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Dynamic Group Formation with Intelligent Tutor Collaborative Learning: A Novel Approach for Next Generation Collaboration

Lookup NU author(s): Dr Husnain SheraziORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2013 IEEE. Group Formation (GF) strongly influences the collaborative learning process in Computer-Supported Collaborative Learning (CSCL). Various factors affect GF that include personal characteristics, social, cultural, psychological, and cognitive diversity. Although different group formation methods aim to solve the group compatibility problem, an optimal solution for dynamic group formation is still not addressed. In addition, the research lacks to supplement collaborative group formation with a collaborative platform. In this study, the next level of collaboration in CSCL and Intelligent Tutoring System (ITS) platforms is achieved. First, initial groups are formed based on students learning styles, and knowledge level, i.e. for knowledge level, an activity-based dynamic group formation technique is proposed. In this activity, swapping of students takes place on each permutation based on their knowledge level. Second, the formed heterogeneous balanced groups are used to augment the collaborative learning system. For this purpose, a hybrid framework of Intelligent Tutor Collaborative Learning (ITSCL) is used that provides a unique and real-time collaborative learning platform. Third, an experiment is conducted to evaluate the significance of the proposed study. Inferential and descriptive statistics of Paired T-Tests are applied for comprehensive analysis of recorded observations. The statistical results show that the proposed ITSCL framework positively impacts student learning and results in higher learning gains.


Publication metadata

Author(s): Haq IU, Anwar A, Rehman IU, Asif W, Sobnath D, Sherazi HHR, Nasralla MM

Publication type: Article

Publication status: Published

Journal: IEEE Access

Year: 2021

Volume: 9

Pages: 143406-143422

Online publication date: 15/10/2021

Acceptance date: 10/10/2021

Date deposited: 24/05/2024

ISSN (electronic): 2169-3536

Publisher: IEEE

URL: https://doi.org/10.1109/ACCESS.2021.3120557

DOI: 10.1109/ACCESS.2021.3120557


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