The dominant educational paradigm in the 20th century was based on easily recognizable ideas about how the human brain works and how to design classrooms to help human brains learn. R. Keith Sawyer (2006), a scholar from the University of Washington, articulated five assumptions in which curriculum and instruction has been grounded: Those assumptions appear Read More
Author: Gary Ackerman
On Data Quality
Education demands data. This isn’t just about lively debate; it requires educators to act as educational researchers, asking clear questions, designing robust data collection methods, and analyzing findings to draw reasonable conclusions. At the heart of this process lies the critical twin pillars of ethical data gathering and rigorous data validation. Only through these can Read More
Introduction to Access Databases
Many of us start organizing information using simple lists in word-processing programs or spreadsheet. This works fine when the amount of data is small, but as these lists grow, managing them becomes challenging. You might start noticing repetitions or inconsistencies in the data, making it hard to understand or find what you need. When these Read More
On Pseudoscience
We live in a world where claims about everything from climate change to health remedies are constantly vying for our attention. How do we figure out which claims are grounded in solid science and which belong to the realm of pseudoscience? This isn’t just an academic puzzle; it has real-world consequences for our health, our Read More
Karl Popper’s View of Science
Have you ever wondered what truly distinguishes genuine science from pseudoscience? It’s a question with significant practical and theoretical importance. While many might intuitively say science is about finding evidence that supports a theory, the philosopher Karl Popper offered a surprisingly different answer. Born in Vienna in the early 20th century, an era when theories Read More
Prompt Engineering
Prompts can be composed of text, images, or both, depending on the model. Fundamentally, prompts get converted into tokens, and the quality of this initial input strongly influences the relevance and accuracy of the model’s response. While there’s no single formula, effective prompts often contain elements like keywords, guidelines, formatting instructions, and examples. Several techniques Read More
Retrieval-Augmented Generation (RAG)
Generative AI (GenAI) has burst onto the scene, capturing global enthusiasm and driving the next wave of digital transformation. At the heart of many GenAI applications are Large Language Models (LLMs), powerful AI models trained on vast amounts of text data to understand and generate human-like text. LLMs, like OpenAI’s GPT series, Google’s PaLM and Read More
Elevator Pitch: The New Theory of Disuse
The New Theory of Disuse (NTD): This theoretical framework provides a rationale for why difficulties can be desirable. The NTD characterizes an item in memory by two strengths: Storage Strength: Represents how well learned and interconnected an item is in memory. The theory assumes that storage strength, once accumulated, is never lost . Retrieval Strength: Read More
Science and Pseudoscience
We often hear claims about what is or isn’t “scientific.” Science holds a distinctive place in modern society; we trust its pronouncements on everything from building bridges to who counts as an expert. Yet, history is full of scientific theories that turned out to be wrong. This leads us to a fundamental question: what exactly Read More
Large Language Models
Large language models, or LLMs, represent a notable advancement in the field of artificial intelligence. These models are a central topic of any discussion of generative AI which aims to provide an introduction to their workings and significance. Understanding LLMs involves grasping their fundamental principles and the components that enable their capabilities. LLMs are built Read More