Feedback Generation For Programming

Feedback Generation for Programming is a computational method that systematically produces formative evaluations of code artifacts by analyzing syntactic, semantic, and structural properties of student programs to provide targeted, actionable guidance for improvement within programming education contexts.

228

Publications

10.5K

Citations

592

Authors

219

Institutions

Publications per year

2017–2026

120

Authors

592

  1. TP
    Thomas Price

    North Carolina State University, United States

    9 publications · 423 citations

    9

    h-index

  2. SG
    Sumit Gulwani

    Microsoft (United States), United States

    7 publications · 724 citations

    7

    h-index

  3. RS
    Rishabh Singh

    Microsoft (United States), United States

    7 publications · 762 citations

    7

    h-index

  4. JJ
    Johan Jeuring

    Utrecht University, Netherlands

    7 publications · 510 citations

    7

    h-index

  5. EL
    Elena L. Glassman

    Harvard University Press, United States

    6 publications · 390 citations

    6

    h-index

1–5 of 592

Venues

  1. arXiv (Cornell University)

    Repository · 5 publications · 266 citations

    5

    h-index

  2. Australasian Computing Education Conference

    Conference · 4 publications · 89 citations

    4

    h-index

  3. Computer Applications in Engineering Education

    CAE · 4 publications · 164 citations

    4

    h-index

  4. IEEE Transactions on Education

    4 publications · 143 citations

    4

    h-index

  5. ACM SIGCSE Bulletin

    4 publications · 234 citations

    4

    h-index

1–5