Evaluating animations as student aids in learning computer algorithms

We conducted two experiments designed to examine whether animations of algorithms would help students learn the algorithms more effectively. Across the two studies we used two different algorithms — depth-first search and binomial heaps — and used two different subject populations — students with li...

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Published in:Computers and education Vol. 33; no. 4; pp. 253 - 278
Main Authors: Byrne, Michael D., Catrambone, Richard, Stasko, John T.
Format: Journal Article
Language:English
Published: New York, N.Y Elsevier Ltd 01.12.1999
Pergamon Press
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ISSN:0360-1315, 1873-782X
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Abstract We conducted two experiments designed to examine whether animations of algorithms would help students learn the algorithms more effectively. Across the two studies we used two different algorithms — depth-first search and binomial heaps — and used two different subject populations — students with little or no computer science background and students who were computer science majors — and examined whether animations helped students acquire procedural and conceptual knowledge about the algorithms. The results suggest that one way animations may aid learning of procedural knowledge is by encouraging learners to predict the algorithm's behavior. However, such a learning improvement was also found when learners made predictions of an algorithm's behavior from static diagrams. This suggests that prediction, rather than animation per se, may have been the key factor in aiding learning in the present studies. These initial experiments served to highlight a number of methodological issues that need to be systematically addressed in future experiments in order to fully test the relationship between animation and prediction as well as to examine other possible benefits of animations on learning.
AbstractList We conducted two experiments designed to examine whether animations of algorithms would help students learn the algorithms more effectively. Across the two studies we used two different algorithms — depth-first search and binomial heaps — and used two different subject populations — students with little or no computer science background and students who were computer science majors — and examined whether animations helped students acquire procedural and conceptual knowledge about the algorithms. The results suggest that one way animations may aid learning of procedural knowledge is by encouraging learners to predict the algorithm's behavior. However, such a learning improvement was also found when learners made predictions of an algorithm's behavior from static diagrams. This suggests that prediction, rather than animation per se, may have been the key factor in aiding learning in the present studies. These initial experiments served to highlight a number of methodological issues that need to be systematically addressed in future experiments in order to fully test the relationship between animation and prediction as well as to examine other possible benefits of animations on learning.
Author Catrambone, Richard
Stasko, John T.
Byrne, Michael D.
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  surname: Catrambone
  fullname: Catrambone, Richard
  organization: School of Psychology, Georgia Institute of Technology, Atlanta, GA 30332-0170, USA
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  givenname: John T.
  surname: Stasko
  fullname: Stasko, John T.
  organization: College of Computing, Georgia Institute of Technology, Atlanta, GA 30332-0280, USA
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Snippet We conducted two experiments designed to examine whether animations of algorithms would help students learn the algorithms more effectively. Across the two...
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SubjectTerms Applications in subject areas
Evaluation of CAL systems
Interactive learning environments
Media in education
Pedagogical issues
Title Evaluating animations as student aids in learning computer algorithms
URI https://dx.doi.org/10.1016/S0360-1315(99)00023-8
https://www.proquest.com/docview/1877120402
Volume 33
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