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A Misconception Taxonomy for State, References, and Mutation in Introductory Python

Sabbir Hosen Mamun, Joris T. Vandenberghe

ACM International Computing Education Research Conference, pp. 201-214, Virtual Event · ACM

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Abstract

Misconceptions about state and mutation are difficult to diagnose because incorrect programs can fail for many surface-level reasons. We derive a taxonomy from think-aloud sessions, exam responses, and 8,300 submitted Python programs. The resulting categories distinguish aliasing errors, stale mental models of loop variables, and incorrect assumptions about object identity, providing a basis for targeted automated feedback.

Cite this work

@inproceedings{Mamun2021A,
  title = {A Misconception Taxonomy for State, References, and Mutation in Introductory Python},
  author = {Sabbir Hosen Mamun and Joris T. Vandenberghe},
  year = {2021},
  booktitle = {ACM International Computing Education Research Conference},
  pages = {201-214},
  address = {Virtual Event},
  publisher = {ACM},
  abstract = {Misconceptions about state and mutation are difficult to diagnose because incorrect programs can fail for many surface-level reasons. We derive a taxonomy from think-aloud sessions, exam responses, and 8,300 submitted Python programs. The resulting categories distinguish aliasing errors, stale mental models of loop variables, and incorrect assumptions about object identity, providing a basis for targeted automated feedback.},
}