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Instructor Dashboards for Early Intervention in Programming Courses: A Field Evaluation

Sabbir Hosen Mamun†, Helena R. Novak, Lena M. Schreiber† Corresponding author

International Journal of Artificial Intelligence in Education, Vol. 34, No. 3, pp. 410-438 · SpringerQ1, IF 4.2, Scopus

Journal202417 citationsField evaluation
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Abstract

Early-warning dashboards promise timely instructor intervention, but many systems surface too many signals without indicating which actions are appropriate. We evaluate a dashboard that groups programming-course signals into progress, persistence, and misconception indicators, each linked to suggested instructor responses. Field deployment across 611 students showed faster identification of inactive groups and more targeted office-hour outreach, with instructors reporting lower triage effort.

Cite this work

@article{Mamun2024Instructor,
  title = {Instructor Dashboards for Early Intervention in Programming Courses: A Field Evaluation},
  author = {Sabbir Hosen Mamun and Helena R. Novak and Lena M. Schreiber},
  year = {2024},
  journal = {International Journal of Artificial Intelligence in Education},
  volume = {34},
  number = {3},
  pages = {410-438},
  publisher = {Springer},
  abstract = {Early-warning dashboards promise timely instructor intervention, but many systems surface too many signals without indicating which actions are appropriate. We evaluate a dashboard that groups programming-course signals into progress, persistence, and misconception indicators, each linked to suggested instructor responses. Field deployment across 611 students showed faster identification of inactive groups and more targeted office-hour outreach, with instructors reporting lower triage effort.},
}