A design study was conducted to test a machine learning (ML)-enabled automated feedback system developed to support students' revision of scientific arguments using data from published sources and simulations. This paper focuses on three simulation-based scientific argumentation tasks called Trap, Aquifer, and Supply. These tasks were part of an…

This paper describes HASbot, an automated text scoring and real-time feedback system designed to support student revision of scientific arguments. Students submit open-ended text responses to explain how their data support claims and how the limitations of their data affect the uncertainty of their explanations. HASbot automatically scores these…