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Assessment of learning in environments interactive through fuzzy cognitive maps

Abstract

Fuzzy cognitive maps have been applied in different areas to express the dynamic behavior of a set of related concepts. These maps are powerful tools for analysis and generate simulations in dynamic systems. Nowadays, individuals use a lot of different technological media: smart TV, Internet, video games, mobile phones, etc. Some of these media present new ways to play, express, learn and communicate. The use of multimedia has become popular in the education field, these multimedia techniques can allow students to get more entertainment, immersion, and interactivity. An interactive learning environment can provide useful information to analyze the student learning process. Information such as: when the student initiates and completes a task, time between interactions, number of attempts, sequence of decisions taken, results related to the aggregate of the group, etc. This research work presents a learning assessment system that uses multivariate analysis based on structural equation modeling and fuzzy cognitive maps as a tool. The main aim of the proposed system is to facilitate assessment of learning on interactive environments. To validate the proposal, we have performed an empirical evaluation. As a part of the evaluation, we apply a sequence of scenarios to stimulate cognitive function of planning in a child population. In this evaluation, it was observed that most practical tasks obtain better results, confirming the Hebb rule on learning and cellular neurophysiological relationship.

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Correspondence to Rubén González Crespo.

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Communicated by V. Loia.

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Barón, H.B., Crespo, R.G., Pascual Espada, J. et al. Assessment of learning in environments interactive through fuzzy cognitive maps. Soft Comput 19, 1037–1050 (2015). https://doi.org/10.1007/s00500-014-1313-x

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  • DOI: https://doi.org/10.1007/s00500-014-1313-x

Keywords

  • Intelligent assessment system
  • Fuzzy cognitive map
  • Interactive learning environments
  • Game-based assessment