Communications of the ACM
Introduction to algorithms
Empirical investigation throughout the CS curriculum
Proceedings of the thirty-first SIGCSE technical symposium on Computer science education
Algorithms in C
Fundamentals of Computer Alori
Fundamentals of Computer Alori
The greedy trap and learning from mistakes
SIGCSE '03 Proceedings of the 34th SIGCSE technical symposium on Computer science education
PathFinder: A Visualization eMathTeacher for Actively Learning Dijkstra's Algorithm
Electronic Notes in Theoretical Computer Science (ENTCS)
The design and coding of greedy algorithms revisited
Proceedings of the 16th annual joint conference on Innovation and technology in computer science education
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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Greedy algorithms are one of the most common algorithm design techniques. Despite their apparent simplicity, their design is a demanding task. As a consequence, they are usually taught and learnt in a passive way. In this paper, we make a new proposal aimed at active learning of greedy algorithms. The paper contains two main contributions. First, we introduce a novel approach to their active learning, based on experimentation with and evaluation of alternative greedy strategies for a given problem. Second, we present a family of interactive assistants designed to support this approach. The assistants were evaluated for their usability in real lab situations, having obtained high scores from students as well as useful information to enhance them.