Grover Shuchi, Bienkowski Marie, Niekrasz John, Hauswirth Matthias. Assessing Problem-Solving Process At Scale, in Proceedings of the Third (2016) ACM Conference on Learning @ Scale, ACM, pp. 245-248, 2016.
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.