posted Nov 8, 2010, 7:05 AM by Jon Sticklen
updated Nov 8, 2010, 7:48 AM
On November 15, Prof. Ashok Goel of Georgia Tech will present a talk at 4pm, 212 North Kedzie. This is a CRCSTL/CEER sponsored talk.
Prof. Ashok Goel is senior faculty in the Design & Intelligence Laboratory, School of Interactive Computing, Georgia Institute of Technology. The abstract from Prof. Goel is below.
A second talk by Prof. Goel will be at noon on Tuesday November 16, when he will speak at an Engineering College event at noon in 3540 EB. The second talk will be titled "Creative Analogies in Biologically Inspired Design."
Learning Conceptual Models of Complex Natural Systems
Ashok K. Goel
School of Interactive Computing
Georgia Institute of Technology
Modeling complex systems supports development of important cognitive strategies and skills such as monitoring, measurement, explanation, prediction, diagnosis, and redesign. In this talk, I will first describe Structure-Behavior-Function (SBF) models of hierarchically organized complex systems. Then I will present two experiments in developing interactive learning technologies for stimulating and scaffolding learning of biological systems by constructing SBF models. ACT (for Aquarium Construction Toolkit) enables construction of SBF models to reason about classroom aquaria in middle school science. Initial results from deployment of ACT in several classrooms with a few hundred middle school children indicate statistically significant improvement in students’ classification of the structure, behaviors and functions of classroom aquaria as well as appropriation of SBF modeling by some middle school teachers for modeling other natural systems. DANE (for Design by Analogy to Nature Engine) is an ongoing effort at developing an interactive learning environment for supporting biologically inspired design at the college level. Preliminary results from deployment of DANE in an interdisciplinary undergraduate class on biologically inspired design indicate appropriation of SBF models by the course instructors for modeling natural and technological systems alike as well as apparent enhancement to some students’ conceptual understanding of causal mechanisms in biological systems.