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Multiple criteria performance evaluation of YouTube mathematical educational videos by IS-TOPSIS

Author

Listed:
  • Claudia Margarita Acuña-Soto

    (CINVESTAV - Instituto Politécnico Nacional)

  • Vicente Liern

    (Universidad de Valencia)

  • Blanca Pérez-Gladish

    (Universidad de Oviedo)

Abstract

In this work, a TOPSIS-based approach is proposed based on the idea of ideal similarity. It considers the ideal solution not necessarily related to the optimum values of the decision criteria, but to any values between the minimum and maximum values of the criteria ranges. The proposed method allows the consideration of one or several decision makers; different types of data (single numerical values, intervals or linguistic variables); different normalization functions describing the importance given by the decision makers to the deviation of alternatives from the ideal solution and different weighting schemes. The procedure also allows the decision maker to decide how much information about the intervals he is willing to take into account (e.g. the expected value, the extremes of the interval or the entire set of values in the intervals). In order to illustrate the practical applicability of the approach we include a real example consisting of the ranking of mathematical educational videos based on six didactical dimensions. The rating of educational videos is of great interest for educators due to their high popularity in Internet, especially in platforms as You Tube which has become one of the most used sources of information nowadays.

Suggested Citation

  • Claudia Margarita Acuña-Soto & Vicente Liern & Blanca Pérez-Gladish, 2020. "Multiple criteria performance evaluation of YouTube mathematical educational videos by IS-TOPSIS," Operational Research, Springer, vol. 20(4), pages 2017-2039, December.
    • Handle: RePEc:spr:operea:v:20:y:2020:i:4:d:10.1007_s12351-018-0405-2
    DOI: 10.1007/s12351-018-0405-2
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    References listed on IDEAS

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    Cited by:

    1. Olga Blasco-Blasco & Marina Liern-García & Aarón López-García & Sandra E. Parada-Rico, 2021. "An Academic Performance Indicator Using Flexible Multi-Criteria Methods," Mathematics, MDPI, vol. 9(19), pages 1-19, September.
    2. Andréia C. Müller & Jaime Gil-Lafuente & Joan Carles Ferrer-Comalat, 2024. "Colour Choice as a Strategic Instrument in Neuromarketing," Mathematics, MDPI, vol. 12(14), pages 1-20, July.

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