New Orleans, Louisiana
June 26, 2016
June 26, 2016
June 29, 2016
978-0-692-68565-5
2153-5965
Educational Research and Methods
13
10.18260/p.27342
https://peer.asee.org/27342
578
Ray Essick received the B.S. degree in General Engineering in 2009, and the M.S. degree in Mechanical Engineering in 2011, both from the University of Illinois, Urbana, IL, USA. He is currently a Ph.D. student with Professor Geir Dullerud in the department of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign.
Matthew West is an Associate Professor in the Department of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign. Prior to joining Illinois he was on the faculties of the Department of Aeronautics and Astronautics at Stanford University and the Department of Mathematics at the University of California, Davis. Prof. West holds a Ph.D. in Control and Dynamical Systems from the California Institute of Technology and a B.Sc. in Pure and Applied Mathematics from the University of Western Australia. His research is in the field of scientific computing and numerical analysis, where he works on computational algorithms for simulating complex stochastic systems such as atmospheric aerosols and feedback control. Prof. West is the recipient of the NSF CAREER award and is a University of Illinois Distinguished Teacher-Scholar and College of Engineering Education Innovation Fellow.
Mariana Silva is an Adjunct Assistant Professor and Curriculum Development Coordinator in the Mechanical Science and Engineering Department at the University of Illinois at Urbana-Champaign. She received her BSME and MSME from the Federal University of Rio de Janeiro, Brazil and earned her Ph.D. in Theoretical and Applied Mechanics from the University of Illinois at Urbana-Champaign in 2009. Besides her teaching activities, Mariana serves as an academic advisor in the Mechanical Science and Engineering department.
Dr. Geoffrey L. Herman is a visiting assistant professor with the Illinois Foundry for Innovation in Engineering Education at the University of Illinois at Urbana-Champaign and a research assistant professor with the Department of Curriculum & Instruction. He earned his Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign as a Mavis Future Faculty Fellow and conducted postdoctoral research with Ruth Streveler in the School of Engineering Education at Purdue University. His research interests include creating systems for sustainable improvement in engineering education, promoting intrinsic motivation in the classroom, conceptual change and development in engineering students, and change in faculty beliefs about teaching and learning. He serves as the webmaster for the ASEE Educational Research and Methods Division.
This evidence-based practice paper focuses on techniques for large-scale implementation of collaborative learning. Collaborative learning is a form of pedagogy that views learning as having a social and cultural component. While there are many implementations of this underlying concept, one common approach is to have students work together in small teams on longer-form activities. When implemented correctly, this has been shown to have positive benefits for student motivation, technical learning outcomes, knowledge transfer and broader objectives such as the ability to work in multidisciplinary teams.
A key challenge for collaborative learning is how to implement it at a large scale, especially in introductory courses with students and instructors who are not familiar with this mode of education. In this paper, we describe results from an iterative design and implementation process of collaborative learning in the introductory mechanics course sequence at Midwestern Research University (MRU), where over 1000 students per semester now participate in weekly collaborative learning activities during discussion sections.
Successful collaborative learning at scale is a multifactorial problem, requiring consideration of the learners, the instructors and the environment within which the learning takes place. This paper focuses on three factors that were identified as particularly important at MRU. First, a new active learning classroom was created that altered the traditional authority structure of the classroom, and fostered greater affinity between students within teams. Second, a new Teaching Assistant (TA) training experience was implemented that focused on collaborative learning, because TAs are the primary student interface and yet have almost always had no prior experience of collaborative learning in their own education. This training aimed to highlight the importance of collaborative problem solving skills and prepare TAs to implement this form of pedagogy. Third, student team creation and management at a large scale necessitated the use of the automated CATME system, allowing teams to be formed and evaluated even with many hundreds of students and tens of discussion sections. This paper evaluates the collaborative learning implementation at MRU in the context of learning space theory, teacher-training methodologies, and team interaction and assessment systems. Longitudinal survey data and two-sample hypothesis testing are used to demonstrate the impact of collaborative learning and particular implementation decisions on students.
Essick, R., & West, M., & Silva, M., & Herman, G. L., & Mercier, E. (2016, June), Scaling-up Collaborative Learning for Large Introductory Courses Using Active Learning Spaces, TA training, and Computerized Team Management Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.27342
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