Exploring Eye Gaze Visualization Techniques for Identifying Distracted Students in Educational VR

Rahman, Yitoshee; Asish, Sarker Monojit; Fisher, Nicholas P.; Bruce, Ethan C.; Kulshreshth, Arun K.; Borst, Christoph W.

doi:10.1109/vr46266.2020.00009

Cited by 28 publications

(21 citation statements)

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“…Besides, visual clusters of disruptive gaze information displayed during collaboration may also become less prominent. To investigate collaborative gaze systems that are ergonomic and immersive, researchers have explored the use of emerging technologies such as AR (Lee et al, 2017) (Li et al, 2019), VR (Piumsomboon et al, 2017) (Rahman et al, 2020), and MR (Kim et al, 2020a) (Bai et al, 2020).…”

Section: Visual Interfaces Of Gaze Cues In Collaborationmentioning

confidence: 99%

“…In recent years, the rise of emerging reality-based technologies such as Augmented Reality (AR), Mixed Reality (MR), or Virtual Reality (VR) has enabled novel techniques to overcome the limitations of situated displays. However, the current colocated collaborative gaze visualisation studies conducted using reality-based technologies are often one-directional (single user gaze indicator) (Erickson et al, 2020) (Li et al, 2019), asynchronous (Rahman et al, 2020) with different knowledge level towards the task (Erickson et al, 2020), in a virtual task space (Li et al, 2019), or between a human and virtual collaborator (Erickson et al, 2020) (Li et al, 2019) (Rahman et al, 2020). It is common to represent all gaze behaviours (eye fixation, saccades, and blink etc) using the same virtual cue (e.g., a virtual gaze ray) while richer visualisation of different gaze behaviours combining both spatial and temporal information are neglected.…”

Section: Introductionmentioning

confidence: 99%

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Eye See What You See: Exploring How Bi-Directional Augmented Reality Gaze Visualisation Influences Co-Located Symmetric Collaboration

Jing

May

Lee

et al. 2021

Front. Virtual Real.

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Gaze is one of the predominant communication cues and can provide valuable implicit information such as intention or focus when performing collaborative tasks. However, little research has been done on how virtual gaze cues combining spatial and temporal characteristics impact real-life physical tasks during face to face collaboration. In this study, we explore the effect of showing joint gaze interaction in an Augmented Reality (AR) interface by evaluating three bi-directional collaborative (BDC) gaze visualisations with three levels of gaze behaviours. Using three independent tasks, we found that all bi-directional collaborative BDC visualisations are rated significantly better at representing joint attention and user intention compared to a non-collaborative (NC) condition, and hence are considered more engaging. The Laser Eye condition, spatially embodied with gaze direction, is perceived significantly more effective as it encourages mutual gaze awareness with a relatively low mental effort in a less constrained workspace. In addition, by offering additional virtual representation that compensates for verbal descriptions and hand pointing, BDC gaze visualisations can encourage more conscious use of gaze cues coupled with deictic references during co-located symmetric collaboration. We provide a summary of the lessons learned, limitations of the study, and directions for future research.

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Section: Visual Interfaces Of Gaze Cues In Collaborationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Eye See What You See: Exploring How Bi-Directional Augmented Reality Gaze Visualisation Influences Co-Located Symmetric Collaboration

Jing

May

Lee

et al. 2021

Front. Virtual Real.

View full text Add to dashboard Cite

show abstract

“…There is a risk that is making all data available to users simultaneously, even if possible, will result in more confusion. Hence, guidelines and opportunities to filter data for analysis seem crucial, which is also mentioned by Rahman et al (2020), for larger user groups and in Ugwitz et al (2022). There might also be different needs depending on whether the users are novices or experts.…”

Section: Discussionmentioning

confidence: 99%

“…For the 3D model on screen and in VR, the 3D gaze data have been computed via raycasting and visualized as points in the VE together with a playback of the gaze movements. Rahman et al (2020) explore gaze data supporting a VRbased education scenario. Eye-tracking data can help provide real-time information to see if students are confused or distracted by looking at objects not relevant to the educational aim.…”

Section: Gaze In Virtual Environmentsmentioning

confidence: 99%

A Systematic Review of Visualization Techniques and Analysis Tools for Eye-Tracking in 3D Environments

Sundstedt

Garro

2022

Front. Neuroergonomics

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This systematic literature review presents an update on developments in 3D visualization techniques and analysis tools for eye movement data in 3D environments. With the introduction of affordable and non-intrusive eye-tracking solutions to the mass market, access to users' gaze is now increasingly possible. As a result, the adoption of eye-tracking in virtual environments using head-mounted displays is expected to increase since the trend is to incorporate gaze tracking as part of new technical solutions. The systematic literature review presented in this paper was conducted using the Scopus database (using the period 2017 to 17th of May 2022), which after analysis, resulted in the inclusion of 15 recent publications with relevance in eye-tracking visualization techniques for 3D virtual scenes. First, this paper briefly describes the foundations of eye-tracking and traditional 2D visualization techniques. As background, we also list earlier 3D eye-tracking visualization techniques identified in a previous review. Next, the systematic literature review presents the method used to acquire the included papers and a description of these in terms of eye-tracking technology, observed stimuli, application context, and type of 3D gaze visualization techniques. We then discuss the overall findings, including opportunities, challenges, trends, and present ideas for future directions. Overall the results show that eye-tracking in immersive virtual environments is on the rise and that more research and developments are needed to create novel and improved technical solutions for 3D gaze analysis.

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“…Physiological measures can also benefit classical teacher-student scenarios. Rahman et al (2020) present a virtual education environment in which the teacher is provided with a visual representation of the gaze behavior of students. This allows the teachers to identify distracted or confused students, which can benefit the transfer of knowledge.…”

Section: Virtual Classroomsmentioning

confidence: 99%

A Systematic Review of Physiological Measurements, Factors, Methods, and Applications in Virtual Reality

Halbig

Latoschik

2021

Front. Virtual Real.

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Measurements of physiological parameters provide an objective, often non-intrusive, and (at least semi-)automatic evaluation and utilization of user behavior. In addition, specific hardware devices of Virtual Reality (VR) often ship with built-in sensors, i.e. eye-tracking and movements sensors. Hence, the combination of physiological measurements and VR applications seems promising. Several approaches have investigated the applicability and benefits of this combination for various fields of applications. However, the range of possible application fields, coupled with potentially useful and beneficial physiological parameters, types of sensor, target variables and factors, and analysis approaches and techniques is manifold. This article provides a systematic overview and an extensive state-of-the-art review of the usage of physiological measurements in VR. We identified 1,119 works that make use of physiological measurements in VR. Within these, we identified 32 approaches that focus on the classification of characteristics of experience, common in VR applications. The first part of this review categorizes the 1,119 works by field of application, i.e. therapy, training, entertainment, and communication and interaction, as well as by the specific target factors and variables measured by the physiological parameters. An additional category summarizes general VR approaches applicable to all specific fields of application since they target typical VR qualities. In the second part of this review, we analyze the target factors and variables regarding the respective methods used for an automatic analysis and, potentially, classification. For example, we highlight which measurement setups have been proven to be sensitive enough to distinguish different levels of arousal, valence, anxiety, stress, or cognitive workload in the virtual realm. This work may prove useful for all researchers wanting to use physiological data in VR and who want to have a good overview of prior approaches taken, their benefits and potential drawbacks.

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Exploring Eye Gaze Visualization Techniques for Identifying Distracted Students in Educational VR

Cited by 28 publications

References 0 publications

Eye See What You See: Exploring How Bi-Directional Augmented Reality Gaze Visualisation Influences Co-Located Symmetric Collaboration

Eye See What You See: Exploring How Bi-Directional Augmented Reality Gaze Visualisation Influences Co-Located Symmetric Collaboration

A Systematic Review of Visualization Techniques and Analysis Tools for Eye-Tracking in 3D Environments

A Systematic Review of Physiological Measurements, Factors, Methods, and Applications in Virtual Reality

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