A Fuzzy Skill Predictor for Early Childhood Educators

  • Authors

    • Moses Adah Agana
    • Ruth Wario
    2018-09-07
    https://doi.org/10.14419/ijet.v7i3.19.16986
  • Fuzzy, Skill, Intelligence, Ability, Inference, Prediction

  • Abstract

    This study presents a model of a two-input single output (TISO) Fuzzy Skill Predictor based on Howard Gardner’s theory of multiple intelligences to assist early childhood educators in discovering latent skills in children of early school age as to tailor them towards professional skill development in their future lives. The skill prediction system was developed in two phases beginning with the generation of weighted fuzzy rules and then followed by the development of a fuzzy rule-based decision support system. The Mamdani Fuzzy inference model in MATLAB was used in implementing the system using weighted attributes of intelligence and ability to determine skills. The system was tested with hypothetical data based on Howard Gardner’s theory of multiple intelligence and was found useful for predicting skills based on the parameters used. The system was validated using early school academic records of 7 randomly sampled undergraduates studying various courses in the university. Though limited entries were used to test the system, the model is robust and can be easily modified to accommodate more entries and rules to predict as many skills as possible.

     

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  • How to Cite

    Adah Agana, M., & Wario, R. (2018). A Fuzzy Skill Predictor for Early Childhood Educators. International Journal of Engineering & Technology, 7(3.19), 49-58. https://doi.org/10.14419/ijet.v7i3.19.16986

    Received date: 2018-08-06

    Accepted date: 2018-08-06

    Published date: 2018-09-07