Explaining Individual and Collective Programming Students’ Behavior by Interpreting a Black-Box Predictive Model

Explaining Individual and Collective Programming Students’ Behavior by Interpreting a Black-Box Predictive Model

Predicting student performance as early as possible and analysing to which extent initial student behaviour could lead to failure or success is critical in introductory programming (CS1) courses, for allowing prompt intervention in a move towards alleviating their high failure rate. However, in CS1...

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Bibliographic Details
Main Authors: Filipe Dwan Pereira, Samuel C. Fonseca, Elaine H. T. Oliveira, Alexandra I. Cristea, Henrik Bellhauser, Luiz Rodrigues, David B. F. Oliveira, Seiji Isotani, Leandro S. G. Carvalho
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Explainable artificial intelligence
online judges
learning analytics
CS1
computing in education
early prediction
Online Access:https://ieeexplore.ieee.org/document/9517104/

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