Fuzzy Logic Based Prospects Identification System for Foreign Language Learning Through Serious Games

• Main Authors: Nacim Yanes, Ikram Bououd, Saad Awadh Alanazi, Fahad Ahmad
• Format: Article
• Language: English
• Published: IEEE 2021-01-01
• Series: IEEE Access
• Subjects: Serious games; Foreign language learning; Delphi; investigative study; fuzzy logic; neural networks
• Online Access: https://ieeexplore.ieee.org/document/9409040/

Interest in serious games for education has grown during the last years. The credit goes to the potential for engaging students with new ways to capture and maintain attention. The goal of this paper is to introduce a new multidisciplinary approach that incorporates psychological analysis theory with fuzzy inference and neural networks in the Foreign Language Learning prospects identification through serious games. Our research first used a Delphi method to accumulate Information Systems students’ opinions resulting from a SWOT analysis of the use of serious games to learn English language. Then, we designed a Fuzzy Logic based Foreign Language Learning Prospects Identification System through serious games that takes four standard input parameters (Strengths, Weaknesses, Opportunities, Threats) already identified during our SWOT analysis and predicts the output (Learning Prospects of Foreign Language) by considering impact of certain variations in input parameters. Implementation results have been obtained through (MATLAB R2020a) and have shown reliable incites and findings.