Clustering sequential navigation patterns in multiple‐source reading tasks with dynamic time warping method.

Background: Data‐driven investigations of how students transit pages in digital reading tasks and how much time they spend on each transition allow mapping sequences of navigation behaviours into students' navigation reading strategies. Objectives: The purpose of this study is threefold: (1) to iden...

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Publicado en:Journal of Computer Assisted Learning Vol. 39; no. 3; pp. 719 - 737
Autores principales: He, Qiwei, Borgonovi, Francesca, Suárez‐Álvarez, Javier
Formato: equations & formulas pictorial research tables/charts Journal Article
Publicado: Wiley-Blackwell Jun2023
Acceso en línea:Ver este registro en EBSCOhost
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      jtl: Journal of Computer Assisted Learning
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      dt: Jun2023
      vid: 39
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1111/jcal.12748
        163886537
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        atl: Clustering sequential navigation patterns in multiple‐source reading tasks with dynamic time warping method.
      aug:
        au:
          He, Qiwei
          Borgonovi, Francesca
          Suárez‐Álvarez, Javier
        affil: Educational Testing Service, Princeton New Jersey,, USA
      sug:
        subj:
          Students
          Reading
          Task Performance and Analysis
          Sociodemographic Factors
          Algorithms
          Human
          Male
          Female
          Adolescence
          Cluster Analysis
          Descriptive Statistics
          Data Analysis Software
          Sequence Analysis
          Socioeconomic Factors
          Sex Factors
          Adolescent: 13-18 years
          Male
          Female
      ab: Background: Data‐driven investigations of how students transit pages in digital reading tasks and how much time they spend on each transition allow mapping sequences of navigation behaviours into students' navigation reading strategies. Objectives: The purpose of this study is threefold: (1) to identify students' navigation patterns in multiple‐source reading tasks using a sequence clustering approach; (2) to examine how students' navigation patterns are associated with their reading performance and socio‐demographic characteristics; (3) to showcase how the navigation sequences could be clustered on the similarity measure by dynamic time warping (DTW) methods. Methods: This study draws on process data from a sample of 16,957 students from 69 countries participating in the PISA 2018 study to identify how students navigate through a multiple‐source reading item. Students' navigation sequences were characterized by two indicators: the page sequence that tracks the page transition path and the time sequence that records the time duration on each visited page. K‐medoid partitioning clustering analyses were conducted on pairwise distance similarity measures computed by the DTW method. Results and conclusions: Students' navigation patterns were found moderately associated with their reading proficiency levels. Students who visited all the pages and spent more time reading without rush transitions obtained the highest reading scores. Girls were more likely to achieve higher scores than boys when longer navigation sequences were used with shorter reading time on transited pages. Students who navigated only limited pages and spent shorter reading time were averagely at the lowest rank of socio‐economic status. Implications: This study provides evidence for the exploration of students' navigation patterns and the examination of associations between navigation patterns and reading scores with the use of process data. Lay Description: This study identifies students' navigation patterns in multiple‐source reading tasks by using sequence clustering method.The pairwise distance similarity between navigation sequences is measured by dynamic time warping method.Students' navigation patterns are found moderately associated with their reading performance.Girls are more likely to achieve higher reading scores than boys when longer navigation sequences with revisit patterns were used with shorter reading time.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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