Reading comprehension is widely recognized as a complex cognitive and metacognitive process through which learners construct meaning from written language. Traditionally, this process relies heavily on an active interaction between working memory, prior knowledge, and internal structural mapping. However, the rapid proliferation of Artificial Intelligence (AI) and Large Language Models (LLMs) between 2020 and 2026 has transformed the digital literacy landscape. According to Wolf (2018), the reading circuits in the human brain are plastic and mirror the characteristics of their processing medium. This essay examines how widespread reliance on automated summaries, algorithmic text synthesis, and digital extraction tools alters human text engagement.
It analyzes the cognitive risks of delegated comprehension, explores the capacity of AI to serve as a supportive pedagogical scaffold, and highlights the urgent need for structured instructional interventions to safeguard deep reading. The paper concludes that reading instruction must intentionally shift from testing basic information retrieval to cultivating high-level evaluative analysis and epistemic vigilance in order to maintain independent critical thought.
- Quote paper
- Rolando Salandron (Author), The Cognitive Shift. Navigating Human Reading Comprehension Under the Influence of Artificial Intelligence (2020–2026), Munich, GRIN Verlag, https://www.hausarbeiten.de/document/1742588
