Learners with Disabilities

From Penn Center for Learning Analytics Wiki
Jump to navigation Jump to search

 Loukina & Buzick (2017) pdf

  • a model (the SpeechRater) automatically scoring open-ended spoken responses for speakers with documented or suspected speech impairments
  • SpeechRater was less accurate for test takers who were deferred for signs of speech impairment (ρ2 = .57) than test takers who were given accommodations for documented disabilities (ρ2 = .73)


Riazy et al. (2020) pdf

  • Models predicting course outcome of students in a virtual learning environment (VLE)
  • Disparate impact was found for students with self-declared disabilities, with systematic inaccuracies in predictions for learners in this group.


Permodo et al (2023) pdf

  • Paper discusses system that predicts probabilities of on-time graduation
  • Prediction is more accurate for students with Disabilities than students without Disabilities