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Online Students’ Classification Based on the Formal Concepts Analysis and Multiple Choice Questions

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Business Intelligence (CBI 2021)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 416))

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Abstract

Students orientation in the university is an important research area. Actually, students fill out their choice manually except some specialties in which there is a preselection. These procedures are very classics, they based on the student’s marks to calculate a general average that puts the student above or below a selection bar. Several problems arise from these procedures, the major problem is that a majority of students are misguided. As the solution of this problem, we purpose, in this paper, a new approach for automatic student’s orientation witch incorporate the Formal Concept Analysis (FCA) techniques. On one hand, we have students as objects and the online proposed questions are the attributes, on the other hand we have the specialties as objects and the questions as attributes. These objects and attributes help us to build a Concept Lattice Student (CLS) and Concept Lattice Specialty (CLSp). Then after we introduce two algorithms that explore the two concepts lattices and extract the pair (student, specialty) which is our classification result.

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Authors and Affiliations

  1. TIAD Laboratory, Department of Computer Sciences, Faculty of Sciences and Techniques, Sultan Moulay Slimane University, Beni Mellal, Morocco

    Moulay Amzil & Ahmed El Ghazi

Authors
  1. Moulay Amzil
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  2. Ahmed El Ghazi
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Correspondence to Moulay Amzil .

Editor information

Editors and Affiliations

  1. Université Sultan Moulay Slimane, Beni-Mellal, Morocco

    Mohamed Fakir

  2. Université Sultan Moulay Slimane, Beni-Mellal, Morocco

    Mohamed Baslam

  3. Université Sultan Moulay Slimane, Beni-Mellal, Morocco

    Rachid El Ayachi

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Amzil, M., El Ghazi, A. (2021). Online Students’ Classification Based on the Formal Concepts Analysis and Multiple Choice Questions. In: Fakir, M., Baslam, M., El Ayachi, R. (eds) Business Intelligence. CBI 2021. Lecture Notes in Business Information Processing, vol 416. Springer, Cham. https://doi.org/10.1007/978-3-030-76508-8_10

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  • DOI: https://doi.org/10.1007/978-3-030-76508-8_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-76507-1

  • Online ISBN: 978-3-030-76508-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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