Providing Adaptive Scaffolds and Measuring Their Effectiveness in Open Ended Learning Environments

Abstract

Open ended learning environments (OELEs) offer students powerful learning opportunities, but managing the available tools and choices is challenging for novice learners. Adaptive scaffolding can support learners, but it requires understanding and responding to learner actions and strategies. We discuss a generalized adaptive scaffolding framework for OELEs based on a task and strategy model, and effectiveness and coherence measures for evaluating learner proficiencies for tasks and strategies. We apply this framework to support learners in CTSiM (Computational Thinking using Simulation and Modeling), a learning-by-modeling OELE for synergistic learning of science and computational thinking (CT). The effectiveness of our approach is demonstrated by a classroom study with two conditions. Students in the adaptive scaffolding condition showed a better understanding of science and CT concepts, built more accurate models, used better modeling strategies, and transferred modeling skills better to new scenarios than students in the control condition who received no adaptive scaffolding.