| 1. |
- Mulvey, Fiona, et al.
(författare)
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How reliable is eye movement data?
- 2018
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Konferensbidrag (refereegranskat)abstract
- Eye data quality varies greatly with the eyetracking system, the individual characteristics of participants, the recording environment, and the operator. The quality of the signal has important repercussions for which eye movement measures are valid, and what conclusions can be drawn from them. Reading research often has high demands in terms of spatial precision and accuracy. Reliably detecting events (e.g., fixations, saccades, pursuit, blinks) depends strongly on intrinsic instrument noise and the correct application of parsing algorithms. We define standard measures of data quality across commercial systems and screen area, as well as system robustness to individual variation, from a large data collection. We show differences in the results from parsing algorithms with varying eye data quality, and infer predictive models of data quality as a function of employed systems, operator, and characteristics of the recorded eye across 12 tower mounted and remote eyetracking systems, and 194 participants. We discuss these results in terms of stimulus constraints in reading research. This work is output of the Eye Data Quality Standardization Committee – a collaboration of manufacturers and researchers towards unbiased measures, and the provision of open-source tools for transparency of eye data quality.
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| 3. |
- Wengelin, Åsa, et al.
(författare)
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Combined eyetracking and keystroke-logging methods for studying cognitive processes in text production
- 2009
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Ingår i: Behavior Research Methods. - New York : Springer-Verlag New York. - 1554-351X .- 1554-3528. ; 41:2, s. 337-351
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Tidskriftsartikel (refereegranskat)abstract
- Writers typically spend a certain proportion of time looking back over the text that they have written. This is likely to serve a number of different functions, which are currently poorly understood. In this article, we present two systems, ScriptLog + TimeLine and EyeWrite, that adopt different and complementary approaches to exploring this activity by collecting and analyzing combined eye movement and keystroke data from writers composing extended texts. ScriptLog + TimeLine is a system that is based on an existing keystroke-logging program and uses heuristic, pattern-matching methods to identify reading episodes within eye movement data. EyeWrite is an integrated editor and analysis system that permits identification of the words that the writer fixates and their location within the developing text. We demonstrate how the methods instantiated within these systems can be used to make sense of the large amount of data generated by eyetracking and keystroke logging in order to inform understanding of the cognitive processes that underlie written text production.
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