Fundamentals of algorithmics
Fundamentals of Computer Alori
Fundamentals of Computer Alori
Communications of the ACM - Self managed systems
Data Structures, Algorithms, And Applications In C++
Data Structures, Algorithms, And Applications In C++
Learning from wrong and creative algorithm design
Proceedings of the 39th SIGCSE technical symposium on Computer science education
Education: Alice 3: concrete to abstract
Communications of the ACM - A Blind Person's Interaction with Technology
Active learning of greedy algorithms by means of interactive experimentation
ITiCSE '09 Proceedings of the 14th annual ACM SIGCSE conference on Innovation and technology in computer science education
Introduction to Algorithms, Third Edition
Introduction to Algorithms, Third Edition
Refinement of an experimental approach tocomputer-based, active learning of greedy algorithms
Proceedings of the 17th ACM annual conference on Innovation and technology in computer science education
An Experimental Method for the Active Learning of Greedy Algorithms
ACM Transactions on Computing Education (TOCE)
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In this paper we argue that the most typical instruction method used to teach greedy algorithms is inadequate at achieving certain learning goals and we present several contributions to alleviate this situation. Our first group of contributions highlights the role of selection functions and proposes separate treatment in their discovery and proof of optimality. For discovery, we outline some interesting cases of selection functions and for proofs, we examine the role of counterexamples. Furthermore, we argue that their separation provides more opportunities for instructional activities. Our second group of contributions concerns coding greedy algorithms. We discuss the role and adequacy of the template in current use, and also the role of sorting candidates and how to implement sorting.