextualized interdisciplinary analysis, we seek to shift the conversation to focus onquestioning the ways Whiteness affects pedagogy and research conducted in engineeringeducation research.Introduction White supremacy has a firm grip on engineering and engineering education research.However, in order to show “The Enduring, Invisible, and Ubiquitous Centrality of Whiteness,”[1], we will provide a funneled context that will demonstrate to the reader how
evaluation of the program’s newly launched undergraduate design studiocourse.1 This involved conducting nine months of ethnographic research involving interviewswith faculty and administrators involved in the program’s initial design, observations ofclassroom activities, and follow up interviews and focus groups with the first cohort of students.In the process we gathered insights that provided feedback to faculty and staff that could helpfurther develop the curricular aims of the program, while also theorizing through ourethnographic project how external evaluations can contribute to the development oftransdisciplinary learning communities in higher education. Our external evaluation activity ispresented here as a case study that considers how
Knowledge creation and synthesis are the core of research. How we engage in research orknowledge creation is deeply intertwined with our experiences and the language we use to makesense of the world around us. For us, the co-authors of this paper, the triad concept of Kaya(Body), Vacha (Speech), and Manas (Mind) in the Indian philosophy of ethics and spiritualitypoints to the interdependence of experience, language, and knowledge. Lakoff and Johnson [1]present the same idea as the core motivation for their germinal book Metaphors We Live By; theysuggest that dominant views on meaning-making in Western philosophy and linguistics areinadequate for the way we understand our world and ourselves. They propose that our languageshapes the way we think
wellbeing and equity, diversity and inclusion (EDI) issues in engineering education andthe broader engineering profession. ©American Society for Engineering Education, 2024 Methodologies for evaluating the impact of STEM outreach on historically marginalized groups in engineering: a systematic literature reviewIntroduction and BackgroundAs a form of informal science learning [1], STEM (Science, Technology, Engineering, andMathematics) outreach activities involve the delivery of “STEM content outside of thetraditional student/teacher relationship to STEM stakeholders (students, parents, teachers…) inorder to support and increase the understanding, awareness, and interest in STEM disciplines”[2]. In the K-12 out-of-school
purpose of this practice paper is to suggest a mechanical engineering reasoning diagram(MERD) for equitable teaching in writing-intensive engineering labs 1. Reasoning diagrams aredesigned to describe concepts and the relationships among these concepts in a structured andvisual way. In order to facilitate engineering thinking among undergraduates, a MERD wasdeveloped in this study to capture engineer experts' narratives about their projects and the logicof key Mechanical Engineering (ME) concepts. The model of engineering thinking would alsodemonstrate rhetorical moves of the technical writing process of engineering; this mentalmodeling relates metacognitive knowledge to disciplinary writing. A more explicit way ofteaching lab writing might have
outcomes revealed a higher correlation than homeworkassessments, highlighting the predictive value of such assessments for academic success. Pre/postlecture assessment enables immediate student feedback and the instructor's use of their input forteaching improvements underscores the potential to enhance educational strategies and supportstudent learning. Ultimately, the study advocates for incorporating pre- and post-lectureassessments in courses. This dual benefit approach not only aids students in enhancing theirlearning experience but also provides instructors with early indicators to identify and assiststudents who may need additional support.Figure 1. Integrating Pre/Post Lecture Self-Assessments of Lecture Learning Outcome withBloom's
recognition of the importance of diversity and inclusion in engineering education hasgrown in recent years [1], little is known about the best practices for supporting neurodiversestudents [2-3]. It has been suggested that neurodiverse students benefit from course assessmentsthat allow for a more flexible mode of expressing knowledge [3]. However, evidence forimproved learning outcomes on different types of course assessments is largely anecdotal.Characteristics associated with different forms of neurodiversity, such as attention deficithyperactivity disorder (ADHD), autism spectrum, depression, and anxiety, are suggested to benormally distributed in the population [2]. Indeed, research suggests that these conditions arebest conceptualized as
discourse ondiversity, equity, and inclusion in engineering. Nonbinary and trans* students are rarely even thefocus of research centering on LGBTQ+ student experiences in larger fields such as STEMeducation and higher education studies. Their exclusion can be attributed, in part, to the lack ofdata collected in large national datasets [1], [2], [3]. For instance, the National ScienceFoundation (NSF) has received multiple open letters requesting that NSF collect nonbinary andtransgender identities in their Survey of Earned Doctorates and NSF Center for Science andEngineering Statistics surveys [4], [5], [6]. But the release of the 2024 Survey of EarnedDoctorates revealed they had not heeded these calls; it also omits sexual orientation altogether[7
academy to improve engineering education within the field and across disciplines. ©American Society for Engineering Education, 2024 Not for the Poor: Impacts of COVID-19 on Engineering Students from Lower Socioeconomic BackgroundsIntroductionLike many other fields, engineering is working to become more diverse. Part of this effort includessupporting students pursuing a field who do not fit the traditional archetype of an engineer [1].This outlier population is heavily composed of students who have an intersection of identities, oneof these identities being a member of a low-income household [1]. The COVID-19 pandemicevoked major changes in the lives of many individuals and
skilled professions, incoming faculty have hardly, if any, pedagogical preparation [1],especially on theoretical underpinnings of teaching and the science of how students learn.Paradigm shifts in engineering education have been focused on instructional behaviors, such asactive learning where students are provided opportunity to learn the practice of engineeringthrough “doing” [2]. Rarely do these opportunities include a focus on the relational or affectiveaspects of education, rather, they focus on design and building [2].Learning through practice is not specific to engineering education. In nursing programs, similarapproaches towards teaching and learning are utilized to engage students to learn the practice ofnursing through “doing” [2]. Both
experiencing logistical challenges. In what follows, we shareideas from the literature and from our own observations about engagement-related conflict ondesign teams, and then address the use of MR simulations in educational environments.Engagement-Related Conflict on Engineering Design TeamsTeam-based work is a fundamental tenant of design thinking and the work of an engineer; it iscritical that undergraduate engineering programs include team-based design projects throughoutthe curriculum [1]. The literature has reported on the benefits of and best practices for studentsengaged in team-based design projects [2-4]. Also addressed in the literature are challengesrelated to teamwork, especially with respect to conflicts related to interpersonal dynamics
approach [1], which labels sometraits and conditions as deficits, and where individuals who are neurodivergent (ND) areperceived as abnormal and less competent than neurotypical (NT) students. Others use socio-ecological approaches and asset models when exploring differences [2-3]. This research used theframework of neurodiversity. Neurodiversity frames different neurological conditions of thebrain and nervous system as providing affordances and posing challenges, encompassing bothindividual and social aspects [4].Conditions that are traditionally defined as neurodivergent include attention deficit hyperactivitydisorder (ADHD), autism spectrum disorder (ASD), dyslexia, dyscalculia, dysgraphia, andtrauma-related conditions such as traumatic brain
education.KeywordsStudent-initiated interest groups, engineering leadership, experiential learning, bio-inspiredrobotics, Guinness World Record, electric vehicle technologies, international awardBackgroundThis practice paper introduces a program designed to cultivate the development of student-initiated interest groups (SIGs) with a focus on technological innovation and challenge-basedlearning within the engineering faculty of the University of Hong Kong. In December 2020, thefaculty inaugurated a 2,000-square-meter Tam Wing Fan Innovation Wing [1] (a.k.a. the HKUInno Wing) at a prominent location on campus. This center serves as the hub for the SIGprogram, equipped with cutting-edge prototyping facilities and extensive project spaces. Settingitself apart from
, including engineering sketches like Free Body Diagrams. This paper approaches theidea of using automated grading in conjunction with the SMART pedagogical methodology.SMARTThe supported mastery assessment through repeated testing (SMART) model discouragesineffective studying habits such as problem memorization and copying of homework solutionsfrom various sources such as online sources, solution manuals, and friends [1]. Not only does itdiscourage bad learning habits, it has also been shown to improve student understanding andproblem-solving ability by encouraging students to better understand theory and concepts whichcan be seen through help room and office hours interactions with students [2,3]. While somecourse dependent modifications may be
we complete our study, we believe our findings will sketch the early stages of thisemerging paradigm shift in the assessment of undergraduate engineering education, offering anovel perspective on the discourse surrounding evaluation strategies in the field. These insightsare vital for stakeholders such as policymakers, educational leaders, and instructors, as they havesignificant ramifications for policy development, curriculum planning, and the broader dialogueon integrating GAI into educational evaluation.1. IntroductionThe advent of generative artificial intelligence (GAI) has heralded a new era in higher education,prompting extensive research and discussions, particularly concerning its impact on traditionalassessment practices. Recent
grader toprocess the work and provide feedback. Lengthy feedback times are suboptimal from a learningperspective since the student may miss opportunities to learn from the feedback. Faster feedbackresults in better learning because the feedback has better connection to the work when thememory of the work is fresh.One way to reduce grading time is to employ low-resolution grading, that is, grading methods thatuse low numbers of possible grade levels. Grading on a scale of 100% without fractionalpercentage points has 100 levels. Grading on an A-B-C-D-F scale without pluses and minuses hasfive levels. Miguel and Larson 1 recommend using the lowest number of grading levels that allowsan accurate assessment of student learning, and they state that
state power, occupy an important nexus of power in the modern social system[1]. Throughout its history in the United States, the occupation-turned-profession of engineeringhas grown and expanded in service to a state and the multinational corporations it leverages itsmonopoly on violence to protect, as numerous scholars have named (see for example [1-3]).Overwhelmingly, US engineers are trained to accept and uphold an ideology of businessprofessionalism that situates engineers as rightly beholden to the whims of capitalists helmingmultinational corporations and industries employing engineers [4]; [5]. This acts to disciplineengineers and restrict the legitimized forms of social organization engineers engage in largely tothose which reproduce
adeeply introspective lens through which we can understand broader social phenomena. Inspiredby the work of Guyotte & Sochacka (2016) and Blalock & Akehi (2017), we expand upontraditional autoethnography and emphasize the synergistic effects of our diverse backgrounds,academic and non-academic training, and worldviews. Collaborative autoethnography enhancesthe trustworthiness and transparency of our research, providing a comprehensive and inclusiveperspective on the experiences of non-academic engineering educators.Collaborative autoethnography is effective for three reasons: 1) Personal and ContextualInsights: This method enables authors, as research subjects, to draw upon their experiences,offering a nuanced understanding of the
institutions in four states tosubsidize 160 internships for community college students.These structured and supported internships consisted of the following best practices:Financial Support 1 ● Stipends of at least $7,000 were provided to participants. Partners recognize that finances are a major barrier to persistence in STEM undergraduate pathways, and many low- income/first-generation students work simultaneously while attending school. Students need a competitive financial incentive to mirror top internships in the field. ● Leveraging funds to pay for internship positions prioritized for STEM Core students. Growth Sector
perseverance and motivation to completebaccalaureate studies in an engineering-oriented field. The SBP has enrolled freshman andsophomore level students from TAMUK, as well as community colleges and other universitieswithin the south Texas region. Team-based design projects were one of the major componentsincluded in each year of the SBP. These short design projects centered around the disciplines ofthe participating faculty, chemical, civil, mechanical, electrical, industrial engineering, computerscience, and industrial technology. This paper presents the outcomes for students based on theirparticipation in one of the SBPs held during the past four years at our Hispanic-majorityinstitution [1].The first two years of this SBP (2020 and 2021) were