Los proyectos de esta guía utilizan un enfoque centrado en los alumnos para el aprendizaje. En lugar de solo aprender acerca de la IA con videos o conferencias, los alumnos que realizan estos proyectos son participantes activos en la exploración de ella. En el proceso, los estudiantes trabajarán directamente con tecnologías innovadoras de IA, participarán en actividades no en línea para ampliar su comprensión de cómo funcionan las tecnologías de IA y crearán diversos productos auténticos
desde modelos de aprendizaje automático hasta videojuegos— para demostrar su aprendizaje.

PROYECTO 1: Programación con aprendizaje automático
PROYECTO 2: Jugadores asistidos por IA en videojuegos
PROYECTO 3: Uso de la IA para planificar movimientos robóticos
PROYECTO 4: El aprendizaje automático como un servicio

Esta guía ofrece proyectos centrados en los alumnos que pueden enseñar directamente estándares de áreas de estudio en conjunto con comprensiones fundamentales de los que es la IA, cómo funciona y cómo impacta a la sociedad. Fueron considerados varios enfoques clave para diseñar estos proyectos. Entender estos enfoques sustentará su comprensión y la implementación de los proyectos de esta guía, así como su trabajo para diseñar más actividades que integren la enseñanza sobre la IA en su plan de estudios.

PROYECTO 1: Lo que la IA hace bien y lo que no hace tan bien
PROYECTO 2: Datos de entrenamiento y aprendizaje automático
PROYECTO 3: Los sentidos comparados con los sensores
PROYECTO 4: Navegación e IA

Esta guía ofrece proyectos centrados en los alumnos que pueden enseñar directamente estándares de áreas de estudio en conjunto con comprensiones fundamentales de los que es la IA, cómo funciona y cómo impacta a la sociedad. Fueron considerados varios enfoques clave para diseñar estos proyectos. Entender estos enfoques sustentará su comprensión y la implementación de los proyectos de esta guía, así como su trabajo para diseñar más actividades que integren la enseñanza sobre la IA en su plan de estudios.

PROYECTO 1: Chatbots de IA
PROYECTO 2: Desarrollo de una mirada crítica
PROYECTO 3: Uso de la IA para resolver problemas del medio ambiente
PROYECTO 4: Leyes para la IA

En esta guía, la exploración de la IA por parte de los alumnos se enmarca en el contexto de las consideraciones éticas, y en concordancia con los estándares, conceptos y profundidad adecuados para varias materias de K–12. Dependiendo del nivel de sus alumnos y la cantidad de tiempo que tenga disponible, puede completar todas las actividades de Inicio hasta las actividades de Demostraciones culminantes; puede seleccionar actividades de la lista; o puede llevar el aprendizaje de los alumnos más lejos, aprovechando las extensiones y recursos adicionales proporcionados. Para los alumnos sin experiencia previa de formación en la IA, la exposición misma a las actividades de aprendizaje guiadas creará una comprensión de su mundo que probablemente no tenían antes. Y para aquellos con conocimientos previos en informática o con la IA, los proyectos y recursos completos seguirán desafiando su razonamiento y los expondrán a nuevas tecnologías y aplicaciones de la IA en diversos campos de estudio.

PROYECTO 1: Lo justo es justo
PROYECTO 2: ¿Quién tiene el control?
PROYECTO 3: Las ventajas y desventajas de la tecnología de la IA
PROYECTO 4: La IA y el trabajador del siglo XXI

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Artificial intelligence is making rapid advances in medicine. Already, there are machine learning algorithms that can outperform doctors in some medical fields. There’s only one fairly big problem: experts aren’t quite sure how these algorithms work. While designers know full well what goes into the A-I systems they build and what comes out, the learning part in between is often too complex to comprehend. To their users, machine learning algorithms are effectively black boxes. Now, researchers from the RIKEN Center for Advanced Intelligence Project in Japan are lifting the lid. They’ve developed a deep-learning system that can outperform human experts in predicting whether prostate cancer will reoccur within one year. More importantly, the deep learning system they developed can acquire human-understandable features from unannotated pathology images to offer up critical clues that could help humans make better diagnoses themselves..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

A prompt that a student, educator or researcher can paste into a chatbot in order to explore the assumptions behind their questions. I hope educators and students may remix this to contextualise it to different contexts.

The Shallow and the Deep is a collection of lecture notes that offers an accessible introduction to neural networks and machine learning in general. However, it was clear from the beginning that these notes would not be able to cover this rapidly changing and growing field in its entirety. The focus lies on classical machine learning techniques, with a bias towards classification and regression. Other learning paradigms and many recent developments in, for instance, Deep Learning are not addressed or only briefly touched upon.

Biehl argues that having a solid knowledge of the foundations of the field is essential, especially for anyone who wants to explore the world of machine learning with an ambition that goes beyond the application of some software package to some data set. Therefore, The Shallow and the Deep places emphasis on fundamental concepts and theoretical background. This also involves delving into the history and pre-history of neural networks, where the foundations for most of the recent developments were laid. These notes aim to demystify machine learning and neural networks without losing the appreciation for their impressive power and versatility.

Short Description:
Students in an undergraduate seminar in Cognitive Science share what they've learned, regarding the state of the field in AI research. While AI work is remarkable, even the most astonishing projects are a far cry from replicating human intelligence. Why is that? Well, for one, humans have yet to pin down their own intelligence.

Long Description:
Students in an undergraduate seminar in Cognitive Science share what they’ve learned, regarding the state of the field in AI research. While AI work is remarkable, even the most astonishing projects are a far cry from replicating human intelligence. Why is that? Well, for one, humans have yet to pin down their own intelligence. While work in AI may eventually point humans towards an answers to pressing questions regarding the nature of consciousness and matters of intelligence, at this present moment, the hard problem of consciousness is still that: a problem without a solution.

Word Count: 17607

(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)

Short Description:
Social media, digital devices, and networked communication systems have become fully integrated into our everyday living experience. This e-book touches upon the human experience of contemporary trends that affect how we perceive ourselves, others, and society.

Long Description:
Authored as a companion to COMM601 Trends in Digital & Social Media, Granite State College (USNH), Concord, NH.

Word Count: 25859

(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)

On January 4, 2024 the Curriculum Services Team delivered a 2-hour webinar titled "Using the Magic of AI to Innovate Professional Learning" to a national audience.  Based on a presentation delivered at the AESA National Conference in December 2023, this webinar was a deeper dive into the ways that the WIU Curriculum Services Team leverages AI to develop professional learning activities to support the school districts in Westmoreland County and beyond.

The Northeast OER Summit is a gathering of Open Educational Resources practitioners from the Northeast region of the United States.  Initiated in 2017, the planning committee consists of OER advocates (administrators, librarians, instructional designers, faculty and staff) from the Northeast.  This resource is a session presentation that discusses the intersection of OER and AI.

The LLM course is divided into three parts:
🧩 LLM Fundamentals covers essential knowledge about mathematics, Python, and neural networks.
🧑‍🔬 The LLM Scientist focuses on building the best possible LLMs using the latest techniques.
👷 The LLM Engineer focuses on creating LLM-based applications and deploying them.

The lecture provides an overview of autoregressive language models and how they have evolved from basic count-based approaches to more advanced neural network models. It explains the core concept of predicting the next word in a sequence using previous words and how this has been improved through neural networks that can generalize to unseen examples. The speaker highlights how modern models "compress" and "memorize" patterns from training data, allowing them to make better predictions. Techniques like beam search are also discussed as methods for generating text. While the results of these models can seem magical, the lecture emphasizes that they are built on simple but powerful principles of counting, probability, and compression, drawing on early work in information theory.

The slides can be found here: https://drive.google.com/file/d/1dk3o-fcdH1Y7-rGGqlVR35AZ1CVwz0qi/view

(This summary was generated by asking ChatGPT 4o for a summary of the partial transcript.)