Optimal and Worst-Case Performance of Mastery Learning Assessment with Bayesian Knowledge Tracing

@inproceedings{Fancsali2013OptimalAW,
  title={Optimal and Worst-Case Performance of Mastery Learning Assessment with Bayesian Knowledge Tracing},
  author={Stephen Fancsali and Tristan Nixon and Steven Ritter},
  booktitle={EDM},
  year={2013}
}
By implementing mastery learning, intelligent tutoring systems aim to present students with exactly the amount of instruction they need to master a concept. In practice, determination of mastery is imperfect. Student knowledge must be inferred from performance, and performance does not always follow knowledge. A standard method is to set a threshold for… CONTINUE READING