["TESOL Quarterly, EarlyView. ", "\nAbstract\nThe rapidly evolving use of GenAI leads to a crucial need for new approaches to instruction and assessment of language skills in DMC tasks. The study adopted a convergent mixed‐methods design within an 11‐week action research framework. The study was conducted with 12 Turkish tertiary‐level L2 learners based on a process‐genre pedagogy to design and test a novel assessment framework. The learners engaged in L2 instruction that integrates co‐authoring with GenAI for brainstorming and idea generation, using GenAI tools for L2 DMC tasks, such as authentic tasks (infographics, digital posters), multimodal essays, and social media posts. Data from needs analysis, learner reflections, peer/self‐assessments, and subject‐matter expert reviews were triangulated to propose a formative assessment framework that consists of a criterion‐referenced analytical rubric, multimodal checklists. This research proposed a novel assessment and feedback framework with three key components: (1) a criterion‐referenced analytic rubric for assessing GenAI integration on textual, visual, and auditory DMC elements, (2) multimodal alignment checklists for peer and self‐assessment, and (3) a formative assessment system for monitoring and reflecting on learning progress. The framework is proposed to guide language educators and learners to improve critical AI literacy, learner agency, and authentic language practice through GenAI‐assisted DMC tasks.\n"]