of the school year in late May. An analysis of the initial graffiti response may befound in the results section. Additionally, ‘graffiti’ (using dry erase markers) on the largelaminated map was used throughout the year during individual lessons as a tool for the instructorFigure 3 - Graffiti Session Resultsto gauge student engagement in the classroom activities.2.1.2 Use of NSF GK12 program metricsAs a part of the NSF GK12 program, student interest in engineering is assessed through the useof a third party partner. This partner aided in the collection of data about the American students’STEM interest and awareness. The data was then analyzed to determine the improvements instudent interest in STEM fields. Meanwhile, a Likert metric was
, and assessment of recruitment/retention programs for women and minorities. As founder of CSULB’s "Women in Engineering Outreach” program, she understands the importance of community and parental support; she developed "My Daughter is an Engineer," as a residential program for 5th grade girls/parents/teachers. Recognizing that poverty often sets the trajectory for school readiness, her “Engineering Girls–It Takes A Village” residential program serves homeless girls/mothers. She serves on the Board of Directors for Women in Engineering ProActive Network and American Society for Engineering Education PSW. She is currently completing a Ph.D. in Higher
Paper ID #26600Enhancing the Success of Electronics and Mechanical Engineering Technol-ogy Students with an Engineering Calculus II Class Utilizing Open-sourceMathematical SoftwareDr. Erik A. Mayer, Pittsburg State University Erik Mayer is a Professor at Pittsburg State University in Kansas where he has been instrumental in form- ing the Electronic Embedded Systems emphasis in the Electronics Engineering Technology program. His research interests are power electronics and embedded systems. He previously taught at Bowling Green State University in Ohio where he worked with the Electric Vehicle Institute . In addition, he
AC 2010-2377: CENTER FOR LIFE SCIENCES TECHNOLOGY – A MODEL FORINTEGRATION OF EDUCATION, RESEARCH, OUTREACH AND WORKFORCEDEVELOPMENTRupa Iyer, University of Houston Page 15.268.1© American Society for Engineering Education, 2010 Center for Life Sciences Technology – A Model for Integration of Education, Research, Outreach and Workforce DevelopmentAbstractThe biotechnology industry that originated in the 1970’s has since mushroomed from $8 billionin revenues in 1992 to $50.7 billion and is one of the most research intensive industries in theworld. While biotechnology originated based largely on recombinant DNA techniques,tremendous research in biotechnology has
education, our approach is achieving our Page 10.589.1outcomes. Proceedings of the 2005 American Society for Engineering Education Annual Conference & Exposition Copyright © 2005, American Society for Engineering EducationIntroduction It is widely recognized that undergraduate engineers would benefit from formal educationin ethics. In fact, such education is required for ABET accreditation under criterion 3f,“Engineering programs must demonstrate that their graduates have an understanding ofprofessional and ethical responsibility”[1]. However, students are often resistant to ethics in
industry. Moreover, nano-manufacturing technologies produce nano-materialwastes and nano-particle emissions that have been shown to produce more toxic effects onanimals than bulk materials due to the small particle size and large surface area-to-mass ratio12.In short, impulsive adoption of nano-manufacturing into large-scale industrial productions maypose a severe risk to human health and result in adverse environmental impacts.While the integration of macro-nano manufacturing has begun, and global application of suchmanufacturing systems are expected to expand into a broad array of industrial sectors in the future,the scientific investigations of the sustainability of integrated macro-nano manufacturing, asshown schematically in Figure 1, have
principles. The results of implementing thepedagogical tools and a discussion of these results are presented in Section 6. Finally, Section 7concludes the paper and discusses future work.2. Related WorkProject-based courses in software engineering and development have been reported in theliterature. Early papers by Northrup [15] and Adams [1] describe courses where projects givestudents hands-on experience with programming in-the-large and with the software developmentlife-cycle. Both use the waterfall methodology where change to the documented configuration iscontrolled by a control board. In both papers, the course instructor serves as project manager;however, the manager reported by Adams [1] also serves on the Configuration Control Boardand the
. Additionally, there has been a positive mindset shift amongfaculty members as seeing teaching innovation as less overwhelming and more manageablethrough small, incremental changes.4. Assessment 2: Climate SurveysMethod The participants consisted of faculty members (tenure-track, tenured, and academicprofessional track) and graduate students in the MEEN department. The online climate surveywas distributed 10 times between June 2021 and June 2024 (roughly 3 times per year) to theentire department (including staff members) via Qualtrics. The content of the surveys includedthe following topics for teaching and teaching innovation: means efficacy (i.e., are theresufficient resources), self-efficacy (i.e., do I believe that I am capable of this
sustainable management of water resources.Prof. David Emile Mesple, Texas Tech University David Mesple’ is a Professor of Art and Ideation, as well as a practicing artist. His work has been profiled in textbooks, periodicals, and critical reviews. Currently working on his PhD in Interdisciplinary Fine Arts, His areas of research are directed at investigating the psychological, philosophical, and neuro- biological bases of creativity and problem solving.Mr. Francesco V. Donato, Texas Tech University PhD Candidate, Cognition & Cognitive Neuroscience program.Ibrahim Halil Yeter, Texas Tech University Ibrahim H. Yeter is currently a PhD candidate in the Curriculum and Instruction program at the Col- lege of Education, and
, andsupported a total of 96 GK-12 Fellows. A study was conducted to investigate the long-termimpact of participating in the program on the GK-12 Fellows. In 2011, former Fellows werecontacted and asked to take an online survey about their program experience, and how it affectedtheir career path after graduation. The majority of survey respondents indicated that they felt theGK-12 experience had a large or very large impact on their career path. The time spent activelyteaching in classrooms led to large impacts on teaching, communication, and presentation skills.In addition, other skills such as leadership, teamwork, and time management were also reportedto have been improved. Participants ranked teaching K-12 students – the primary activity in theGK-12
Page 10.564.44 GB of main memory and 160 GB of disk space, of which 90 GB are used for home directories. Proceedings of the 2005 American Society for Engineering Education Annual Conference & Exposition Copyright © 2005, American Society for Engineering EducationThe compute nodes contain 2 GB of main memory and 20 GB disk space. The cluster uses Man-drake Linux as the operating system and is build and maintained using the Warewulf Cluster Tool-kit (http://warewulf-cluster.org). Each compute node is managed from the server and it does notmake a difference if a small or large cluster is maintained—the procedure is identical. Once onenode is booting correctly all additional nodes will work in exactly the same manner
besensitive enough to track small changes in classroom learning opportunities and studentengagement. The tool is not currently designed to provide individual feedback to faculty. Ourgoal with this tool was to be able to collect larger-scale data to assess and monitor theinstructional practices on campus that we were promoting in the teaching and learning center.We also wanted to better understand the patterns of discourse, tasks, and interactions in thecourses, recognizing how these contribute to active learning and socializing intelligence(Resnick, Asterhan, & Clarke, 2015).In an active learning survey disseminated to the Mines faculty in 2015, 62% of the facultyresponded and 92% of the respondents reported using active learning in their
Learning is a form of AI machine learning that has gained a great deal of recognition in thepast 10 years in a wide range of areas such as medical diagnosis, quality assurance, defectdetection, face detection, autonomous vehicles, and many others. Deep learning networks,however, typically require large training databases of labeled images and often requirespecialized hardware and high-level software expertise. Techniques, such as transfer learningand the proper choice of software tools can mitigate some of these requirements. This paperdescribes a new, project-based course module to introduce deep learning and computer vision toundergraduate multidisciplinary engineering students in a robotics design and applications courseusing MATLAB software.1
discussion—all for a single class.In hopes of lightening the students’ technological load, the instructor decided to use the quizassessment functionality in Canvas as the sole assessment method for the course. That meant thatthere would need to be a conversion of the typical 8-10 homework assignments, two tests, and afinal exam into the quiz structure in the Canvas platform. In addition, as the students would bereceiving and completing the quizzes online, the instructor felt the need to customize the quizzesfor each student, largely to encourage academic integrity. In other words, for a class of 100students, the instructor wanted to generate on the order of 300 unique and different quiz versionsfor each assessment so that, when a student needed to
concerning the level of AEdisplayed by various populations is extremely limited in most contexts, be it education orworking professionals. As such, data concerning the level of adaptiveness displayed amongvarious groups needs to be measured if activities designed to promote the development of AE areto be created and then tested in terms of their efficacy. This investigation provides this criticalbaseline data for future studies as we track the AE development of individual, first-year collegestudents through their undergraduate program of study, with a focus on low-income students as ameans to support retention.In this work, we assessed adaptive expertise among low-income STEM students using surveysand interviews. Low-income STEM students from
Learning framework.Initially the course design was a very traditional calculus course. The course was structured tohave small coordinated sections that all used common exams. The professors lectured anddemonstrated problem solving and students worked on practice problems as out-of-class work.There was limited active learning in the classroom and the outcomes achieved were lower levelMoving Beyond Active Learning to Engineering Learning 5(as indicated by Webb’s Depth of Knowledge or Bloom’s Taxonomy). The problems werefocused on computation and the course was driven by topics: integration, applications,sequence/series, and vectors. The primary assessments (exams) were all designed to be easyto administer
student learning. Using a academic backgrounds and career trajectories.mixed-methods approach, we collected data from 35 students (25from DB and 10 from EEM) through pre- and post-study surveys, The significance of integrating prompt engineering intoskills assessments, and qualitative feedback. Key findings reveal curricula spans disciplines. In computational fields, it enhancesthat students in both courses reported an improved understanding technical workflows such as code generation or databaseof AI and proficiency in prompt engineering. Students in the DB optimization, while in engineering or applied sciences, itcourse, which has a
analysis, prototype development and documentation usingeasily scalable to a large class. engineering drawings. • Statics: After working on this activity, I understand how to ASSESSMENT AND GOAL ATTAINMENT perform simple static analysis on load bearing structures using MATLAB. The overall assessment in this segment of the course was • Free Body Diagram (FBD): I am comfortable setting up abased on both, the lab teamwork and the individual
experiences as a means to increase comfort with Lowman’s Model1.Figure 3. Assessment results for the instructors considered in this study.While the rubric captures a ranking score, the intention is not to use the rubric as a measurement,but as a guide for direction. Yoda is a renowned character that most individuals would classify asa complete exemplar. However, in the clip presented in the case study, one can be reminded thathis unique grammatical type of speech can make understanding difficult for a student. Further,his teaching style tends towards a Socratic approach that is more amenable to small classes,seminars, and advanced classes where students are more independently confident. Yoda mayhave an opportunity to improve his teaching skills if it
collegeis seeking an increase in enrollment. These students have applied and been selected to participatein this initiative with an expectation of an average of three hours per week of their time. Thisinitiative is in its first year, the graduate students applied at the start of the semester, and theprogram launch began approximately four weeks into the semester start. This discussion coversthe first ten weeks of the initiative, starting with program launch and the conclusion of the firstsemester. The development of the project management processes over these initial weeks arecentral to this discussion.The first step involved assembling a small team of five graduate engineering students. Theirroles and expectations were clearly defined at the
communication/networks, multimedia bandwidth forecasting, smart grid applications, and engineering education.Dr. Youakim Al Kalaani P.E., Georgia Southern University Youakim Kalaani is an Associate Professor of Electrical Engineering in the Department of Electrical En- gineering at Georgia Southern University. Dr. Kalaani received his B.S. degree in Electrical Engineering from Cleveland State University (CSU). He graduated from CSU with M.S. and Doctoral degrees in Elec- trical Engineering with concentration in power systems. Dr. Kalaani is a licensed professional engineer (PE) and an ABET Program Evaluator (PA). He is a Member of IEEE and ASEE and has research interests in distributed power generations, optimization, and
Missouri. She is PI of the NSF-funded Supporting Collaboration in Engineering Education, and has studied and published on engineering education, women and minorities in STEM, online learning and assessment. Marra holds a PhD. in Educational Leadership and Innovation and worked as a software engineer before entering academe.Dr. Douglas J Hacker, Dr. Hacker is a full professor in the Department of Educational Psychology and participates in both the Learning Sciences Program and the Reading and Literacy Program. Prior to receiving his Ph. D. in educational psychology from the University of Washington in 1994, Dr. Hacker worked as a high school science and math teacher and then as a school counselor. From 1994 to 1999, Dr
theappropriate knowledge and skills to become effective contributors in the manufacturingworkforce and more importantly, to “hit the ground running” once they leave school. In a seriesof industry workshops and surveys that included manufacturing representatives from Fortune500 enterprises (such as Ford Motor Company, General Motors, The Boeing Company, 3MCompany, Motorola, and Caterpillar) and medium- and small-sized companies, the MEP hasidentified 16 competency gaps that need to be closed between industry’s manufacturingworkforce needs and what is provided by current educational programs. In all surveys andworkshops conducted by the MEP since 1997, “hands-on experience in at least one specificmanufacturing process” has been consistently listed among
researchquestions explored to what extent is the new format effective in obtaining the new camp goals..Participation in the formal assessment measures was high, with 88% of participants completing aquestionnaire upon arrival and again at the end of the day. Using this data from 2016 and 2015camps, researchers identified patterns and offer possible explanations for how genderbreakdowns affect student learning and confidence in STEM. Furthermore, using reflectionsfrom camp staff and feedback from students, effective engineering education practices,programs, lessons, and curriculum designs were created and modified.History of Camp (2000-2015)In 2000, the University of St. Thomas first offered a Science, Technology, and EngineeringPreview Summer camp (STEPS
Lecturer and is the recipient of the Fulton Outstanding Lecturer Award. She focuses on designing the curriculum and teaching in the freshman engineering pro- gram. She is also involved in the NAE Grand Challenges Scholars Program, the ASU ProMod project, the Engineering Projects in Community Service program, the Engineering Futures program, the Global Freshman Academy/Earned Admission Program, and the ASU Kern Project. Dr. Zhu also designs and teaches courses in mechanical engineering at ASU, including Statics, Mechanics of Materials, Mechan- ical Design, Mechanism Analysis and Design, Finite Element Analysis, etc. She was a part of the team that designed a largely team and activity based online Introduction to
(the number of participants) because few students haddual degrees as undergraduates. The small fraction (~20%) of students attracted to theinterdisciplinary computational science programs have minors or dual degrees. Among the 12doctoral students participating in the S-STEM program, seven entered doctoral studies directlyafter their undergraduate degrees. All students in the cohort take courses to develop expertise inmathematical modeling, numerical methods, programming, data science and high performancecomputing. Their thesis/dissertation research requires them to develop and apply newcomputational methods to solve practical problems in a science or engineering topic. The application areas of student’s thesis/dissertation research were as
Engineering Program aligns the undergraduate teaching andlearning with their institution's ongoing research portfolio [46]. And at Aalborg University, Denmarkthey have mega projects that consist of interdisciplinary projects that range across the wholeUniversity and involve a large number of students working together [58]. All projects are based onglobal problems as formulated in the United Nations’ 17 SDGs.2.4. Alignment with faculty rolesPrevious studies have shown that faculty who participate in extra- and co-curricular activities reportintrinsic benefits of an altruistic nature [59]. Faculty enjoy the personal contact with students andplaying a more active part in their development. Although the AREND project experience does notdispute this
), network game such as Scrabble or network Battleship (socket programming),USB sensor (writing a DLL plus A/D interface), Windows phone app such as a calculator,embedded remote data collector using FEZ hardware and socket programming, and the travelingsalesman problem (genetic programming).In this paper we present the course structure and grading process, a description of the projects,and assessment based upon student feedback.IntroductionEE 356 (Small System Software) is taught as a variation on the inverted classroom concept1, 2 inwhich there are few standard lectures and students do most of the class work outside of class.This class was taught as a standard lecture class until 2009 when a new instructor tried theinverted format as a way to make
experiences in 2001-02 was a result of the transfer of theprincipal organizer in Turkey to a new position. It is expected that this will be atemporary hiatus, but does illustrate the danger of having any program dependent onparticular faculty.AssessmentThere is plenty of anecdotal evidence that terms abroad are valuable experiences fornearly all students. However, formal surveys are much less comprehensive. Most occursoon after the students return home, when they are still in the glow of the “experience”and haven’t had time to process the lasting impact on their lives. What are really neededare longitudinal outcomes evaluations after graduation. Although the population willinitially be small, the engineering programs at Union College plan to develop
structured to meetthe needs of a ‘white, male, heteronormative’ mentee profile [6], which furtherexacerbates the mentorship gap.Formal mentorship programs within engineering departments across the countryare largely underdeveloped and underutilized [16, 17], which may be due in part toa lack of clarity on what constitutes a well-structured program, overreliance oninformal mentorship relationships, and a lack of funding and resources to supportongoing mentorship efforts [17]. Research on engineering faculty mentorshipdemonstrates an overwhelming positive sentiment around mentorship, but thereremains a need for additional evaluation of mentorship models in variousuniversity settings to inform the future development of evidence-based