Literature DB >> 30225553

Improving the performance of eye trackers with limited spatial accuracy and low sampling rates for reading analysis by heuristic fixation-to-word mapping.

Oleg Špakov1, Howell Istance2, Aulikki Hyrskykari2, Harri Siirtola2, Kari-Jouko Räihä2.   

Abstract

The recent growth in low-cost eye-tracking systems makes it feasible to incorporate real-time measurement and analysis of eye position data into activities such as learning to read. It also enables field studies of reading behavior in the classroom and other learning environments. We present a study of the data quality provided by two remote eye trackers, one being a low-sampling-rate, low-cost system. Then we present two algorithms for mapping fixations derived from the data to the words being read. One is for immediate (or real-time) mapping of fixations to words and the other for deferred (or post hoc) mapping. Following this, an evaluation study is reported. Both studies were carried out in the classroom of a Finnish elementary school with students who were second graders. This study shows very high success rates in automatically mapping fixations to the lines of text being read when the mapping is deferred. The success rates for immediate mapping are comparable with those obtained in earlier studies, although here the data is collected some 10 min after initial calibration of low-sample (30 Hz) remote eye trackers, rather than a laboratory setting using high-sampling-rate trackers. The results provide a solid basis for developing systems for use in classrooms and other learning environments that can provide immediate automatic support with reading, and share data between a group of learners and the teacher of that group. This makes possible new approaches to the learning of reading and comprehension skills.

Keywords:  Data quality; Elementary school; Fixation mapping algorithm; Low-cost eye tracker; Reading aid

Mesh:

Year:  2019        PMID: 30225553     DOI: 10.3758/s13428-018-1120-x

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  5 in total

1.  Eye tracking: empirical foundations for a minimal reporting guideline.

Authors:  Kenneth Holmqvist; Saga Lee Örbom; Ignace T C Hooge; Diederick C Niehorster; Robert G Alexander; Richard Andersson; Jeroen S Benjamins; Pieter Blignaut; Anne-Marie Brouwer; Lewis L Chuang; Kirsten A Dalrymple; Denis Drieghe; Matt J Dunn; Ulrich Ettinger; Susann Fiedler; Tom Foulsham; Jos N van der Geest; Dan Witzner Hansen; Samuel B Hutton; Enkelejda Kasneci; Alan Kingstone; Paul C Knox; Ellen M Kok; Helena Lee; Joy Yeonjoo Lee; Jukka M Leppänen; Stephen Macknik; Päivi Majaranta; Susana Martinez-Conde; Antje Nuthmann; Marcus Nyström; Jacob L Orquin; Jorge Otero-Millan; Soon Young Park; Stanislav Popelka; Frank Proudlock; Frank Renkewitz; Austin Roorda; Michael Schulte-Mecklenbeck; Bonita Sharif; Frederick Shic; Mark Shovman; Mervyn G Thomas; Ward Venrooij; Raimondas Zemblys; Roy S Hessels
Journal:  Behav Res Methods       Date:  2022-04-06

2.  Visualizing the Reading Activity of People Learning to Read.

Authors:  Oleg Špakov; Harri Siirtola; Howell Istance; Räihä Kari-Jouko
Journal:  J Eye Mov Res       Date:  2017-11-15       Impact factor: 0.957

Review 3.  A Systematic Review of Eye-Tracking Studies of Construction Safety.

Authors:  Baoquan Cheng; Xiaowei Luo; Xiang Mei; Huihua Chen; Jianling Huang
Journal:  Front Neurosci       Date:  2022-04-26       Impact factor: 5.152

4.  Expanding horizons of cross-linguistic research on reading: The Multilingual Eye-movement Corpus (MECO).

Authors:  Noam Siegelman; Sascha Schroeder; Cengiz Acartürk; Hee-Don Ahn; Svetlana Alexeeva; Simona Amenta; Raymond Bertram; Rolando Bonandrini; Marc Brysbaert; Daria Chernova; Sara Maria Da Fonseca; Nicolas Dirix; Wouter Duyck; Argyro Fella; Ram Frost; Carolina A Gattei; Areti Kalaitzi; Nayoung Kwon; Kaidi Lõo; Marco Marelli; Timothy C Papadopoulos; Athanassios Protopapas; Satu Savo; Diego E Shalom; Natalia Slioussar; Roni Stein; Longjiao Sui; Analí Taboh; Veronica Tønnesen; Kerem Alp Usal; Victor Kuperman
Journal:  Behav Res Methods       Date:  2022-02-02

5.  Algorithms for the automated correction of vertical drift in eye-tracking data.

Authors:  Jon W Carr; Valentina N Pescuma; Michele Furlan; Maria Ktori; Davide Crepaldi
Journal:  Behav Res Methods       Date:  2021-06-22
  5 in total

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