This module introduces language educators to the foundational concepts, historical evolution, and technical architectures of Generative AI. It explores the data-training-inference lifecycle, common sources of bias, and emphasizes the critical necessity of human-in-the-loop oversight in education.
2. Ethical Dimensions of AI in Language Education
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This module examines the ethical, regulatory, and socio-technical implications of GenAI, guided by frameworks like the EU AI Act and GDPR. Participants will critically analyze macro-level harms such as data colonialism and environmental impacts, while developing micro-level strategies to foster critical AI literacy and prevent classroom misuse.
3. Pedagogically Aligned GenAI Use in Language Teaching
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This module equips teachers to select and integrate GenAI tools purposefully, ensuring alignment with specific language learning outcomes and learner needs. Through frameworks like TPACK and constructive alignment, educators learn to design ethical prompts, manage pedagogical risks, and facilitate safe, meaningful learner-AI interactions.
4. GenAI-Enhanced Lesson Design and Materials Development
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Educators learn to transition from basic AI usage to advanced, pedagogically aligned lesson and material co-creation using the Before-With-After framework. The module emphasizes rigorous prompt engineering, material verification against hallucinations, and maintaining human pedagogical agency to prevent student cognitive offloading.
5. Evaluating, Reflecting, and Growing with GenAI in Teaching
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As a capstone experience, this module guides participants in critically evaluating GenAI tools and reflecting on their evolving professional competencies. Educators will build a personalized Continuous Professional Development (CPD) roadmap and an integration plan to sustainably apply these AI resources in their teaching practice.
Comprehension Check: Mapping AI Social Biases to Classroom Realities
