Designing Automated Guidance to Improve Diverse Students’ Understanding of Energy Flow

• In Event: Differentiation, Diversity, and Technology

Abstract

This study compares two forms of automated guidance designed to improve student-generated concept diagrams in an online inquiry unit on photosynthesis and cellular respiration. 262 seventh-grade students were randomly assigned to either a direct guidance (that precisely identified what should be improved) or a knowledge integration guidance (that suggested revisiting a relevant visualization to locate useful information) condition and revised their concept diagrams. The results show that knowledge integration guidance was more effective than direct guidance in helping students with low prior knowledge improve their depiction of energy flow. These results suggest that automated guidance that promotes inquiry processes can serve diverse students’ learning by encouraging them to diagnose problems and use evidence from the unit to revise their work.

Authors

• Kihyun (Kelly) Ryoo, University of North Carolina - Chapel Hill

• Marcia Linn, University of California - Berkeley