{'fraction_non_alphanumeric': 0.017225747960108794, 'fraction_numerical': 0.0, 'mean_word_length': 5.167597765363128, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Using Instructive Data Mining Methods to Revise the Impact of Virtual Classroom in E-Learning

In the past few years, Saudi universities have boarded to utilize e-learning tools and technologies to expand and look up their educational services. After a few years of carrying out e-learning programs, a discussion took place within the directors, supervisors, executives and managers or decision makers of the e-learning associations regarding which activities are the most impact on the learning development for online students. This research is expected to inspect the impact of a number of e-learning actions on the students’ learning development. The results show that involvement in virtual classroom sessions has the most considerable impact on the students’ final scoring or grade. This paper presents the procedure of applying data mining methods to the web observing records of students’ behaviors in a practical learning environment. The main idea is to rank the learning activities supported on their importance in order to develop students’ performance by focusing on the most important ones.