The Use of Cooperative Learning’s Round Robin for the Implementation of Deep Learning to Enhance Students’ Speaking Skill

Abstract

Although speaking fluency is widely recognized as a central and highly observable dimension of communicative competence, it continues to pose significant challenges for learners to master. These challenges are largely attributed to limited exposure to authentic language input and a lack of confidence among students. Many learners struggle to find opportunities for real-time communication, which is essential for developing fluency. Without sufficient practice in realistic settings, they may find it difficult to transfer passive knowledge into active speech. Round Robin, a cooperative learning technique, which encourages meaningful interaction and active student participation, presents a supportive platform for learners to articulate their thoughts and practice English in a low-anxiety setting. This model also encourages peer-to-peer learning, allowing students to benefit from each other’s strengths and perspectives. This pedagogical approach aligns closely with the principles of Deep Learning, which prioritizes higher-order cognitive processes such as analysis, evaluation, and creation, which are core components of sustained and deep intellectual engagement. This conceptual article investigates the impact of integrating Cooperative Learning through the Round Robin strategy within Deep Learning framework on the enhancement of English- speaking proficiency, particularly in English as a Foreign Language (EFL) contexts. The article proposes a theoretical lens for understanding how such integration may support the development of communicative competence in EFL classroom.