Web application for the analysis of assessment tests


  • Paula Prata Instituto de Telecomunicações; Departamento de Informática, Universidade da Beira Interior, Covilhã, Portugal
  • Luís Duarte Departamento de Informática, Universidade da Beira Interior, Covilhã, Portugal
  • Maria Eugénia Ferrão Universidade da Beira Interior, CEMAPRE - Centro de Matemática Aplicada à Previsão e Decisão Económica e Departamento de Matemática, Covilhã, Portugal




Classical test theory, E-assessment;, Data analysis


Introduction: An assessment test enables the evaluation of an individual’s competence or ability. Such tests are important for both teaching and professional training institutions, as well as for the recruiting of human resources in the enterprise.

Objectives: The present paper introduces the “Evaluate” web application, for the analysis of assessment tests.

Methods: The design and implementation of the application is described, which allows the management of assessment items, used to constitute evaluation tests, upon which results the main descriptive statistic values used under the classical test theory in the analysis of assessment tests are calculated. The application was developed in Python, within the Django framework, and tested with real assessment tests.

Results: Scores are assigned to each assessment item, and various statistics — such as difficulty and discrimination index, point-biserial correlation, test internal consistency coefficient — can be obtained upon the answers of the subjects, as well as a graphic analysis of the performance of each subject on each assessment item, as well as on the test as a whole.

Conclusions: The “Evaluate” application makes a meaningful contribution to a better knowledge of assessment tools used in competence evaluation, by allowing the detection of inconsistencies and the consequent improvement in the process.


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How to Cite

Prata, P., Duarte, L., & Ferrão, M. E. (2018). Web application for the analysis of assessment tests. Millenium - Journal of Education, Technologies, and Health, 2(7), 91–101. https://doi.org/10.29352/mill0207.08.00176



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