A Composition Approach to Design of Educational Animations - Archive ouverte HAL Accéder directement au contenu
Chapitre D'ouvrage Année : 2017

A Composition Approach to Design of Educational Animations

(1, 2) , (1)
1
2

Résumé

The educational effectiveness of conventionally designed animations that portray complex, unfamiliar subject matter in a behaviorally realistic fashion too often falls well short of expectations. Previous research indicates that the veridical dynamic properties of these comprehensive animations make a major contribution to their lack of effectiveness. Due to these dynamics, there is a substantial mismatch between the processing demands these animations impose on learners and the characteristics of the human information processing system. As a result, the quality of the mental models that learners are able to construct is compromised. Interventions intended to improve learners’ processing of such animations have met with only limited success. This chapter argues that substantial gains in the educational effectiveness of animations will require a fundamental change in the assumptions underlying how they are designed. An alternative design approach based on the Animation Processing Model (APM) is outlined that aims to facilitate the learner’s composition of an internal representation by adopting a different perspective on the characteristics of the animation as an external representation. This Composition Approach presents learners with information in an incremental, cumulative manner that is better matched with their processing capacities. The practical application of this approach is illustrated and implications for future research are canvassed.
Fichier non déposé

Dates et versions

hal-01798577 , version 1 (23-05-2018)

Identifiants

Citer

Richard K Lowe, Jean-Michel Boucheix. A Composition Approach to Design of Educational Animations. Richard Lowe, Rolf Ploetzner. Learning from Dynamic Visualization: Innovations in Research and Application, Springer International Publishing, pp.5-30, 2017, 978-3-319-56202-5. ⟨10.1007/978-3-319-56204-9⟩. ⟨hal-01798577⟩
45 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook Twitter LinkedIn More