The goal of this research is to explore hypothesis-driven approaches that can be combined with data-driven ones to better interpret student actions and processes in log data captured from block-based programming environments with the goal of measuring and assessing students’ CT skills.
Measuring Student Learning in Introductory Block-Based Programming: Examining Misconceptions of Loops, Variables, and Boolean Logic
This research aims to develop assessment items for measuring student understanding in introductory CS classrooms in middle school using a principled approach for assessment design.
Learner Modeling for Adaptive Scaffolding in a Computational Thinking-Based Science Learning Environment
We develop a learner modeling and adaptive scaffolding framework for CTSiM –an open ended learning environment that supports synergistic learning of science and Computational Thinking for middle school students.