LAUSR

This paper proposes the Digital Metacognitive Question–Answer Relationship (dmQAR) Framework, an adaptation of traditional QAR models for the complexities of digital reading environments. In response to the nonlinear, multimodal, and algorithmically curated nature of online texts, the dmQAR Framework scaffolds purposeful metacognitive questioning to support comprehension, evaluation, and critical engagement. Drawing on research in metacognition, critical literacy, and digital reading, the framework reinterprets “Right There,” “Think and Search,” “Author and Me,” and “On My Own” question categories to align with the demands of digital spaces. Practical instructional strategies, including think-alouds, student-generated questioning, digital annotation, and reflection journals, are detailed to support implementation across diverse educational contexts. The paper emphasizes that developing self-regulated questioning is essential for fostering critical literacy and resisting surface-level engagement with digital texts. Implications for instruction highlight the need for explicit metacognitive scaffolding and equitable access to digital literacy tools. Future research directions include empirical validation of the framework’s impact on digital reading comprehension and exploration of developmental differences in metacognitive questioning practices. In an era of widespread misinformation and algorithmic bias, embedding metacognitive questioning into literacy education is vital for preparing students to navigate digital landscapes critically and reflectively.