Feedback on how students progress through completing subgoals can improve students' learning and motivation in programming. Detecting subgoal completion is a challenging task, and most learning environments do so either with "expert-authored" models or with "data-driven" models. Both models have advantages that are…

The first intelligent tutoring systems for computer programming have been proposed more than 30 years ago, mostly focusing on well defined programming tasks e.g. in the context of logic programming. Recent systems also teach complex programs, where explicit modelling of every possible program and mistake is no longer possible. Such systems are…

Intelligent Tutoring Systems (ITSs) have shown success in the domain of programming, in part by providing customized hints and feedback to students. However, many popular novice programming environments still lack these intelligent features. This is due in part to their use of open-ended programming assignments, which are difficult to support with…

Data-driven methods have been a successful approach to generating hints for programming problems. However, the majority of previous studies are focused on procedural hints that aim at moving students to the next closest state to the solution. In this paper, I propose a data-driven method to generate remedy hints for BOTS, a game that teaches…