This source is an academic article by Michael Gerlich titled "From Offloading to Engagement: An Experimental Study on Structured Prompting and Critical Reasoning with Generative AI," published in Data 2025. The study investigates how individuals engage with generative AI (GenAI) in reasoning tasks, testing four conditions.

Today, we're diving into a fascinating exploration of AI in education, specifically how NotebookLM, a Google Gemini-powered platform, can be used as a Socratic tutor for physics. This discussion will explore the design, implementation, and preliminary observations of this RAG-based tool. 

The collected sources focus extensively on the imperative need for and challenges surrounding Artificial Intelligence (AI) literacyacross educational settings.

This podcast  outlines a comprehensive framework for designing and building personalised AI tutors, emphasising a structured approach that blends technical capabilities with sound pedagogical principles. It details a multi-phase development journey, starting from discovery

The episode explores the impact of artificial intelligence on the workforce, dispelling the common fear that AI will entirely replace human jobs. It highlights that AI excels at repetitive, data-driven tasks such as analysis, content generation, and customer service, leading to the automation of certain roles like administrative work or entry-level customer support.    👉 Check out our courses here: MJR Learning Academy Courses Let’s connect if you’d like help choosing a course or setting up your own AI teaching toolkit.

oin us on AI Insights, the podcast that illuminates the transformative world of Artificial Intelligence. Whether you're a curious beginner or looking to deepen your understanding, we break down complex AI concepts into clear, engaging discussions, helping you navigate and make the most of these evolving technologies.   Join our free courses at   MJR Learning Academy

In this episode of AI Insights, we cut through the buzzwords and explore how artificial intelligence is really being used in education today. What’s working? What’s just marketing fluff? And how can educators move from experimental tools to strategies grounded in solid evidence? Join us for a practical, down-to-earth look at the evolving role of AI in classrooms and training environments.

n this episode of AI Insights, we dive into one of the most talked-about forecasts in tech: the AI 2027 scenario. Could superintelligent AI emerge within just two years? What would that mean for education, jobs, governance, and human agency? MJR Learning Academy

Context Engineering: AI's Thinking Partner in Education 1 source The provided text, "Context Engineering: AI's Thinking Partner in Education," explains a significant evolution in interacting with artificial intelligence. While prompt engineering focuses on crafting effective individual questions, context engineering involves proactively embedding comprehensive background information into AI systems. This allows the AI to operate within a predefined "environment" by preloading elements such as curriculum frameworks, learning objectives, and even examples of desired outputs. The article highlights how this approach transforms educational applications, enabling adaptive lesson generation, nuanced AI marking, and the development of synthetic educators that respond within a specified identity or role. Ultimately, for educators and instructional designers, context engineering provides a more sophisticated way to interact with AI, leading to more aligned and meaningful outputs by giving the AI situational awareness.     A short description for my podcast Ai Insights Welcome to AI Insights, your guide to context engineering – the strategic shift transforming artificial intelligence into a true thinking partner. Discover how preloading background knowledge and defining your environment enables AI to deliver nuanced, domain-specific outputfrom adaptive lesson generation to smarter marking. Learn to shape your AI collaborators for higher fidelity outcomes.

n this episode, we explore how educators can use ChatGPT not as a crutch, but as a springboard for active learning. Based on the article "Active Learning with ChatGPT: Beyond Cognitive Offloading", we dive into practical strategies like retrieval quizzes, reflective journaling, and critical AI analysis—designed to deepen cognitive engagement and prevent over-reliance on generative tools. Backed by educational research and cognitive science, these techniques help foster memory retention, metacognition, and critical thinking. Whether you're a teacher experimenting with AI or an instructional designer building new workflows, this episode offers hands-on ideas and implementation tips to ensure students stay in the driver’s seat.

This study investigated the cognitive and neural impacts of using large language models (LLMs) versus traditional search engines or no tools at all for essay writing. Researchers employed electroencephalography (EEG) to monitor brain activity, coupled with natural language processing (NLP) to analyse essay content and post-session interviews to gauge participant experiences, including essay ownership and quoting ability.

The provided texts collectively discuss the evolving relationship between humans and Artificial Intelligence (AI) in the workplace, emphasising the concept of co-intelligence or human-AI collaboration. Several sources highlight AI's capacity to enhance efficiency, improve decision-making, and automate repetitive tasks, freeing humans for more creative and strategic work.

As artificial intelligence (AI) technologies increasingly integrate into educational practice, a critical design challenge emerges: how might we move beyond AI as a reactive assistant and toward agentic AI systems that function as digital apprentices--systems that actively learn from and co-develop with educators? This article introduces a conceptual framework for designing agentic AI as pedagogical apprentices capable of observing, adapting to, and co-constructing instructional practice in partnership with human teachers.

Are traditional exams still fit for purpose in a world powered by artificial intelligence? This podcast dives into how AI is challenging the very foundation of assessment, from its impact on memorisation and test anxiety to the shifting landscape of academic integrity. We explore why the "factory model" of testing is becoming obsolete and what uniquely human skills truly matter in an AI-driven economy. 

n this episode of AI Insights, we explore how AI is becoming a powerful partner in supporting learners with dyslexia. From real-time voice and eye-tracking tools to adaptive reading systems, discover how emerging tech is not replacing educators—but empowering them to reach every learner more effectively.

Explore how agentic AI is redefining the educator's role, shifting focus from content delivery to human connection and learning design. Discover how to embrace AI as an enhancement, not a replacement, and lead the charge in the classroom of the future.

Discover how to build AI agents with LLMs—core concepts, use cases, design tips, and safety guardrails explained.

This text explores the potential for artificial intelligence (AI) to fundamentally reshape higher education, arguing that it represents a wave of creative destruction similar to the shift from film to digital photography.

This source explores the emerging concept of the neo-human, defined as a person augmented by AI through various integrations, from wearable devices to neural implants

The source highlights that with the increasing presence of AI in education, mastering "prompt craft"—effectively communicating with AI tools—is becoming as vital for teachers as traditional lesson planning.