Teamwork Construction In E-Learning System: A Systematic Literature Review

With the increasing diversity of learners, forming suitable learning groups, in collaborative learning, represents a complex and a time-consuming task. Several researchers focus on the theory of teamwork organizations, based on academic performances, learning styles, learning settings, gender, etc. Therefore, grouping learners based on their predicted academic performance level in each subject separately may be more effective in a collaborative learning environment, but it still a challenging subject. First of all, we present in this paper a systematic literature review (SLR) to identify the relevant studies that address the problem of predicting academic performance and to extract the used data mining methods such as Decision Tree, Naive Bayes, Neural Network, Support Vector Machine, etc. At the beginning, a set of 658 papers were selected. After applying the different SLR's steps, this selection has been filtered to 12 papers using specific selection criteria and a careful analysis of each paper. Then, the selected studies were used to answer the defined research questions. Finally, synthesis data, current research gaps and recommendations for further work are discussed in this paper.