Supporting Learners’ Construction of Understandings of Animal Behaviors From Large Image Sets

• In Event: Technology, Instruction, Cognition, and Learning Research in K-12 and Higher Education

Abstract

This paper presents the design rationale underlying a mobile software tool, PhotoMAT (Photo Management and Analysis Tool), and students’ experience with this tool within a scaffolded curricular unit - Neighborhood Safari. PhotoMAT was designed to support learners’ investigations of backyard animal behavior and works with image sets obtained using fixed-position field cameras. We outline our design strategies for supporting young learners' engagement with such "big data" sets and scaffolding their transformation into scalar representations of relative frequency. We then describe the experiences of learners in a fifth grade classroom as they learned to use the camera traps and PhotoMAT tool and used them in self-initiated studies of animal habitat and diet preference over a five-week instructional unit.

Authors

• Tia Renee Shelley, University of Illinois at Chicago

• Chandan Dasgupta, University of Illinois at Chicago

• Tom Moher, University of Illinois at Chicago

• Leilah Lyons, University of Illinois at Chicago