T7. LANGUAGE, COMMUNICATION & GENERATIVE AI FOR LEARNING
SCOPE:
Explores how language and generative intelligence shape human–AI communication, educational discourse, and automated content creation. The track spans conversational learning interfaces, multimodal dialogue systems, and generative tools for assessment, authoring, and curriculum design.
A. DIALOGUE & COMMUNICATION IN LEARNING
Conversational intelligent tutoring systems; dialogue-based learning agents; AI generated tutoring systems; large language model (LLM) tutoring; discourse and argumentation analysis; multimodal conversation modeling; pragmatic and semantic adaptation; turn-taking and dialogue flow optimization; collaborative dialogue learning; peer–AI conversational scaffolding; empathy and politeness modeling; teacher–AI communication analytics; metadialogue and reflection support; discourse coherence evaluation; multimodal conversational grounding; cross-lingual dialogue adaptation; affect-aware conversational design; question–answer generation; error correction and clarification dialogue; discourse parsing and knowledge extraction; personalized conversational feedback.
FOCUS: understanding and designing dialogue systems that support learning interactions — from tutoring conversations to reflective, metacognitive communication between human and AI agents.
B. GENERATIVE CONTENT & ASSESSMENT
Automated question generation; test and rubric design using AI; generative curriculum authoring; learning objective alignment; AI-assisted educational material creation; large language model evaluation; content quality assurance; automatic feedback generation; open-ended response scoring; essay evaluation with explainability; code and problem generation for learning; multimodal content synthesis; image and text generation for instruction; AI co-authoring tools; adaptive assessment engines; content validation frameworks; bias detection in educational generation; human-in-the-loop content curation; instructional prompt engineering; generative explainability and transparency in education.
FOCUS: the creation, evaluation, and validation of generative AI content for education — from questions and rubrics to adaptive instructional materials and assessments.