delivery readiness. The PI then depositsthe finalized contents in a shareable media for delivery and dissemination. An iterative review method depicted Focus groups Decide on Active Learning Contents in Figure 2 is being used to ensure and Formats (case study, class exercise, or case study video) the modules reflect both academic research and industry best practices. The content development process PI & Co-PI refine Contents List
their curriculum, (2) both course and overall curriculum level assessments arepossible, where the assessment scores reflect the development on an absolute scale, and (3)instruments and rubrics can be upgraded over time to reflect the progress in the assessment ofspecific professional skills.The Model of Domain Learning (MDL) proposed by Alexander et al.1 is a learning theorycharacterized by the interrelations that exist between the learning-based constructs and theexperience-based stages in academic domains. In this study, the MDL based framework isapplied to develop assessment rubrics mapped to the interaction between the experience-basedstages and the learning-based components. The experience-based growth stages in ascendingorder of
Students specifically mentioned splitting up projects into pieces and never necessarilyworking together as a team. The delegation of tasks occurred in such a way that limitedteammate interactions. This reflects a lack of relatedness, neglecting the process of workingtogether to integrate individual aspects of the project and sharing knowledge. In essence, teammembers did not engage in teamwork; instead, they completed what amounts to individualprojects. In fact, the following student quotes depict teamwork as a last resort or even go as far asexpressing an interest in not working together at all. In some instances, groups assigned one specific team member the individual task of“putting all the pieces together.” Interestingly, in the quote
. For the studied group of engineering students, there are no significantcorrelations between Creativity Index and GPA or the Creativity Index and SAT scores,indicating that SAT scores and GPA are poor predictors of creativity. Because creative potentialis not reflected in the current evaluation methodology, the most creative engineering studentsmay not be at the top of their class, so their unique potential may be underappreciated inengineering programs. This observation indicates the urgent need to revisit the studentevaluation is performed in the current engineering education. Potentially low GPA of highlycreative engineering students may become an impediment for their recruitment for jobs that arehigh demand for creative ideas. The
literature [12-14], the conceptof shortage of time repeated throughout the interviews. A participant reflects on the lack of timeissue: I would say that the largest cost has been our individual time, the faculty members' individual time. Because it takes some time to think about your course syllabus in a different way, thinking about ... Because in the curriculum plan, it shows you ... or there's indications of what courses might be prerequisites. But then we had to go back and think about what topics within that course are the most relevant.Another participant recounts what resources could make more time possible: I think that there's probably something as a carrot and a stick to get faculty together to do
the effectiveness of the applied/active learning activities and to see ifthey correlate with an increase in later success in Engineering courses, we analyzed studentperformance in the Applied Mechanics I class. The current prerequisite to the AppliedMechanics I class is Physics for Engineers I. Before the redesign of Physics curriculum theprerequisite was PHYS 215, Engineering Physics I, which was a traditional Physics class. It washeavily oriented towards theory and the lab components were rather disjointed with thetheoretical learning activities. We compared the Applied Mechanics I class final grade pointaverage (which reflects all assignment grades, including homework, quizzes, and a total of threeexams) as a measure of the performance
problem, reconstructing the main problem, and performingindependent and collaborative studies, students then revisit the original problem with a renewedapproach, new knowledge, and skills (Savery & Duffy, 1995; Barrows, 2002). The action ofreconnecting to the problem with a constructive approach encourages students to take ownershipof their short- and long-term learning goals. As part of life-long learning skills, students developself-learning habits to understand the need for recognizing real-life problems, allocating time todo independent research and reflect upon findings (Hmelo-Silver, 2004; Hoidn & Kärkkäinen,2014).3.0 ENVIRONMENTS FOR FOSTERING EFFECTIVE CRITICAL THINKINGThe Environments for Fostering Effective Critical Thinking, or
can create online and Page 23.871.13dynamic course materials that can be updated easily and frequently as needed. The workpresented in this paper and the instruments described will also guide any systematic evaluation ofa pedagogical novelty on similar student learning outcomes.AcknowledgementThis material is supported by the National Science Foundation under TUES Phase-II Grantnumber 1022932. Any opinions, findings, conclusions, or recommendation presented are thoseof the authors and do not necessarily reflect the views of the National Science Foundation.References1. Bransford, J. D., Brown, A. L., & Cocking, R. R., (2000). How people
Arizona State University. His research interests include social media, narrative storytelling, cyberlearn- ing, embodied mixed-media learning, affective computing, and instructional design. He holds a M.Ed. in Curriculum and Instruction from Arizona State University and is a former middle/high school English teacher. His work is steeped in a multi-disciplinary background including education, design, filmmaking, music, programming, sociology, literature and journalism. He is a member of ASU’s Advancing Next Generation Learning Environments (ANGLE) and Reflective Living research groups.Dr. Sandra Houston, Arizona State University Dr. Sandra Houston is a member of the Geotechnical Engineering faculty in the School of
. Retrospective interviewing will occur immediately after the think-aloud to help participants reflect on and verbalize their thought processes during the think-aloud, drawing from both long-term and short-term memory (e.g., “Describe the process you used to think about the case”). In addition, interviews will include questions to clarify comments participants made during the process and to explicate how knowledge and experiences were used. Transcriptions will be examined using a constant comparison methodA3, with specific attention given to participants’ references to prior knowledge and experiences. Initially, each researcher will conduct an analysis of a single transcription, looking for evidence
for chondrogenicdifferentiation and whether these reflect the existence of origin-specific biological signatures. Students will design their experimental inquiries to determine how culture conditions altercell differentiation. Teams of 2-3 students will independently design and execute studies to testhow the following influences the formation of differentiated chondrocytes: 1) undifferentiatedcell types, and 2) addition of growth factors (e.g, transforming growth factor b (TGF-b) family,bone morphogenic protein (BMP) family, basic fibroblast growth factor (FGF-2), insulin-likegrowth factor-1, IGF-1). Students will assay cell viability, cell number and differentiation. Eachstudent team will assay differentiation by one of the following 1
course mainly included the introductory and essential robotics concepts for the teamdesigns: locomotion concepts, fixed and mobile robot kinematics, actuators and basic sensors.The course lecture and hands-on laboratory content reflected the IEEE Region-5 roboticscompetition guidelines, related project descriptions, hands-on design specifications, tasks,timeline, and a component list. High School Mentorship opportunities provided valuablerobotics and engineering design experiences for the robotics students who strengthened theirrobotics knowledge and skill sets to high school students for their high school level roboticscompetitions. Robotics-II course maintained the robot design continuity by requiring the sameteams from Robotics-I, with their
Lisa D. McNair is an Associate Professor of Engineering Education at Virginia Tech, where she also serves as Assistant Department Head of Graduate Programs and co-Director of the VT Engineering Com- munication Center (VTECC). She received her PhD in Linguistics from the University of Chicago and a c American Society for Engineering Education, 2014 Paper ID #10091B.A. in English from the University of Georgia. Her research interests include interdisciplinary collabora-tion, design education, communication studies, identity theory and reflective practice. Projects supportedby the National Science Foundation include
disorders like narcolepsy, periodic limb movement disorder, hypersomnia, andsleep apnea. While a PSG provides valuable data to characterize sleep quality, the signal-acquisition technologies are obtrusive and not easily tolerated by children.6 The cost of the Page 24.374.2procedure and the necessary travel to a sleep laboratory also make it impractical for long-termsleep monitoring. For instance, biopotential measurements require wired electrodes in constantcontact with the skin. Oxygen saturation is typically measured with a bulky finger-clip sensor,although reflectance-mode sensors are becoming available. An unmet need remains for thedevelopment
necessarychanges to engineering curriculum to attract a more diverse student and practitioner population. Page 25.321.6Engineering IdentityThe construction of professional or personal identity is dynamic and multiple. In other words,identity reflects membership in many groups and changes over time. Socialization into aprofession may be done via many avenues. However, it is commonly suggested that havingexamples of people like oneself may be a strong contributor. In STEM fields with low femalemembership, this may hinder the entry and retention of females into engineering38–40.STEM study and work is perceived by students as more difficult than many social
Page 25.1351.8surprising that students in any semester do not have knowledge of the outcome coming in toEELE 201.Two-sample t-tests comparing the Fall 2011 student responses on the pre-survey to the responseson the post-survey produced significant results (post-survey responses being higher) for alloutcomes questions of interest (p < .05).All pre- and post- survey results (average survey responses) are shown in Table III below: Table III. Pre- and Post-Survey Results (Means) for Fall 2010 and Fall 2011 Learning Outcomes of InterestLearning Outcome: Please complete the followinganonymous survey by selecting the statement thatbest reflects your current knowledge in a given area. 1 = Strongly Disagree 2
diagrams. The current results also reflect earlier findings from58, in which the AA conditionperformed significantly better than the CC condition. Overall, these results support the notionthat abstract representations foster learning through allowing learners to focus on the underlyingstructure of the problem at hand, rather than the superficial elements of each individual problem.Thus, these learners do not observe worked-example problems considering, for example, abattery and a light bulb, rather noting that any type of voltage source and any type of electricaldevice could be present. Since these college students, although novices to electric circuitanalysis, have the requisite experience to know what objects can serve as electrical
as close as possible to those reported by the in-person group. 4. The students in the remote group perform at least as well as the in-person group in terms of understanding of the concepts related to databases as reflected by grades for the ISBL assignments.Statistical Comparisons and ResultsTable 2 provides the mean, median, and standard deviation of the outcomes measured in thisexperiment. The outcomes include average ISBL assignment grades, score for each motivationconstruct and the overall motivation, scores for experiential learning constructs environment andutility, self-assessment scores for each of the four database concepts and the averageself-assessment score over all concepts, and the SUS score. To compare the two
diverse levels ofcompetence learn from one another and their instructors. In a WisCom, learners collaborativelyfollow an inquiry cycle of learning challenges, exploration of possibilities and resources,continuous reflection, negotiation among fellow participants, and preservation of their new-found knowledge.We are applying this framework to generate a learning community among ECE students andinstructors [10]. Research shows that individuals in a shared academic community often interactthrough social media beyond their courses and become colleagues as they build their careers. Toremediate the lack of belonging that our Latinx ECE students feel, sociocultural learning theorieshave been proposed which frame the design, development, implementation
reflects the student experiences from one medium sized university in West Texas, thesefindings may not be representative of student experiences of a larger sample from other areas ofthe country. Further, as many of the participants were early in their academic careers, theirexperiences may not reflect those who are farther along in their STEM studies. Due to the cross-sectional nature of this study, retention rates of participants within STEM majors were notmeasured. One of the individuals who participated in the focus groups started college as a STEMmajor but changed their major to history. This student provided feedback about theirexperiences after changing majors saying: "I've definitely felt more supported in the historydepartment. Maybe it's
clear and logical algorithms is crucial, demanding proficiency incomputer programming languages commonly used in engineering, such as Python, Java,MATLAB, or others relevant to the discipline. Additionally, CT serves as a foundational skill fordata analysis and modeling across various engineering disciplines. Its widespread adoption inSTEM education institutions, as evidenced by the incorporation of Next Generation ScienceStandards (NGSS), reflects a positive trajectory in developing CT abilities and meeting thedemands for skilled technical workers [12]. The implementation of CT in engineering education necessitates a shift towards student-centered learning strategies to mirror the complexities of real-world problem-solving
spontaneous questions toexplore, deepen understanding, and clarify answers to earlier questions [15]. Interviews wereconducted by the third author during the latter half of the fall semester and were audio recordedbefore being transcribed by Otter.ai (Otter.ai Inc, 2023) and edited for clarity by the second author.Interview questions were derived from theory and prompted participants to reflect on theirexperiences with mastery-based learning, features of the program, individual and communityefficacy as educators, as well as their perceptions of the student’s failure mindset, attitudestoward assessment, performance/ competence, metacognition (thinking about learning process),agency (ownership of learning), and engineering identity (Table 1). The semi
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
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
their chosen study program, and highlight the importance of early courses for success in the later stages of a study program [13]. Our findings indicate that such a model improves the retention and persistence of students in the critical period of adaptation to college life.iii. A strategy to use a cognitive apprentice framework to combine coaching, peer-led team learning, and reflection/self-assessment to boost leadership skills among Hispanic LIATS [14]. The combination of these methodologies enabled the development of leadership competencies among students impacting their emotional intelligence and demonstrated, in later stages of the study, to influence the roles assumed by them when given the opportunity of
the ideas related to career readiness, employability, and life careers [4].According to NACE, career readiness is “a foundation from which to demonstrate requisite corecompetencies that broadly prepare the college educated for success in the workplace and lifelong1 This project is supported by NSF Grant #2000847. Findings, opinions, or recommendationsexpressed are those of the author(s) and do not necessarily reflect the views of the NSF.career management” [4, Para. 1]. Gained through a variety of actions and activities, the eightcareer readiness competencies are: career & self-development; communication; critical thinking;equity & inclusion; leadership; professionalism; teamwork; and technology.These competencies provide a helpful
. Wereceived both positive and negative team stories from the participants. In addition, we found itwas not only the engineering classes, clubs, and teams that seemed to affect the sense ofbelonging, but also where the participants lived. Our preliminary results indicate that students’making experiences, especially in the context of project teams, influence how they feel asengineers. We will continue to explore these themes into the second year of our project.AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grant No.2204738. 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
REU Site wassuccessful in its goal of providing an inclusive and supportive learning environment forneurodiverse students, suggesting that further research and programming in this area would bebeneficial.AcknowledgementsThis research was a part of a project funded by the National Science Foundation (NSF), Divisionof Engineering Education and Centers under the Award Number 2051074. Any opinions,findings, and conclusions or recommendations expressed in this material are those of the authorsand do not necessarily reflect the views of the National Science Foundation. The authors alsoacknowledge and thank the graduate and faculty mentors for the participants.References1. Sparks RL, Javorsky J, Philips L. College students classified with ADHD
, or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.8. References[1] N. Baumer and J. Frueh, “What is Neurodiversity?,” Harvard Health, 2021. [Online]. Available: https://www.health.harvard.edu/blog/what-is-neurodiversity-202111232645. [Accessed: 15-Dec-2022].[2] S. Comberousse, “A begginer’s guide to neurodiversity,” Learning Disability Today, 2019. [Online]. Available: https://www.learningdabilitytoday.co.uk/abeginners-guide-o- diversity. [Accessed: 15-Dec-2022].[3] E. V. Cole and S. W. Cawthon, “Self-disclosure decisions of university students with learning disabilities,” J. Postsecond. Educ. Disabil., vol