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Answer Set Programming (ASP), a modern development of Logic Programming,enables a natural integration of Computing with STEM subjects. This integrationaddresses a widely acknowledged challenge in K-12 education, and earlyempirical results on ASP-based integration are promising. Although ASP isconsidered a simple language when compared with imperative programminglanguages, programming errors can still be a significant barrier for students.This is particularly true for K-12 students who are novice users of ASP.Categorizing errors and measuring their difficulty has yielded insights intoimperative languages like Java. However, little is known about the types anddifficulty of errors encountered by K-12 students using ASP. To address this,we collected high school student programs submitted during a 4-session seminarteaching an ASP language known as SPARC. From error messages in this dataset,we identify a collection of error classes, and measure how frequently eachclass occurs and how difficult it is to resolve.

A Preliminary Data-driven Analysis of Common Errors Encountered by Novice SPARC Programmers