Assessing Problem-Solving Process At Scale

Abstract

Authentic problem solving tasks in digital environments are often open-ended with ill-defined pathways to a goal state. Scaffolds and formative feedback during this process help learners develop the requisite skills and understanding, but require assessing the problem-solving process. This paper describes a hybrid approach to assessing process at scale in the context of the use of computational thinking practices during programming. Our approach combines hypothesis-driven analysis, using an evidence-centered design framework, with discovery-driven data analytics. We report on work-in-progress involving novices and expert programmers working on Blockly games.