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.

Feasibility of EEG to monitor cognitive performance during venous cannulation: EEG Distracted Intravenous Access (E-DIVA)

2016 ◽  
Vol 2 (3) ◽  
pp. 68-72 ◽  
Author(s):  
David J Lowe ◽  
Scott A James ◽  
Adam Lloyd ◽  
Gareth R Clegg
Keyword(s):  
Cognitive Load ◽  
Clinical Performance ◽  
Educational Interventions ◽  
Task Completion ◽  
Cognitive Workload ◽  
Simple Arithmetic ◽  
Arithmetic Task ◽  
Significant Difference ◽  
Set Up ◽  
The Impact

BackgroundThe feasibility study aims to evaluate the use of EEG in measuring workload during a simulated intravenous cannulation task. Cognitive workload is strongly linked to performance, but current methods to assess workload are unreliable. The paper presents the use of EEG to compare the cognitive workload between an expert and novice group completing a simple clinical task.Methods2 groups of volunteers (10 final year medical students and 10 emergency medicine consultants) were invited to take part in the study. Each participant was asked to perform 3 components of the simulation protocol: intravenous cannulation, a simple arithmetic test and finally these tasks combined. Error rate, speed of task completion and an EEG-based measure of cognitive workload were recorded for each element.ResultsEEG cognitive workload during the combined cannulation and arithmetic task is significantly greater in novice participants when compared with expert operators performing the same task combination. EEG workload mean measured for novice and experts was 0.62 and 0.54, respectively (p=0.001, 95% CI 0.09 to 0.30). There was no significant difference between novice and expert EEG workload when the tasks were performed individually.ConclusionsEEG provides the opportunity to monitor and analyse the impact of cognitive load on clinical performance. Despite the significant challenges in set up and protocol design, there is a potential to develop educational interventions to optimise clinician's awareness of cognitive load. In addition, it may enable the use of metrics to monitor the impact of different interventions and select those that optimise clinical performance.

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 Computer-generated facial areas of interest in eye tracking research: A simulation study

2021 ◽  
Author(s):  
Antonia Vehlen ◽  
William Standard ◽  
Gregor Domes
Keyword(s):  
Eye Tracking ◽  
Voronoi Tessellation ◽  
Data Accuracy ◽  
Type I ◽  
Type Ii ◽  
Eye Tracker ◽  
Type I Errors ◽  
Areas Of Interest ◽  
Type Ii Errors ◽  
The Impact

Advances in eye tracking technology have enabled the development of interactive experimental setups to study social attention. Since these setups differ substantially from the eye tracker manufacturer’s test conditions, validation is essential with regard to data quality and other factors potentially threatening data validity. In this study, we evaluated the impact of data accuracy and areas of interest (AOIs) size on the classification of simulated gaze data. We defined AOIs of different sizes using the Limited-Radius Voronoi-Tessellation (LRVT) method, and simulated gaze data for facial target points with varying data accuracy. As hypothesized, we found that data accuracy and AOI size had strong effects on gaze classification. In addition, these effects were not independent and differed for falsely classified gaze inside AOIs (Type I errors) and falsely classified gaze outside the predefined AOIs (Type II errors). The results indicate that smaller AOIs generally minimize false classifications as long as data accuracy is good enough. For studies with lower data accuracy, Type II errors can still be compensated to some extent by using larger AOIs, but at the cost of an increased probability of Type I errors. Proper estimation of data accuracy is therefore essential for making informed decisions regarding the size of AOIs.

scholarly journals THE EFFICIENCY OF IRRIGATION AND VARIETY ON THE HARVEST RATIO OF THREE COTTON TYPES (Gossypium hirsutum L.)

2020 ◽  
Vol 1 ◽  
pp. 6-13
Author(s):  
Galina Gospodinova ◽  
Galina Gospodinova ◽  
Velika Kuneva
Keyword(s):  
Irrigation Water ◽  
Efficiency Coefficient ◽  
Gossypium Hirsutum L ◽  
Factorial Anova ◽  
Irrigation Rate ◽  
Main Effect ◽  
Irrigation Effect ◽  
Set Up ◽  
The Impact ◽  
The Given

The purpose of this research is to investigate the impact of variety and irrigation on three cotton types, and to study the effectiveness of irrigation on the productivity of these cotton types which were fed by different norms of mineral nutrition. To assess the impact of soil humidity and fertilizer amount, we set up a field trial with three varieties of cotton. The field experiment was carried out within the Faculty of Agriculture, Trakia University, Stara Zagora, Bulgaria between 2018-2019. A two way factorial ANOVA (with variety and irritation as factors) suggested a significant main effect of irrigation (p< .001). Variety showed the strongest impact on the differences in "flowering" of cotton which were 64% in 2018 and 41% for 2019 respectively. We established an efficiency coefficient (KEF) representing the ratio of the additional harvest and the actual irrigation rate. The KEF of irrigation water varied depending on the cotton varieties and the levels of fertilization. The highest values of KEF were recorded after fertilization by N8 as given by units of cultivar Helius (EF = 0.67).  The effect of irrigation, expressed as a harvest per unit of irrigation water considerably varied over years. It was established as a ratio between the irrigation rate and the additional cotton  produce. At zero fertilization Helius, each cubic meter of water carried an average 2.24 kilograms of cotton harvest over two years. Optimizing the water supply and fertilizing with N16 provided 2.83 kilograms. On average, the Darmi variety irrigation effect ranged from 0.63 kilograms (N24) to 2.43 kilograms per cubic meter (N16) during the given period.

Learning from screencast videos for software training : a comparison of dual and single-monitor learning environments

2017 ◽  
Author(s):  
◽  
Douglas Paul Kueker
Keyword(s):  
Working Memory ◽  
Eye Tracking ◽  
Cognitive Load ◽  
Working Memory Capacity ◽  
Worked Examples ◽  
Memory Capacity ◽  
Instructional Efficiency ◽  
Experimental Conditions ◽  
Split Attention ◽  
Set Up

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Learning to use software programs using worked examples in screencast videos presents a classic split-attention problem that requires learners to mentally integrate information from the video with a target application. While much is known about sound screencast tutorial design, little is known about the features of the learning environment, such as monitor configuration, that may influence learning from this form of instruction. An experiment was conducted with 42 novice learners to fill this gap by comparing the effects of two common monitor configurations which split attention in different ways. In one condition, subjects split attention temporally by toggling back and forth between the video and target application on one monitor, while the other condition required subjects to split attention spatially by shifting their gaze between the video and target application displayed on two side-by-side monitors. Effects due to the monitor set-up were assessed for measures of cognitive load, instructional efficiency, and motivation using a 2x2 study design that controlled for task order. Results indicated that cognitive load as measured through task evoked pupil response was significantly higher, pless than .05, for groups with two monitors during both instruction and testing, even after controlling for working memory capacity. Analyses of three gaze-related eye-tracking metrics and NASA-TLX ratings did not indicate any differences in workload due to the experimental treatment; however, attentional patterns indicated by the eye-tracking data were shaped by two- and three-way interactions between working memory capacity and the experimental conditions. Measures of instructional efficiency indicated that the single monitor set-up was most efficient as learners attempted to transfer learning. While task efficacy and relevance ratings increased after training, monitor set-up did not affect post-training motivation.

scholarly journals What can gaze behaviors, neuroimaging data, and test scores tell us about test method effects and cognitive load in listening assessments?

2021 ◽  
pp. 026553222110268
Author(s):  
Vahid Aryadoust ◽  
Stacy Foo ◽  
Li Ying Ng
Keyword(s):  
Eye Tracking ◽  
Cognitive Load ◽  
Test Scores ◽  
Test Validity ◽  
Test Methods ◽  
Load Test ◽  
Test Method ◽  
Functional Near Infrared Spectroscopy ◽  
Listening Test ◽  
The Impact

The aim of this study was to investigate how test methods affect listening test takers’ performance and cognitive load. Test methods were defined and operationalized as while-listening performance (WLP) and post-listening performance (PLP) formats. To achieve the goal of the study, we examined test takers’ ( N = 80) brain activity patterns (measured by functional near-infrared spectroscopy (fNIRS)), gaze behaviors (measured by eye-tracking), and listening performance (measured by test scores) across the two test methods. We found that the test takers displayed lower activity levels across brain regions supporting comprehension during the WLP tests relative to the PLP tests. Additionally, the gaze behavioral patterns exhibited during the WLP tests suggested that the test takers adopted keyword matching and “shallow listening.” Together, the neuroimaging and gaze behavioral data indicated that the WLP tests imposed a lower cognitive load on the test takers than the PLP tests. However, the test takers performed better with higher test scores for one of two WLP tests compared with the PLP tests. By incorporating eye-tracking and neuroimaging in this exploration, this study has advanced the current knowledge on cognitive load and the impact imposed by different listening test methods. To advance our knowledge of test validity, other researchers could adopt our research protocol and focus on extending the test method framework used in this study.

scholarly journals The Effects of Digitally Mediated Multimodal Indirect Feedback on Narrations in L2 Spanish Writing: Eye Tracking as a Measure of Noticing

Languages ◽  
2021 ◽  
Vol 6 (4) ◽  
pp. 159
Author(s):  
Laura E. Valentin-Rivera ◽  
Li Yang
Keyword(s):  
Eye Tracking ◽  
Corrective Feedback ◽  
Target Language ◽  
Eye Tracker ◽  
Revision Process ◽  
Video Tutorial ◽  
Written Corrective Feedback ◽  
L2 Development ◽  
Indirect Feedback ◽  
The Impact

Written corrective feedback (CF) could pave the way for L2 development, especially when embedded in multimodality. Building on prior research, this descriptive study drew a relationship between specific types of errors that were most successfully revised and noticing measured by eye-tracking techniques. Additionally, this study furthers our understanding of the impact of indirect CF (i.e., codes accompanied by metalinguistic hints) delivered by two multimodal components: (a) a video tutorial on how to approach teachers’ comments and (b) a soundless video displaying individualized teacher feedback. To this end, three L2 learners of Spanish completed a narration in the target language, watched a tutorial on attending to CF, received indirect feedback via the personalized soundless video (i.e., option “b” above), and corrected their errors. An eye tracker recorded all ocular activity while the participants watched both recordings. The results suggested that receiving training on approaching teachers’ comments may enhance the overall success rate of revisions, especially in verb and vocabulary-related errors. Last, a detailed unfolding of the revision process unveiled by eye-tracking data accounted for (1) an explanation of why two specific types of errors were more successfully revised and (2) some pedagogical recommendations.

scholarly journals Design and development of a low-cost mask-type eye tracker to collect quality fixation measurements in the sport domain

2018 ◽  
Vol 233 (1) ◽  
pp. 116-125
Author(s):  
Jesús Morenas Martín ◽  
Vicente Luis del Campo ◽  
Luis Jesús Manso Fernández-Argüelles
Keyword(s):  
User Interface ◽  
Eye Tracking ◽  
Tracking System ◽  
Low Cost ◽  
Eye Tracker ◽  
Spatial Accuracy ◽  
Quality Of Data ◽  
Research Fields ◽  
Accuracy And Precision ◽  
Mask Type

The aim of the study was to build a low-cost mask-type eye tracker with accuracy and precision levels similar to those reported for commercial eye tracking devices. To this end, head-mounted hardware was designed and developed, while open-source software was modified for digital image capture, manipulation, and fixation analysis. An image recognition application was also included with different lighting scenarios. Moreover, parallax and viewing perspective errors were controlled to ensure the quality of data collection. The device was wireless and lightweight (99 g) to allow for natural movement and avoid participant discomfort. After calibration of a 9-target monocular grid, spatial accuracy and precision of the eye tracker was evaluated by 30 participants, at four different lighting setups, both before and after a climbing task. Validity tests showed high levels of accuracy in all conditions as evidenced by a systematic error for a 13-target grid of <0.5°. The reliability tests also showed consistent measurements with no differences in accuracy recorded between participants, lighting conditions, and visual behaviors for the pre- versus post-climbing task. These results suggest that the present eye tracker reports spatial accuracy similar to other commercial systems with levels of high quality. Altogether, this innovative user interface is suitable for research purposes and/or performance analysis in physical activity and sport-related activities. Also, features of this mask-type eye tracking system make it a suitable perceptual user interface to investigate human–computer interactions in a large number of other research fields including psychology, education, marketing, transportation, and medicine.

scholarly journals MLGaze: Machine Learning-Based Analysis of Gaze Error Patterns in Consumer Eye Tracking Systems

Vision ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 25
Author(s):  
Anuradha Kar
Keyword(s):  
Machine Learning ◽  
Eye Tracking ◽  
Data Quality ◽  
Regression Models ◽  
Operating Conditions ◽  
Eye Tracker ◽  
Error Sources ◽  
Error Patterns ◽  
Machine Learning Methods ◽  
The Impact

Analyzing the gaze accuracy characteristics of an eye tracker is a critical task as its gaze data is frequently affected by non-ideal operating conditions in various consumer eye tracking applications. In previous research on pattern analysis of gaze data, efforts were made to model human visual behaviors and cognitive processes. What remains relatively unexplored are questions related to identifying gaze error sources as well as quantifying and modeling their impacts on the data quality of eye trackers. In this study, gaze error patterns produced by a commercial eye tracking device were studied with the help of machine learning algorithms, such as classifiers and regression models. Gaze data were collected from a group of participants under multiple conditions that commonly affect eye trackers operating on desktop and handheld platforms. These conditions (referred here as error sources) include user distance, head pose, and eye-tracker pose variations, and the collected gaze data were used to train the classifier and regression models. It was seen that while the impact of the different error sources on gaze data characteristics were nearly impossible to distinguish by visual inspection or from data statistics, machine learning models were successful in identifying the impact of the different error sources and predicting the variability in gaze error levels due to these conditions. The objective of this study was to investigate the efficacy of machine learning methods towards the detection and prediction of gaze error patterns, which would enable an in-depth understanding of the data quality and reliability of eye trackers under unconstrained operating conditions. Coding resources for all the machine learning methods adopted in this study were included in an open repository named MLGaze to allow researchers to replicate the principles presented here using data from their own eye trackers.

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.

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