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An Approach for Defining and Measuring Student’s Knowledge in Online Education Systems
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
2022 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The educational industry has evolved with the development of computer technology. The online education system (OES) provides a more effective and efficient educational strategy for students benefiting from computer science technologies. There is a need for a mapping of knowledge definition from the traditional education system to the data gathered from the non-traditional OES. This would make the measurement of knowledge possible for OES. The study aims to (a) find an appropriate knowledge definition through a literature review process, and (b) based on the definition measure students’ knowledge in OES, such as Hypocampus, by using machine learning techniques. Experiments were conducted using a well-known Bayesian KnowledgeTracing (BKT) model. The evaluation was performed on 3300 students studying medicine in France using Hypocampus OES. As a result, the student’s knowledge was measured in skills, performance, and achievement per subject with 81% average accuracy. The obtained results suggest the potential of the presented approach for measuring students’ knowledge in OES.

Place, publisher, year, edition, pages
2022.
Keywords [en]
knowledge definition, knowledge measurement, online education systems, Bayesian Knowledge Tracing, machine learning
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:lnu:diva-114313OAI: oai:DiVA.org:lnu-114313DiVA, id: diva2:1671569
External cooperation
Hypocampus
Subject / course
Computer Science
Educational program
Software Technology Programme, 180 credits
Supervisors
Examiners
Available from: 2022-06-17 Created: 2022-06-17 Last updated: 2022-06-17Bibliographically approved

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fulltext(1590 kB)100 downloads
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1de62f5c6a406c93acdb18ae66ebf6e5903c9f8554523ea8d8726413c92b6f868719352f45e3f91c7f3c48fef6acb36a83a33f0f7fe1ee538bf3eb5806d1e415
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Department of computer science and media technology (CM)
Computer Sciences

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf