, orexcellent.Results are very preliminary. Most participants appear to be satisfied with their match, but noconclusions can be made on the effectiveness of MentorMatch. Although first round ofpreliminary data does not reflect the perceived percentages, it collects the participantspreferences on the dimensions and point the research to the right direction with regardsalgorithm. Most participants deemed the application experience and design as satisfactory in itscurrent stage. More experimental data needs to be collected and analyzed before making changesto the algorithm.IV. FUTURE WORKSThere is a need to increase the sample size to change the current algorithm. Continuing to expandthe number of participants by recruiting more mentors and mentees is a priority
sophomore retention rate of 73%.Sophomore SurveyAt the end of their second year, INNOV sophomores were asked to reflect on their experience inan anonymous survey. Related to the innovation experience courses in their first year and how itimpacted them in their sophomore year courses and/or in life outside the classroom, • 81% felt the courses helped them feel more comfortable expressing their ideas. • 76% said the courses helped them feel more comfortable taking risks. • 63% felt the courses were valuable to their future educational and career goals. • 54% said that the courses helped them be more creative and innovative. • 54% felt that the courses helped motivate them to continue in their STEM degree program.Related to the non
play a role in the retention of engineering doctoralstudents: diversity, perceived cultural diversity, authenticity, psychological safety, psychosocialsafety, mastery, performance, organizational support, and sexual harassment climates. Weexplored how power and inequality are embedded in or emphasized by those nine climates andprovided guidance for future empirical work on organizational climate in engineering doctoraleducation to inform leadership efforts in promoting the retention of students from historicallyexcluded groups. This paper presents a framework of nine focused climates and the perceptionscaptured or reflected in 23 sources representing 19 studies.Climate Scale Development Based on our identification of climate factors
imitates the results of random assignment of students tothe two conditions (i.e., participating in a first year experience and not).3.1 ParticipantsSampling for the study involved a stratified approach. A random selection of alumni who had notbeen invited to participate in the most recent prior alumni study were invited to respond to thesurvey. The resulting pool of 2,336 respondents reflect a convenience sample from which weenrolled all 210 alumni who had participated in the first year experience, due to this being themost limited high-impact practice in this study’s setting. These participants were then matchedwith participants who did not enroll in a GPS course using propensity score matching proceduresthat expanded the sample to 420 alumni.The
and conferences dedicated to materials engineering and fracture mechanics, reflecting his active engagement and expertise in the field. Dr. Na received the Best Paper Award in Failure Analysis and Prevention at the Society of Plastic Engineers (SPE) annual technical conferences in 2013 and 2016. ©American Society for Engineering Education, 2024 Effect of Carbon Nanomaterials on the Compressive Strength of Cement Mortar: Research at Marshall University’s 2023 REU Site 1. AbstractThis paper describes the experience and outcomes of a non-engineering major who participatedin a 10-week Research Experience for Undergraduates (REU) program at
regulators, and data conversion circuits.Students obtained more accurate results, matching calculations, and simulations compared tousing breadboards. In addition, students gained time spent on additional testing and analysis.Students completed assignments using both the customized PCBAs and conventionalbreadboards. Quantitative and qualitative surveys have been conducted to assess the impact ofPCBAs on students' learning experience, technical effectiveness, and educational impact. Studentfeedback on using PCBAs compared to traditional breadboarding has been analyzed and sharedin this paper. The use of custom PCBAs addresses known breadboarding impediments, includingloose connections, noise, probing challenges, and cluttered layouts. They reflect
better understand whole–class testing or try to fill ingaps left by the three main data sources in design summaries, yet we did not need to do so often.Together, the table group video, journals, and interviews both (a) overlapped, triangulating oneanother as data sources especially in response to RQ2 and RQ3; and (b) offered unique insights(e.g., interviews were more reflective while group videos were in the moment). There were casesin which data sources conflicted (e.g., one design plan written in a journal but another enacted);we noted those conflicts in the design summaries. Even when we primarily drew from one datasource (e.g., interviews for RQ1) in answering a research question, we could interpret evidencefrom that data source in the
the engineering school. Please note thatthe collection of the 2020 survey data was completed just before the breakout of the COVID-19pandemic in March 2020 in North America; thus the data reflected the student experiences priorto the pandemic.The bulk of these data sets were from the National Student Engagement Survey (NSSE) data thatthe university collected on a three-year basis (that is, 2017 and 2020 data). We included the 5following variables from the NSSE data into our study: 10 engagement indicators that fall underfour themes (i.e., academic challenge, learning with peers, experience with faculty, and campusenvironment),1 six variables
more positive attitudes and higher confidence toward programming compared tomechanical engineering students. Future research will further investigate this question with thefollowing survey responses and seek to understand the influence of programming lab activitieson students’ programming experiences.Keywords: programming, attitudes, self-efficacy, mechanical engineering, industrial engineeringIntroductionAs computer programming has been widely used in both academic research and industrialpractice, the skill is becoming increasingly important in engineering education. According to A.Bandura, self-efficacy accurately predicts both subsequent behaviors and outcomes [1], and self-efficacy toward programming could reflect confidence in performing
Millennium Scholars. Before joining FGCU, she was a visiting Assistant Professor of Biotechnology in the Division of Science and Technology at the United International College (UIC) in Zhuhai China. She has trained with ASCE’s Excellence in Civil Engineering Education (ExCEEd) initiative, been exploring and applying evidence-based strategies for instruction, and is a proponent of Learning Assistants (LAs). Her scholarship of teaching and learning interests are in motivation and mindset, teamwork and collaboration, and learning through failure and reflection. Her bioengineering research interests and collaborations are in the areas of biomaterials, cellular microenvironments, and tissue engineering and regenerative
chemical engineering programs across the U.S. have seen stagnation or decreases inenrollment numbers, there have been efforts to redefine what chemical engineers do. Whilechemical engineering has strong ties to the oil and gas industry, there are also strong connectionsto renewable energy, energy storage, and broader sustainability topics. Students acrossuniversities have expressed interest and desires to learn about sustainability-focused topicsacross disciplines. While many faculty in chemical engineering have been working in researchand practice of sustainability engineering for years, the undergraduate curriculum has beenslower to reflect these changes.Importantly, sustainability is a cross-cutting space that is defined and operationalized
of a written reflection on their learning.Because statics is built upon physics, we used Harper et al.’s taxonomy as the basis for our own.Previously, we shared our process for creating—and subsequently modifying—a taxonomy foruse in categorizing the quality of questions students ask about statics [1]. We developed ourscheme to define a higher-quality question to be one that requires or demonstrates higher-levelthinking to answer – such as a question about understanding how or why something happens, ora question probing extension of knowledge to a new application – as opposed to a question thatcould be answered by a simple definition, or a procedural explanation of how to complete a task.Our taxonomy was approximately hierarchical, in which
be impacted differently through professionaldevelopment and intervention, with explicit reflection activities and those that support contentand pedagogical mastery as having the greatest impact on teachers’ overall engineering self-efficacy across the five domains [18].Supporting Engineering Self-efficacy for Rural STEM TeachersRural schools offer STEM educators many benefits, including close-knit communities, greaterteacher autonomy, and close relationships, all which can have positive outcomes for studentachievement and teacher retention [19]. Yet despite the unique assets associated with ruralcommunities and schools, there are also challenges faced by rural teachers that may impact theiraccess to professional learning and, therefore, the
Paper ID #41114Board 324: Is Adaptive Learning for Pre-Class Preparation Impactful in aFlipped STEM Classroom?Dr. Renee M Clark, University of Pittsburgh Renee Clark is Associate Professor of Industrial Engineering, Data Engineer for the Swanson School, and Director of Assessment for the Engineering Education Research Center (EERC). She uses data analytics to study techniques and approaches in engineering education, with a focus on active learning techniques and the professional formation of engineers. Current NSF-funded research includes the use of adaptive learning in the flipped classroom and systematic reflection and
with a librarian collaborator toidentify age-appropriate books that highlight diverse scientists and engineers that can bepromoted in the library and provide information supplemental to the curriculum.Table 1.Study DesignSurvey A quantitative survey was designed using existing, validated quantitative measures,combined with open-ended response questions. Based on pilot results and in consultation withproject advisory board members, we designed a retrospective survey in the next phase of thiswork. A retrospective test is administered at the end of an implementation and asks participantsto reflect on psychological factors and report their current perceptions for each item [17]. In thiscase, after the soft robotics implementation, students will be
the students on AI Literacy so they can analyze and interpret the syntheticallygenerated outputs.The course “Introduction to the Engineering Experience” is a required course offered every Fallsemester to all first-year engineering students at our university. The course is grounded on theapproach of Raymond Landis, who coined the term World Class Engineering Student (WCES)[10]. The approach focuses on development of soft skills including collaboration, reflection, peerreview, and time management; skills which are increasingly recognized as an important part ofstudent development and success in engineering education, and essential in the development of aWCES [11]. In the Fall of 2023 semester, the AI literacy module was added and delivered
, necessitating effective team dynamics – this is true ofour core research team as well as the larger CoP. The emergence of the science of Team Science(SciTS) reflects the growing recognition of the complexities inherent in collaborative researchefforts [1]. SciTS is an interdisciplinary field focused on understanding the conditions thatfacilitate or hinder effective team-based research and its unique outcomes in productivity,innovation, and translation [2].Team Science is a collaborative research approach that promotes openness, mutual respect, andshared responsibility among team members [3]. It encourages researchers to tap into a broaderrange of expertise, leading to more comprehensive and innovative solutions [4]. Effectivecommunication and teamwork
switch,for example 900C, and press the yellow push button The first meter will reflect this setting byturning the needle to 9. Turn the 2nd dial by dragging the mouse on it to set it to 4, and thevalue will be reflected on the 2nd meter, as shown in Fig 2(b). Fig 6. Individual Lab scores over three termsD. Comparison of Student Performance in In-Person and On-Line Classes With the use of zPLC Lab, we were able to make our summer 2020 Robotics andProgrammable Logic Controllers course offering a complete online class, in which each studentgot an installation of the zPLC software on their home computer. For this term, all labs wereperformed by students individually on the zPLC software and the collected lab scores
. The presentation appears to beeffective in impacting students’ perceptions of teaching both immediately and longer-term withrespect to the main topics it covers.A curious result is the significant p-values in the category of “Personal Enjoyment.” Though thepractical significance of these results was “small” or “negligible,” we found statisticallysignificant differences in this category for pre/post, post/delayed, and pre/delayed t-tests of thetreatment groups in both years and of the control group in Year 2. This is intriguing because thepresentation was not designed to address “Personal Enjoyment.” Rather than influencing throughcontent, the act of viewing a presentation about teaching may have sparked self-reflection in thetreatment groups
developer reflect upon and address those biases? How can we check our assumptions? Competitors The competitors would always come up with a better deep learning model for the system. Decolonizing Question for Competitors: How does the ethical conduct of your entity or project influence the accepted norms of how others in the field conduct their own systems design and implementation? Can your work set a standard for ethics and justice in the design process that influences the field?As you can see the decolonization questions help emphasize a critical view of power dynamicsand community engagement to ensure that a more full, accurate understanding of influences onthe design process. In each phase, we
for the curriculum revision were identified to be:1. Content modernization to reflect changing needs and practices in software engineering2. Cohesive alignment of vertical progression that links each year of study3. Increased integration of course concepts and collaborative pedagogy4. Keep current with leading-edge technologies and approaches5. Student-focused to provide skills and knowledge needed to thrive in industry or graduate programs6. Raise department profile and increase competitiveness with other software engineering programsThe degree program objectives were identified as a) to graduate future software engineers aspractitioners, researchers, developers and collaborators, b) to integrate fundamental knowledgeand applied skills
. IntroductionEngineering education faces the continuous challenge of incorporating the latestresearch findings into its curriculum to ensure graduates are well-equipped totackle current and future technological challenges. Traditional methods ofcurriculum development often struggle to keep pace with the rapid advancementof technology and emerging research areas [1, 2]. Current approaches tointegrating research into engineering education primarily involve the introductionof elective courses, predetermined laboratory classes, or the occasional inclusionof term papers from existing courses. However, these methods have limitations,including insufficient coverage of new technologies and the lag in updating coursecontent to reflect the latest research developments
range, 25 scored in the 2-3 range, 2 scoredin the 0-1 range. These scores reflected the averaging of the two instructor’s scores (eachinstructor would decide on the overall score based on their sub-scores), but there was very goodagreement between them.For the CATME scores, we used their adjustment factor (without self). From the CATME webpage [6]: “The adjustment factor compares an individual student’s ratings with the average ratings of everyone in the team. This helps to see if the student was harsher than the average, or less harsh. There are two different adjustment factors, “Adj Factor w/Self”, which includes the student’s self-rating in the calculation, and “Adj Factor w/o Self”, which does not
and reflectively. In essence, formative assessment is fundamentally concerned withnurturing students' learning and development [9], rendering it a vital component in the fusion ofassessment and teaching [3], [10].Brown [11] describes the formative assessment as the evaluation of learners in the process of"forming" their skills and competencies, facilitating their continuous growth. It encompasses allactivities conducted by instructors and learners alike, supplying information that can beharnessed as feedback to refine ongoing learning and teaching practices [12]. Importantly, thisdefinition underscores the active involvement of both students and teachers, making formativeassessment an integral component for enhancing students
shortest. Similarly, 28% of students who chose Professional Soft Skills did so because it had the most points. The most popular course was Getting Started with Microsoft Office 365; 21% of the students who chose this one said they did so because they used a different suite (often Google) in high school, but the University of Arkansas supports Microsoft products.Question 5: Reflecting back to the courses on your pathway, what was the most useful course onyour pathway? In response to which course in their pathway was most useful, students had varied opinions. The table below summarizes some of the top responses for each pathway. Learning Excel Desktop had the highest percentage within its pathway at 44%. This is likely because we also
could be used to update priorestimates for flexure performance. They were prompted to explore multiple solution paths andnot accept the established solutions per KEEN’s curiosity framework. At the end of the allottedtime, a random student was selected to present their group’s findings to the class as an informaldesign review. After the design review, students all returned to their original seats, where a quizwas delivered on the online learning management system (LMS). The quizzes were nottraditional knowledge-testing quizzes; they were reflection exercises. The students wereprompted to compare and contrast the methods used by the presenting group and their own.They were also prompted to reflect on how well their group functioned during the
Engineering and co-founder of the Integrative Learning Portfolio Lab in Career Education at Stanford University. She earned her undergraduate degree from UCLA and her PhD in Communication with a minor in Psychology from Stanford. Her scholarship is focused on engineering and entrepreneurship education, portfolio pedagogy, reflective practices, non-degree credentials, and reimagining how learners represent themselves through their professional online presence.Prof. George Toye Ph.D., P.E., is adjunct professor in Mechanical Engineering at Stanford University. While engaged in teaching project based engineering design thinking and innovations at the graduate level, he also contributes to research in engineering education
-making process that maynot have emerged organically (Crandall et al., 2006). The questions in the fourth sweep arebroadly divided into four categories, 1) expert-novice contrasts, 2) hypotheticals, 3) experience,and 4) aids. Question prompts include, "Would a novice have noticed the same cues you did inthis situation?" or "How could additional training have offered an advantage here?"(Crandall etal., 2006). Some of the prompts are skipped if they were covered in earlier discussions on theproblem.At the conclusion of the CDM, the interviewers determine if enough information has beencollected to satisfy the eight dimensions of KAM. Reflecting on the results of the interview sofar, the interviewers determine which of these dimensions require
having the opportunity to pilottheir learning modules with other students and then iterate on the module will better highlight thepotential contributions of these elements to their learning. To capture the impact of thoseopportunities (i.e., conference publication, piloting modules) in relation to others we included inthe Fall survey, we will also ask students to reflect on the impact of those elements in the post-clinic surveys of future semesters.Future WorkWe will continue to offer this clinic for the next two years, generating a database of modules (upto five new per year) that can be implemented as mini-projects to broaden soft-robotics exposure.We plan to continue to iterate on existing projects, gather the perspectives of student
, worth 37.5%. The intervention group had two midterm exams (worth 30%) andone group research presentation (7.5%). We included the research presentation for the purpose ofthe intervention. The mindset interventions [2] included the following tasks: (1) contemplating theidea of intelligence and the importance of having a growth mindset while studying chemicalengineering after watching a talk [3] and a video [4] on growth mindset during the first week’sgroup session, (2) having reflections on various attributes related to growth mindset (response tofeedback, learning new things, response to making mistake or failure) through hypotheticalscenarios incorporated into the homework problems, (3) practicing learning from mistakes byresubmitting midterm