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Taxshila Research Page

Threat-Driven Neural States and Their Influence on Cognitive Performance

By Shiva Narayan
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Human cognition does not operate in isolation from emotional and physiological states. When individuals perceive threat, uncertainty or social pressure, the brain activates protective neural mechanisms often referred to as survival mode. Threat-Driven Neural States and Their Influence on Cognitive Performance The threat-driven neural states influence attention, memory, decision-making and behavior, often prioritizing immediate safety over long-term cognitive processing. This research article examines the neurobiological foundations of survival responses and analyzes their consequences for learning, working and knowledge transfer systems. Drawing from affective neuroscience and cognitive science, the study explores how limbic activation, stress hormones, and defensive attention patterns shape cognitive performance. The paper also discusses how emotionally secure environments can regulate threat responses and promote higher-order thinking, creativity, and collaborative knowledge propagat...
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15-Year Knowledge Transfer Model That Completes Formal Education by Age 20

By Shiva Narayan
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Taxshila Span (545) introduces a scientifically structured 15-year academic pathway designed to streamline gyanpeeth architecture while strengthening deep knowledge transfer. Built on the five years of primary learnography, four years of secondary learnography, five years of university learnography, and one year of apprenticeship, this model eliminates unnecessary repetition and aligns learning with brainpage development. Taxshila Model: Designing School 2020 for Deep Knowledge Transfer Taxshila Model – School 2020 as a Knowledge Civilization for Early Mastery At the heart of this transformation is the Taxshila Model, the foundation of School 2020. Instead of fragmented period-based teaching, it operates through System Learnography. This is structured book-to-brain learning using the One Day One Book approach. Learners build brainpage maps and modules, engage in miniature school collaboration, and demonstrate real-time understanding through Goal Oriented Task Operation (GOTO). By synch...
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Taxshila Model: From Syllabus Completion Education to Knowledge Creation Learnography

By Shiva Narayan
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What if classrooms were designed not for lectures, but for knowledge creation? The Taxshila Model introduces a neuroscience-based framework that transforms traditional schooling into structured knowledge transfer ecosystems. Inspired by the ancient spirit of Takshashila and powered by system learnography and motor science, this model replaces passive learning with active brainpage classrooms and miniature school architecture (7×7+1). From Brainpage to Breakthrough: Transformative Power of Taxshila Model Instead of memorizing content, pre-trained learners construct visual brainpage maps and modules, teach peers, and build knowledge modules. Taxshila learners progress through defined developmental levels (0–5), from basic understanding to research-level mastery. The system integrates motor engagement, distributed leadership, and reciprocal learnography to strengthen retention, deepen comprehension, and enhance cross-domain thinking. By shifting the focus from syllabus completion to knowl...
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Deep Dive Mode as Cognitive Engineering Strategy in Knowledge Transfer Systems

By Shiva Narayan
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Modern education operates in an era of abundant information but limited structural understanding. Many knowledge transfer systems emphasize speed, coverage, and assessment performance without ensuring deep cognitive integration. As a result, learners may recall facts temporarily but struggle with application, synthesis, and long-term retention. Cognitive Architecture Building through DIYA-Driven Deep Dive Learning Deep Dive Mode addresses this limitation by repositioning learning as a form of cognitive engineering. Instead of consuming information, learners systematically dismantle, analyze, reorganize, and reconstruct knowledge into structured internal representations. This engineered depth strengthens neural encoding, enhances retrieval accuracy, and improves transfer to unfamiliar contexts. The purpose of this paper is to define Deep Dive Mode as a replicable strategy for designing knowledge transfer systems that produce durable understanding and cognitive independence. 👁️ Research...
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DIYA Ethic in Knowledge Transfer: Structural Model of Self-Directed Classroom Learning

By Shiva Narayan
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Traditional classrooms frequently rely on expert-centered instruction, where learners depend heavily on teachers for explanation, interpretation, and validation. While this approach can transmit information, it often limits autonomous knowledge construction. In contrast, the DIYA ethic of learnography emphasizes learner-driven engagement, where students build their own understanding through structured activity. DIYA-Based Book-to-Brain Transfer for Sustainable Academic Achievement DIYA in the Gyanpeeth Architecture parallels its practical meaning in craftsmanship — building, repairing or modifying without relying on professionals. Applied to knowledge transfer, it means learners actively construct brain-based learning modules by engaging reading, writing, organizing, and problem-solving circuits independently. The structural model presented in the Taxshila Model reframes the classroom as a knowledge-construction environment, where pre-trained learners function as the designers of their...
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