necessitate covering aspects from adiverse range of topics, including fundamentals of digital design, computer architecture, parallelprogramming, and systems thinking. Although such concepts naturally intersect within thediscipline of computer engineering, structural considerations within our master’s programs anddisparate prior knowledge within our cohort entail students inherently experience the subject asinterdisciplinary in nature. This presents numerous challenges in subject design but offers anopportunity for developing interdisciplinary competencies and an appreciation for otherdisciplinary ways of thinking. Based on instructor observations while teaching, we reflect on thesuccesses and shortcomings in the subject’s design that impact
knowledge to elicit performance (Gagne’s Event #6). This is done by applying problem-solving tasks and group projects that require students to apply their abilities in a hands-on manner. The discussion questions and case studies in the course encourage collaboration, experimentation, and creativity and encourage students to solve real-world problems in simulated environments. • The course instructor has a clear plan to offer constructive feedback (Gagne’s Event #7) during discussions and project milestones and after students have submitted assignments. This emphasizes the importance of self-assessment and encourages reflective thinking in students about the concepts they have learned during
change.Impact of the Work on the SELs: It was my first time doing any ADEI work, and I have learned from this experience that it is a very hard thing to navigate. I have learned that I am very passionate about efforts like this, especially ones that I am involved in such as my department, so I have learned that professionally this is something that I want to continue with doing in relation to my career. -KAThe faculty members of the ECO group asked each of the SELs to reflect upon their experiencewith the culture related work. The purpose of the reflection was to better understand theexperience of the students leading the work to help determine what supports they might needgoing forward and the overall impact of the work
provided table file). Operating conditions that do not meet the system requirements should be highlighted red. • Evaluating Solutions Against Requirements – for each solution, evaluate the solution against the requirements. Discuss the strengths and weaknesses of the solution. If the solution does not meet one or more of the requirements, discuss approaches to correcting the issue (which should be reflected in the subsequent solution). At minimum, you must have three iterations. There is always a way to improve your design. • Making Trade-offs – Discuss any trade-offs made throughout the design iteration process. Discuss any other changes that were made throughout the design iteration process and
. Research Team Dr. Walter Lee Malini Josiam Artre Turner Crystal Pee Taylor Johnson Dr. Janice Hall Associate Professor PhD Student PhD Student PhD Student PhD Student Postdoc This material is based upon work supported by the National Science Foundation under Grant No. 1943811. "Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation
design and manufacturing. Chijhi is a teaching assistant in the College of Engineering Education, instructing the Transforming Ideas to Innovation I & II courses, which introduce first-year students to the engineering profession using multidisciplinary, societally relevant content.Dr. Robert P. Loweth, Purdue University Robert P. Loweth (he/him) is a Visiting Assistant Professor in the School of Engineering Education at Purdue University. His research explores how engineering students and practitioners engage stakeholders in their engineering projects, reflect on their social identities, and consider the broader societal contexts of their engineering work. The goals of his research are 1) to develop tools and
, quantitative and qualitative approach to fully comprehendwhat happens holistically during the immersion experience. The goal should be not just to collectobjective data with validated psychometric instruments such as the IDI, but rather to obtain morenuanced insights into the students’ study abroad experience and processing of their sojournsabroad through qualitative analysis of student reflections. Similarly, Cohen et al [10] argue thatsolely relying on quantitative assessment may not bring to light important nuances of thecomplex experience abroad. Likewise, Streitwieser and Light [11] call for placing emphasis onindividual student perceptions and reflections. Most recently, Mu et al [12] have shown thatimportant insights can be gained when zeroing
,reflection notes writing, fits the objectives of the present study of finding whether the machinelearning-based data analysis resulting in similar and usable results as compared with the analysisresults from the inductive process of the grounded theory. Raised as a theory-construction methodthat takes data as the basis for theories to emerge, grounded theory has a unique fit with themachine learning-based analysis approach in that both are inductive in nature.Machine learning (ML)-based or mixed approachesPreviously researchers have conducted ML-based analysis on the sentiment of financial newsreports or labeled information of survey questions [7]. Sentiment analysis is a classification taskthat can be handled by manual labeling of a small set of
processes. Students worked in groups tocreate 3D parts with cultural or historical perspective. Students searched for art forms, traditions, socialhabits, and rituals from the chosen cultural background or a significant time in history and used it asinspiration to create unique CAD designs and then 3D printed models. Students were required to incorporatethe best DfAM practices required to successfully design a part using additive manufacturing. Each studentgroup prepared a poster that was shared in a gallery walk [17]. Everyone explored the variety of culturallyand historically inspired projects during the gallery walk and self-reflected on the information in an essay.Students were encouraged to include thoughts on unconscious bias, norms, habits
scenarios, students are trained to apply engineering ethics knowledge to practice.Implement educational reform in the form of debate competitions, and conduct engineeringethics debate competitions in various engineering ethics course teaching classes. Practical activities not only fully leverage the leading role of teachers, but also reflect thesubjectivity of students. Student debaters can gain a deeper understanding of the basic concepts,principles, guidelines, moral values, public safety obligations, social responsibilities, and otherelements of engineering ethics from different perspectives through discussions and in-depthanalysis of the topic. This can enhance moral awareness, cultivate moral emotions, and regulatemoral behavior. Under the
It has been well established that for adult learning to occur, motivation and reflection must be present[19]. To achieve intrinsic motivation, the learner must have a sense of autonomy, competence, and afeeling of belonging [20]. Educators play a multifaceted role in promoting those needs by activelyfacilitating inclusive and engaging learning experience while tailoring their approach to meet the diverseneeds of adult learning, thereby promoting autonomy and competence[21]. When learners collaborate ona PBL assignment, intrinsic motivation can either be enhanced or disturbed. The determinant factors ofintrinsic motivation level in this case are self-evaluation, attitude of the learning about education, and theimportance of goals [19]. When
countries. his student underscores a motivation for a more equitable world due to the perceived harmTcaused by their high-income country, particularly in terms of the environmental degradation that will affect low-resource communities.I n summary, while the motivations varied among students, this study identified all students at one point expressing a motivation for social justice, often using vocabularies such as justice and equality. While this exploration was not exhaustive in capturing the entirety of students' experiences, we found that students reflected on a spectrum of emotions. These include a sense of solidarity with marginalized populations they once lived with, drawing inspiration from the resilience and
valuable guidance forfuture educational strategies and policies.keywords: curricular complexity, causal inference, student success, graduation rates, educationaldata mining1 IntroductionCurriculum complexity, an intrinsic characteristic of educational programs, has increasingly be-come a focal point of academic research due to its presumed impact on student performance. Thearchitecture of a curriculum – encompassing the breadth and depth of content, the sequencingof subjects, and the interplay of various pedagogical approaches – directly influences the learningenvironment. This influence is often reflected in key educational outcomes such as student engage-ment, comprehension, retention, and graduation rates. The complexity of a curriculum
member’s pre-existing social capital. The cultivation of these relationships in L&L is also reflected inthe culture of the space, as described by participant 5 . ”[L&L] is kind of a very open, inclusive culture. It’s very similar to the ESED culture. [...] Everyone seems to like, get along. They’re happy to see one another and talk.” - Participant 5Participant 5 describes the culture of L&L as inclusive and open. Their statement shows how social capital is facilitated throughL&L, as it promotes an environment where individuals feel welcomed while they join together to discuss education research.L&L provides a semi-formal space to develop graduate student relationships. The semi-formal register of the space is intendedto
answers." This statement reflects the idea that data science involves more than just numerical analysis; it requires an integration of subject matter expertise to ensure meaningful interpretations. • Another perspective offered was, "Data is in sensors and economics in chemical engineering; data science is interpreting these values and creating a story." This view emphasizes the narrative aspect of data science, where data from diverse sources is synthesized into coherent stories that inform decision-making processes.Unsure What Data/Data Science IsA segment of the participants expressed uncertainty about the precise definitions of data and datascience, reflecting a perception of these concepts as
will detail our methodology, present our findings, and discuss the benefitsand limitations of integrating ChatGPT into qualitative analysis for engineering educationresearch.MethodsTo gather qualitative data, our team devised a semi-structured interview protocol comprisingfour segments: introduction and warm-up, engineering identity, teamwork, and conclusion.When time permitted, we asked the interviewees to reflect upon stories of practicing engineers,which were compiled from publicly accessible accounts of the day-to-day experiences ofpracticing engineers. This interview framework and other relevant aspects of our research designreceived approval from our institution’s Institutional Review Board.Throughout the RIEF project, we conducted a
be attributed to the fact that GradTrack’s main focus and mission is the preparation ofstudents for graduate school, particularly with their applications. This theme also emergedfrequently in student reflections as one of the most helpful aspects of the program. One studentreflecting on this said: “I also found all of the resources, examples, and a timeline of when to accomplish certaingraduate school application tasks to be rewarding and allowed me to prepare my applications as best as I could have.”Another student remarked: “I found completing my application documents and getting them reviewed to be the most valuable part about my GradTrack mentorship experience.”Further, within the
disposition towards command line programming, which wasalso reflected in their initial struggle to adjust to using a command line tool. On the other hand,the OOP students showed a better performance and disposition towards command lineprogramming, but this could have been influenced by acquired experiences both prior andexternal with using such tools.1. IntroductionDeveloping ways to effectively teach early computer science (CS) majors how to program hasbeen an important topic of interest for some time. When addressing student learning in earlyprogramming courses, there have been a variety of elements researched and observed, notableones being: 1) the type of paradigms that are ideal for introducing students to programming [1],[2], [3], [4], 2) the
an accessible and reliable assessmentsystem for assessing conceptual STEM understanding for colleges and universities that aligns withSTEM curriculum and uses Artificial Intelligence (AI) based assessment methods. Table 1: Operational Definition of Terms Term Operational Definition Example(s) Proficiency The proficiency of a person reflects the probability • Percentage correct on of answering test items correctly. The higher the static exams. individual’s proficiency, the higher the probability • Theta estimate on CATs. of a correct response. Different fields refer to proficiency as ability, latent trait, theta. Content
unpack tensions, historicalcontext, and practice of a liberal engineering education. Engineers have long positionedthemselves as “problem-solvers” uniquely situated to use technical knowledge to proposesolutions to complex problems. Recent work has identified the need to better integratenontechnical knowledge into engineering education as a way of reflecting the complex social andpolitical landscapes that structure engineering practice (Reddy, Kleine, Parsons, & Nieusma2023). Here we explore using a framework for “engineering as conflict” as a compelling practiceof sociotechnical integration at the undergraduate level. Here, conflict refers to the practice orprocess of disagreement, difference of opinion, or tensions.From the perspective of
parallel study of this project, we aim to further investigate the findings from thisstudy by examining engineering doctoral students’ perceptions on their preparedness to teach varybased on their demographic characteristics, prior teaching experiences and trainings, etc. [16]. Inanother study, we analyze engineering doctoral students’ expectations, reflections, and concernsregarding their future in academia [17].Theoretical FrameworkThe survey instrument developed is grounded in the self-efficacy and self-perception theory. Theself-efficacy theory provides a framework to act as a predictor of how individuals may perform inthe future based on their confidence in their ability in a certain task or domain [18]. According toBandura [19], [20], a
3outcomes. Moreover, antecedents and interpersonal outcomes may differ across contexts,resulting in different ways empathy might be observed and different facets that might be mostcritical to empathy’s manifestation. Thus, for the next stop on our tour of empathy models, weexplore Smeenk, Sturm, and Eggen’s [16] Empathic Formation Compass.Smeenk, Sturm, and Eggen’s Empathic Formation CompassSmeenk and colleagues [16] developed their empathic formation compass through a focus onproviding a model that addresses empathy as a construct and process, supports reflection ondesign action, and focuses on designers’ roles and design decisions. The empathic formationcompass integrates several empathy and design models to create a more robust sense of
& Viable Business Models, Multicultural, and Social Consciousness. This e-portfolio includes but is not limited to undergraduate research, projects, and high-impact experiences that can be leveraged to pursue future academic and professional careers. ombining e-portfolios with an interdisciplinary approach to education scenarios allows us toCperform the analysis of our cohort's growth in varied ways. Previous cohorts were tasked with the performance of a pre-and post-program survey as well as a traditional reflection essay[2]. Extrapolating on that idea and the engineers' inherent drive for innovation, in this 2023 cohort we elevated the research design by adding concept maps to assess student
-evaluation, andactive involvement in learning processes contribute to student's academic experiences andoutcomes. Each construct has been carefully chosen and defined to capture the multifacetednature of student engagement in first-year engineering courses. Building on the theoreticalframeworks we discussed earlier, it's important to note how each construct within our instrumentis aligned with specific dimensions of student engagement in first-year engineering courses.Constructive EngagementCourse Knowledge, reflecting the dimension of constructive engagement, is grounded in theconstructive aspect of Chi's ICAP theory [10]. Michelene Chi's ICAP framework categorizesstudent cognitive engagement into four distinct levels based on their interaction
-credit-hour seminar series on aCredit/No Credit basis in the fall and spring semesters (10 semesters total), which included eightsessions (twice a month) each semester. Students completed up to four semesters of NRTSeminar. The NRT Seminar consisted of training sessions related to inclusion, career pathways,campus resources, science communication, and exposure to FEW research initiatives. Internaland external guest speakers led the seminars. Students completed a reflection activity after eachseminar session. To receive credit for the NRT Seminar, students completed six, out of eight,reflection activities and a required science communication activity.To understand the interdisciplinary nature of FEW resource challenges in rural communities, andto
insufficient training inprerequisite courses has contributed to the poor grades students receive in statics. Failure tofully understand these prerequisites plays a huge role in the high rate of D, F and W grades inthe course.Inconsistent Use of Available ResourcesThis theme reflects the instructors' perceptions of how students utilize the resources providedto assist them. The transcripts from the instructors revealed that students do not fully utilizethe available resources intended to help them understand the course material, whichcontributes to the high rates of D, F, and W grades. The instructors noted students' attendancein recitations and lectures and their willingness to take notes in class. Recitation sessionswere introduced to provide students
Tools/Materials: NGSS-aligned quantum- Fundamental concepts Increase in infused science Teachers’ reflective in quantum quantum curriculum. feedback information science understanding are teachable and engaging within formal Participant + Task science learning Structures
patronization, saviorism, and poverty voyeurism.The Ohio State University (OSU) has been offering engineering service-learning courses sincethe early 2000s, that have spanned mostly the international context. These early courses adopteda traditional approach to service-learning which often did not see the community as co-equalpartners and overlooked systemic inequalities. Reflecting on this period, the success of manyimplemented projects (from Honduras to Haiti) remains unclear. To rectify this and transitionengineering service learning to a critical paradigm, with the aim to deconstruct systems of powerand dismantle the inequalities they perpetuate, a collaborative effort among faculty members,also the authors of this paper, teaching local and
fromcomputer science (University of Maryland Baltimore County) participated in the sustainablerobotic agriculture project and worked closely with undergraduates in Agriculture and Engineeringmajors from the home institution to assist with setting up experiments; collecting and analyzingdata. The students were required to submit a short report reflecting on the experience and resultsof the findings. During the entire academic year, there were 5 students (2 as a part of theirundergraduate research experience; and 3 as part of their paid assistantships) participated in thisproject. Out of the six students; two were from general engineering majors; one from agriculturemajor; one from computer science major; and two were from Biology majors.2.2 Farmbots
literature review (ScLR) conducted toelucidate the current landscape, trends, methods, and potential gaps in the literature surroundingequitable design pedagogy in engineering education. The ScLR follows the methodologypresented by Arksey and O’Malley (2005), which breaks the process into five stages: (1)identifying the research questions, (2) identifying the relevant studies, (3) study selection, (4)charting the data, and (5) collating, summarizing, and reporting the results. These stages wereperformed iteratively, which allowed for reflection and study team collaboration along eachstage. The study was grounded in four central inclusion criteria: (1) equitable design, (2)engineering education, (3) engineering course, and (4) secondary education