Difference between revisions of "Learners with Disabilities"

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  Loukina & Buzick (2017) [[https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ets2.12170 pdf]]
 Loukina & Buzick (2017) [https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ets2.12170 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 (ρ<sup>2</sup> = .57) than test takers who were given accommodations for documented disabilities (ρ<sup>2</sup> = .73)
 
 
Riazy et al. (2020) [https://www.scitepress.org/Papers/2020/93241/93241.pdf 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.


* 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 (ρ<sup>2</sup> of .57) than test takers who were given accommodations for documented disabilities (ρ<sup>^2</sup>2 of .73)
Permodo et al (2023) [https://www.researchgate.net/publication/370001437_Difficult_Lessons_on_Social_Prediction_from_Wisconsin_Public_Schools pdf]
* Paper discusses system that predicts probabilities of on-time graduation
* Prediction is more accurate for students with Disabilities than students without Disabilities

Latest revision as of 21:13, 28 June 2023

 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