In the “interruption age”, we are getting used to frequently shifting our attention to secondary tasks while working on a primary one. After an interruption, resuming the primary task is difficult since users may not remember their previous intentions and behaviors. Eye trackers are a promising technology to provide task resumption support (TRS). Consequently, users can be reminded of their previous visual behavior and resume the primary task properly. In this research project, we design and develop different gaze-based TRS types and investigate the role of individual user characteristics (e.g., working memory capacity) on their effectiveness.
