Graphical Exploratory Analysis of Educational Knowledge Surveys with Missing and Conflictive Answers Using Evolutionary Techniques

  • Luciano Sánchez
  • Inés Couso
  • José Otero
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6077)


Analyzing the data that is collected in a knowledge survey serves the teacher for determining the student’s learning needs at the beginning of the course and for finding a relationship between these needs and the capacities acquired during the course. In this paper we propose using graphical exploratory analysis for projecting all the data in a map, where each student will be placed depending on his/her knowledge profile, allowing the teacher to identify groups with similar background problems, segment heterogeneous groups and perceive the evolution of the abilities acquired during the course.

The main innovation of our approach consists in regarding the answers of the tests as imprecise data. We will consider that either a missing or unknown answer, or a set of conflictive answers to a survey, is best represented by an interval or a fuzzy set. This representation causes that each individual in the map is no longer a point but a figure, whose shape and size determine the coherence of the answers and whose position with respect to its neighbors determine the similarities and differences between the students.


Knowledge Surveys Graphical Exploratory Analysis Multidimensional Scaling Fuzzy Fitness-based Genetic Algorithms 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Luciano Sánchez
    • 1
  • Inés Couso
    • 1
  • José Otero
    • 1
  1. 1.Computer Science and Statistics DepartmentsUniversidad de OviedoGijon(Spain)

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