Evaluating animations as student aids in learning computer algorithms

We conducted two experiments designed to examine whether animations of algo rithms would help students learn the algorithms more effectively. Across th e two studies we used two different algorithms - depth-first search and bin omial heaps - and used two different subject populations - students with li ttle or no computer science background and students who were computer scien ce majors - and examined whether animations helped students acquire procedu ral and conceptual knowledge about the algorithms. The results suggest that one way animations may aid learning of procedural knowledge is by encourag ing 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 pr esent studies. These initial experiments served to highlight a number of me thodological issues that need to be systematically addressed in future expe riments in order to fully test the relationship between animation and predi ction as well as to examine other :possible benefits of animations on learn ing. (C) 2000 Published by Elsevier Science Ltd. All rights reserved.