scholarly journals Analyzing Engineering Design through the Lens of Computation

2014 ◽  
Vol 1 (2) ◽  
pp. 151-186 ◽  
Author(s):  
Paulo Blikstein

Learning analytics and educational data mining are introducing a number of new techniques and frameworks for studying learning. The scalability and complexity of these novel techniques has afforded new ways for enacting education research and has helped scholars gain new insights into human cognition and learning. Nonetheless, there remain some domains for which pure computational analysis is currently infeasible. One such area, which is particularly important today, is open-ended, hands-on, engineering design tasks. These open-ended tasks are becoming increasingly prevalent in both K–12 and post-secondary learning institutions, as educators are adopting this approach in order to teach students real-world science and engineering skills (e.g., the “Maker Movement”). This paper highlights findings from a combined human–computer analysis of students as they complete a short engineering design task. The study uncovers novel insights and serves to advance the field’s understanding of engineering design patterns. More specifically, this paper uses machine learning on hand-coded video data to identify general patterns in engineering design and develop a fine-grained representation of how experience relates to engineering practices. Finally, the paper concludes with ideas on how the specific findings from this study can be used to improve engineering education and the nascent field of “making” and digital fabrication in education. We also discuss how human–computer collaborative analyses can grow the learning analytics community and make learning analytics more central to education research.

Author(s):  
Tandra Lea Tyler-Wood

Digital fabrication and the “maker movement” can play a major role in bringing computational technology into the 21st century classroom. Digital fabrication is defined as the process of translating a digital design developed on a computer into a physical object or any process for producing/printing a three-dimensional (3D) object. The maker movement is a platform for today's futuristic artisans, craftsmen, designers and developers to create, craft, and develop leading ideas and products. Digital fabrication and “making” could provide a new platform for bringing powerful ideas and meaningful tools to students. Digital fabrication has the potential to be “the ultimate construction kit.” Digital fabrication has strong ties to the maker movement. Maker spaces provide students with safe areas that allow students to safely use digital fabrication to make, build, and share their creations. This chapter will look at the role that digital fabrication can play in incorporating computational technology into the K-12 classroom.


Author(s):  
Abigail Konopasky ◽  
Kimberly Sheridan

The Maker Movement is a broad international movement celebrating making with a wide range of tools and media, including an evolving array of new tools and processes for digital fabrication such as 3D printers and laser cutters. This article discusses who makers are in education, what that making entails, and where that making happens. akers are people of all ages who find digital and physical forums to share their products and processes. Educators and researchers in the Maker Movement in education are working to expand who makers are, providing critiques of traditional conceptions of maker identities and seeking to broaden participation in terms of race, gender, socioeconomic status, and ability status. Making entails a diversity of media, tools, processes and practices. Likewise, the Maker Movement in education purposefully transcends academic disciplines, drawing both on traditional academic subjects like engineering and math along with everyday life skills like sewing, carpentry and metalwork. Making happens across a variety of spaces where there is an educational focus, both informal (museums, community centers, libraries, and online) and formal (from K–12 to higher education, to teacher education). In these spaces, the specific goals and practices of the supporting organizations are woven together with those of the Maker Movement to support a range of learners and outcomes, including family inquiry, equity, access to technology, virtual community and support, social interaction, creativity, engineering education, and teacher candidate confidence. Maker education is often framed as a reaction to more “traditional” educational approaches and frequently involves the incorporation of making into STEM (science, technology, engineering, and math) and STEAM (science, technology, engineering, art, and math) approaches.


Author(s):  
Swaroop S. Vattam ◽  
Michael Helms ◽  
Ashok K. Goel

Biologically inspired engineering design is an approach to design that espouses the adaptation of functions and mechanisms in biological sciences to solve engineering design problems. We have conducted an in situ study of designers engaged in biologically inspired design. Based on this study we develop here a macrocognitive information-processing model of biologically inspired design. We also compare and contrast the model with other information-processing models of analogical design such as TRIZ, case-based design, and design patterns.


Author(s):  
Jennifer L. Chiu ◽  
Glen Bull ◽  
Robert Q. Berry ◽  
William R. Kjellstrom

2016 ◽  
Vol 3 (2) ◽  
pp. 220-238 ◽  
Author(s):  
Paulo Blikstein ◽  
Marcelo Worsley

New high-frequency multimodal data collection technologies and machine learning analysis techniques could offer new insights into learning, especially when students have the opportunity to generate unique, personalized artifacts, such as computer programs, robots, and solutions engineering challenges. To date most of the work on learning analytics and educational data mining has been focused on online courses and cognitive tutors, both of which provide a high degree of structure to the tasks, and are restricted to interactions that occur in front of a computer screen. In this paper, we argue that multimodal learning analytics can offer new insights into students’ learning trajectories in more complex and open-ended learning environments. We present several examples of this work and its educational application.


Author(s):  
Thomas F. C. Woodhall ◽  
David S. Strong

Education research strongly links methods of course assessment with the student learning process. In open-ended engineering design courses, assessment based on student deliverables as “product” may focus student attention on a content checklist rather than effectively learning process and techniques that are critical to professional engineering practice. By developing a rubric assessment scheme that relates directly to the course learning objectives and sharing it openly with students, it is proposed that students are more likely to achieve deeper learning on the process of engineering design.


2017 ◽  
Author(s):  
Devin R. Berg ◽  
Matthew Wigdahl ◽  
Charis D. Collins

This Work in Progress paper presents on the design of project-based learning approach focused on assistive technology as applied in a freshmen level engineering course which also integrates outreach with the local K12 system. The university course targets general education topics as well as an introductory engineering design experience and includes content on the engineering design process, societal implications of engineering design, and a participatory lab-based design project. A partnering class of 5th graders from a local elementary school made use of a daily block of time set aside for academic interventions and individual project-based work to collaborate with the university class. A qualitative assessment was conducted and has thus far has revealed that the university students found the assistive technology theme of the semester-long design project to be meaningful. For the K12 students, the survey results and anecdotal observations suggest that we were only moderately successful in constructing a meaningful and purposeful design experience, from their perspective.


Author(s):  
Tamara J. Moore ◽  
Aran W. Glancy ◽  
Kristina M. Tank ◽  
Jennifer A. Kersten ◽  
Karl A. Smith ◽  
...  

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