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

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.

• Publication year

  2019

• Venue

  International Conference on Advanced Learning Technologies

• Publication date

  2019-07-01

• Fields of study

  Computer Science, Education

• Identifiers
  DOI 10.1109/ICALT.2019.00116
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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