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Elo-Rating Method: Towards Adaptive Assessment in E-Learning

Mangaroska, Katerina; Vesin, Boban; Giannakos, Michail
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Mangaroska (424.9Kb)
URI
http://hdl.handle.net/11250/2635519
Date
2019
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  • Institutt for datateknologi og informatikk [6337]
  • Publikasjoner fra CRIStin - NTNU [35008]
Original version
10.1109/ICALT.2019.00116
Abstract
The success of technology enhanced learning can be increased by tailoring the content and the learning resources for every student; thus, optimizing the learning process. This study proposes a method for evaluating content difficulty and knowledge proficiency of users based on modified Elo-rating algorithm. The calculated ratings are used further in the teaching process as a recommendation of coding exercises that try to match the user's current knowledge. The proposed method was tested with a programming tutoring system in object-oriented programming course. The results showed positive findings regarding the effectiveness of the implemented Elo-rating algorithm in recommending coding exercises, as a proof-of-concept for developing adaptive and automatic assessment of programming assignments.
Publisher
Institute of Electrical and Electronics Engineers (IEEE)

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