Research Article
Dynamic Difficulty Adjustment through a Learning Analytics Model in a Casual Serious Game for Computer Programming Learning
@ARTICLE{10.4108/eai.27-12-2017.153509, author={Adilson Vahldick and Antonio Jose Mendes and Maria Jose Marcelino}, title={Dynamic Difficulty Adjustment through a Learning Analytics Model in a Casual Serious Game for Computer Programming Learning}, journal={EAI Endorsed Transactions on Serious Games}, volume={4}, number={13}, publisher={EAI}, journal_a={SG}, year={2017}, month={12}, keywords={Novice programmers, learning analytics, dynamic difficulty adjustment, fuzzy systems.}, doi={10.4108/eai.27-12-2017.153509} }- Adilson Vahldick
Antonio Jose Mendes
Maria Jose Marcelino
Year: 2017
Dynamic Difficulty Adjustment through a Learning Analytics Model in a Casual Serious Game for Computer Programming Learning
SG
EAI
DOI: 10.4108/eai.27-12-2017.153509
Abstract
Teachers have used games as a support tool to engage students in learning tasks. As they often record student’s performance as learning progresses, it is interesting and useful to discuss how that information can be used to assess learning and to improve the learning experience. For instance, teachers can use that information to give personalized attention in classes and the game can use it to provide challenges of the “right” difficulty. In computer programming learning, games can provide an alternative way to introduce concepts and, mainly, to practice them. This paper proposes a model to identify the students’ progress considering their performance in programming tasks. The model is demonstrated by an implementation in a casual computer programming serious game. We illustrate how this game could use this model to personalize its challenges.
Copyright © 2017 Adilson Vahldick et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.