Perceived Internet Usage Behaviours as Predictor to Outlier Detection in Students’ Communities in Academic Environments

Abstract

It is important to provide perspectives about the effects of Internet usage on students' personal and social behaviours along with the impacts of these usages on their academic performances. To explore students' Internet usage behaviors and predicting outliers in student's community, we have developed Web based data mining tool named Education Data Miner (EDMiner), which provides user friendly interface for different stockholders of the system including professors and deans. This research study was conducted with a sample of 5210 students from one engineering college in India during 36 months continually. The primary focus of this study is to extract Internet usage pattern of students by exploring proxy server access log files. These patterns were then used for identifying outliers in students' community. We have applied centroid and density based clustering methods to identify outliers. Further, the relationship between Internet usage behaviours and various Academic and Non-academic activities were explored. Based on our results the majority of visited Websites, 35 percent, belongs to Websites under Extra-Curricular category whereas for curricular Websites it is 24 percent. Further, our results also contradict the perception that the Internet usage adversary affects the academic performance. Moreover, our analysis results show higher average time spent on Internet did result into nonparticipation in other activities, which are very essential for the growth of these students. This nonparticipation in other activities may prove to be an indicator for loneliness of these individuals.