Workshop Aims and Scope
The FATED (Fairness, Accountability, and Transparency in Educational Data) 2022 Workshop will be held in conjunction with the 15th International Conference on Educational Data Mining (EDM2022). The workshop will take place on 27 July and will be hybrid, with the in-person event in Durham, England.
FATED 2022 will bring an education-specific lens to fair machine learning topics and questions. We’re particularly excited to spur discussion around what educational datasets should be used for comparison in the context of bias detection or correction algorithms; how to evaluate fairness and bias in educational tasks, including challenges that arise due to limited demographic information; and algorithmic bias detection and countermeasure design for education-specific tasks.
- 27 May 2022: Submission deadline for all types of papers
- 24 June 2022: Notification of acceptance
- 8 July 2022: Camera-ready submission
- 27 July: Workshop, from approximately 8:30am-5pm GMT [in-person in Durham, England, and online]
We invite submissions in the following categories:
Dataset Papers (2-4 pages)
Short papers describing datasets (either created by themselves or by others) that they think should be widely used by fairness researchers in educational machine learning (EML). Papers will identify what EML questions the dataset is well-suited for, why the dataset should be widely used by bias and fairness researchers, and provide specific documentation about the contents of the dataset, including what demographic information, how it was collected, and what procedures were taken to safeguard participants’ privacy and rights. Submissions on this track combine elements of a datasheet that documents a dataset (Gebru et al. 2021) and go further by contextualizing the dataset for fairness research in EML/EDM. Papers should include a link to the dataset or information about how to obtain it if it is not publicly posted; datasets must be obtainable by researchers not involved in the original data collection.
Evaluation Protocol Papers (2-4 pages)
Short papers on the importance of particular bias and fairness evaluation protocols (including metrics). We welcome papers that draw on published and/or newly presented research to argue for the importance of particular bias and fairness evaluation protocols specifically for EML tasks. Papers in this track may also elucidate a challenge related to fairness and EML, such as addressing issues of fairness given privacy restrictions on sharing student demographic data, or take a position on what is needed to address such issues.
Research Papers (4-8 pages)
New or in-progress work related to algorithmic fairness and EML. Papers should be clearly placed with respect to the state of the art, state the contribution of the proposal in the domain of application, and describe the methodology in detail.
Reproducibility Papers (4-8 pages)
These papers should replicate prior experiments on influential methods in the literature, preferably using the original source code, to further generalize and validate or not previous work from a bias or fairness perspective (e.g., reproducing a prior method on success prediction, originally evaluated based only on overall accuracy, to investigate how its estimates change within demographic groups). Using the original source code is recommended but not mandatory.
Encore Papers (no page restrictions)
This track is for recently published pieces relevant to the workshop. Authors submit an abstract and a link or PDF of the recently published work.
Authors of accepted papers in any track will be invited to present at a poster session, and presenters may be invited to give spotlight talks. Dataset, Evaluation Protocol, and Reproducibility papers will be included in the workshop proceedings. Authors of accepted papers on the Research track will have the option to include abstracts or full papers in the workshop proceedings; in either case, full papers will be linked on the workshop website. Abstracts of Encore papers will be published on the workshop website, and a link to the original publication will be included.
Submission Logistics and Formatting
Page limits above do not include references; any number of additional pages with references may be used.
All papers must be submitted by 27 May 2022.