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Implementing a Challenge-Based Approach to Teaching Selected Courses in CS and Computational Sciences

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2016 ASEE Annual Conference & Exposition


New Orleans, Louisiana

Publication Date

June 26, 2016

Start Date

June 26, 2016

End Date

June 29, 2016





Conference Session

Emerging Computing and Information Technologies II

Tagged Division

Computing & Information Technology

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Paper Authors


Mahmoud K. Quweider University of Texas - Rio Grande Valley

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M K Quweider is a Professor of Computer & Information Sciences at the U. of Texas at UTRGV. He received his Ph.D. in Engineering Science (Multimedia and Imaging Specialty) and B.S. In Electrical Engineering, M.S. in Applied Mathematics, M.S. in Engineering Science, and M.S. in Biomedical Engineering all from the University of Toledo, Ohio. He also holds a Bachelor of English and a Masters of Business Administration from the University of Texas at Brownsville. After graduation, he was employed at several corporations including Pixera, a digital multimedia processing company in Cupertino, CA, 3COM, a networking and communication company in Schaumberg, IL, and Mercantec, an E-Commerce company in Naperville, IL. He has more than 40 publications in the field, and has served as a reviewer/moderator for several scientific and educational journals and conferences. He joined UTB in the Spring of 2000. His areas of interest include Imaging, Visualization and Animation, Networking and Cyber Security, Web Design, Computer Graphics, and Linguistics.

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Fitratullah Khan University of Texas - Rio Grande Valley

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Professor Fitratullah Khan has been teaching computer science courses since 1992. His areas of expertise are computer architecture, networking, database systems, computing platforms and languages. As the director of Infrastructure, Telecommunications, and Networking (ITNet), and later as the Chief Technology Officer, at UT Brownsville, he implemented state of the art networking using campus wide fiber ring with redundant links to facilities. He established diskless computer labs to provide uniform computing platform across campus, and modernized classrooms to make them congenial to online learning. He was the PI on NSF funded BCEIL (Beowulf-based Curriculum Enrichment Integrated Laboratory) grant and Co-PI on NSF funded MCALL (Multimedia based Computer Assisted Learning Lab) grant.

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Challenge based learning/instruction (CBI) has been championed as an effective methodology to engage students in their own learning process, allowing them to bring real-life problems and projects that need to be solved. As The New Media Consortium eloquently puts it, " It [Challenge-based learning] calls for a new way of thinking about the role of the teacher, one in which he or she had to be comfortable as the students struggled and wrestled with a meaningful challenge, letting them choose their own path to understanding." The approach is even more challenging to implement in the SMT (Science, Mathematics, and Technology) fields at minority-serving institutions. To overcome these challenges, the author who is a Computer Science faculty with over twenty years industrial and academic experience in Computer Graphics and Imaging, was chosen to attend a set of extensive workshops, sponsored by the NSF (National Science Foundation), on how to effectively prepare course material and implement the learning method in strategically selected portions of any adopted course. Our paper describes in detail our efforts to implement Challenge based learning in the Computer Science curriculum in general, and Computer Graphics (CG) and Software Engineering (SWE) in particular. The effort is part of an NSF grant awarded to UT-Pan Am and UT Brownsville (both are now part of the newly merged university of UT-RGV). The CG/SWE courses were selected because of the initial high number of students’ enrollment in the class but the low retention rate by the class’s end. The paper will document/detail the efforts that have been taken in specific areas of the newly implemented courses. These include: 1. The process of identifying course major module objectives and module sub-objectives: In particular, those that are relevant to CBI implementation. 2. Identifying expected difficulties: What are the difficulties that students face when taking the course. 3. Real-world contexts: Why is the course an important part of the CS curriculum, and where can you find its applications. 4. Model of knowledge: What is the conceptual model for the course, including prerequisites, course dependencies, and course level. What concepts and techniques should be considered enduring understanding or important to do and know, or just worth being familiar with. 5. Assessment of learning: How do you change the traditional testing and assessment methods to make sure they include formative assessment (individual and group, in class and outside the class homework) as well as summative assessment. Data analysis and conclusions from the pilot project has been made public to benefit other faculty in CS and other SMT fields nationwide. Keywords Challenge based learning/instruction (CBI), Interdisciplinary Studies, Engineering, Computational Science, Computer Graphics, Software Engineering. SMT (Science, Mathematics, and Technology) fields at minority-serving institutions.

Quweider, M. K., & Khan, F. (2016, June), Implementing a Challenge-Based Approach to Teaching Selected Courses in CS and Computational Sciences Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.25589

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