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A Systems Approach to Analyzing Design-Based Research in Robotics-Focused Middle School STEM Lessons through Cognitive Apprenticeship

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2017 ASEE Annual Conference & Exposition


Columbus, Ohio

Publication Date

June 24, 2017

Start Date

June 24, 2017

End Date

June 28, 2018

Conference Session

Assessment of Student Work

Tagged Division

Educational Research and Methods

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Paper Authors


S. M. Mizanoor Rahman New York University

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Mizanoor Rahman received his Ph.D. degree in Mechanical Engineering from Mie University at Tsu, Japan in 2011. He then worked as a research fellow at the National University of Singapore (NUS), a researcher at Vrije University of Brussels (Belgium) and a postdoctoral associate at Clemson University, USA. He is currently working as a postdoctoral associate at the Mechanical and Aerospace Engineering Department, NYU Tandon School of Engineering, NY, USA. His research and teaching interests include robotics, mechatronics, control systems, electro-mechanical design, human factors/ergonomics, engineering psychology, virtual reality, artificial intelligence, computer vision, biomimetics and biomechanics with applications to industrial manipulation and manufacturing, healthcare and rehabilitation, social services, autonomous unmanned services and STEM education.

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Vikram Kapila New York University Orcid 16x16

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Vikram Kapila is a Professor of Mechanical Engineering at NYU Tandon School of Engineering (NYU Tandon), where he directs a Mechatronics, Controls, and Robotics Laboratory, a Research Experience for Teachers Site in Mechatronics and Entrepreneurship, a DR K-12 research project, and an ITEST research project, all funded by NSF. He has held visiting positions with the Air Force Research Laboratories in Dayton, OH. His research interests include K-12 STEM education, mechatronics, robotics, and control system technology. Under a Research Experience for Teachers Site, a DR K-12 project, and GK-12 Fellows programs, funded by NSF, and the Central Brooklyn STEM Initiative (CBSI), funded by six philanthropic foundations, he has conducted significant K-12 education, training, mentoring, and outreach activities to integrate engineering concepts in science classrooms and labs of dozens of New York City public schools. He received NYU Tandon’s 2002, 2008, 2011, and 2014 Jacobs Excellence in Education Award, 2002 Jacobs Innovation Grant, 2003 Distinguished Teacher Award, and 2012 Inaugural Distinguished Award for Excellence in the category Inspiration through Leadership. Moreover, he is a recipient of 2014-2015 University Distinguished Teaching Award at NYU. His scholarly activities have included 3 edited books, 8 chapters in edited books, 1 book review, 59 journal articles, and 133 conference papers. He has mentored 1 B.S., 21 M.S., and 4 Ph.D. thesis students; 38 undergraduate research students and 11 undergraduate senior design project teams; over 400 K-12 teachers and 100 high school student researchers; and 18 undergraduate GK-12 Fellows and 59 graduate GK-12 Fellows. Moreover, he directs K-12 education, training, mentoring, and outreach programs that enrich the STEM education of over 1,000 students annually.

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Under the design-based research (DBR) process, the design and implementation of a lesson undergoes several iterations, the outcomes of each iteration are analyzed, and the necessary changes and refinement in the design are proposed for implementation and adaptation in the next iterations. Such a strategy may ultimately improve learning outcomes and help yield novel learning theories and artifacts. The DBR approach is especially important to design STEM lessons with robotics because the flexibility and uncertainty of robotics applications require investigations on various alternative approaches to identify the most appropriate, feasible, reliable, and cognitively appealing approach for using robotics in the lesson design that promote students' intrinsic and extrinsic motivation to engage in the lesson. Moreover, application of DBR in STEM education with robotics provides numerous opportunities examine the feasibility and benefits of incorporating constructs of various learning theories such as: cognitive apprenticeship, situated cognition, problem-based learning, and inquiry-based learning. However, application of DBR in STEM education using robotics has not received significant attention yet. From the review of available literature, it is evidenced that while rich qualitative observations and analysis of outcomes guide DBR iterations, a systematic quantitatively-guided approach is lacking. The prevailing DBR strategy may not fully capture true scenario of an iteration and may fail to suggest appropriate modifications for next iteration. This may limit the effectiveness of DBR as currently practiced.

This paper is based on our collaboration with a school teacher who is designing and implementing 7th grade math lessons using robotics. First, students build robots based on the instructions of the teacher and then the teacher designs math lessons using robotics and implements them in classes. The learning activities are sequentially performed in several sessions, which we treat as 'iterations.' In each iteration of robot building, the students discuss among themselves and with the teacher and researcher under a student-teacher-researcher co-design approach, which fosters collaborative learning and co-generation. The students receive researcher's expert opinion that provides the advantages of cognitive apprenticeship. In each iteration, two separate groups of students work towards building two identical robots. For one group, the teacher and researcher use traditional qualitative observation, brainstorming, discussion, questionnaire, and feedback methods to analyze the outcomes of the iteration. For the second group, in addition to traditional methods, they follow some advanced systems engineering approaches under the cognitive apprenticeship of the expert researcher. The DBR is treated as a continuous improvement (CI) method, and resembles as the Deming or Plan-Do-Check-Act cycle. They observe the outcomes in each iteration and analyze them using cause and effect diagrams (fishbone analysis). Then, they apply the Pareto principle (80-20 rule) to identify the vital few causes that contribute to the major outcomes. At the end of an iteration, outcomes for the systems approach are compared to that for the traditional approach. The results show that the system approach is more effective. The results are novel that enrich the DBR method and improve its efficacy in designing STEM lessons using robotics for middle school classrooms.

Rahman, S. M. M., & Kapila, V. (2017, June), A Systems Approach to Analyzing Design-Based Research in Robotics-Focused Middle School STEM Lessons through Cognitive Apprenticeship Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio.

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