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Educational Data Mining for Problem Identification

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Frontier and Future Development of Information Technology in Medicine and Education

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 269))

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Abstract

Students face a number of difficulties studying mathematics on all educational levels. Data mining techniques applied on educational data can allow better understanding of the large amount of challenges students meet taking mathematical courses. Many researches focus on investigating various factors causing exam failure or even drop out. They often refer to study anxiety as being one of the serious reasons for students failure in mathematics. We believe that application of methods from market basket analysis can assist for identifying students, experiencing significant difficulties in their studies.

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Author information

Authors and Affiliations

  1. Stord/Haugesund University College, Bjørnsong 45, 5528, Haugesund, Norway

    Sylvia Encheva

Authors
  1. Sylvia Encheva
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Correspondence to Sylvia Encheva .

Editor information

Editors and Affiliations

  1. Cognitive Science, Xiamen University, Xiamen, People's Republic of China

    Shaozi Li

  2. Human Informatics and Cognitive Sciences, Waseda University Networked Information Systems Lab, Waseda, Japan

    Qun Jin

  3. School of Systems Information Science, Future University Hakodate, Hakodate, Hokkaido, Japan

    Xiaohong Jiang

  4. Department of Computer Science and Engineering, Seoul University of Science & and Technology (SeoulTech), Seoul, Korea, Republic of (South Korea)

    James J. (Jong Hyuk) Park

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© 2014 Springer Science+Business Media Dordrecht

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Encheva, S. (2014). Educational Data Mining for Problem Identification. In: Li, S., Jin, Q., Jiang, X., Park, J. (eds) Frontier and Future Development of Information Technology in Medicine and Education. Lecture Notes in Electrical Engineering, vol 269. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7618-0_455

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  • DOI: https://doi.org/10.1007/978-94-007-7618-0_455

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-7617-3

  • Online ISBN: 978-94-007-7618-0

  • eBook Packages: EngineeringEngineering (R0)

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