Analysis of questionnaires for Virtual Learning Environments based on Item Response Theory | Zendy

Óscar Romero | Zendy; Guilherme Medeiros Machado | Zendy; Leandro Krug Wives | Zendy

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Analysis of questionnaires for Virtual Learning Environments based on Item Response Theory

Author(s) -

Óscar Romero,

Guilherme Medeiros Machado,

Leandro Krug Wives

Publication year - 2019

Publication title -

anais do xxx simpósio brasileiro de informática na educação (sbie 2019)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.5753/cbie.sbie.2019.509

Subject(s) - item response theory , ranking (information retrieval) , categorization , computer science , tutor , context (archaeology) , machine learning , human–computer interaction , information retrieval , artificial intelligence , mathematics , statistics , psychometrics , paleontology , biology , programming language

This paper presents a model for the design and creation of virtual adaptive evaluations for e-learning environments, combining Item Response Theory (IRT) along with log analysis of previous questionnaires. The proposed model allows the definition of a methodology for the ranking and categorization of questions. Such ranking provides valuable feedback to the teacher or tutor who can refine and adapt the questionnaire. Experiment results reveal that IRT parameters are sufficient for ranking and selecting questions that are more appropriate to teach specific topics. We believe that this approach should become an essential tool for the creation of questionnaires that are more concise and effective in the context of virtual courses.

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