learning, enabling students to comprehend, reflect, and apply their learning toward solving new problems. Al- though critical thinking could be used toward solving challenging problems, it is sometimes considered as a similar concept of “challenging level” among students and instructors. This study aims to investigate this similarity issue by evaluating students’ opinions based on critical thinking, and challenging level of course as- signments in computer and software engineering courses. Students are asked to rank each assignment based on how much each assignment stimulated their critical think- ing, and how much it challenged them. Moreover, instructors provide their opinions about critical components of each course assignment for
were also encouraged to conduct a class debriefingsession related to the questionnaire content as either an orientation or reflection, at the beginningor end of the course, respectively. Because it was conducted as a class activity, it was permittedthat all students would complete the items; however, student assent and parent consent wereneeded for student data to be included in our analysis.Student ParticipantsExamining the construct validity of the questionnaire was conducted in two stages, first for EFA,then for CFA. The data for each stage were drawn from consenting student responses to the itemsat 6 high schools in consecutive years. In the first year, nearly 500 students were enrolled in theclasses, but the number of fully consenting
is occurringabout how to best utilize AI tools such as ChatGPT. For example, a recent Chronicle article [2]outlined one student’s positive experiences in leveraging ChatGPT to get some specific advicetowards an assignment. This work touches on a newly developing field called “promptengineering.” The reader is referred to the article by Lo [3] to provide additional guidance to usersof AI tools, pointing to the CLEAR Framework acronym (Concise, Logical, Explicit, Adaptiveand Reflective). These concepts have also been discussed in several forums, including the chemicalengineering division of ASEE at the 2023 meeting [4], and provide a framework for our modeldevelopment.Development of a college-level / university-specific chatbot would be
strangest thing I learned is that the height of a population is not always tied to genetics. … Humans are a lot more similar than we give each other credit for and the barriers of race, genetics, or even politics are very thin. At the end of the day, everybody is just human [emphasis added].”What a powerful statement from a student growing in understanding of people, planet,prosperity, partnerships, and peace, or the 5 Ps.This example reflects an approach to people that is atypical for many students of engineeringwho often focus on the technical and economic aspects of engineering design and problemsolving. By engaging with aspects of public environmental health nursing, such as understandingpeople as individuals
enhancingteamwork skills among STEM students, underscoring the importance of behavioral theory ineducational strategy development.IntroductionTeamwork in STEM education holds paramount significance as it mirrors the collaborativenature of modern professional workplaces. STEM field involves solving complex problems thatrequire multidisciplinary approaches with effective teamwork [1]. This necessity is reflected inthe curriculum of STEM education, which frequently incorporates project work and groupassignments to simulate real-world challenges. These educational strategies are not just aboutteaching technical skills; they are also about fostering an environment where students learn tocollaborate effectively, share ideas, negotiate solutions, and manage group
blendof curriculum modification, textbook selection, grading policy refinement, an interactiveimplementation structure, and a meticulously crafted week-by-week schedule. Thiscomprehensive approach ensures alignment with the overarching goal of equipping students witha complete understanding of automotive engineering principles, encompassing both traditionaland emerging technologies.The first step in reshaping the Automotive Engineering course involves a modification of thecourse description to reflect the expanded scope and objectives of the revamped curriculum. Thismodification is guided by the recognition that the automotive industry is undergoing a profoundtransformation with the emergence of EVs and AI integration into vehicle systems. As
, instructors, staff, and administratorscan observe data directly from the students, allowing them to make more informed decisionsabout the programs, courses, and curricula they offer within their departments.Methods This paper describes the results of a mixed methods explanatory design-based researchand development project involving the implementation of project interventions in authenticcontexts for iterative, real-world data collection and analysis. The initial survey was a modified version of the original MAE [2]. Modificationsincluded changing verbiage to reflect the course in which the SPECTRA students were involved.The original survey was meant to be taken in core curriculum classes for each participant'sdegree program. The new
imaginative context invoked by the comparison may influenceaudience response. Implied comparisons are powerful modes of representation andcommunication but notoriously imprecise, in part because what is evoked depends a great deal onthe knowledge and prior experience of the audience. Analogical reasoning puts us in a position tobe more deliberate in our choice of analogies and more creative with respect to the rhetoricalstrategies we use. As the next section explains, our choice of rhetorical strategy should reflect thekind of relationship we wish to establish with the intended audience.III. A New Metaphor for the Discourse on Diversity: FromOration to ConversationBoth classical rhetoric and modern social psychology suggest that conversation is a
the motors by selecting sensor values and their corresponding motorpositions in the training mode. Subsequently, the motor determines the position based on thesensor input using a nearest neighbor algorithm in the running mode.MethodsResearch Question: What makes teachers’ confidence in using and teaching ML emergingtechnology tools shift?Background: Several participants in this co-design workshop had taught in themachine-learning workshop in the summer of 2022 with upper elementary school students[22].Based on their feedback and reflections we learned that they were confused about the curriculaand activities design, and they didn’t have enough confidence to teach emerging technologieswithout professional training. They suggested we improve
understanding of how the design problem-solving behaviors ofundergraduate engineering participants differ based on their levels of spatial ability while, whysuch differences exist and how they might affect their learning outcomes is yet to be known. Futureresearch provide us some insight into it.ACKNOWLEDGMENTSThis work was made possible by a grant from the National Science Foundation (NSF #2020785).Any opinions, findings, and conclusions, or recommendations expressed in this material arethose of the authors and do not necessarily reflect the views of the National Science Foundation. 11REFERENCES 1. R. Gorska and S. Sorby, "Testing instruments for the
decision-making, and an appropriate division of labor in thedevelopment of the software.The resulting computer program with an intuitively designed user interface allows thesimulation of different scenarios due to a variety of adjustable parameters. The visual outputof the program reflects the different model assumptions and thus promotes the understandingof model building in general and of self-organization and swarm behavior in particular. Theprogram is freely available and can be downloaded from our institution’s home page.IntroductionSwarm behavior, often exemplified by the coordinated movement of birds or fish, has longcaptivated the fascination of scientists, engineers, and nature enthusiasts alike. The collectiveintelligence displayed by
backgrounds and their struggles are reflected in a higher rate ofD/F/W’s (18% in Fall 2021) than students entering at other calculus levels.Mastery grading was introduced in Calculus I in Fall 2022, largely to address disparities in thepreparation of the students, and to combat anxiety and lack of confidence. Key features ofmastery grading include breaking the course material into distinct learning outcomes. Studentsare allowed multiple attempts to demonstrate mastery in each learning outcome [1]. Thisapproach aims to create a supportive and inclusive environment where students can achievemastery at their own pace and foster a growth mindset by emphasizing continual learning overgrades. Two sections were taught using the mastery grading approach, and
] synthesized a set of characteristics and teaching/learningpractices from the literature. First, constructivism assumes that we all have unique perspectives;thus, there are multiple perspectives and representations of different concepts or learning topics.Further, activities should encourage individuals to participate in learning processes of self-analysis and self-reflection. One of the best ways to facilitate this process is to foster learningenvironments that emphasize the “real world” through relevant and authentic practices. Littleton[35] highlights the relevance of Murphy’s principles within museum settings as an ideal place tofoster constructivist learning.Stemming from constructivist theory, active learning is a pedagogical approach that
-audio.Guiding Theory: Identity and agency in figured worldsThe overarching framework guiding the A4I Project is Identity and Agency in Figured Worlds.Holland and colleagues [8] introduced this conceptual framework to elucidate the intricatedynamics between social systems and individuals. They define it as the realized capacity of anindividual to deliberately and reflectively engage in activities situated within "socially-produced,culturally-constructed" contexts (i.e., figured worlds, [8], p. 40-41). In this project, we use thisframework to conceptualize engineering education as figured world in addition to others, such asrace and gender, that overlap and influence students’ experiences in their engineering programs.As students iteratively interact
by Chinese-American,Anglo-Indian, or Latino writers [15]. Code-switching can take on various forms, but in this paper,we define it as the use of both Spanish and English in bilingual communication. This showcasesthe intricate linguistic dance that bilingual speakers engage in, which reflects a blend of linguis-tic choice and cultural narrative. This phenomenon is especially prominent in communities whereboth languages are woven into the social and cultural fabric, allowing individuals to fluidly navigatetheir bilingual identities [16], [17]. Beyond simple language mixing, code-switching incorporatesa sophisticated amalgamation of grammatical structures, cultural cues, and contextual relevance,highlighting the cognitive dexterity of bilingual
interactions. Again, this section reflects the NSF emphasis on working cohesively acrossdifferent institutions, disciplines, and areas of expertise to solve large, complex problems.Section 3. Culture of Inclusion Items: Respondents are presented with 11 items, based on theliterature, that measure feelings of inclusion within a group. When we present the visual forcommunicating about the survey below, we will discuss the evidence in support of using it. In the2022 survey, these items were presented to each respondent randomly. The reason for this was todetermine if these 11 items still fell into two factors as they did in 2021, even when not presentedtogether as sets of items.Section 4: Recruiting and Mentoring Activities: In previous iterations of the
include foundational sustainability principles, corporateenvironmental, social, and governance (ESG) reporting, decarbonization, sustainability inmaterials, life cycle assessment (LCA), renewable energy, and sustainable engineering designprinciples. In addition, students participate in three lab components—two experiments and onedemonstration—exploring alternative energy sources including the production of H2 fuel, solarpower, and polymer pyrolysis to fuel oil. Student learning is assessed through reflection papers atthe end of each unit, two lab reports, and a group project at the end of the semester. A newcourse in LCA will be taught in the department in Spring 2024 to supplement the sustainabilitycurriculum.The Introduction to Sustainable
significantly increased duringthe semester for the group of students exposed to the design sprint early on. Students whocompleted the design sprint later in the semester reported an increase in engineering identitymetrics, but it was not statistically significant. Interestingly, survey results indicate both thedesign sprint and an environmental engineering water filter challenge provided students anopportunity to reflect on the EM. Findings support other work that shows an increase inengineering identity in first-year engineering experiences. Future work will examine howengineering identity and EM differ across demographics and students’ selected majors.ResourcesA “Card” – i.e., an information repository – has been created for this paper on the
efficiency [9]. Integrating Lean SixSigma further bolsters comprehensive process optimization, reflecting the ongoing evolution ofquality engineering practices [10].The dynamic nature of today's industrial operations demands a workforce that is theoreticallyknowledgeable and practically proficient in applying quality engineering principles [11]. Withthe increasing complexity of manufacturing processes and the integration of new technologies,effectively utilizing quality tools has become crucial for ensuring efficiency, reducing waste, andmaintaining competitive advantage [12]. Moreover, integrating quality engineering principles iscritical to achieving operational excellence and customer satisfaction [13].In response to this need, the significance
increasingly directinfluence on higher education [8], [9]. Further, the specific institutional relations formedbetween AMUT and MIT reflect the friendly relations between the U.S. and Iran in the 1970s,and routine educational and cultural interactions between the nations in that era [11]. Mutualnational interests and reciprocity were built into the fabric of U.S.-Iran relations. For the U.S.,the Shah was the most significant strategic ally in the Middle East, truly an unimaginable featureof U.S. policymaking in the current geopolitical context. Further, as early as the 1950s, the Shahhad actively recruited those he deemed the most talented of Iranian students to attend Westerninstitutions for graduate education and return with advanced skills to lead
cingulate cortex regions of the brain, has been linkedto inhibition control [26-27]. A section of the literature highlights the N400, a prominent negativecomponent peaking around 400 milliseconds, as pertinent to interference control in Stroop tasks[28-29]. The N400 reflects the higher cognitive demand involved in managing the interferencebetween conflicting sources of information, such as ink color and word name in incongruentconditions. Additionally, alongside the N200 and N400, studies have reported a late negativity infrontal regions or a late positivity in centro-parietal regions, typically occurring around 600milliseconds [29-30]. These late components are indicative of processes like executiveengagement, conflict resolution, response
the 2D plane. MARVLS provides opportunities for students to reflect on interactions with the physicalcube and digital model by allowing students to rotate digital model by rotating the cube. Thisallows students to manipulate aspects of the digital models by modifying current flow, shape ofcomponents, and orientation of the system to explore complex interactions between objects andfields. Activities then scaffold students to map these interactions to formalisms, such as Lorentzforces, Gauss’s Law, and Ampere’s Law, as well as abstractions, such as mathematical equationslike Maxwell’s equations. By connecting equations and formalisms to a variety of actionsgrounded in conceptual metaphors and intuitive understanding, MARVLS facilitates
frameworks to foster environments of intrinsic knowledgedevelopment [8, 9]. Kolb’s learning model [10], for example, defines a cyclic four-stage model(concrete experience or “feeling”, reflective observation or “watching”, abstractconceptualization or “thinking”, and active experimentation or “doing”) which considers“learning” as a continuum, rather than discrete pockets of time, and generates intrinsicmotivation in learners. Similarly, authors Poitras & Poitras [11] stated the importance ofapprentice style education for engineering, an approach that leverages active participation,hands-on exercises, and active experimentation, and use technology to enhance learningoutcomes and facilitate the understanding of industry workflows and the
group due to the low materials cost of the activity. This meant building eight kits perclassroom set. The team at Southern Illinois University chose a group size of 5 middle or highschool students per group due to the larger physical dimensions of their activity, which meantthat 4 kits were constructed per classroom set with an expected enrollment of approximately 20students per class. The size of the classroom set also reflected the need for the kits to be portable.Both sets of kits were sized to fit neatly into one or two large plastic totes. Each team created two classroom sets of equipment necessary to perform the labs. In lateApril, three weeks before the end of the semester, the full group held a second in-personmeeting. At this
their curriculum development project also revealed their increasedawareness of their own understanding of the material and the challenges for curriculum design.Based on the feedback provided by the first cohort of students to receive this project, the nextoffering of the project will have students present a rough draft of their curriculum in class atmidterm to receive feedback from their peers. Each student will then also participate in amidterm interview with the instructor to discuss how to incorporate that feedback in their finaldeliverable. The authors hope these changes will help students make further progress on theircurriculum design, but also provide the students additional opportunities to reflect on and learnfrom the curriculum
Engineering Technology, the careeris Engineering” trademarked by the American Society for Engineering Education reflected thetypical experience of ET graduates. However, despite these and other efforts to assert that ETis a separate but equal, less mathematically rigorous, more practical pathway to a traditionalengineering career, this messaging is often inconsistent with the reality of opportunities andadvancement in college and after graduation. Many employers do not hire ET graduates forengineering positions for a variety of reasons, including a lack of familiarity with the preparation 1and qualifications of ET graduates, and the tendency for many employers to still associate ETwith a two-year
majorityof respondents rating it as "Very Well" or "Extremely Well." This reflects an elevated level ofsatisfaction with the AI’s ability to streamline and refine lecture content, removing unnecessaryelements such as pauses and distractions. However, a small group of the participants rated thisaspect as "Well," suggesting some room for improvement in content refinement.(c) Utility of Final Segmented Lecture ProductWe noticed a wide variation in the responses to the question of the utility of the final segmentedlecture which was one of the products of Transcriptto. One participant rated the product as notvery useful, but a majority of the respondents did find the product to the somewhat useful to veryuseful. The focus group data were used to
speeches. It involves analyzing a speaker's tone, pitch, tempo, andvolume to determine their emotional state. This process is complex as it requires not only wordrecognition but also an understanding of the delivery that reflects various emotional states [1].In utterance-level SER, emotions are classified for an entire spoken utterance, typically acomplete thought or statement. Here the emotions are considered as attributes of the wholeutterance, disregarding the temporal variations within it. The goal is to identify the dominantemotion conveyed in the utterance.Frame-level SER delves into a more detailed analysis by breaking the speech into smallersegments, often milliseconds long [2]. This approach allows the detection of emotional changeswithin
requirement for all students in the program, students will consider thecollapse of the skywalks in the Hyatt Regency in Kansas City, MO in a module similar to the onedescribed by Bottomley [12]. In Internship Reflection, students are equipped to seek discernmentof vocational plans based on their internship experience, the readings and discussions throughoutthe semester, and alignment with their personal values, beliefs, and goals. The aforementionedvirtue ethical theory helps students connect what they want to do with who they want to become. Shared Curriculum Engineering Major Core 150 Required for all students Statics Required Core 250 Required for
contexts is in generating the correct prompt, to assure that the technology willrespond as expected by the teacher. Prompt engineering can be described as a combination of AI,linguistics, and UX [18]. One of the possible frameworks to craft efficient prompts is CLEAR, a5 components model depicted in Table 1, that stands for Concise, Logical, Explicit, Adaptive,and Reflective [19].Table 1. CLEAR framework for prompt engineering Model Component Description C Concise Prompts must be short and have clarity on what they state L Logical Prompts must be structured and coherent E Explicit Prompts must clearly specify inputs and outputs A Adaptive