Title: Automatic exercise sequencing-based algorithmic skills

Authors: Meriem Abdessemed; Tahar Bensebaa; Takie Eddine Belhaoues; Anis Bey

Addresses: Computer Science Department, Laboratory of Research in Computer Science (LRI), Badji Mokhtar Annaba University, Annaba, Algeria ' Computer Science Department, Laboratory of Research in Computer Science (LRI), Badji Mokhtar Annaba University, Annaba, Algeria ' Computer Science Department, Laboratory of Research in Computer Science (LRI), Badji Mokhtar Annaba University, Annaba, Algeria ' Computer Science Department, Laboratory of Research in Computer Science (LRI), Badji Mokhtar Annaba University, Annaba, Algeria; Ecole Supérieure des Sciences de Gestion (ESSG), Annaba, Algeria

Abstract: In any learning systems and especially automated assessment tools, the most common task is to evaluate the students' performance using training exercise. The selection of the next exercise is generally performed as a static set of exercises or free by students. But, it would clearly be advantageous if this exercise selection process were to be automated based on their previous performances. Therefore, the focus of this paper is the development of a method capable of determining exercise progression and sequencing during a training session based on the students' past performance. A dynamic planning of algorithmic exercises was developed based on a semantic and pedagogical description to be used in training exercise.

Keywords: sequencing; algorithmic; assessment; learning programming; exercises.

DOI: 10.1504/IJIL.2018.088788

International Journal of Innovation and Learning, 2018 Vol.23 No.1, pp.104 - 121

Received: 01 Aug 2016
Accepted: 04 Feb 2017
Published online: 19 Dec 2017 *

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