Towards Extraction of Subjective Reading Incomprehension

Abstract

One way to optimize learning processes is to clearly inform the learner about problematic areas. Recent work on gaze-based CHI showed that a reader's language skill can be inferred by gaze analysis. However, only few approaches have been proposed to identify those document parts a reader finds problematic. Our goal is to develop a computational method for reading incomprehension extraction. As initial work, we analyze which eye gaze features are useful for such part-based reading incomprehension extraction at three levels of document structure: paragraphs, segments and words.

Confidence-Aware Learning Assistant

“…Moreover, about the relation between the behavior of eyes and self-confidence, it has been proved that low self-confidence is characterized by a frequent rereading of questions and long gaze on choices [17]. Okoso et al have proposed a method of extracting difficult parts of a document for a reader to comprehend and found some effective features [18]. Lee et al have proposed to build a virtual tutor to support the learning of a student [19].…”

Semi-automatic Text and Graphics Extraction of Manga Using Eye Tracking Information

“…For example, important parts of document for many readers can be distinguished by readingskimming detection proposed by Biedert et al [9]. The total number of words and words per minute of a certain reader and the difficult to understand words can be also detected by using eye-tracking devices [2], [3]. Although lots of work investigate eye gaze with reading documents, there are few researches which involve manga images.…”