Dataset for Use of eye data for developing adaptive systems: A systematic literature review
Description
This dataset contains the data extracted and synthesized as part of the systematic literature review entitled “Use of eye data for developing adaptive systems: A systematic literature review.” The review examined peer-reviewed studies published between 2015 and May 2026 that used eye-tracking data to infer user states and support the development, implementation, validation, or evaluation of adaptive systems. The dataset includes information on the selected studies, including publication characteristics, application domains, eye-tracking devices and sampling rates, calibration and validation procedures, preprocessing methods, event-detection techniques and parameters, eye-related measures and features, computational inference methods, inferred user states, and the adaptations implemented by the analyzed systems. It also includes the methodological quality assessment conducted for the included studies. The data were collected from studies identified through searches in ACM Digital Library, IEEE Xplore, and ScienceDirect, complemented by a snowballing procedure. The dataset is intended to support transparency and reproducibility of the systematic review and may also facilitate further research on eye-tracking-based adaptive systems, gaze-aware interaction, and adaptive user interfaces.