مریم حق شناس

Although social softwares are interactive and communication tools that play an effective role in the field of learning and teaching, unfortunately, the interactive educational method using web2 tools is a new approach in Iran. In the other hand, the learning management system used by many virtual universities to improve the learning and learning process of students has some shortcomings and problems. According to research conducted by researchers, the combination of a learning management system and a social software in universities has reduced many of these constraints. The purpose of this research is to provide a model for utilizing social soft wares in a learning management system. In this regard, the research strategy is to provide a research model and validate it. This research is applied in terms of purpose, and in terms of information gathering, it is a descriptive survey. The data gathering tool was a researcher made questionnaire. Sampling method is targeted judgment. Therefore, by reviewing the literatures, first, the capabilities of various social softwares (wiki, blog, social networking, podcast and tag) were identified in the field of learning and education and a model for using these softwares in each module of the learning management system in order to overcome some of the problems caused by these systems in virtual universities were provided. Then, the proposed model was approved by a survey of 15 experts in the fields of e-learning and communications and media. Based on the findings of the analysis of the collected data, the use of various social softwares in the LMS modules was confirmed and ranked in importance.

Data mining as a science is a search process for finding new, valuable, and unknown information among a wealth of data. This approach is among the top 10 developing knowledge that will face the next decade with a technological revolution and has been expanding rapidly in recent years. The purpose of this research is to explore learners' behavior in interactive educational environments using data mining algorithms. Exploration and extraction of meaningful relationships among different factors with the help of data mining algorithms can be used to provide solutions to improve learners' performance. The research instrument was a questionnaire. The validity of the questionnaire was obtained through content analysis and its reliability was measured through re-testing. The data collection discussed in this study relates to the activities and interactions of 200 active students in a university social network. After gathering information about learners' interactions, the Apriori algorithm of data mining is used to analyze the behavior of learners through the use of rules. The main goal is to facilitate the education along with obtaining the proficiency of the courses. Improved interactive content is obtained from feedback information based on the data mining techniques of the data management system. Therefore, the results of this research can help educational system managers to plan their education and optimize educational processes in the interactive environment.