Efficiency Algorithm: A New AI-Based Tools for Adaptive Learning Environments

Arwa Hasan Zabian^*

• Jadara University Faculty of Science and Information Technology, Irbid, Jordan

The learning process is characterized by its variability rather than linearity. As individuals differ in how they receive, process, and store information. In traditional learning, taking into consideration the individual differences between students can be difficult, in consequence many talented students may fail because their learning speed is not aligned with the assessment requirements. Objectives: In this paper, we propose efficiency algorithm that is a new assessment method for adaptive learning that is based on artificial intelligence to evaluate the differences in learning speed between students and attempt from us to have competent graduates in their discipline. Methods: Our assessment method is based on how effectively the students apply the knowledge they have acquired to complete tasks. Using four important parameters that always answer the question of how the student completes the job not on its completeness or not. These parameters are information search, information evaluation, information processing, and information communication that constitute the basic components of our efficiency algorithm. Key findings: Our results show that using Naïve Bayes Algorithm we can determine with high accuracy (93 %) in which part of the learning process (information search, evaluation, processing or communication) the student encounter difficulties. Contribution: our proposed approach helps in designing personalized learning plans that directly target individual weaknesses.