Content on this Guide was adapted from https://pascalsc.libguides.com/ai, a LibGuide developed by the PASCAL Training Working Group with some assistance from ChatGPT, a language model created by OpenAI.
Artificial Intelligence (AI) encapsulates the endeavor to engineer machines that replicate human intelligence. The formal inception of AI as a distinct field of study occurred in 1956 at a Dartmouth College workshop, marking the commencement of an academic and practical exploration into cognitive simulation. The trajectory of AI has been characterized by cycles of ambitious advancements and subsequent periods of disillusionment, known as "AI winters," due to unmet expectations.
In the contemporary era, AI manifests across a diverse spectrum of applications, including but not limited to, machine learning, natural language processing, and autonomous systems, exemplified by virtual assistants (like Siri and Alexa), personalized recommendation engines (as seen on Netflix and Amazon), and self-navigating vehicles.
Generative AI, a subset of AI, focuses on creating new content or data that is similar but not identical to existing data. It involves algorithms that can generate text, images, videos, and music that resemble human-like creativity. Tools like GPT (Generative Pre-trained Transformer) and DALL-E are prominent examples, showcasing the ability of AI to produce novel content based on learned patterns and data.
For a comprehensive list of terms, visit the Glossary of Terms page.
This glossary provides concise definitions of key terms related to artificial intelligence in education, offering insight into how AI, particularly generative AI, influences teaching and learning processes.
Example: Using virtual reality simulations to provide students with hands-on experiences in historical settings or scientific experiments, supplemented with AI-generated feedback and guidance.