Algorithmic Problem Solving Task: Difference between revisions
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=== 2011 === | === 2011 === | ||
* ([[Backhouse, 2011]]) ⇒ [[Roland Backhouse]]. ([[2011]]). “Algorithmic Problem Solving. | * ([[Backhouse, 2011]]) ⇒ [[Roland Backhouse]]. ([[2011]]). “Algorithmic Problem Solving.” John Wiley & Sons. | ||
=== 2005 === | === 2005 === | ||
* ([[Carlisle, 2005]]) ⇒ [[Martin C. Carlisle]], [[Terry A. Wilson]], [[Jeffrey W. Humphries]], and [[Steven M. Hadfield]]. ([[1993]]). “RAPTOR: a visual programming environment for teaching algorithmic problem solving. | * ([[Carlisle, 2005]]) ⇒ [[Martin C. Carlisle]], [[Terry A. Wilson]], [[Jeffrey W. Humphries]], and [[Steven M. Hadfield]]. ([[1993]]). “RAPTOR: a visual programming environment for teaching algorithmic problem solving.” In ACM SIGCSE Bulletin, vol. 37, no. 1, pp. 176-180. ACM, 2005. | ||
=== 1993 === | === 1993 === | ||
Latest revision as of 04:35, 8 May 2024
An Algorithmic Problem Solving Task is a problem solving task that requires an algorithmic problem solution.
- …
- Example(s):
- “Given a graph representing cities and connecting highways, some of the cities house a Red Cross warehouse while one other city experiences a disaster; describe an algorithm for locating the closest Red Cross warehouse.”
- Counter-Example(s):
- See: Algorithm, Algorithmic Problem Solving Education, Process-Oriented Guided Inquiry Learning.
References
2011
- (Backhouse, 2011) ⇒ Roland Backhouse. (2011). “Algorithmic Problem Solving.” John Wiley & Sons.
2005
- (Carlisle, 2005) ⇒ Martin C. Carlisle, Terry A. Wilson, Jeffrey W. Humphries, and Steven M. Hadfield. (1993). “RAPTOR: a visual programming environment for teaching algorithmic problem solving.” In ACM SIGCSE Bulletin, vol. 37, no. 1, pp. 176-180. ACM, 2005.
1993
- (Nakhleh & Mitchell, 1993) ⇒ Mary B. Nakhleh and Richard C. Mitchell. (1993). “Concept Learning Versus Problem Solving: There is a difference.” In: Journal of Chemical Education, 70(3).
- ABSTRACT: Previous studies indicate that there is little connection between algorithmic problem solving skills and conceptual understanding. The authors provide some ways to evaluate students along a continuum of low-high algorithmic and conceptual problem solving skills. The study shows that current lecture method teaches students to solve algorithms rather than teaching chemistry concepts.