@inproceedings{96ed45928e504079a7af8d5d755a6f94,
title = "The Elusive Metrics-Are We Telling the Full Story in Educational Data Mining?",
abstract = "The use of Education Data Mining (EDM) has seen a significant increase in recent years. A recent report identified notable concerns with the literature relating to the lack of metrics presented in EDM research (in particular, predicting student performance). This poster presents details on these concerns that may inhibit future re-validation studies or worse, models that initially report strong findings which may not generalise. This poster also declares a call to action for future studies to present such metrics, and finally describes ongoing work in this space (a systematic literature review).",
keywords = "EDM, educational data mining, metrics, re-validation",
author = "Keith Quille and Keith Nolan and Stephen Colgan",
note = "Publisher Copyright: {\textcopyright} 2021 Owner/Author.; 26th ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE 2021 ; Conference date: 26-06-2021 Through 01-07-2021",
year = "2021",
month = jun,
day = "26",
doi = "10.1145/3456565.3460071",
language = "English",
series = "Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE",
publisher = "Association for Computing Machinery",
pages = "642",
booktitle = "ITiCSE 2021 - Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education",
address = "United States",
}