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Showing posts from: AI in Education & Work. Swipe categories on mobile to switch.

Featured Feb 27, 2026

The Corporate Mindset

The Corporate Mindset: Engineering the Professional Future | Dr. Vishwajeet Vinayak Gaike A National Milestone for Employability Architecting the 10x Engineer The Corporate Mindse…

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Insight Feb 07, 2026

AI as Futuristic companion for Faculty

AI: The Futurist Companion for Faculty | 1-Day FDP New Era Faculty Development AI: The Futurist Companion for Faculty Reclaim your time and reignite your classroom. A 6-hour inten…

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Insight Jan 27, 2026

Harnessing AI Tools for Deeper Research (FDP)

“Harnessing AI Tools for Deeper Research” is a two-day FDP hosted at Sandipani Leadership Development Centre, SIU Lavale (08–09 Dec 2025). With 33 faculty participants, the sessio…

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Insight Jan 05, 2026

Andragogy for AI-Enabled Productivity: 5 Shifts That Drive Real Adoption

AI adoption fails when we teach tools like tutorials. This post explains five andragogy-based shifts—prompt ownership, experience-driven inputs, pressure-moment learning, use-case…

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Insight Dec 30, 2025

AI-Assist, Not AI-Replace: How to Write Plagiarism-Safe Academic Content

Using AI in academic writing is not automatically wrong—but using it without a defensible workflow is risky. This guide explains how to “AI-assist, not AI-replace” by building a v…

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Insight Dec 30, 2025

Citation Accuracy Checklist: How to Cross-Verify References Before Submission

Citation mistakes are not minor formatting issues—they are credibility issues. In the AI era, researchers face an additional risk: hallucinated references that look real but do no…

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Insight Dec 30, 2025

AI-Era Literature Review: A Step-by-Step Workflow for Faster, Better Papers

AI can make literature reviews faster—but it can also introduce fake citations and shallow synthesis if you do not follow a strict workflow. This guide provides a step-by-step, AI…

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Insight Dec 30, 2025

AI at Work Without Risk: Practical Guardrails & Ethics

AI risk at work is rarely “AI gone wrong.” It’s unclear rules, risky data handling, unverified outputs, and missing human oversight. This practical guide provides 10 workplace gua…

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