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Evaluating the Explainers: Black-Box Explainable Machine Learning for
  Student Success Prediction in MOOCs

Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs

1 July 2022
Vinitra Swamy
Bahar Radmehr
Natasa Krco
Mirko Marras
Tanja Kaser
    FAtt
    ELM
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Papers citing "Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs"

3 / 3 papers shown
Title
The future of human-centric eXplainable Artificial Intelligence (XAI) is
  not post-hoc explanations
The future of human-centric eXplainable Artificial Intelligence (XAI) is not post-hoc explanations
Vinitra Swamy
Jibril Frej
Tanja Kaser
39
14
0
01 Jul 2023
Trusting the Explainers: Teacher Validation of Explainable Artificial
  Intelligence for Course Design
Trusting the Explainers: Teacher Validation of Explainable Artificial Intelligence for Course Design
Vinitra Swamy
Sijia Du
Mirko Marras
Tanja Kaser
24
17
0
17 Dec 2022
Do Not Trust a Model Because It is Confident: Uncovering and
  Characterizing Unknown Unknowns to Student Success Predictors in Online-Based
  Learning
Do Not Trust a Model Because It is Confident: Uncovering and Characterizing Unknown Unknowns to Student Success Predictors in Online-Based Learning
Roberta Galici
Tanja Kaser
Gianni Fenu
Mirko Marras
29
6
0
16 Dec 2022
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