illustrated. Learners are alsoactively participating in the activity. Finally, the instructor asks the same sets of questions toassess how well students comprehend the experiment. ECP Module Instructional Design Template Module Information Synoptic/Purpose of Instructional Instructor Module Process Reflection a. Developers/Instructors a. Essential Questions a. Materials needed/Expected Reflection Institution for use. b. Module Objectives b. Mobile Title/Topic b. Procedures c. Placement within
disciplinary and everyday language in students’ responses. This can help us make thetool a more inclusive generative AI tool that understands the various language students may useto explain their thinking. In turn, instructors and researchers will be more aware of the diverselanguage and thought patterns students use to wrestle with challenging concepts in the discipline.AcknowledgmentsWe acknowledge the support from the National Science Foundation (NSF) through grant EEC2226553. Any opinions, findings, conclusions, or recommendations expressed are those of theauthors and do not necessarily reflect the views of the NSF.References[1] H. Auby, N. Shivagunde, A. Rumshisky, and M. Koretsky, “WIP: Using machine learning to automate coding of student
persistence among low socioeconomic status students," Journal of Experiemntal Social Psychology, vol. 72, pp. 45-52, 2017.[22] R. M. Stwalley III, "Assessing improvement and professional career skill in senior capstone design through course data," International Journal of Engineering Pedagogy 7, no. 3, pp. 130-146, 2017.[23] R. M. Stwalley III, "Professional career skills in senior capstone design," in ASEE Capstone Conference - Columbus, Washington, DC, 2016.[24] J. McCarthy, "Reflective writing, higher education, and professional practice," Journal for Education in the Built Environment, vol. 6, no. 1, pp. 29-43, 2011.[25] G. Bolton, "Narrative writing: reflective enquiry into professional practice," Educational Action
Exercise DescriptionThe robotic platforms were used in an operating systems and systems programming course at PennState Behrend as a part of a lab exercise to demonstrate concepts related to task design, timing,synchronization, and mutual exclusion mechanisms. The exercise was divided into sections:Introduction to the robotic platform operation, task design using timing and synchronizationmechanisms, and feedback and reflection on the lesson learned.The tudentts were first introduced to the basic operation of the robotic arm using manual controland Application Programming Interfaces (API) control through a Python control program. Thechallenges of moving the arm in space using different coordinates and keeping track of the arm’sposition were
on this positive interest from students, a committee of faculty who taught in math andsciences was convened to develop the program. Because of the institution’s historical strengths inthe sciences, the committee recommended that the institution offer a B. S. in EngineeringScience, which was subject to the same ABET criteria as B.S. programs in Engineering andEngineering Physics.[7] It was also believed that the program named Engineering Sciencewould be better accepted at a liberal arts institution where a degree such as engineering might beviewed by some as a strictly vocational major. The intent of the degree to equip students with abroad and general engineering background also reflected key principles of the liberal artsapproach.The
with the specific focus of each survey section, we aimed toensure the relevance and coherence of our assessment tools. This alignment provides a clearerframework for understanding the survey results and reflects the complexity and interconnectednessof sustainability in engineering education.Research Questions: 1. Impact of Active Learning Approaches: How are active learning strategies and hands- on curricular implementations in engineering classrooms related to changes observed in undergraduate engineering students' responses in a six-section pre-post sustainability survey and their open-ended feedback? 2. Comparative Analysis Across Disciplines: How do the pre-post sustainability survey results differ among students
frustrated when it happened.Discussion This study investigated how students perceive generative AI (GAI) for designing mood boards ina computer-aided design (CAD) course regarding design creativity. Specifically, we introduced a workshopand a homework assignment that incorporated the GAI tool Midjourney into the students' final CADprojects, aiming to teach 20 students how to use GAI in conceptual design. Through surveys and interviews,we examined students' creativity in the mood board design process and the final products, comparing themto those created without GAI. Our findings revealed that most students (17 out of 20) believed GAI boostedtheir creativity, although expert evaluations of their works did not reflect this. Additionally, we
in Spring 2023Overall, compared to previous years [18],[19] the gender and racial diversity of the eligibleapplicants and ACCESS scholars decreased despite the wide range of outreach efforts, some ofwhich specifically targeted underrepresented groups of students. The decline in diversity,especially compared to Cohort 1, may partially be due to the fact that many current WestVirginia University students from underrepresented groups, who were eligible for the ACCESSscholarship, applied and were selected in the earlier years of the ACCESS project. In addition,decreased diversity may be reflecting the broader trends in college enrollment, broader genderand racial disparities in Computer Science and
al.’s researcher identity scales, which aim to measure the sameconstructs as in the current research, originally contained 26 total items, but were reduced 16total items following the factor analyses of these scales and those of the related identities(scientist and engineering). One unique advantage of Perkin et al.’s approach is that many of theitems provided a more detailed reflection on the specific context of doctoral education. Forexample, the dissertation advisor is proposed as a critical external source of recognition and thusthe following item was added: “My advisor(s) see me as a RESEARCHER.”2 Similarly, thecompetence scale in Perkins et al. work focuses more on specific competencies associated withresearch, such as delivering
68% 84% 0.0327Class SurveysA weekly reflection and survey were conducted with Likert scale multiple-choice questions. Forthis study, only the results from the beginning of the class (pre) and end of the class (post) wereanalyzed. The complete wording of the Likert questions and answer choices are shown inAppendix I. The survey results analyzed by gender are shown in Table 4. The table shows thesum of the top 2 Likert responses, such as Effective and Very effective to indicate the percentageof students with a positive assessment in each topics area. To show the effect of training moreclearly both the pre- and post- questions are shown when the same question were present in bothsurveys. In Table 4 the pre- and post- questions
professionals who will enter management and leadership roles. Nonetheless, research andanecdotal experience have indicated that both students and practicing professionals shy away fromstrategic networking, a stance that can hinder their careers. This paper reports on work-in-progress ofdesign and evaluation of course interventions to promote strategic networking among undergraduateengineering students. These experiences are part of a course in Engineering Leadership at Texas A&MUniversity. This paper offers first a literature review and then detail on our course content, networkingactivities, and a reflection connected with effective strategic networking for this class. Mixed-methodsanalysis of the results of student surveys provide insights of
statistically significant differences for Scenario 3.LimitationsThere are several limitations inherent to this work. Given the diffuse subject recruitment strategy,it is possible that ethically minded individuals are overrepresented in the sample (i.e., thatethically minded individuals would be more likely to respond to a voluntary survey onengineering ethics). Further, this survey examined individuals at one Research 1 institution in theUnited States and the results may to a degree reflect that (e.g., individual’s views on code sharingmay be influenced by institutional academic integrity culture and rules). Subjects were askedabout their perceptions of the views of industry, but contemporaneous surveying of individualsfrom industry was not an
introductorymechanical engineering design course that involved both lecture (2 credits) and laboratory (1credit) sessions. Learning objectives for the mini-mill experience were to: (1) learn the safetyand controls of a manual milling machine and basic milling operations that included fixed,material scaffolds designed by the course instructor; (3) practice reading and manufacturing fromstandard engineering drawings; and (2) independently apply knowledge of milling machinecontrols and operations to create a basic part with adaptive, pedagogical scaffolding fromteaching assistants and machinists. All deliverables for this exercise were individually completedby students and required a mixture of hands-on activity, written reflection, and online trainingand survey
simultaneously. Most of these foreign nationals areeventually naturalized and become citizens. While the immigration status of these faculty istransitional, their specific cultural and racial identity carries forward. Unfortunately, theclassification of these individuals in URM/Non-URM status is complicated [25], as 1) the URMdefinition used by NSF is based on underrepresentation in STEM fields relative to the overall U.S.population, but FB faculty are drawn from the world population where the ethnic groups adverselyaffected by systemic inequities may or may not align with the U.S. definitions; 2) FB faculty ofBlack and Hispanic backgrounds are included in URM, which raises the number of URM facultybut does not reflect an improvement in the including of
manufacturing under guidance of Dr. Fidan. He also works as student manager of iMakerSpace Innovation lab at Tennessee Technological University. ©American Society for Engineering Education, 2024 Unique Instructional Delivery of Additive Manufacturing: A Holistic ReviewAbstractAdditive Manufacturing (AM), often referred to as 3D Printing (3DP), has emerged as atransformative technology compared to traditional manufacturing across industries such asaerospace, healthcare, and automotive. With this evolution, the demand for specialized educationand training in AM is growing. This brief concept paper provides a condensed review ofdistinctive instructional delivery methods in the field of AM, reflecting the dynamic nature
existed in convenience and ethical consideration [18]. Karunaratne and Adesina [19]used a survey to examine the use of ChatGPT in the information retrieval process amongstudents at higher education institutes. Through their survey they found “ChatGPT has reducedthe anxiety of information search, and increased the confidence with which students seekinformation” [19]. Lo [20] proposes the “CLEAR framework” (Concise, Logical, Explicit,Adaptive, and Reflective) as a mechanism “to optimize interactions with generative AI languagemodels. The focus of Lo’s work is on improving prompt engineering skills of people usinggenerative AI tools [20]. Jin et.al. [21] discussed potential use cases for generative AI in medicalliterature indicating potential
tasksinto instructional activities, making the assessment process less intrusive and more reflective ofstudents' actual learning processes [23]. Assessment tasks are designed to be directly relevant tothe learning objectives and often require students to apply their knowledge and skills in authenticcontexts. This approach enables educators to assess not only the final product of learning but alsothe learning process itself, including students’ problem-solving strategies, critical thinking, andability to apply knowledge in real-world situations [24].Embedded assessment comes with many challenges. Teachers must be skilled in designingassessment tasks and in interpreting the evidence of learning these tasks provide [25]. Due toembedded assessment’s
toconsider the various aspects of wellbeing for the design of instruction as well as policy.Acknowledgements We thank Erin Rowley, the engineering librarian at the University at Buffalo, for hersupport in the database selection and helpful recommendations for conducting this systematicreview. We also thank Joseph McCusker, engineering student at University at Buffalo, and anundergraduate researcher at DARE to CARE lab, for his invaluable assistance with the review ofthe studies. This material was partially supported by the National Science Foundation Grant No.2147193. Any opinions, findings, and conclusions, or recommendations expressed in this materialare those of the author(s) and do not necessarily reflect the views of the National
internships because they believe companies “preferto hire students who have completed their entire degree program at a single institution." There isno proof that being a transfer student will put them at any statistical disadvantage in the job orinternship market as a student who finished their whole degree at one university. These issues re-veal deeper insights outside of registering for classes and choosing a major. They reflect a lack offlexibility and support for non-traditional students who juggle employment and education, as wellas misconceptions that can negatively influence students’ perceptions and decisions.5 Conclusion and future workRising costs at 4-year universities are bringing a shift in acquiring a bachelor’s degree by attendinga
graduatestudents. Items that received lower average scores focused on mentoring skills related tocommunication, coordination, personal relationships, and career planning. This was reflected inthe open-response questions, where participants frequently cited these areas as problems orpoints of stress in their relationships with their advisor(s). Items that received higher averagescores focused on research skill building, resource acquisition, feedback, and trust. These areastend towards some of the more technical aspects of mentoring that advising requires, whichengineering doctoral advisors may feel more comfortable with. For example, setting researchgoals with students may come more naturally for faculty members than helping students preparefor a career
SUNY Discovers (research, entrepreneurship, field study, experiences abroad, and creative work) [6]• SUNY Applied Learning Plan [6]• Campus Applied Learning Plans: Applied Learning Plans parts II to VII for each system campus [6]• Applied Learning Guidance to Campuses (includes an action timeline) [6]• SUNY Board of Trustees Resolution on Experiential and Applied Learning [6]• Criteria for Campus-Approved Applied Learning Activities: The activity is structured, intentional, and authentic; requires preparation, orientation, and training; must include monitored and continuous improvement; requires structured reflection and acknowledgment; must be assessed and evaluated [6]• Service-Learning in SUNY: Current Status and
style teaching, the interventionwould occur after the assignment has been submitted and therefore would reflect poorly upon thestudent, where with the new tool, the student can recognize their gap in knowledge and seek theaid of the instructor to be able to correct that gap in knowledge and then go attempt quizzes orassignments once more to verify that the issues have been corrected; in this case, the grades wouldreflect greatly upon the student.ResultsThe effectiveness of the newly developed teaching strategy was evaluated in a Statics classcomprising 21 students through a survey consisting of 29 questions that focused on the themes ofskill development. Sixteen out of 21 students completed the survey. The responses to the surveyquestions were
Oklahoma pre-statehood, andits ongoing success can be attributed to the readily available and abundant raw materials presentwithin the state [22]. Some of these include natural gas and coal to fire the kiln and limestone, akey ingredient in cement. All the examples further justify the importance of an Oklahoma cementindustry decarbonization public perception study. A survey was chosen as the preferred method of gathering data, as it best fit with our goal toanalyze data reflecting the public perception of the cement industry decarbonization withinOklahoma. A survey allowed us to ask a multitude of questions that touched on many topics. Thequantitative nature of the survey allowed for all responses to be categorized numerically, whichcould then
variable student experiences thatmay not be represented within this work. Another limitation in the study can be found within thesurvey design. Initially, the project took a deficit framing and developed the survey instrument tocontain questions related to barriers rather than student experiences. In doing this, results may beskewed more towards sharing frustrations or negatively framed experiences in replacement ofauthentic positive experiences that may not have been elicited provided the question framing.Lastly, the students were asked to reflect on experiences at the end of the course, in which theexperience reflected in a student’s response may not be representative of their authentic as timeand other experiences may have skewed memory of
. Aaron W. Johnson, University of Michigan Aaron W. Johnson (he/him) is an Assistant Professor in the Aerospace Engineering Department and a Core Faculty member of the Engineering Education Research Program at the University of Michigan. His lab’s design-based research focuses on how to re-contextualize engineering science engineering courses to better reflect and prepare students for the reality of ill-defined, sociotechnical engineering practice. Their current projects include studying and designing classroom interventions around macroethical issues in aerospace engineering and the productive beginnings of engineering judgment as students create and use mathematical models. Aaron holds a B.S. in Aerospace Engineering
examination. Following each coding session, reflections, emotions, impressions, andinterpretations were recorded in a memo document to note emerging trends. After thepreliminary coding, a second-pass axial coding was conducted on the Excel sheet to identifycommon themes related to the control/treatment group and the decision to stay/leave. Theseemergent codes were discussed with the second author to refine the claims made from the dataand for coding consensus.The authors of this paper have varied experiences with engineering and as members of thegroups we interviewed. The research team of faculty, postdoctoral scholars, graduate students,and undergraduate students included researchers from higher education and engineeringeducation. Three of the
experience. Eighty-seven percent of Seniors (20+ years) reported reasonswhy standards are important. 11The idea is further reinforced by the shifting analytical categories reported by increasing levels(i.e., more years on the job). First, the trend for reasons of Importance seen in the overall data islargely apparent and is reflected in the analytical category Expectations of the Profession whenanalyzed based on Level. As engineers gain experience, the types of technical challenges theyface change, as does the number of challenges they face and their respective knowledge aboutthem. The free-response data suggests this is due to the changing awareness
engineeringpractitioners. Intuition is a skill used by experts in the decision-making process when problemsolving, and believed to develop alongside expertise largely through experience. Previous worksupports that at least six years of experience is necessary for expertise development. Wesubsequently define early-career as up to six years of post-baccalaureate experience and expectthat this population will not yet have expertise and therefore not use intuition. However,research has shown that early-career practitioners who graduated from a primarily undergraduateinstitution (PUI) prior to the onset of COVID-19 both claim expertise and report using intuitionin their decision-making. This unexpected result may be reflective of the PUI’s emphasis onhigh-impact
, reflection, teamwork, and communication skills [3]. And finally, from [6] “We knowfrom research that the more students engage with other students in the class, as well as withprofessors, the more likely they are going to stay and get their baccalaureate degrees.” Boud [3]also suggests that peer learning suits some students better than learning individually, particularlywomen and students from some cultural backgrounds.The approach here is to use CATE to enhance learning in a peer-learning environment. This isintended to provide the many benefits of peer learning without an increased time commitment forthe instructor.Figure 2. A randomly generated circuit and associated step-by-step analysis. The CATE systemincludes an algorithm to select component
. Students can ask any remaining questions they may have 14 Wrap-Up and Reflection about the program and reflect on what they learned about the nature of engineering practice over the semester.Example Lecture: Week 3 – Differentiating STEM Fields Since the first year of most engineering programs consists of mainly science and mathematicscourses, it was pertinent to explicitly describe how engineering is different from these fields and howtechnology interacts with them. The lecture extended these topics to also cover STEAM, where the ‘A’stands for art. The notion of combining art into these fields that are usually viewed as inartistic hasdiscovered a resurgence in the importance of