scholarly journals It is all in the surv-eye: can eye tracking data shed light on the internal consistency in self-report questionnaires on cognitive processing strategies?

2020 ◽  
Vol 8 (3) ◽  
pp. 26-39
Author(s):  
Margot Chauliac ◽  
Leen Catrysse ◽  
David Gijbels ◽  
Vincent Donche
Keyword(s):  
Eye Tracking ◽  
Cognitive Processing ◽  
Internal Consistency ◽  
Self Report ◽  
Tracking Data ◽  
Processing Strategies ◽  
Shed Light

The Opposition of Surprisal and Semantic Similarity in the Prediction of Language Processing: Evidence from Eye-tracking Data

2020 ◽  
Author(s):  
Kun Sun
Keyword(s):  
Eye Tracking ◽  
Semantic Similarity ◽  
Cognitive Processing ◽  
Language Processing ◽  
Language Comprehension ◽  
Word Processing ◽  
Reading Time ◽  
Computational Models ◽  
Tracking Data ◽  
Dynamic Approach

Expectations or predictions about upcoming content play an important role during language comprehension and processing. One important aspect of recent studies of language comprehension and processing concerns the estimation of the upcoming words in a sentence or discourse. Many studies have used eye-tracking data to explore computational and cognitive models for contextual word predictions and word processing. Eye-tracking data has previously been widely explored with a view to investigating the factors that influence word prediction. However, these studies are problematic on several levels, including the stimuli, corpora, statistical tools they applied. Although various computational models have been proposed for simulating contextual word predictions, past studies usually preferred to use a single computational model. The disadvantage of this is that it often cannot give an adequate account of cognitive processing in language comprehension. To avoid these problems, this study draws upon a massive natural and coherent discourse as stimuli in collecting the data on reading time. This study trains two state-of-art computational models (surprisal and semantic (dis)similarity from word vectors by linear discriminative learning (LDL)), measuring knowledge of both the syntagmatic and paradigmatic structure of language. We develop a `dynamic approach' to compute semantic (dis)similarity. It is the first time that these two computational models have been merged. Models are evaluated using advanced statistical methods. Meanwhile, in order to test the efficiency of our approach, one recently developed cosine method of computing semantic (dis)similarity based on word vectors data adopted is used to compare with our `dynamic' approach. The two computational and fixed-effect statistical models can be used to cross-verify the findings, thus ensuring that the result is reliable. All results support that surprisal and semantic similarity are opposed in the prediction of the reading time of words although both can make good predictions. Additionally, our `dynamic' approach performs better than the popular cosine method. The findings of this study are therefore of significance with regard to acquiring a better understanding how humans process words in a real-world context and how they make predictions in language cognition and processing.

Reading patterns and cognitive processing in an eye-tracking study of note-reading in consecutive interpreting

Interpreting ◽  
2020 ◽  
Author(s):  
Sijia Chen ◽  
Jan-Louis Kruger ◽  
Stephen Doherty
Keyword(s):  
Eye Tracking ◽  
Phase I ◽  
Cognitive Load ◽  
Cognitive Processing ◽  
Phase Ii ◽  
Preliminary Evidence ◽  
Tracking Data ◽  
Note Reading ◽  
Reading Patterns ◽  
Consecutive Interpreting

Abstract This article reports on the eye-tracking data collected from 18 professional interpreters while they performed consecutive interpreting with notes. It is a pioneering study in its visualisation of the way in which note-reading occurs. Preliminary evidence suggests that note-reading proceeds in a nonlinear manner. The data collected in this study also report on indicators of cognitive processing in consecutive interpreting, particularly during note-reading, which appears to be a cognitively demanding process. It differs from reading for comprehension in various ways, while staying closer to reading in sight translation. In addition, the data show that the note-taking choices made during Phase I of consecutive interpreting, in which interpreters listen to the source speech and write notes, affect the level of cognitive load in Phase II, in which interpreters read back their notes and produce a target speech.

scholarly journals Eye tracking scanpath analysis techniques on web pages: A survey, evaluation and comparison

2015 ◽  
Vol 9 (1) ◽  
Author(s):  
Sukru Eraslan ◽  
Yeliz Yesilada ◽  
Simon Harper
Keyword(s):  
Eye Tracking ◽  
Cognitive Processing ◽  
Sequential Analysis ◽  
Transition Probabilities ◽  
Third Party ◽  
Web Pages ◽  
Tracking Data ◽  
Analysis Techniques ◽  
Survey Evaluation ◽  
Scanpath Analysis

Eye tracking has commonly been used to investigate how users interact with web pages, with the goal of improving their usability. This article comprehensively revisits the techniques that could be applicable to eye tracking data for analysing user scanpaths on web pages. It also uses a third-party eye tracking study to compare these techniques. This allows researchers to recognise existing techniques for their goals, understand how they work and know their strengths and limitations so that they can make an efficient choice for their studies. These techniques can mainly be used for calculating similarities/dissimilarities between scanpaths, computing transition probabilities between web page elements, detecting patterns in scanpaths and identifying common scanpaths. The scanpath analysis techniques are classified into four groups by their goals so that researchers can directly focus on the appropriate techniques for a sequential analysis of user scanpaths on web pages. This article also suggests dealing with the limitations of these techniques by pre-processing eye tracking data, considering cognitive processing and addressing their reductionist approach.

The Coping Scales From the German Stress and Coping Questionnaire for Children and Adolescents

2020 ◽  
Vol 36 (4) ◽  
pp. 545-553 ◽  
Author(s):  
Heike Eschenbeck ◽  
Uwe Heim-Dreger ◽  
Denise Kerkhoff ◽  
Carl-Walter Kohlmann ◽  
Arnold Lohaus ◽  
...  
Keyword(s):  
Emotion Regulation ◽  
Children And Adolescents ◽  
Internal Consistency ◽  
Stress And Coping ◽  
Self Report ◽  
Partial Metric ◽  
Confirmatory Factor Analyses ◽  
Language Version ◽  
English Speaking ◽  
And Coping

Abstract. The coping scales from the Stress and Coping Questionnaire for Children and Adolescents (SSKJ 3–8; Lohaus, Eschenbeck, Kohlmann, & Klein-Heßling, 2018 ) are subscales of a theoretically based and empirically validated self-report instrument for assessing, originally in the German language, the five strategies of seeking social support, problem solving, avoidant coping, palliative emotion regulation, and anger-related emotion regulation. The present study examined factorial structure, measurement invariance, and internal consistency across five different language versions: English, French, Russian, Spanish, and Ukrainian. The original German version was compared to each language version separately. Participants were 5,271 children and adolescents recruited from primary and secondary schools from Germany ( n = 3,177), France ( n = 329), Russia ( n = 378), the Dominican Republic ( n = 243), Ukraine ( n = 437), and several English-speaking countries such as Australia, Great Britain, Ireland, and the USA (English-speaking sample: n = 707). For the five different language versions of the SSKJ 3–8 coping questionnaire, confirmatory factor analyses showed configural as well as metric and partial scalar invariance (French) or partial metric invariance (English, Russian, Spanish, Ukrainian). Internal consistency coefficients of the coping scales were also acceptable to good. Significance of the results was discussed with special emphasis on cross-cultural research on individual differences in coping.

Individual differences in white and grey matter structure associated with verbal habits of thought

2019 ◽  
Author(s):  
Justin C. Hayes ◽  
Katherine L Alfred ◽  
Rachel Pizzie ◽  
Joshua S. Cetron ◽  
David J. M. Kraemer
Keyword(s):  
Individual Differences ◽  
White Matter ◽  
Cognitive Processing ◽  
Grey Matter ◽  
Structural Changes ◽  
Structural Integrity ◽  
Diffusion Tensor ◽  
Self Report ◽  
White Matter Tracts

Modality specific encoding habits account for a significant portion of individual differences reflected in functional activation during cognitive processing. Yet, little is known about how these habits of thought influence long-term structural changes in the brain. Traditionally, habits of thought have been assessed using self-report questionnaires such as the visualizer-verbalizer questionnaire. Here, rather than relying on subjective reports, we measured habits of thought using a novel behavioral task assessing attentional biases toward picture and word stimuli. Hypothesizing that verbal habits of thought are reflected in the structural integrity of white matter tracts and cortical regions of interest, we used diffusion tensor imaging and volumetric analyses to assess this prediction. Using a whole-brain approach, we show that word bias is associated with increased volume in several bilateral language regions, in both white and grey matter parcels. Additionally, connectivity within white matter tracts within an a priori speech production network increased as a function of word bias. These results demonstrate long-term structural and morphological differences associated with verbal habits of thought.

Attentional Bias to Untrustworthy Faces: Evidence From Eye Tracking Data

2015 ◽  
Vol 23 (9) ◽  
pp. 1508
Author(s):  
Qiandong WANG ◽  
Qinggong LI ◽  
Kaikai CHEN ◽  
Genyue FU
Keyword(s):  
Eye Tracking ◽  
Attentional Bias ◽  
Tracking Data

scholarly journals Mining reading patterns from eye-tracking data: method and demonstration

2019 ◽  
Vol 19 (2) ◽  
pp. 345-369 ◽  
Author(s):  
Constantina Ioannou ◽  
Indira Nurdiani ◽  
Andrea Burattin ◽  
Barbara Weber
Keyword(s):  
Eye Tracking ◽  
Tracking Data ◽  
Reading Patterns

scholarly journals Tracking eye-gaze in smart home systems (SHS): first insights from eye-tracking and self-report measures

2021 ◽  
Author(s):  
Federico Cassioli ◽  
Laura Angioletti ◽  
Michela Balconi
Keyword(s):  
Eye Tracking ◽  
Personality Traits ◽  
Smart Home ◽  
Near Infrared ◽  
Tracking System ◽  
Eye Gaze ◽  
Self Report ◽  
Visual Exploration ◽  
Living Room ◽  
Psychological Traits

AbstractHuman–computer interaction (HCI) is particularly interesting because full-immersive technology may be approached differently by users, depending on the complexity of the interaction, users’ personality traits, and their motivational systems inclination. Therefore, this study investigated the relationship between psychological factors and attention towards specific tech-interactions in a smart home system (SHS). The relation between personal psychological traits and eye-tracking metrics is investigated through self-report measures [locus of control (LoC), user experience (UX), behavioral inhibition system (BIS) and behavioral activation system (BAS)] and a wearable and wireless near-infrared illumination based eye-tracking system applied to an Italian sample (n = 19). Participants were asked to activate and interact with five different tech-interaction areas with different levels of complexity (entrance, kitchen, living room, bathroom, and bedroom) in a smart home system (SHS), while their eye-gaze behavior was recorded. Data showed significant differences between a simpler interaction (entrance) and a more complex one (living room), in terms of number of fixation. Moreover, slower time to first fixation in a multifaceted interaction (bathroom), compared to simpler ones (kitchen and living room) was found. Additionally, in two interaction conditions (living room and bathroom), negative correlations were found between external LoC and fixation count, and between BAS reward responsiveness scores and fixation duration. Findings led to the identification of a two-way process, where both the complexity of the tech-interaction and subjects’ personality traits are important impacting factors on the user’s visual exploration behavior. This research contributes to understand the user responsiveness adding first insights that may help to create more human-centered technology.

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