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Full-Text Articles in Engineering Education
Hybrid Course Design: Leading A New Direction In Learning Programming Languages, Lulu Sun, Matthew Kindy, Caroline Cecile Marcelle Liron, Christopher Grant, Shirley Waterhouse
Hybrid Course Design: Leading A New Direction In Learning Programming Languages, Lulu Sun, Matthew Kindy, Caroline Cecile Marcelle Liron, Christopher Grant, Shirley Waterhouse
Publications
“Introduction to Computing for Engineers” is a programming course emphasizing problem solving. The lack of practice time, in addition to the algorithm-centric nature of programming, results in an inadequate comprehension of course material. In the fall of 2010, three faculty members created and implemented online activities consisting of video lecture slides, and mini on-line quizzes at Embry-Riddle Aeronautical University to give students more “hands-on” learning (rather than expecting them to absorb content through lecture). Students do online lecture study by themselves, then come to the lab to practice on the following day with the instructor and teaching assistant. In the …
(Re)Defining Computing Curricula By (Re)Defining Computing, Charles Isbell, Lynn Stein, Robb Cutler, Jeffrey Forbes, Linda Fraser, John Impagliazzo, Viera Proulx, Steve Russ, Richard Thomas, Yan Xu
(Re)Defining Computing Curricula By (Re)Defining Computing, Charles Isbell, Lynn Stein, Robb Cutler, Jeffrey Forbes, Linda Fraser, John Impagliazzo, Viera Proulx, Steve Russ, Richard Thomas, Yan Xu
Lynn Andrea Stein
What is the core of Computing? This paper defines the discipline of computing as centered around the notion of modeling, especially those models that are automatable and automatically manipulable. We argue that this central idea crucially connects models with languages and machines rather than focusing on and around computational artifacts, and that it admits a very broad set of fields while still distinguishing the discipline from mathematics, engineering and science. The resulting computational curriculum focuses on modeling, scales and limits, simulation, abstraction, and automation as key components of a computationalist mindset.