courses are so rigorous that the cost of fully engaging intheir engineering courses is high.Consistent with existing literature that use multiple elements of value to investigate the nuancesin academic outcomes [28], [29], [32], this study uses items that both reflect intrinsic and utilityvalue. In addition to expectancy and value measures, several control variables are relevant to thisstudy of cognitive engagement. Specifically, we control for gender, race, ethnicity, familyincome, first generation status, and international student status in our regression models. We alsostudy the contribution of broad prior interests (to pursue engineering) as well as more specificintrinsic interests to self-efficacy, value, and ultimately to cognitive
timeline that reflects theresearcher’s tenure at the university. At this level, faculty members can tailor meaningful projectsfor researchers over a set period. The last and broadest level of participation is short-termengagement through undergraduate and graduate courses. For short-term engagement, studentsparticipate in community-based class projects for one semester or can take elective courses thatoffer community-based research. With short-term engagement, students apply concepts ofcommunity-based research. This participatory approach serves as an opportunity for students toconduct research and advance into mid-term engagement opportunities (Figure 1). These levels ofengagement provide a more diverse audience that is engaged in community-based
learn. For example, according to the Carnegie Initiative on the Doctorate, a well-structured program should be purposeful (i.e., programmatic requirements and elements should be aligned with specific goals). It should also be created by a process of iterative individual and collective reflection, transparent (i.e., collectively understood by the faculty and graduate students), and accessible (i.e., elements can be evaluated in terms of their contribution in achieving the purposes of the program) (Golde et al., 2006).● A cascading mentorship model works well, in which members of research groups receive mentorship from more senior members and provide it to more junior members (Feldon et al., 2019).● Institutional
populated by male students. Among the faculty members present was the First-Year Engineering Programs Coordinator, who posed questions about the program and soughtsuggestions on how OWISE and other faculty members could enhance and support their first-year experience.The students expressed positive reflections on their first year but highlighted certain aspects ofthe course that felt intimidating. Many shared their experiences of entering classespredominantly composed of male students, feeling overwhelmed and uncertain about where tosit—a notable departure from their high school environments. Additionally, they conveyedfeelings of under-confidence and intimidation, particularly when dealing with fabricationequipment used in the courses. There was a
, 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
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
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
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
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
-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
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
inequality, ignoring communityquestions and concerns, or failing to consider the consequences of communities when assessingprogram success [14]. The research tested CC with 150 students in two US universities through asurvey consisting of 46 items that capture systems of oppression in civil engineering throughthree indicators (Critical Reflection: Perceived Inequality; Critical Reflection: Egalitarianism;and Critical Action: Sociopolitical Perception). The study highlighted that such an instrumentcan also be used to assess ABET SOs 2 and 4.Baideme et al. conducted an evaluation on how group learning impacted the curriculum andcourses across junior- and senior-level environmental engineering courses at 14 institutions,considering ABET SO 5 which
further tested for student motivation in the future.Maalouf and Putzeys (2020) blended multiple interventions focusing on learning withtechnology and conducted a hybrid classroom before the pandemic lockdown. The paper waswell structured and used a very consistent standardized language and presented every aspect ofits work in detail explaining how they conducted their intervention and why. Their outcomeswere similar to Davishahl et al. (2022) in the sense that despite its results lacking significance,the students’ written and surveyed responses showed a preference for new changes incomparison to other previous traditional courses.Goldberg et al. (2015) conducted a practice-based intervention focused on student reflection andself-regulation
only presented in English [7] and inaccurate assessment results that may artificiallylower GPAs [7], these factors generate a potential hardship and disadvantage in any STEM internshipapplication process.In attempts to remove these barriers, the traditional cover letter and resume application format were substitutedwith visual application requirements designed to reflect a candidates’ enthusiasm for STEM topics and aninsight into persistence and problem-solving abilities. Additionally, the PROPEL team created 1-2 min. videoswith host labs that relate the lab focus and the summer internship project. Applicants were asked to write a brief,250-word essay reflecting on a personal or academic challenge. This enabled the PROPEL applicationcommittee
theclosing of the university campus and makerspace. When classes resumed in-person, themakerspace did not return to pre-pandemic student usage levels. As a result of this down-time inworking with students, both students and university staff had the opportunity to re-designsystems, including hiring. This forced pause and reflection, while not ideal, was an importantlesson learned to remind staff to re-evaluate existing systems. This shift resulted in a staff thatwas close to pre-pandemic gender parity levels at the time of interviews in 2022. One female-identifying student staff member described the this as “a good thing, In engineering, I have faceddiscrimination, of course, just being one of the minority women. I know in petroleumengineering, we're
understanding of these students’ experiences. Todate, the research team has recruited and conducted Zoom interviews with 22 undergraduateengineering students from over 11 universities. The interviews consist of three major parts: 1)Students’ identity and impact on lives, 2) Engineering-related experiences, and 3) Reflection andGiving Back to the community. The details of the bigger project are described elsewhere [17]. 4We adopted narrative and discourse analysis techniques [18], [19] to construct narratives fromthe transcribed interviews. Constructed narratives centered around the final question of ourinterview protocol (i.e., “If you could tell
similardistricts.To accomplish the goal of including emergent bilingual students in engineering activities, we areemploying a design-based research approach with a participatory framework [3] to design,implement, and investigate a standards-aligned professional learning model for monolingualteachers. School leaders, principals, and teachers are working with the research team to co-construct and iterate a model of professional learning. This model introduces teaching toengineering design along with translanguaging (i.e., using all the linguistic resources in anylanguage that a student brings to the classroom within their engineering work). Our model alsoasks teachers to reflect on their language ideologies, or beliefs and conceptions of how languageis used in
indicate consistent use of digital Engineering Design ID Materials Process Log (EDPL) during implementation of 8th grade curricula, as suggested. Several teachers also observed using the EDPL with 6th and/or 7th grade classes as well. Teacher Interviews document teacher reflections on which stages of the EDP they Facilitation/Student found most challenging to facilitate. Challenges related to the Ideate and Engagement in Evaluate stages were most common. For example, Teacher 1 described Engineering Design students’ reluctance ideate and the challenge of facilitating iteration: Process “The biggest thing that they struggled with is the ideate
of a shortanswer question in which students succinctly describe their post-graduation plans, a freeresponse question which asks students to reflect on their personal strategic focus as a member ofthe BME community, and a copy of their professional résumé at the time they were enrolled inthe course.To date, we have collected over 1000 individual student assignments between both courses andare currently in the process of pairing them so the same students can be tracked across the twotime points. In addition to the students’ assignments, we are also collecting information about thefirst position students attained post-graduation, if available, from public sources such asLinkedIn or the alumni directory. Once data from all three time points is
Faculty Communities Exploring Data and Sharing Their StoriesMotivation and Project OverviewThis NSF Improving Undergraduate STEM Education (IUSE: EHR) Institutional andCommunity Transformation (ICT) capacity-building project is designed to support faculty tocollaboratively explore questions on student learning and success in introductory and gatewayundergraduate STEM courses, such as early engineering courses as well as prerequisite math andscience courses. The project is motivating faculty to consider evidence-based teaching strategiesby including them as co-designers of learning analytics tools and storytellers inspired by the dataand their reflections. Learning analytics uses data about learners and learning to draw
underscores the program's commitment to advancing STEAMeducation by empowering educators to inspire the next generation of innovators and problem-solvers in their classrooms and communities.Mobile Roadshow InitiativeThe AIR Program at Pittsburg State University is pioneering a mobile roadshow initiative toenhance access to its transformative workshops. Recognizing barriers to STEAM education, theprogram aims to bring robotics opportunities directly to underserved communities [3].This initiative offers condensed versions of the Summer Youth Workshops in a portable format,making STEAM learning more accessible to communities facing resource limitations orlogistical challenges. Beta-tested in October 2022, the roadshow concept reflects the
completion of the activity and/or demo. • Completing focus groups with students not in the design group to see if their activity is pedagogically beneficial. • Developing protocols for implementation of the activity and/or demo for faculty and graduate students to teach in their classes.All teams presented their final prototype via poster and a demonstration at the College ofEngineering’s capstone design symposium as well as a final oral presentation in class.Student Authors’ ReflectionsOur team was brought together in our senior Chemical Product Design course. We were joinedby our collective interest in creating a product related to undergraduate chemical engineeringacademia. During initial brainstorming, we reflected on our
Collegesand Employers (NACE) Career Competencies framework into engineering courses. More thanthree quarters of engineering students are seeking career advancement or career changes withengineering degrees. The integration of NACE Career Competencies helps translate ABETstudent outcomes into practicable career readiness strategies. The courses used projects andguided reflection students to practice eight career competencies: Career and Self Development,Communication, Critical Thinking, Equity and Inclusion, Leadership, Professionalism,Teamwork, and Technology. Preliminary observations from student reflections and advisinginterviews suggest students are intrinsically motivated to connect course exercises to careercompetencies. This study provides a
engineering course Itook. In this course, students were put into groups and had to complete an engineering task (inmy case, build a simple robot); however, the class’s primary learning outcomes focused on non-technical concepts like engineering ethics, which made this course like a mini capstone wherestudents had to find the information themselves to complete their projects. Reflecting on thisproject, I realized that researching and building circuitry for robots was the primary reason forselecting Electrical Engineering. Therefore, when I look at the department’s RED program, I seea similar ideology: an attempt to teach students more about the professional side of engineeringand empower students to take responsibility for learning. I still have not
the student,rather on the instructor as the case with the traditional form of leraning [4]. This has brought asignificant improvement during the learning process of many students. Active learning is apedagogical tool that has helped promote ‘students’ cognitive capabilities when it comes tomastery of the content [5]. Meaningful conversations, proper reflection, and content mastery areproducts of this learning mode [6].Experiment-centric-pedagogy (ECP), an instructional technique that facilitates activite learning,offers an alternate route for acquiring technical skills and information both inside and outside ofthe classroom. ECP enabls students with different learning styles to learn at their own pace and intheir own settings. Instructors
students’ agentic engagement, self-efficacy, growth mindset, and other related aspects. 1In recent years, there has been increasing attention paid to students’ epistemic beliefs and theirimpact on learning efficacy. Epistemic belief, which reflects students’ views on the nature ofknowledge and knowing, plays a crucial role in the cognitive, metacognitive, and affectivedimensions of students’ learning. Research has demonstrated that interventions targeting epistemicbeliefs can significantly enhance learning outcomes (Greene et al., 2018). Epistemic cognition -mostly measured in terms of belief (Greene et al., 2018) – is identified as the apex of