Implicit gaze based annotations to support second language learning

Okoso, Ayano; Kunze, Kai; Kise, Koichi

doi:10.1145/2638728.2638783

Cited by 13 publications

(7 citation statements)

References 6 publications

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“…In their system, a long dwell time was chosen to minimise the 'Midas touch' effect when employing gaze as an input modality [30]. Similarly, implicit annotation of documents has been explored by employing the user's reading behaviour to distinguish the areas of the document that had been thoroughly read or just skimmed [11,39,58]. For instance, Okoso et al employed eye-tracking to propose a feedback mechanism for second language readers.…”

Section: Document Annotation Using Gaze and Voicementioning

confidence: 99%

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Gavin

Khan

Newn

Kelly

et al. 2021

ACM Trans. Comput.-Hum. Interact.

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Annotation is an effective reading strategy people often undertake while interacting with digital text. It involves highlighting pieces of text and making notes about them. Annotating while reading in a desktop environment is considered trivial but, in a mobile setting where people read while hand-holding devices, the task of highlighting and typing notes on a mobile display is challenging. In this article, we introduce GAVIN, a gaze-assisted voice note-taking application, which enables readers to seamlessly take voice notes on digital documents by implicitly anchoring them to text passages. We first conducted a contextual enquiry focusing on participants’ note-taking practices on digital documents. Using these findings, we propose a method which leverages eye-tracking and machine learning techniques to annotate voice notes with reference text passages. To evaluate our approach, we recruited 32 participants performing voice note-taking. Following, we trained a classifier on the data collected to predict text passage where participants made voice notes. Lastly, we employed the classifier to built GAVIN and conducted a user study to demonstrate the feasibility of the system. This research demonstrates the feasibility of using gaze as a resource for implicit anchoring of voice notes, enabling the design of systems that allow users to record voice notes with minimal effort and high accuracy.

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Section: Document Annotation Using Gaze and Voicementioning

confidence: 99%

“…This was done by implicitly annotating the document with reading features such as the reading speed, amount of re-reading and number of fixations. [39].…”

Section: Document Annotation Using Gaze and Voicementioning

confidence: 99%

Gavin

Khan

Newn

Kelly

et al. 2021

ACM Trans. Comput.-Hum. Interact.

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“…Thus, stored annotations can be shared among multiple learners through this file accessible via the network. Eye-Gaze [5], ASRLM [16], Livenotes [14], and A.nnotate [44] are based on the model 'Common Annotation Framework' expressed in Resource Description Framework (RDF) [55] and interpreted by associated server. Although, the storage of annotations outside of annotated resource is rather complex.…”

Section: B To Store Annotationsmentioning

confidence: 99%

“…For example, a feature designed to help the learner to enrich his knowledge about the studied domain is presented by EyeGaze [5], ASRLM [16], and Crocodoc [46]. These annotation systems identify a list of documents by making inferences from the annotated passages and other documents in database annotations.…”

Section: G To Recommend Data Related To Annotationsmentioning

confidence: 99%

Functionalities provided by Annotation Systems for Learners in Educational Context: An Overview

Kalboussi

Mazhoud

Kacem

2016

Int. J. Emerg. Technol. Learn.

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Abstract-During his activities, the learner usually uses comments, highlights and circles sections to tag consulted digital documents. Therefore, many systems have been developed to annotate different electronic resources, often adapted to specific users and for particular uses of documents. This great variety of annotation systems reveals a lack of a clear strategy of how to compare the developed annotation systems of the literature according to their functionalities. As a result, few works have tried to present comparative studies of these tools. The aim of this article is to provide a study of some annotation tools used by learners in educational practices. Therefore, we present a comparison of functionalities provided by forty annotation systems developed by industry and academia during the last decade. The study further reveals gaps in systems and opportunities for further research.

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“…Thus, it can be hard to tell which word a fixation belongs to (see also Figure 3). Previous work showed that gaze data can be robustly associated with a paragraph, since spaces between paragraphs are relatively large in a normal document [8]. Therefore, we consider that a paragraph-level is the smallest unit which can contain document features.…”

Section: Segment Level Gaze Featurementioning

confidence: 99%

Towards Extraction of Subjective Reading Incomprehension

Okoso¹,

Toyama

Kunze

et al. 2015

Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems

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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.

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Implicit gaze based annotations to support second language learning

Cited by 13 publications

References 6 publications

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Gavin

Functionalities provided by Annotation Systems for Learners in Educational Context: An Overview

Towards Extraction of Subjective Reading Incomprehension

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