Current Volume 6
This mixed-method research utilizing descriptive-developmental design is about designing and evaluating Personalize Learning Management System Platform using Artificial Intelligence Rule-Based Techique employsan incremental prototyping model in thedevelopment. Consultative meetings,interview and the used of survey questionaires were held to obtain data from 10 information technology experts as the alpha evaluators and 10 teachers who is practicing ICT education as the beta evaluators chosen using purposive sampling. Results show that personalize learning management system is excellent in terms of functional suitability (M=4.70), performance efficiency (M=4.80), compatibility (M=4.85), usability (M=4.80), reliability (M=4.80), security (M=4.71), maintainability (M=4.69), portability (M=4.76) recording a grand mean of 4.76 interpreted as excellent. This means that the system satisfies both software quality standards and end-user requirements. Thus, it is ready for adoption. Along with its implementation, it is recommended to gather feedback regularly conduct and conduct an impact analysis of the effectiveness of using the personalize learning management system platform using artificial intelligence rule-based technique.
Prototyping model, LMS, Artificial Intelligence, Rule-based technidue, Philippines, Platform
Anthony U. Concepcion , Joseph D. Espino "Personalize Learning Management System Platform Using Artificial Intelligence Rule-Based Technique" Iconic Research And Engineering Journals Volume 6 Issue 11 2023 Page 108-115
Anthony U. Concepcion , Joseph D. Espino "Personalize Learning Management System Platform Using Artificial Intelligence Rule-Based Technique" Iconic Research And Engineering Journals, 6(11)