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Understanding Reading Patterns of Albanian Native Readers Through Mouse Tracking Analysis

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AUIKMXVXB" target="_blank" >RIV/00216208:11320/26:UIKMXVXB - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-031-87763-6_38" target="_blank" >http://dx.doi.org/10.1007/978-3-031-87763-6_38</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-031-87763-6_38" target="_blank" >10.1007/978-3-031-87763-6_38</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Understanding Reading Patterns of Albanian Native Readers Through Mouse Tracking Analysis

  • Original language description

    Eye-tracking has been recognized as an effective method for studying reading patterns in various languages, proving its value in diverse linguistic contexts. However, the high cost of eye-tracking devices leads many labs to explore more affordable alternatives, such as web-based eye-tracking experiments, self-paced reading (SPR) studies and mouse tracking experiments. In this study we utilize the MoTR (Mouse Tracking for Reading) tool developed by Wilcox et al. [1] to conduct experiments with 50 native Albanian speakers. We present the adaptions made to the tool to address the specific requirements of our research and analyze the collected data to understand participants’ reading patterns and comprehension of the stimuli texts. Our analysis includes participant behavior, average experiment duration and the identification of keywords in each text. The findings provide valuable insights into reading speed and linguistic processing, advancing language research for Albanian and laying the groundwork for future data post-processing efforts. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Lecture Notes on Data Engineering and Communications Technologies

  • ISSN

    23674512

  • e-ISSN

  • Volume of the periodical

    245

  • Issue of the periodical within the volume

    2025

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    11

  • Pages from-to

    433-443

  • UT code for WoS article

  • EID of the result in the Scopus database

    2-s2.0-105005412088