Using algorithm animations to assist teaching state space search: an empirical evaluation

ABSTRACT

Traditional laboratory activities for students trying to develop a deep understanding of state space search methods involves them working at programming implementations of search methods. This study aimed to determine if interactive algorithm animations of search methods would make a suitable alternative laboratory activity.

The specific hypotheses investigated were: (i) the animation group would develop at least as good an overall understanding of state space search methods; (ii) the animation group would develop a deeper understanding of state space search concepts pertaining to qualitative characteristics of search methods and the relationship between search methods.

The basic experimental method adopted was a classical emperical quantitative evaluation involving 30 participants divided into one control group and one experimental group. All participants attended the same lecture presentations on state space search methods, but were split into distinct groups for undertaking the laboratory activities.

Results provided good evidence that the animation laboratory activity was at least as effective as traditional programming activities in aiding understanding of state space search methods, and that the animation group students developed a deeper understanding of one aspect of state space search methods.

REFERENCES

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INDEX TERMS

Keywords:
AI education, algorithm animation, empirical evaluation, state space search methods