Design of Automated Guidance to Support Effortful Revisions and Knowledge Integration in Science Learning

• In Event: 54.018 - Promising Scholarship in Education: Dissertation Fellows and Their Research

Abstract

Supporting students to revise their written explanations in science can help students to integrate disparate ideas and develop a coherent, generative account of complex scientific topics. Using natural language processing to analyze student written work, we compare forms of automated guidance designed to motivate productive revision and help students integrate their understanding of science. Research shows the benefit of providing timely, transparent guidance to students and identifies some challenges. Specifically, (a) students often believe online guidance is generic rather than adapted to their response; and (b) students do not always engage effortfully with online guidance to improve their written responses. This dissertation examines designs of automated guidance that promote knowledge integration and increase students’ motivation to engage effortfully in learning science. The Web-based Inquiry Science Environment (WISE; http://wise4.berkeley.edu) was used to deliver inquiry instruction and guidance as well as conduct randomized comparison studies and log student activities. Informed by the knowledge integration framework and established ideas about student motivation, these research studies examine effective designs for automated guidance.

Author

• Charissa Tansomboon, University of California Berkeley