AC 2010-1868: IMPLEMENTING AN INVERTED CLASSROOM MODEL INENGINEERING STATICS: INITIAL RESULTSChristopher Papadopoulos, University of Puerto Rico, Mayagüez Christopher Papadopoulos is a faculty member in the Department of General Engineerng at the University of Puerto Rico, Mayagüez, where he coordinates the Engineering Mechanics Committee. His research interests include nonlinear structural mechanics, biomechanics, engineering education, and engineering ethics, and he serves as secretary of the ASEE Mechanics Division. He holds BS degrees in Civil Engineering and Mathematics from Carnegie Mellon University, and a PhD in Theoretical and Applied Mechanics, Cornell University. He was
Paper ID #7331Leveraging Simulation Tools to Deliver Ill-Structured Problems in Statics andMechanics of Materials: Initial ResultsProf. Christopher Papadopoulos, University of Puerto Rico, Mayaguez Campus Christopher Papadopoulos is an Assistant Professor in the Department of General Engineering at the Uni- versity of Puerto Rico, Mayag¨uez (UPRM). He earned B.S. degrees in Civil Engineering and Mathematics from Carnegie Mellon University (1993) and a Ph.D. in Theoretical & Applied Mechanics at Cornell Uni- versity (1999). Prior to coming to UPRM, Papadopoulos served on the faculty in the Department of Civil
the University of Wisconsin-Milwaukee (UWM). Papadopoulos has diverse research and teaching interests in structural mechanics, biomechanics, appro- priate technology, engineering ethics, and engineering education. He is PI of two NSF sponsored research projects and is co-author of Lying by Approximation: The Truth about Finite Element Analysis. Pa- padopoulos is currently the Program Chair Elect of the ASEE Mechanics Division and serves on numerous committees at UPRM that relate to undergraduate and graduate education.Dr. Aidsa I. Santiago-Rom´an, University of Puerto Rico, Mayaguez CampusDr. Genock Portela-Gauthier, University of Puerto Rico, Mayaguez Campus
todescribe the Engineering Genome.For the purposes of this research project, an ontology is composed of several parts: (i) astructured, explicit description of a knowledge domain that indicates relationships among classesof objects in that domain, (ii) properties or traits (which we will call “genes”) that describevarious attributes of those classes of objects, and (iii) individual instances (in our case, multimedia Page 23.753.4learning elements) that are classified according to the set of classes and traits from items (i) and(ii). As a concrete example, consider a multimedia file (say, a movie) that is a video solution to aparticular problem
their Dynamics curriculum, they encountered similardifficulties in translating research to practice10. These faculty members wanted to create a newresource- and technology-rich learning environment. However, while each component of theproposed classroom had its own robust body of literature, there was little existing research tohelp integrate these diverse methods into a single course. Thus, these instructors relied on their extensive past experience as educationalpractitioners to guide an initial course redesign. The resulting curriculum, now referred to as theFreeform learning environment, was successful by many metrics. For example, grades inDynamics improved as the percentage of students earning D, F, or W (withdrawal) grades
MaterialsIntroductionThe work reported in this paper begins with the end of a previous research project. Our earlierwork investigated student understanding of mechanics of materials1–3. After describing howstudents understand this topic, we wanted to move on to developing course materials to helpbuild on students’ existing understanding and address misconceptions. This is not an unusualprogression, and, indeed, our initial research in this area showed us that most course materialsthat are developed from research never achieve broad adoption4. Many engineering educatorsdevelop their own materials, duplicating researchers’ efforts and potentially denying students thebenefit of research-based materials with proven effectiveness. The lack of adoption is a
address topical areas as part of an NSF-funded project. One of these focused on Statics and Dynamics; 24 instructors from research-based, community colleges, and MS granting institutions participated in the Mechanics VCP.The VCP was centered on aligning the classroom around teaching objectives, classroomactivities, and assessment and utilized the How Learning Works framework for discussions.Topics included Bloom’s taxonomy and writing learning objectives, active learning strategies,collaborative learning, conceptual understanding, hands-on activities, and flipping the classroom.An initial 8 week period introduced these topics and helped the instructors formulate their plansfor the upcoming term, and a follow-on period is currently underway to
AC 2010-1069: FOUR FREE-VIBRATION LABORATORY EXPERIMENTS USINGTWO LUMPED MASS APPARATUSES WITH RESEARCH CALIBERACCELEROMETERS AND ANALYZERRichard Ruhala, Southern Polytechnic State University Richard Ruhala earned his BSME from Michigan State in 1991 and his PhD in Acoustics from The Pennsylvania State University in 1999. He has 3 years industrial experience at General Motors and 3 years at Lucent Technologies. He was an Assistant Professor in the Engineering Department at the University of Southern Indiana before joining the faculty at Southern Polytechnic State University in 2010 as an Associate Professor, where he also serves as director for their new mechanical engineering program. He has
likely have different abilities as they start the course, which cancloud the relation between performance and engagement. This paper reports on a study ofstudents’ learning progress in one Statics course where students used web-based coursematerials. In particular, we focus on preliminary findings about the relation between studentengagement with the materials and their final knowledge, accounting for entering ability.2. DESCRIPTION OF OLI ENGINEERING STATICS COURSEThe web-based Statics course has been developed by two of the authors (AD and PS) as a part ofthe Carnegie Mellon Open Learning Initiative (OLI) and is available to individual learners andinstitutions free of charge. The course has benefited from prior research into
D,W,F percentage for ten semestersof Elements of Structures at 10.6% (p = .000531). A central concern for engineering educators is how to get students to master so manyequations and definitions while also understanding the physical mechanisms in such a limitedtime [2]. Recent research initiatives have demonstrated that engineering faculty do not possess agood solution. They found that contrary to high passing rates, students are failing tocomprehensively understand the concepts that they need to master in mechanics of solids courses[3]. This failure has prompted many researchers to investigate potential causes of thisdiscrepancy with the intention of identifying teaching and learning approaches that can helpstudents develop a
of processing as thechallenges required of students. In this second study, additional questions were added to theexams to better align with the challenges. Initial analysis of the data indicates that studentsincrease their ability to generate ideas and questions using concepts and principles applied in theearlier challenges. The analysis of results also helps describe the limits of students’ conceptualunderstanding of the governing principles and how these limits diminish with time. Therefore,students are on a learning progress that increases their potential for generalizing their knowledgewhich will increase their potential to use it in less familiar context. The results of this study willbe interesting to instructors and researchers
Paper ID #10411Evaluation of Impact of Web-based Activities on Mechanics Achievement andSelf-EfficacyProf. Sarah L. Billington, Stanford University Sarah Billington is Professor and Associate Chair of the Department of Civil & Environmental Engineer- ing at Stanford University. Her research group focuses on sustainable, durable construction materials and their application to structures and construction. She teaches an undergraduate class on introductory solid mechanics as well as graduate courses in structural concrete behavior and design. Most recently she has initiated a engineering education research project on
faculty beliefs about teaching and learning. He is a recipient of the 2011 American Society for Engineering Education (ASEE) Educational Research and Methods Division Apprentice Faculty Grant. He helps steer the Col- lege of Engineering Dean’s Strategic Instructional Initiatives Program and consults with the Academy for Excellence in Engineering Education at the University of Illinois. Page 24.1148.1 c American Society for Engineering Education, 2014 Sustainable Reform of Introductory Dynamics Driven by a Community of Practice
Post 0.38 0.14 Traditional Non-flipped Pre 0.03 0.06 Control Group (n = 11) Change, 0.36 0.14To address the second research question as to whether, after controlling for prior academicachievement and initial levels of content-specific achievement, students participating in a flippedinstructional delivery section of an engineering course perform better on content-specificachievement measures than those in a traditional section of the same course, multiple linearregression was employed. Control variables, prior academic achievement and initial levels ofcontent-specific achievement entered in
embeddedinteractive exercises offering individualized feedback and help to students, while givinginstructors summary information on student performance. Various efforts to assess theeffectiveness of courseware have been presented in the past and summarized here.As demonstrated in past research, students exhibit significant gains in diagnostic quizzes afterusing OLI modules. Also, quiz scores have been shown to correlate positively with otherimportant measures of performance, such as exams and statics concept inventory scores.However, it has been found that overall course performances do no correlate with how manyoptional exercises a student initiates. This result was to some extent expected, since in thesestudies students were not required to undertake a
) on the pre-test but increased to over 0.44on the post-test. Question 8 of the aDCI is shown in Figure 3, and the DCI authors hypothesizedthat the main misconception associated with this problem is that tension is equivalent to weight5.While the item discrimination for Question 8 rose above the 0.2 suggested value on the post-test,it had the lowest proportion of students answering it correctly out of any of the questionsincluded in the test. This may suggest that the tension-weight-equivalence misconception shouldbe addressed more effectively in the curriculum.Future Work Regarding aDCI DevelopmentBased on the initial psychometric results presented above and those published by otherresearchers, it may be valuable for the Freeform researchers
AC 2008-87: TEACHING MULTIBODY DYNAMICS IN AN UNDERGRADUATECURRICULUM – AN INTUITIVE AND EXPLICIT FORMALISM BASED ONPARASITIC ELEMENTSGeoff Rideout, Memorial University of Newfoundland Geoff Rideout received his B.Eng. (Mechanical) from Memorial University in 1993, his M.A.Sc. (Eng.) from Queen's University in 1998, and his Ph.D. from the University of Michigan in 2004. He is currently an assistant professor of engineering at Memorial University, teaching mechanics and design courses. He is conducting research in the area of automated generation of computer simulation models for dynamic system design
spatial intervention course rather than continuing torandomly select participants for the spatial intervention as was done before. The students thatwere accepted and voluntarily took the spatial ability class demonstrated roughly the samepercentage increase as did the randomly selected group the year prior. Continued data collectionrevealed an average student gain of 27% on their PSVT:R test results3. While some may extendthis research to discover how much spatial ability improves in those who already have a higherlevel initially, the work conducted nevertheless shows that spatial ability is not innate andresponds to training and experiences within the studied demographics.It has also been verified that spatial ability can be learned through
, but that growing class sizes and demands on teachingtime, as well as students’ prior knowledge and experiences, have deemphasized aspects ofproblem solving that align with research on learning and evidence-based pedagogical practices.Educational researchers argue that technology-rich learning environments can be used toovercome these challenges and thus foster conceptual understanding. To systematicallyinvestigate how a technology-rich problem-solving interface can enhance the teaching, learning,and assessment of complex engineering knowledge, researchers must initially develop 1prerequisite understandings of both the processes by which students
2006-936: SOLVING NONLINEAR GOVERNING EQUATIONS OF MOTIONUSING MATLAB AND SIMULINK IN FIRST DYNAMICS COURSEAli Mohammadzadeh, Grand Valley State University ALI R. MOHAMMADZADEH is currently assistant professor of Engineering at School of Engineering at Grand Valley State University. He received his B.S. in Mechanical Engineering from Sharif University of Technology And his M.S. and Ph.D. both in Mechanical Engineering from the University of Michigan at Ann Arbor. His research area of interest is fluid-structure interaction.Salim Haidar, Grand Valley State University SALIM M.HAIDAR is currently associate professor of Mathematics at Grand Valley State University. He received his B.S. in
student learning in a “flipped” classroom. Some work has also been done on the “flipped” classroom in college-level engineeringmechanics courses. Papadopoulos and Santiago2 considered an inverted classroom in a staticscourse. They found instructors favored the inverted approach while students’ perceptions weresomewhat mixed. In this initial research, they found improvement in scores over standard Page 26.135.2approaches, but stated more data is needed to achieve more conclusive results. Swithenbank andDeNucci3 found that flipping a dynamics class showed some evidence of positive outcomes;however, they suggested a more detailed study would be
projects & incorporates civil engineering examplesand real-world applications with much more emphasis on vibration than in a traditional dynamicscourse.The increased emphasis on the vibration material keeps our civil engineering students moreengaged in the course. There is an initial resistance to learning the material when all students seeare box-spring examples when first going through the derivation of the equation of motion forsingle degree of freedom systems. Instead of starting with the simplified model, a one-storybuilding is presented to the class and the first step in solving the problem is the development ofthe analytical model for the system. This also serves to connect the concepts of the dynamicscourse with other courses in the
Paper ID #34252Work-in-Progress: Computer Simulations to Deliver Inquiry-BasedLaboratory Activities in MechanicsMr. Jacob Matthew Cook, Oregon State University Jacob Cook received his Honors B.S. in Bioengineering and his Honors B.S. in Electrical and Com- puter Engineering from Oregon State University in Spring 2020. During his undergraduate studies he was a researcher and software developer for the Koretsky Education group, focusing on web-based JavaScript physics simulations. His primary research interests include engineering education, biomed- ical devices/instrumentation, integrated circuit design, computational
information and data from public sourcesChallenge statement: Can you design the best web-based game to review an important solidmechanics concept?a. Generate ideas: Initially students are asked to go through different games (puzzles) developedby previous undergraduate students and review important solid mechanics concepts. Afterstudents get familiar with the games, the challenge of designing a new game or a level of anexisting game is given to groups of students.b. Multiple perspectives: At this point, students have opportunities to obtain information frominternal and external resources about the relevance of their proposed game and typical gameplatforms (work in progress).c. Research and Revise: Reference materials to help the student revise their
. Papadopoulos has diverse research and teaching interests in structural mechanics and bioconstruction (with emphasis in bamboo); appropriate technology; engineering ethics; and mechanics education. He has served as PI of several NSF-sponsored research projects and is co-author of Lying by Approximation: The Truth about Finite Element Analysis. He is active in the Mechanics Division.Eric Davishahl, Whatcom Community College Eric Davishahl holds an MS degree in mechanical engineering and serves as associate professor and engineering program coordinator at Whatcom Community College. His teaching and research interests include developing, implementing and assessing active learning instructional strategies and auto-graded online
wereactively thinking about things. Now this is a much better use of their time than me droning on infront of the class.”The MRU2 instructor describes learning about the workshop model from a specific colleague inhis department initially and then following up by becoming familiar with the literature on activelearning and pursuing additional professional development seminars offered at his university.The MRU1 instructor, who received a 28/100 score on the RTOP scale, was the least reformedinstructor in the study. He is a tenure-track assistant professor in his first semester in anengineering department at MRU. He has previous teaching experience in statics as a graduatestudent and post-doctoral research fellow. His classroom methods focused on lecture
from Carl Jung’s theory ofpsychological types.2 His foundational work suggested that people function and interact withdifferent learning/communication types. This psychological research led to the development ofhow people can be evaluated for their preference of learning. Work done by Kolb,1 Felder3 andMyers-Briggs4 each contributed extensive research in assessing how individuals learn and theirpreference of learning style. Each developed similar test questions to categorize and define thelearning preference of a student. These learning styles in the Klob’s research are diverging,accommodating, converging and assimilating. In a classroom setting research done by Mills5indicated that learning is optimized by the application of the above
sustainorganizational initiatives [31]. The fundamental principles for AI suggest that the inquiry shouldbegin with appreciation, should be collaborative, and should be applicable. AI begins with theidentification of positive attributes and then connects those attributes with the community’svision and action for change [32]. Thus, AI research methodology is highly generative in natureand consists of a 4-D cycle of phases: discovery, dream, destiny, and design. For example, AIresearch methodology places emphases on strategically engaging stakeholder representatives(key faculty at the host institutions, students, and graphic artists) in a networked improvementcommunity in order to gather relevant contextually bound data pertaining to each
Paper ID #19122Student Perceptions of Learning Experiences in Large Mechanics Classes:An Analysis of Student Responses to Course Evaluation SurveysMs. Michelle Soledad, Virginia Tech and Ateneo de Davao University Michelle Soledad is a doctoral student and graduate research assistant in the Department of Engineer- ing Education at Virginia Tech. Her research interests include faculty development and data-informed reflective practice. Ms. Soledad has degrees in Electrical Engineering (BS, ME) from the Ateneo de Davao University (ADDU) in Davao City, Philippines, where she continues to be a faculty member of the Electrical
Paper ID #34539Do They Need To See It To Learn It? Spatial Abilities, RepresentationalCompetence, and Conceptual Knowledge in StaticsEric Davishahl, Whatcom Community College Eric Davishahl holds an MS degree in mechanical engineering and serves as associate professor and engineering program coordinator at Whatcom Community College. His teaching and research interests include developing, implementing and assessing active learning instructional strategies and auto-graded online homework. Eric has been a member of ASEE since 2001. He currently serves as awards chair for the Pacific Northwest Section and was the recipient of