Motivating Factors and Potential Deterrents of Using Wikipedia in Teaching in Higher Education

Data mining techniques have been shown its success in analyzing data to assist factors and make decisions in many different applications. In this work, we analyzed universities' faculty members attitudes toward using Wikipedia in teaching in higher education. This may help in developing appropriate solutions to improve Wikipedia's effectiveness in education and provide the developers of Wikipedia with factors that may negatively impact using Wikipedia in teaching in higher education. Three different classification algorithms (Jrip Rule, Decision tree (J48) and Naïve Bayes) have been carried out in the free and open source software WEKA (Waikato Environment for Knowledge Analysis) on used dataset. The accuracy and Receiver Operating Characteristic curves for all classifiers discussed. Our results show that there are some factors influences the faculty using of Wikipedia in activity teaching which are unobserved in other studies.