Automatic recognition of misconceptions in visual algorithm simulation exercises

Visual algorithm simulation (VAS) is an activity in which students practice their understanding of algorithms: They simulate the steps of an algorithm by manipulating a bespoke visualization within a supporting software system. Multiple instances of a VAS exercise may be automatically generated for different learners or for repetitive practice by a single learner. In this work-in-progress report, we discuss how misconceptions might be automatically detected in students´ solutions to VAS exercises and how misconception-aware feedback might be provided in VAS. We identify two strategies for producing multiple instances of VAS exercises and evaluate them against several criteria. The tradeoffs so identified are also pertinent for similar process-simulation practice beyond VAS and computing education.