student studying Public Policy at Oregon State University. She also holds an M.S. in Environmental Engineering and a B.S. in Mechanical Engineering from Oregon State Univer- sity. Her research in engineering education is focused on student teams engaged in the Virtual Bioreactor (VBioR) Laboratory project. She is specifically interested in understanding the student-instructor interac- tions and feedback that occur during this project and how these factors influence student learning.Dr. Debra M. Gilbuena, Oregon State University Debra Gilbuena is a postdoctoral scholar in the School of Chemical, Biological, and Environmental Engi- neering at Oregon State University. Debra has an M.BA, an M.S, and four years of industrial
demonstratedthe importance of research experiences for the preparation of eventual graduate students. At thepre-graduate level, themes related to network access and the role of the institution in facilitatingintellectual experiences were important for the study participants. At the graduate level, identity-trajectory reiterated the need for careful design of the research laboratory, and the importance ofnetworks for graduate student success.Overview of literatureIdentity-trajectory, introduced by McAlpine 8,10 is a theoretical framework used to understand theprofessional development of graduate students and early career academics through threestrands11: network, intellectual and institution. Network focuses on the relationships andresponsibilities that
Education, 2014 Student Autonomy: Implications of Design-Based Informal Learning Experiences in EngineeringAbstractAs part of their college-based undergraduate degree experience, a large portion of engineeringstudents are involved in different informal learning experiences, such as co-curricular designteams, student organizations, and undergraduate research. The purpose of this qualitative studywas to better understand engineering students’ learning experiences in informal learning sites,particularly their sense of autonomy, which emerged as a major theme in initial data analysis.Specifically, this study investigates a hands-on design and manufacturing laboratory forengineering students in a large research and state
techniques used by the battery industrythrough leaning the theoretical and practical aspects of battery fabrication. The instructional teamdesigned this course to build students’ conceptual understanding by integrating the usevisualization and graphical artifacts, like the ones depicted in figure two, and engaging thestudents in the use of modeling and computational analysis to complete class projects andhomework assignments.In addition, the instructor focused on teaching students how to model and analyze batterysystems using analytical and computational techniques used by practitioners and research expertsin battery systems design. The computation tool used in the course was the Virtual Kinetics ofMaterials Laboratory (VKML). The VKML tool is an
Student- Centric Learning), promoting Leadership in Sustainability and Management Practices. He is also an Affiliate Researcher at Lawrence Berkeley National Laboratory, Berkeley, CA, focusing on the energy ef- ficiency of IT Equipment in a Data Centers. Before his teaching career, he had a very successful corporate management career working in R&D at Lucent Technologies and as the Director of Global Technology Management at Qualcomm. He initiated and managed software development for both the companies in India. He holds MS in Engineering and MBA degrees. Page 24.140.1 c
Professor of Mechanical and Biomedical Engineering at the University of Michigan (UM). She earned her Ph.D. in 2007 in Medical Engineering and Bioastronautics from the Harvard-MIT Division of Health Science and Technology, and holds an S.M. in Aeronautics & Astronautics from MIT and a B.S. in Materials Engineering from the University of Kentucky. She directs both the Sensory Augmentation and Rehabilitation Laboratory (SARL) and the Laboratory for Innovation in Global Health Technology (LIGHT). SARL focuses on the design, develop- ment, and evaluation of medical devices, especially for balance-impaired populations such as individuals with vestibular loss or advanced age. LIGHT focuses on the co-creative design of
undergraduate years as a liminalspace or time[4,7] during which students can explore possible selves and possible professionalidentities. Ibarra and Petriglieri characterize this kind of activity as identity play, acharacterization we share. They define identity play as “people’s engagement in provisional butactive trial of possible future selves”[6]. We have identified a number of course experiences aspotential sites for this identity play. These include: • the lab courses where students put on lab coats and safety goggles as they become familiar with standard laboratory equipment and protocols and the technical knowledge of chemistry; • a communication course where students visit schools as the subject matter expert to
engineering. International Journal of Engineering Education, 26(5), 1097-1110.7 Boxall, J. & Tait, S. (2008). Inquiry-based learning in civil engineering laboratory classes. Proceedings of the ICE - Civil Engineering, 161(4), 152 –161.8 Burns, R. A., Butterworth, P., Kiely, K. M., Bielak, A. A., Luszcz, M. A., Mitchell, P., Christensen, H., Von Sanden, C., & Anstey, K. J. (2011). Multiple imputation was an efficient method for harmonizing the mini-mental state examination with missing item-level data. Journal of Clinical Epidemiology, 64(7), 787- 793.9 Busch-Vishniac, I., Kibler, T., Campbell, P. B., Patterson, E., Darrell, G., Jarosz, J., Chassapis, C., Emery, A., Ellis, G., Whitworth, H., Metz, S., Brainard
simple inquiries about what they read [13]. This givesthe instructor the ability to adjust where necessary the class content based on student concerns. Inthis strategy, the class session can better maximize what concepts such are focused on and howwell the students engage themselves since the class would have been formatted to reflect theirlevel of understanding.It has also been discussed that while much attention has been paid to the use of active learningapproaches in lecture class, laboratory classes themselves have some measure of passiveengagement that requires the application of active activities [14]. The use of laboratory manualswith step-by-step discussions of how to conduct experiment causes students to learn concepts byrote
Youngstown State University, with a Bachelors of Engineering degree in Electrical Engineering in 1981. He then obtained his MS and Ph.D. in Electrical Engineering from GA Tech in 1982, and 1988 respectively. He joined the Electrical and Computer Engineering department at the University of New Mexico where he is currently professor and was the chair between 2005 and June 30, 2011. Since July 1, 2011, Professor Abdallah is the Provost and Executive Vice President for Academic Affairs at UNM. Professor Abdallah conducts research and teaches courses in the general area of systems theory with focus on control and communica- tions systems. His research has been funded by national funding agencies, national laboratories, and by
material with the students.(2)There are several strands of pedagogies of engagement under the umbrella of active learningmethods that have received attention by engineering educators world-wide. (2, 3) For many Page 24.949.2faculty, there remain questions about what “active learning” is and how it differs from traditionalengineering education, since the latter involves activities through homework assignment,laboratories, and, often, group projects. Adding to the confusion, engineering faculty do notalways understand how the common forms of “active learning” differ from each other and mostare not inclined to search for answers. Of the most known and
researching human disease and working to find newsolutions to human health problems – clinical laboratory technologist, medical scientist,biomedical engineer, epidemiologist, and pharmacologist.” This career interest section of thesurvey used a four-point response scale (1 = not at all interested to 4 = very interested). A moredetailed description of the development of the S-STEM Survey, including validity and reliabilityresults, can be found in Faber (2013).17 This prior published work provides details on how career Page 24.1114.3areas were derived from U.S. Department of Labor classifications, prior research, expert review,and field testing of the
studies in learning, thinking, and reaction time2. Below, we summarize some ofthe relevant works on cognition relating to our research based on the extended summary ofcognition, value and decision-making research by Sprehn18.Earlier studies on cognition began in 1940s, where laboratory studies aimed at identifying groupsof people with significant differences in their cognitive processes. Some of the predominanttheories of this epoch are: 1) Perceptual versus Conceptual Groupers3, 2) Sharpeners andLevelers4, 3) Field Dependency/Independency5, and 4) Impulsive versus Reflective Thinkers6,7.We refer the readers to Kozhevnikov8 for an in depth review in this area. One salient criticism ofthese early theories, as voiced by Walker9, Kogan and Saarni10
official journal of the National Association for Science, Technology & Society (NASTS) 23(4), 236-245. 3. Shabani, R., Massi, L., Zhai, L., Seal, S., & and Cho, H.J. (2011). Classroom modules for nanotechnology education: Development, Implementation and Evaluation. European Journal of Engineering Education 36(2), 199-210. 4. Moosavifazel, V., Kumar, A., Cho, H.J., Seal, S. (2013). Laboratory research motivated chemistry classroom activity to promote interests among students towards science. J of Nanotechnology Education 5, 1-5. 5. Massi, L., Georgiopoulos, M., Young, C., Geiger, C., Lancey, P., & Bhati, D. (2011). Defining an evaluation framework for undergraduate research
business. He also is a faculty member in the Department of Computer Science and Engineering. In the decade of the 90s, Dr. Sticklen founded and led a computer science laboratory in knowledge-based systems focused on task specific approaches to problem solving, better known as expert systems. Over the last decade, Dr. Sticklen has pursued engineering education research focused on early engineering with an emphasis on hybrid course design and problem-based learning; his current research is supported by NSF/DUE and NSF/CISE.Prof. Abdol-Hossein Esfahanian, Michigan State UniversityHannah McQuade, The Center for Engineering Education ResearchAndrew League, Michigan State UniversityMr. Chris John Bush, Center for Engineering
, the use of real-timebehavioural rubrics in laboratories has allowed TAs to become more aware of studentexperimental skills and adapt their instruction to student need16. These behavioural rubrics wereuseful in this context as the TA to student ratio was 1:2, but in ratios much higher than this, itwould not be possible for TAs to fill them out in real-time and respond to student needssimultaneously. One approach that could allow student assessment of larger classrooms is the useof behavioural checklists, such as those used to simultaneously assess technical and non-technical skills in medicine17, which provide a binary assessment of the existence of observablebehaviours. While this has potential for demonstrating weaknesses in terms of
founding faculty member of the James Madison Uni- versity Department of Engineering. At JMU, Dr. Pierrakos is the Director of the Center for Innovation in Engineering Education (CIEE) and Director of the Advanced Thermal Fluids Laboratory. Her interests in engineering education research center around recruitment and retention, engineer identity, engineering design instruction and methodology, learning through service, problem based learning methodologies, assessment of student learning, as well as complex problem solving. Her other research interests lie in cardiovascular fluid mechanics, sustainability, and K-12 engineering outreach. Dr. Pierrakos is a 2009 NSF CAREER Awardee. Dr. Pierrakos holds a B.S. in Engineering
particularsection of Introduction to Engineering and one particular chemistry laboratory and lecturecombination. Between three and eight learning communities would be established each semester;more for the fall semester and fewer in the spring. Students would enroll in the learningcommunity after learning about these via email, word of mouth, or during summer orientationsessions. Although these learning communities involved different departments, it was truly alevel zero stage, as the intended use of the benefit was strictly for engineering students (refer toTable 1, Column B). Over time, some of the benefits of these learning communities had diffusedto other departments in science and mathematics, which led in 2007-2008 to increasing thenumbers and types
) theyare required courses and (2) they are upper-level courses typically taken in the Junior or Senioryears. The instructors of these courses are free to select an assessment instrument (e.g., examquestion, homework question, project report, laboratory report, or presentation) for eachPerformance Indicator associated with their assigned SO. Based on the assessment instrumentchosen, the instructor develops a rubric for each Performance Indicator and selects PerformanceCriteria that are used to evaluate the students’ ability to meet that Performance Indicator. Theinstructor’s rubric generally follows a three-tiered approach for assessing the students’performance: “Developing”, “Satisfactory” and “Proficient.” The instructor may select a