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An Intelligent Approach for the Effect of Social Media on Undergraduate Students Performance: A Case Study in the University of Jordan

Promoting the learning environment within Jordanian universities and maximizing the students' academic gain are essential national-level problems. Since learning and teaching systems are main building bricks to grow individuals who are responsible for developing and flourishing culture and civilization for Jordanian society. Educational data mining focuses on developing new smart algorithms devoted to analyzing the resulted data from educational systems; in order to better understand students and the learning environments. In this paper, we are analyzing major factors affecting university students' performance and the effect of social media usage on them. Furthermore, predicting the students' performance by adopting different rule-based data mining algorithms like rule learner based on Repeated Incremental Pruning to Produce Error Reduction (JRIP) and a type of decision tree called (PART). We have conducted a research survey within the University of Jordan students that is covering all faculties and cover a vast range of different students. Using both JRIP and PART we have concluded fundamental remarks; mainly, we have noticed that using YouTube as a learning resource has positive impacts on students' performance especially within scientific faculties. Moreover, we have interpreted the impact of other factors, such as having an Internet connection, having several social media applications and others. Certainly, upon our findings, we recommend the importance of integrating YouTube as a learning resource within universities learning environments.