Adaptable and non-adaptable gamified e-learning model using chatbots

DOI

10.2991/978-94-6463-360-3_24How to use a DOI?

Keywords

e-Learning; Gamification; Chatbots

Abstract

Is true that human interaction can play a significant role in learning process. The lack of these interactions can lead to feelings of isolation and disengagement among learners. Several researchers have proposed gamified e-learning model as an effective way to increase learners’ motivation by providing them with autonomy, relatedness, and competence. Basing on literature we can divide gamification models into two categories: adaptable models and non-adaptable models.

In order to help designers of gamified e-learning systems and teachers to choose the right games element to display, we propose a new model that incorporates game elements using the two models mentioned above. This model aims to address the limitations of traditional e-learning platforms by providing a more engaging and personalized learning experience for learners.

Our proposed system is based on the interaction between three main actors: the System, the Teacher, and the Learner. These actors are interconnected and can interact with each other in various ways to create an engaging and personalized learning experience. They can interact via the application settings or via direct communication or chatbot communication. In this way, our proposed system is designed to foster interactions between the three actors, to create a personalized, engaging and dynamic learning experience. The system continuously monitors and adapts to the learners’ needs, while the teacher provides guidance and support, and the learner actively participates in the learning process.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Zecri Ezzoubair
AU  - El Haddioui Ismail
AU  - Ouzzif Mohammed
AU  - Souali Kamal
PY  - 2024
DA  - 2024/02/05
TI  - Adaptable and non-adaptable gamified e-learning model using chatbots
BT  - Proceedings of the E-Learning and Smart Engineering Systems (ELSES 2023)
PB  - Atlantis Press
SP  - 224
EP  - 231
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-360-3_24
DO  - 10.2991/978-94-6463-360-3_24
ID  - Ezzoubair2024
ER  -