Use expert knowledge instead of data: generating hints for hour of code exercises

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Within the field of on-line tutoring systems for learning programming, such as Code.org’s Hour of code, there is a trend to use previous student data to give hints. This paper shows that it is better to use expert knowledge to provide hints in environments such as Code.org’s Hour of code. We present a heuristic-based approach to generating next-step hints. We use pattern matching algorithms to identify heuristics and apply each identified heuristic to an input program. We generate a next-step hint by selecting the highest scoring heuristic using a scoring function. By comparing our results with results of a previous experiment on Hour of code we Titl that a heuristics-based approach to providing hints gives results that are impossible to further improve. These basic heuristics are sufficient to efficiently mimic experts’ next-step hints.
Original languageEnglish
Title of host publicationProceedings of the Fifth Annual ACM Conference on Learning at Scale
Place of PublicationNew York
DOIs
Publication statusPublished - 2018

Keywords

  • Hints
  • Student data
  • Expert knowledge
  • Learningprogramming
  • Interactive learning environments

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