Speaker
Description
Task-Based Language Teaching (TBLT) represents a cornerstone in the realm of second language (L2) pedagogy, extensively studied and employed by educators worldwide. Central to TBLT is the utilization of tasks as a fundamental unit for various pedagogical processes, including needs analysis, material design, activity organization, and performance evaluation in real-world contexts. However, despite its effectiveness, each stage of TBLT implementation is marked by considerable time and labor investments.
This presentation delves into an innovative experiment aimed at leveraging the power of generative artificial intelligence (GenAI) tools to streamline and enhance TBLT practices. By harnessing GenAI, educators can revolutionize the efficiency of TBLT implementation across its key stages. Specifically, GenAI facilitates swift and accurate needs assessment, automates the generation of diverse and contextually relevant tasks, aids in the creation of engaging learning activities, and simplifies the development of comprehensive assessment templates.
Through showcasing tangible examples and practical demonstrations, this presentation offers language educators invaluable insights into how GenAI can be seamlessly integrated into TBLT methodologies, amplifying teaching effectiveness and optimizing resource utilization. By embracing GenAI-enabled TBLT approaches, educators can unlock new possibilities for enhancing language learning outcomes and student engagement in diverse educational settings
