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Digital Psychological Platform for Mass Web-Surveys

Author

Listed:
  • Evgeny Nikulchev

    (Department of Intelligent information security systems, MIREA—Russian Technological University, 119454 Moscow, Russia)

  • Dmitry Ilin

    (Department of Intelligent information security systems, MIREA—Russian Technological University, 119454 Moscow, Russia
    Center for Interdisciplinary research in education, Russian Academy of Education, 119121 Moscow, Russia)

  • Anastasiya Silaeva

    (Department of Intelligent information security systems, MIREA—Russian Technological University, 119454 Moscow, Russia
    Center for Interdisciplinary research in education, Russian Academy of Education, 119121 Moscow, Russia)

  • Pavel Kolyasnikov

    (Center for Interdisciplinary research in education, Russian Academy of Education, 119121 Moscow, Russia)

  • Vladimir Belov

    (Department of Intelligent information security systems, MIREA—Russian Technological University, 119454 Moscow, Russia
    Center for Interdisciplinary research in education, Russian Academy of Education, 119121 Moscow, Russia)

  • Andrey Runtov

    (Center for Interdisciplinary research in education, Russian Academy of Education, 119121 Moscow, Russia)

  • Pavel Pushkin

    (Department of Intelligent information security systems, MIREA—Russian Technological University, 119454 Moscow, Russia)

  • Nikolay Laptev

    (Center for Interdisciplinary research in education, Russian Academy of Education, 119121 Moscow, Russia)

  • Anna Alexeenko

    (Department of Intelligent information security systems, MIREA—Russian Technological University, 119454 Moscow, Russia)

  • Shamil Magomedov

    (Department of Intelligent information security systems, MIREA—Russian Technological University, 119454 Moscow, Russia)

  • Alexander Kosenkov

    (Department of Hospital Surgery, Sechenov Moscow State Medical University, 119992 Moscow, Russia)

  • Ilya Zakharov

    (Center for Interdisciplinary research in education, Russian Academy of Education, 119121 Moscow, Russia
    Psychological Institute of Russian Academy of Education, 125009 Moscow, Russia)

  • Victoria Ismatullina

    (Center for Interdisciplinary research in education, Russian Academy of Education, 119121 Moscow, Russia
    Psychological Institute of Russian Academy of Education, 125009 Moscow, Russia)

  • Sergey Malykh

    (Center for Interdisciplinary research in education, Russian Academy of Education, 119121 Moscow, Russia
    Psychological Institute of Russian Academy of Education, 125009 Moscow, Russia)

Abstract

Web-surveys are one of the most popular forms of primary data collection used for various researches. However, mass surveys involve some challenges. It is required to consider different platforms and browsers, as well as different data transfer rates using connections in different regions of the country. Ensuring guaranteed data delivery in these conditions should determine the right choice of technologies for implementing web-surveys. The paper describes the solution to transfer a questionnaire to the client side in the form of an archive. This technological solution ensures independence from the data transfer rate and the stability of the communication connection with significant survey filling time. The conducted survey benefited the service of education psychologists under the federal Ministry of Education. School psychologists consciously took part in the survey, realizing the importance of their opinion for organizing and improving their professional activities. The desire to answer open-ended questions in detail created a part of the answers in the dataset, where there were several sentences about different aspects of professional activity. An important challenge of the problem is the Russian language, for which there are not as many tools as for the languages more widespread in the world. The survey involved 20,443 school psychologists from all regions of the Russian Federation, both from urban and rural areas. The answers did not contain spam, runaround answers, and so on as evidenced by the average response time. For the surveys, an authoring development tool DigitalPsyTools.ru was used.

Suggested Citation

  • Evgeny Nikulchev & Dmitry Ilin & Anastasiya Silaeva & Pavel Kolyasnikov & Vladimir Belov & Andrey Runtov & Pavel Pushkin & Nikolay Laptev & Anna Alexeenko & Shamil Magomedov & Alexander Kosenkov & Ily, 2020. "Digital Psychological Platform for Mass Web-Surveys," Data, MDPI, vol. 5(4), pages 1-16, October.
    • Handle: RePEc:gam:jdataj:v:5:y:2020:i:4:p:95-:d:423950
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    References listed on IDEAS

    as
    1. Andra-Selina Pietsch & Stefan Lessmann, 2018. "Topic modeling for analyzing open-ended survey responses," Journal of Business Analytics, Taylor & Francis Journals, vol. 1(2), pages 93-116, July.
    2. Pietsch, Andra-Selina & Lessmann, Stefan, 2018. "Topic Modeling for Analyzing Open-Ended Survey Responses," IRTG 1792 Discussion Papers 2018-054, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    Full references (including those not matched with items on IDEAS)

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