Toward Automatic Hint Generation for Logic Proof Tutoring Using Historical Student Data

@inproceedings{Barnes2008TowardAH,
  title={Toward Automatic Hint Generation for Logic Proof Tutoring Using Historical Student Data},
  author={Tiffany Barnes and John C. Stamper},
  booktitle={Intelligent Tutoring Systems},
  year={2008}
}
  • Tiffany Barnes, John C. Stamper
  • Published in Intelligent Tutoring Systems 2008
  • Computer Science
  • We have proposed a novel application of Markov decision processes (MDPs), a reinforcement learning technique, to automatically generate hints for an intelligent tutor that learns. We demonstrate the feasibility of this approach by extracting MDPs from four semesters of student solutions in a logic proof tutor, and calculating the probability that we will be able to generate hints at any point in a given problem. Our results indicate that extracted MDPs and our proposed hint-generating functions… CONTINUE READING

    Create an AI-powered research feed to stay up to date with new papers like this posted to ArXiv

    Figures, Tables, and Topics from this paper.

    Citations

    Publications citing this paper.
    SHOWING 1-10 OF 96 CITATIONS

    Data-Driven Hint Generation in Vast Solution Spaces: a Self-Improving Python Programming Tutor

    VIEW 12 EXCERPTS
    CITES METHODS
    HIGHLY INFLUENCED

    Data-driven Hint Generation from Peer Debugging Solutions

    VIEW 10 EXCERPTS
    CITES METHODS & BACKGROUND
    HIGHLY INFLUENCED

    Estimating the Local Size and Coverage of Interaction Network Regions

    VIEW 6 EXCERPTS
    CITES BACKGROUND
    HIGHLY INFLUENCED

    Graph Grammar Induction via Evolutionary Computation

    VIEW 9 EXCERPTS
    CITES BACKGROUND & METHODS
    HIGHLY INFLUENCED

    FILTER CITATIONS BY YEAR

    2008
    2019

    CITATION STATISTICS

    • 11 Highly Influenced Citations

    • Averaged 10 Citations per year from 2017 through 2019

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 14 REFERENCES