Combining Concurrent Think-Aloud Protocols and Eye-Tracking Observations: An Analysis of Verbalizations and Silences

Elling, Sanne; Lentz, Leo; Jong, Menno D.T. de

doi:10.1109/tpc.2012.2206190

Cited by 64 publications

(41 citation statements)

References 34 publications

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“…This is different from the commonly used think aloud method that requires that the participants should not be disturbed by the experimenter [83,84]. While the approach of allowing free talk can reveal doubts, judgments, and frustrations which cannot be obtained from eye-movement data directly [85,86], it suffers the criticism that the verbalizing of thoughts can distract participants' attention [49]. In addition, although the experimenter kept his response levels as low as possible during this experiment, these communications could also be seen to interfere with the participant thought processes and have an effect on the comparability between participants and the generality of the results.…”

Section: Limitationsmentioning

confidence: 97%

An Exploratory Study Investigating Gender Effects on Using 3D Maps for Spatial Orientation in Wayfinding

Liao

Dong

2017

IJGI

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3D representations in applications that provide self-localization and orientation in wayfinding have become increasingly popular in recent years because of technical advances in the field. However, human factors have been largely ignored while designing 3D representations in support of pedestrian navigation. This exploratory study aims to explore gender effects on using 3D maps for spatial orientation. We designed a 3D map that combines salient 3D landmarks and 2D layouts, and evaluated gender differences in their performance during direction-pointing tasks by administrating an eye tracking experiment. The results indicate there was no significant overall gender difference on performance and visual attention. However, we observed that males using the 3D map paid more attention to landmarks in the environment and performed better than when using the conventional 2D map, whereas female performance did not show any significant difference between the two types of map usage. We also observed contrary gender differences in visual attention on landmarks between the 3D and 2D maps. While males fixated longer on landmarks than females when using the 3D map, females paid more visual attention to landmarks than males when using the 2D map. In addition, verbal protocols showed that males had more confidence while make decisions. These empirical results can be helpful in the design of map-based wayfinding enhancement tools.

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Section: Limitationsmentioning

confidence: 97%

An Exploratory Study Investigating Gender Effects on Using 3D Maps for Spatial Orientation in Wayfinding

Liao

Dong

2017

IJGI

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“…Methodologically, the paper adds value by proposing eye-tracking as a new way of measuring destination image formation, and shows how eye-tracking can help to understand the real-time formation process in a more precise way (Elling et al, 2012;Jordan et al, 2013).…”

Section: Discussionmentioning

confidence: 99%

“…Despite their distinct advantages, the traditional methods used to understand web behaviour such as diaries, think-aloud techniques and post-search interviews all give room for undesired post-rationalisation (Elling et al, 2012). Less intrusive eye-tracking, on the contrary, records users" real time eyemovements (such as the number of fixations and fixation length) and precisely reflects moment-to-moment cognitive processes (Balatsoukas and Ruthven, 2012; Mariussen The Typology and Role of Online Information Sources... 149…”

Section: Stage 2: Trip Planning Exercisementioning

confidence: 99%

The Typology and Role of Online Information Sources in Destination Image Formation: An EyeTracking Study

Mariussen¹

2014

IJDAR

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Abstract. The construct of destination image and its formation are well researched. Numerous studies are conducted to investigate how destination images impact tourists" attitudes, behaviour and destination choice and what factors influence their destination image formation. However, much of this research focuses on post-visit images, and little is still known about the actual process of destination image formation as it unfolds, particularly prior to visiting a destination. Understanding this process of image development is meanwhile critical, as tourist numbers worldwide continue to grow. Destinations face fiercer competition, and their expanding image representations on the Internet are more frequently created outside Destination Management Organisations" (DMO) offices. This study attempts to shed light on a destination image formation process prior to visiting a destination. By triangulating click-stream, eye-tracking, questionnaire and interview data, the work explores the types of online information sources involved in this process and examines their significance for destination image formation.

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“…Other than the adaptation of models, one requirement of a good proactive tutoring system is unobtrusiveness. Before eye-tracking technology was applied widely, research used the thinking aloud protocol [28,29]-i.e., speaking out what is on one's mind during the thinking process-to probe the cognitive process. However, this method interferes with the participants' behavior because it requires participants to perform extra tasks beyond the regular thinking process [30].…”

Section: Related Workmentioning

confidence: 99%

Predicting Spatial Visualization Problems’ Difficulty Level from Eye-Tracking Data

Younes

Bairaktarova

et al. 2020

Sensors

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The difficulty level of learning tasks is a concern that often needs to be considered in the teaching process. Teachers usually dynamically adjust the difficulty of exercises according to the prior knowledge and abilities of students to achieve better teaching results. In e-learning, because there is no teacher involvement, it often happens that the difficulty of the tasks is beyond the ability of the students. In attempts to solve this problem, several researchers investigated the problem-solving process by using eye-tracking data. However, although most e-learning exercises use the form of filling in blanks and choosing questions, in previous works, research focused on building cognitive models from eye-tracking data collected from flexible problem forms, which may lead to impractical results. In this paper, we build models to predict the difficulty level of spatial visualization problems from eye-tracking data collected from multiple-choice questions. We use eye-tracking and machine learning to investigate (1) the difference of eye movement among questions from different difficulty levels and (2) the possibility of predicting the difficulty level of problems from eye-tracking data. Our models resulted in an average accuracy of 87.60% on eye-tracking data of questions that the classifier has seen before and an average of 72.87% on questions that the classifier has not yet seen. The results confirmed that eye movement, especially fixation duration, contains essential information on the difficulty of the questions and it is sufficient to build machine-learning-based models to predict difficulty level.

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Combining Concurrent Think-Aloud Protocols and Eye-Tracking Observations: An Analysis of Verbalizations and Silences

Cited by 64 publications

References 34 publications

An Exploratory Study Investigating Gender Effects on Using 3D Maps for Spatial Orientation in Wayfinding

An Exploratory Study Investigating Gender Effects on Using 3D Maps for Spatial Orientation in Wayfinding

The Typology and Role of Online Information Sources in Destination Image Formation: An EyeTracking Study

Predicting Spatial Visualization Problems’ Difficulty Level from Eye-Tracking Data

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