Conventionally-designed animations depicting complex content may fail to produce the high quality mental models characteristic of deep understanding. In a previous study (Lowe & Boucheix, 2016), an unorthodox ‘Compositional’ approach to designing complex animation produced learner mental models superior to those from a conventional, behaviourally-realistic (‘Comprehensive’) animation design. However, this benefit was not without some associated costs. The experiment reported in this presentation tested the relative effectiveness of a hybrid design that selectively combined features of Compositional and Comprehensive designs by using anti-cueing. Compositional, Comprehensive (Control) and Hybrid groups of thirty-one participants each studied different versions of a piano mechanism animation, with participants’ eye movements being recorded during their study. Mental model quality scores were highest for the Hybrid version (but not significantly higher than the Compositional version) with both being significantly higher than scores from the Control version. Implications for design practice and future research will be considered.
Publication
Année de publication : 2020
Type :
Document de conférence
Document de conférence
Auteurs :
Lowe, R.K.
Boucheix, J-M.
Lowe, R.K.
Boucheix, J-M.
Titre de la présentation :
Improving animations: Compositional anti-cueing makes conventional designs more effective
Improving animations: Compositional anti-cueing makes conventional designs more effective
Mois :
August
August
Nom de la conférence :
EARLI SIG2, Comprehension of Text and Graphics. Charles University, Prague, Czech Republic. Online Conference, August 31-September 2.
EARLI SIG2, Comprehension of Text and Graphics. Charles University, Prague, Czech Republic. Online Conference, August 31-September 2.