Collaborative Optimization of Learning Team Formation Based on Multidimensional Characteristics and Constraints Modeling: A Team Leader-Centered Approach via E-CARGO

Abstract

With the massive popularization of e-learning, collaborative learning via learning teams has become indispensable to enhancing the learning efficiency and learning quality of overall learners. The team leader usually plays a key role in collaborative learning. However, the existing research ignores the key characteristics of learners and constraints relevant to e-learners when identifying appropriate team leaders and compatible members. A novel collaborative optimization approach to learning team formation is proposed based on a refined learner model and the environments—classes, agents, roles, groups, and objects (E-CARGO) model. With the proposed approach, a learner is modeled by combining 5-D characteristics (i.e., cognitive ability, leadership, sociability, learning style, and personality) and three types of constraints (e.g., conflicts, genders, and the number of members), and an assessment mechanism is designed to measure the comprehensive abilities of learners for identifying an ideal team leader and selecting the team members for a team. By innovatively introducing the role-based collaboration theory and E-CARGO model, the leader-centered learning team formation problem is formalized as a collaborative optimization problem. The mathematical model and the constraint relations are established for this problem, which is solved based on the IBM CPLEX package. Finally, a case study and experiments demonstrate that the proposed approach is efficient and feasible, in favor of improving the satisfaction degree of learners.