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Using Information Gap Learning Techniques in Embedded Systems Design Education

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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, 2017

Conference Session

The Best of the Computers in Education

Tagged Division

Computers in Education

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Paper Authors


J.w. Bruce Mississippi State University

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J.W. Bruce is an Associate Professor in the Department of Electrical & Computer Engineering at Mississippi State University.

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Ryan A. Taylor Mississippi State University Orcid 16x16

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Mr. Ryan Taylor is currently a doctoral candidate in the Department of Electrical and Computer Engineering at Mississippi State University. He received his BSEE and MSEE from the University of Alabama, where his thesis centered on microcontroller education tools. His doctoral research focuses on asynchronous circuit synthesis. In the past he has served as a graduate research assistant at Mississippi State University as well as the instructor of record of multiple courses at both UA and MSU.

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Using Information Gap Learning Techniques in Embedded Systems Design Education

Commercial market trends tend to trickle into engineering program curricula. In the computing systems marketplace, customers are demanding ever more complex features as computing systems become more capable and affordable. Today, engineering educators are feeling the pressure to provide more realistic, comprehensive, and complex lab experiences to students in order to remain relevant and keep students' attention. These demands are especially difficult in the university environment where students may lack basic skills, and professors and students work under a 15-week schedule.

In order to take students from neophyte to accomplished designer of embedded systems, operating systems (OS-es) specialized for embedded systems may be used to offload many housekeeping and flow control tasks. Many embedded OS-es exist; however, commercial offerings are often cost-prohibitive while others are simply too feature-rich to deploy in the classroom during a typical semester. To this end, the authors have developed a capable, but simple cooperative multitasking OS targeting resource-limited systems. This OS has been deployed in a semester-long cumulative design using teaming, problem based experiential learning. As embedded systems become increasingly complex, subsystems are increasingly hidden and black box design skills are required. Use of our OS emulates these design constraints, but unlike commercial OS-es, professors and lab assistants have full knowledge of OS behavior, and can provide detailed guidance to students typically unavailable with commercial or open-source OS-es. Once students have a firm understanding of OS use and operation, hardware and software interface issues are fully explored using experiential learning by requiring the OS be modified and extended by the students. In this manner, students gain a more complete understanding of the limits of the OS and the technical reasons for them. Provided with mature hardware, pertinent libraries, and an OS, the resulting student deliverables are complex and highly functional, with many advanced features. However, students have reported a steep learning curve, especially during the early weeks of the semester, which leads to high stress levels and sometimes discouraged students.

To ease student workloads but maintain the complex system design levels, the authors decided to provide a basic design framework to the student. Instead of course deliverables being completely designed by the students, the students were forced to ascertain the overall approach sufficiently well so that they could complete the information gaps or design the small missing portions of the provided design framework. The intent was to maintain the complex feature-rich design outcomes, foster deep student understanding, while reducing the required student workload.

This paper describes the structure of the authors’ approach and the methods by which students are required to complete a cumulative design using a team-based experiential laboratory experience with information gaps. Student evaluations and assessments, both qualitative and quantitative, are provided that compare the results of student learning using the previous high-workload methods and the information gap learning approach described in this paper.

Bruce, J., & Taylor, R. A. (2017, June), Using Information Gap Learning Techniques in Embedded Systems Design Education Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--29078

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