scholarly journals Understanding the use of eye-tracking recordings to measure and classify reading ability in elementary children school

2020 ◽  
pp. 69-74
Author(s):  
Karim Fayed ◽  
Birgit Franken ◽  
Kay Berkling
Keyword(s):  
Eye Tracking ◽  
Skill Acquisition ◽  
Reading Ability ◽  
Reading Speed ◽  
After School ◽  
Tracking Data ◽  
Eye Tracker ◽  
L2 Acquisition ◽  
Set Up ◽  
Eu Project

The iRead EU Project has released literacy games for Spanish, German, Greek, and English for L1 and L2 acquisition. In order to understand the impact of these games on reading skills for L1 German pupils, the authors employed an eye-tracking recording of pupils’ readings on a weekly basis as part of an after-school reading club. This work seeks to first understand how to interpret the eye-tracker data for such a study. Five pupils participated in the project and read short texts over the course of five weeks. The resulting data set was extensive enough to perform preliminary analysis on how to use the eye-tracking data to provide information on skill acquisition looking at pupils’ reading accuracy and speed. Given our set-up, we can show that the eye-tracker is accurate enough to measure relative reading speed between long and short vowels for selected 2-syllable words. As a result, eye-tracking data can visualize three different types of beginning readers: memorizers, pattern learners, and those with reading problems.

scholarly journals The Power of Eye Tracking in Economics Experiments

2016 ◽  
Vol 106 (5) ◽  
pp. 309-313 ◽  
Author(s):  
Joanna N. Lahey ◽  
Douglas Oxley
Keyword(s):  
Economic Theory ◽  
Data Analysis ◽  
Eye Tracking ◽  
Data Management ◽  
Tracking Data ◽  
Eye Tracker ◽  
Hiring Decisions ◽  
Economics Experiments ◽  
Set Up ◽  
Tracking Technology

Eye tracking is a technology that tracks eye activity including how long and where a participant is looking. As eye tracking technology has improved and become more affordable its use has expanded. We discuss how to design, implement, and analyze an experiment using this technology to study economic theory. Using our experience fielding an experiment to study hiring decisions we guide the reader through how to choose an eye tracker, concerns with participants and set-up, types of outputs, limitations of eye tracking, data management and data analysis. We conclude with suggestions for combining eye tracking with other measurements.

scholarly journals The impact of translation modality on user experience: an eye-tracking study of the Microsoft Word user interface

2021 ◽  
Author(s):  
Ana Guerberof Arenas ◽  
Joss Moorkens ◽  
Sharon O’Brien
Keyword(s):  
User Interface ◽  
Eye Tracking ◽  
Cognitive Load ◽  
Task Completion ◽  
Eye Tracker ◽  
Software Products ◽  
Microsoft Word ◽  
Set Up ◽  
The Impact ◽  
The Given

AbstractThis paper presents results of the effect of different translation modalities on users when working with the Microsoft Word user interface. An experimental study was set up with 84 Japanese, German, Spanish, and English native speakers working with Microsoft Word in three modalities: the published translated version, a machine translated (MT) version (with unedited MT strings incorporated into the MS Word interface) and the published English version. An eye-tracker measured the cognitive load and usability according to the ISO/TR 16982 guidelines: i.e., effectiveness, efficiency, and satisfaction followed by retrospective think-aloud protocol. The results show that the users’ effectiveness (number of tasks completed) does not significantly differ due to the translation modality. However, their efficiency (time for task completion) and self-reported satisfaction are significantly higher when working with the released product as opposed to the unedited MT version, especially when participants are less experienced. The eye-tracking results show that users experience a higher cognitive load when working with MT and with the human-translated versions as opposed to the English original. The results suggest that language and translation modality play a significant role in the usability of software products whether users complete the given tasks or not and even if they are unaware that MT was used to translate the interface.

USING EYE-TRACKING TO INVESTIGATE TOPICS IN L2 ACQUISITION AND L2 PROCESSING

2013 ◽  
Vol 35 (2) ◽  
pp. 213-235 ◽  
Author(s):  
Leah Roberts ◽  
Anna Siyanova-Chanturia
Keyword(s):  
Eye Tracking ◽  
Real Time ◽  
Language Processing ◽  
Target Language ◽  
Tracking Data ◽  
L2 Acquisition ◽  
Tracking Method ◽  
L2 Processing ◽  
Major Benefit ◽  
The Moment

Second language (L2) researchers are becoming more interested in both L2 learners’ knowledge of the target language and how that knowledge is put to use during real-time language processing. Researchers are therefore beginning to see the importance of combining traditional L2 research methods with those that capture the moment-by-moment interpretation of the target language, such as eye-tracking. The major benefit of the eye-tracking method is that it can tap into real-time (or online) comprehension processes during the uninterrupted processing of the input, and thus, the data can be compared to those elicited by other, more metalinguistic tasks to offer a broader picture of language acquisition and processing. In this article, we present an overview of the eye-tracking technique and illustrate the method with L2 studies that show how eye-tracking data can be used to (a) investigate language-related topics and (b) inform key debates in the fields of L2 acquisition and L2 processing.

scholarly journals The Influence of Articulatory Suppression on Reading Among Chinese Children with Developmental Dyslexia: An Eye-Movement and Case-Control Study

2020 ◽  
Author(s):  
Xiuhong Li ◽  
Weidong Li ◽  
Buyun Liu ◽  
Jinxin Zhang ◽  
Jingwen Ma ◽  
...  
Keyword(s):  
Eye Movement ◽  
Developmental Dyslexia ◽  
Reading Ability ◽  
High Speed ◽  
Articulatory Suppression ◽  
Reading Speed ◽  
Chinese Children ◽  
Phonological Loop ◽  
Eye Tracker ◽  
Core Deficit

Abstract Background: In Western countries, phonological processing deficit was regard as a core deficit in developmental dyslexia (DD). As Chinese is a logographic language, it’s still controversial whether and how the articulatory suppression influences reading ability and processing of Chinese children with DD. The study aimed to examine how the phonological loop influences reading ability and processing in Chinese children with DD.Methods: This study included 30 children with DD and 37 children without DD. Two types of articles (i.e., scenery prose and narrative story) and two conditions (under the conditions of articulatory-suppression and silent reading) were applied. An eye-link II High-Speed Eye Tracker was used to track a series of eye-movement parameters. The data was analyzed by the linear Mixed-Effects model. Results: Compared with children without DD, Children with DD had lower reading achievement (RA), frequency of saccades (FS) and frequency of fixations (FF), longer reading time (RT) and average fixation duration (AFD), slower reading speed (RS), shorter average saccade amplitude (ASA) and fixation distance (FD), more number of fixations (NF) and number of saccades (NS). There were significant interactions between participant group and articulatory suppression on RT and FD. We also observed interaction effects between article types and articulatory suppression on RA, AFD, ASA, and FS.Conclusion: Children DD exhibit abnormal phonological loop and eye movements while reading. The role of the articulatory suppression on reading varies with the presentation of DD and the article type.

scholarly journals The Influence of Articulatory Suppression on Reading Among Chinese Children With Developmental Dyslexia: An Eye-Movement Study

2021 ◽  
Vol 9 ◽  
Author(s):  
Xiuhong Li ◽  
Weidong Li ◽  
Buyun Liu ◽  
Jinxin Zhang ◽  
Jingwen Ma ◽  
...  
Keyword(s):  
Eye Movement ◽  
Developmental Dyslexia ◽  
Reading Ability ◽  
High Speed ◽  
Articulatory Suppression ◽  
Reading Speed ◽  
Chinese Children ◽  
Phonological Loop ◽  
Eye Tracker ◽  
Movement Parameters

Objective: The study aimed to examine how the phonological loop influences reading ability and processing in Chinese children with developmental dyslexia (DD).Methods: This study included 30 children with DD and 37 children without DD. Two types of articles (i.e., scenery prose and narrative story) and two conditions (under the conditions of articulatory-suppression and silent reading) were applied. An eye-link II High-Speed Eye Tracker was used to track a series of eye-movement parameters. The data were analyzed by the linear Mixed-Effects model.Results: Compared with children without DD, Children with DD had lower reading achievement (RA), frequency of saccades (FS) and frequency of fixations (FF), longer reading time (RT) and average fixation duration (AFD), slower reading speed (RS), shorter average saccade amplitude (ASA) and fixation distance (FD), more number of fixations (NF), and number of saccades (NS). There were significant interactions between participant group and articulatory suppression on RT and FD. We also observed interaction effects between article types and articulatory suppression on RA, AFD, ASA, and FS.Conclusion: Children DD exhibit abnormal phonological loop and eye movements while reading. The role of articulatory suppression on reading varies with the presentation of DD and the article type.

scholarly journals Algorithms for the automated correction of vertical drift in eye-tracking data

2021 ◽  
Author(s):  
Jon W. Carr ◽  
Valentina N. Pescuma ◽  
Michele Furlan ◽  
Maria Ktori ◽  
Davide Crepaldi
Keyword(s):  
Eye Tracking ◽  
Vertical Axis ◽  
Great Promise ◽  
Tracking Data ◽  
Eye Tracker ◽  
Algorithm Selection ◽  
Vertical Drift ◽  
Gradual Loss ◽  
Adjacent Line ◽  
Dynamic Time

AbstractA common problem in eye-tracking research is vertical drift—the progressive displacement of fixation registrations on the vertical axis that results from a gradual loss of eye-tracker calibration over time. This is particularly problematic in experiments that involve the reading of multiline passages, where it is critical that fixations on one line are not erroneously recorded on an adjacent line. Correction is often performed manually by the researcher, but this process is tedious, time-consuming, and prone to error and inconsistency. Various methods have previously been proposed for the automated, post hoc correction of vertical drift in reading data, but these methods vary greatly, not just in terms of the algorithmic principles on which they are based, but also in terms of their availability, documentation, implementation languages, and so forth. Furthermore, these methods have largely been developed in isolation with little attempt to systematically evaluate them, meaning that drift correction techniques are moving forward blindly. We document ten major algorithms, including two that are novel to this paper, and evaluate them using both simulated and natural eye-tracking data. Our results suggest that a method based on dynamic time warping offers great promise, but we also find that some algorithms are better suited than others to particular types of drift phenomena and reading behavior, allowing us to offer evidence-based advice on algorithm selection.

scholarly journals Investigating the Use of Eye Fixation Data for Emotion Classification in VR

2021 ◽  
Vol 12 (3) ◽  
pp. 1852-1857
Author(s):  
Lim Jia Zheng Et.al
Keyword(s):  
Eye Tracking ◽  
Classification Accuracy ◽  
Preliminary Investigation ◽  
Support Vector ◽  
Tracking Data ◽  
Eye Tracker ◽  
Emotion Classification ◽  
Learning Classifier ◽  
Rbf Kernel ◽  
Tracking Technology

Eye-tracking technology has become popular recently and widely used in research on emotion recognition since its usability. In this paper, we presented a preliminary investigation on a novelty approach for detecting emotions using eye-tracking data in virtual reality (VR) to classify 4-quadrant of emotions according to russell’scircumplex model of affects. A presentation of 3600 videos is used as the experiment stimuli to evoke the emotions of the user in VR. An add-on eye-tracker within the VR headset is used for the recording and collecting device of eye-tracking data. Fixation data is extracted and chosen as the eye feature used in this investigation. The machine learning classifier is support vector machine (SVM) with radial basis function (RBF) kernel. The best classification accuracy achieved is 69.23%. The findings showed that emotion classification using fixation data has promising results in the prediction accuracy from a four-class random classification.

scholarly journals Algorithms for the automated correction of vertical drift in eye tracking data

2020 ◽  
Author(s):  
Jon W Carr ◽  
Valentina Nicole Pescuma ◽  
Michele Furlan ◽  
Maria Ktori ◽  
Davide Crepaldi
Keyword(s):  
Eye Tracking ◽  
Vertical Axis ◽  
Great Promise ◽  
Tracking Data ◽  
Eye Tracker ◽  
Algorithm Selection ◽  
Vertical Drift ◽  
Gradual Loss ◽  
Adjacent Line ◽  
Dynamic Time

A common problem in eye tracking research is vertical drift—the progressive displacement of fixation registrations on the vertical axis that results from a gradual loss of eye tracker calibration over time. This is particularly problematic in experiments that involve the reading of multiline passages, where it is critical that fixations on one line are not erroneously recorded on an adjacent line. Correction is often performed manually by the researcher, but this process is tedious, time-consuming, and prone to error and inconsistency. Various methods have previously been proposed for the automated, post-hoc correction of vertical drift in reading data, but these methods vary greatly, not just in terms of the algorithmic principles on which they are based, but also in terms of their availability, documentation, implementation languages, and so forth. Furthermore, these methods have largely been developed in isolation with little attempt to systematically evaluate them, meaning that drift correction techniques are moving forward blindly. We document ten major algorithms, including two that are novel to this paper, and evaluate them using both simulated and natural eye tracking data. Our results suggest that a method based on dynamic time warping offers great promise, but we also find that some algorithms are better suited than others to particular types of drift phenomena and reading behavior, allowing us to offer evidence-based advice on algorithm selection.

scholarly journals Predicting Video Saliency Using Crowdsourced Mouse-Tracking Data

2019 ◽  
Author(s):  
Виталий Людвиченко ◽  
Vitaliy Lyudvichenko ◽  
Дмитрий Ватолин ◽  
Dmitriy Vatolin
Keyword(s):  
Eye Tracking ◽  
Large Scale ◽  
Peripheral Vision ◽  
Tracking Data ◽  
Eye Tracker ◽  
Mouse Tracking ◽  
Saliency Maps ◽  
Video Viewing ◽  
Computer Mouse ◽  
Neural Network Algorithm

This paper presents a new way of getting high-quality saliency maps for video, using a cheaper alternative to eye-tracking data. We designed a mouse-contingent video viewing system which simulates the viewers’ peripheral vision based on the position of the mouse cursor. The system enables the use of mouse-tracking data recorded from an ordinary computer mouse as an alternative to real gaze fixations recorded by a more expensive eye-tracker. We developed a crowdsourcing system that enables the collection of such mouse-tracking data at large scale. Using the collected mouse-tracking data we showed that it can serve as an approximation of eye-tracking data. Moreover, trying to increase the efficiency of collected mouse-tracking data we proposed a novel deep neural network algorithm that improves the quality of mouse-tracking saliency maps.

scholarly journals Product Recommendation Based on Eye Tracking Data Using Fixation Duration

2021 ◽  
Vol 5 (4) ◽  
pp. 109
Author(s):  
Juni Nurma Sari ◽  
Lukito Edi Nugroho ◽  
Paulus Insap Santosa ◽  
Ridi Ferdiana
Keyword(s):  
Eye Tracking ◽  
Collaborative Filtering ◽  
Fixation Duration ◽  
Product Information ◽  
Sensor Technology ◽  
Tracking Data ◽  
Eye Tracker ◽  
Product Recommendation ◽  
User Attention ◽  
Product Recommendations

E-commerce can be used to increase companies or sellers’ profits. For consumers, e-commerce can help them shop faster. The weakness of e-commerce is that there is too much product information presented in the catalog which in turn makes consumers confused. The solution is by providing product recommendations. As the development of sensor technology, eye tracker can capture user attention when shopping. The user attention was used as data of consumer interest in the product in the form of fixation duration following the Bojko taxonomy. The fixation duration data was processed into product purchase prediction data to know consumers’ desire to buy the products by using Chandon method. Both data could be used as variables to make product recommendations based on eye tracking data. The implementation of the product recommendations based on eye tracking data was an eye tracking experiment at selvahouse.com which sells hijab and women modest wear. The result was a list of products that have similarities to other products. The product recommendation method used was item-to-item collaborative filtering. The novelty of this research is the use of eye tracking data, namely the fixation duration and product purchase prediction data as variables for product recommendations. Product recommendation that produced by eye tracking data can be solution of product recommendation’s problems, namely sparsity and cold start.

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