Abstract:
This paper explores the use of science learning activation to understand how various types of visitors engage with different exhibits. In particular, we examined how learners engaged in two very different resource-rich exhibits using two distinct analytic techniques. Regression analyses revealed that learners’ prior science learning activation can be used to predict learners’ engagement at each of the exhibits. A latent class analysis grouped learners into four emergent activation profiles (Low Motivation, High Motivation, Low Ability and High Ability), and found that learners within each profile engaged differently with the two exhibits. Analyses across the two approaches suggest that engagement in a science center exhibit experience can vary widely by learners’ activation. The study provides an analytic lens for understanding which learners are being engaged by an exhibit. Finally, the paper discusses the implications of this study for design, selection, and evaluation of exhibits in science centers.

Recommended Citation:
Dorph, R., Cannady, M. A., & Schunn, C. D. (2019). What drives visitor engagement in exhibits? The interaction between visitor activation profiles and exhibit features. Curator: The Museum Journal.

View Article:
https://www.lrdc.pitt.edu/schunn/papers/dorph-etal2019-curator.pdf