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Generating Data-driven Hints for Open-ended Programming

A new data-driven algorithm is presented, based on the Hint Factory, to generate hints for open-ended programming assignments, that can provide hints that successfully lead students to solutions from any state, help students achieve assignment objectives, and align with the student’s future solution.
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Evaluation of a template-based puzzle generator for an educational programming game

  • Yihuan DongT. Barnes
  • Computer Science
    Artificial Intelligence and Interactive Digital…
  • 14 August 2017
It is shown that the template-based, automatic puzzle generator can generate puzzles with expert-designed educational goals while saving experts more than 80% of creation time, and these puzzles exhibit structural and visual novelty compared to expert-created puzzles.
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iSnap: Towards Intelligent Tutoring in Novice Programming Environments

Results from a pilot study of iSnap are shared, indicating that students are generally willing to use hints and that hints can create positive outcomes, and some key challenges encountered in the pilot study are highlighted.
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Infusing computational thinking into middle grade science classrooms: lessons learned

Initial lessons learned while conducting design-based implementation research on integrating computational thinking into middle school science classes are presented and case studies suggest that several factors including teacher engagement, teacher attitudes, student prior experience with CS/CT, and curriculum design can all impact student engagement in integrated science-CT lessons.
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PRADA: A Practical Model for Integrating Computational Thinking in K-12 Education

Initial findings indicate that the PRADA model supported core content teachers in successfully infusing CT into their existing curricula and increased their self-efficacy in CT integration.
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A Comparison of the Quality of Data-Driven Programming Hint Generation Algorithms

This work presents the QualityScore procedure, a novel method for automatically evaluating and comparing the quality of next-step programming hints using expert ratings, and demonstrates that the automated QualityScore ratings agree with experts’ manual ratings.
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Defining Tinkering Behavior in Open-ended Block-based Programming Assignments

This study is the first in this domain to define tinkering based on student behaviors in a block-based programming environment and introduces three general categories of tinkering behaviors derived from student data, and uses case studies to demonstrate how students exhibited these behaviors in problem-solving.
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Toward Data-Driven Example Feedback for Novice Programming

This work presents a method for automatically generating and selecting adaptive, example-based programming feedback using historical student data, and suggests that the DDF approach allows more relevant examples to be selected than existing approaches, and that it may be able to leverage interactivity with the student to further improve example quality.
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Position: Scaffolded Coding Activities Afforded by Block-Based Environments

This paper outlines and presents examples for a set of Scaffold Activities developed for use in novice programming settings that are found in practice to be successful in easing students into programming.
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BOTS: Selecting Next-Steps from Player Traces in a Puzzle Game

The problems with the current hint policy, assuming all edges are the same cost, are discussed, and potential alternative hint selection policies the authors have considered are discussed.
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