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Visualization of Student-Item Interaction Matrix

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F21%3A00123675" target="_blank" >RIV/00216224:14330/21:00123675 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/chapter/10.1007/978-3-030-81222-5_20" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-81222-5_20</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-030-81222-5_20" target="_blank" >10.1007/978-3-030-81222-5_20</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Visualization of Student-Item Interaction Matrix

  • Original language description

    One type of visualization of data from digital learning environments focuses on students’ interaction with the educational content. Students may, for example, answer questions, read texts, or solve problems. We can represent these interactions as a matrix, where rows correspond to students, columns to educational items, and values to some aspect of student activity (e.g., the correctness of answers, response times, the order of actions). Visualizing this matrix is useful for several purposes. For teachers, it can provide an understanding of the skill and behavior of their students. For system developers, it can provide insight into the behavior of both students and adaptive algorithms, and it can also help detect suspicious activity. For researchers, it can provide an understanding of the properties of datasets used in experiments and valuable warnings about biases that are present in data. However, suitable visualization of the student-item interactions is nontrivial. To facilitate the design of the visualization, we provide a systematic discussion of approaches to student-item matrix visualization. Using data from an introductory programming exercise, we also provide specific illustrations of different visualization designs.

  • Czech name

  • Czech description

Classification

  • Type

    C - Chapter in a specialist book

  • 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

    S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2021

  • Confidentiality

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

Data specific for result type

  • Book/collection name

    Visualizations and Dashboards for Learning Analytics

  • ISBN

    9783030812218

  • Number of pages of the result

    18

  • Pages from-to

    439-456

  • Number of pages of the book

    611

  • Publisher name

    Springer

  • Place of publication

    Cham

  • UT code for WoS chapter