Learning Neuroscience with Technology: a Scaffolded, Active Learning Approach

Abstract

Mobile applications (apps) for learning technical scientific content are becoming increasingly popular in educational settings. Neuroscience is often considered complex and challenging for most students to understand conceptually. iNeuron is a recently developed iOS app that teaches basic neuroscience in the context of a series of scaffolded challenges to create neural circuits and increase understanding of nervous system structure and function. In this study, four different ways to implement the app within a classroom setting were explored. The goal of the study was to determine the app’s effectiveness under conditions closely approximating real-world use and to evaluate whether collaborative play and student-driven navigational features contributed to its effectiveness. Students used the app either individually or in small groups and used a version with either a fixed or variable learning sequence. Student performance on a pre- and post-neuroscience content assessment was analyzed and compared between students who used the app and a control group receiving standard instruction, and logged app data were analyzed. Significantly, greater learning gains were found for all students who used the app compared to control. All four implementation modes were effective in producing student learning gains relative to controls, but did not differ in their effectiveness to one another. In addition, students demonstrated transfer of information learned in one context to another within the app. These results suggest that teacher-led neuroscience instruction can be effectively supported by a scaffolded, technology-based curriculum which can be implemented in multiple ways to enhance student learning.