Different ways to implement education:
- teaching/instruction
- discussion
- directed research
- training
- storytelling

Methods of Education

Education can take place in three general settings:
- informal
- formal
- non-formal

Educational Settings

Add your Education reference node as a child node here.

Education References

Informational material on topics related to sex, sexuality, and relationships. Usually presented in an academic setting.

Sexuality Education (Sex Ed)

An educational course is a structured program of study designed to teach specific knowledge or skills in a particular subject area.

Educational Course

This reference document contains a sample final examination for a MATH 102 course, accompanied by detailed handwritten solutions. The material covers a broad range of algebraic and pre-calculus concepts, including analyzing function properties, solving logarithmic and exponential equations, and graphing trigonometric functions. It also features applied word problems involving rates of change, compound interest, and piecewise tax functions. The first page presents eleven specific problems, while the subsequent pages demonstrate step-by-step methods for solving each equation and inequality, serving as a comprehensive study guide for exam preparation.

Maths papers

This reference guide by Carl Erickson provides a comprehensive overview of Object-Oriented Programming (OOP) principles and design methodologies. It addresses the management of software complexity through foundational concepts such as abstraction, encapsulation, inheritance, and polymorphism. The text bridges theory and practice using C++ and Java examples, while detailing the development process through UML notation, CRC cards, and various analysis techniques. Additionally, it explores advanced topics like concurrency, persistence, and design pitfalls. The document concludes by establishing metrics for evaluating code quality, emphasizing low coupling and high cohesion to create robust, maintainable software architectures.

Object Oriented Programming

This reference presents PT-LiRPA, a novel neural network verification framework that combines Linear Relaxation-based Perturbation Analysis (LiRPA) with statistical sampling. By utilizing Extreme Value Theory to estimate tight intermediate reachable sets, the method significantly reduces the over-approximation errors typical of formal verification tools. PT-LiRPA provides probabilistic guarantees on verification soundness while maintaining low computational costs. Extensive experiments demonstrate that this approach tightens output bounds and outperforms state-of-the-art verifiers on complex benchmarks, offering robust certification in scenarios where traditional deterministic methods fail.

Probabilistically Tightened Linear Relaxation-based PerturbationAnalysis for Neural Network Verification

This survey reviews the emerging field of Agentic Large Language Models (LLMs), defining them as models capable of reasoning, acting, and interacting. It organizes the literature into a taxonomy comprising three key pillars: reasoning enhancements like self-reflection and chain-of-thought; acting capabilities involving tool use, robotics, and specialized assistants; and social interaction within multi-agent environments. The paper explores applications in high-impact domains such as medicine and scientific research while outlining a future research agenda focused on safety, emergent behaviors, and the use of agent-generated data for training.

Agentic Large Language Models, a Survey

This survey explores Agentic Large Language Models (LLMs), defining them as systems capable of reasoning, acting, and interacting to achieve goals. The authors organize research into three core categories: reasoning techniques like self-reflection and Chain of Thought; acting through tool use and robotics; and interaction within multi-agent simulations. The paper highlights how these capabilities form a virtuous cycle that generates new training data and improves performance. Additionally, it outlines a research agenda addressing critical challenges in safety, ethics, and reliability as LLMs evolve into autonomous assistants for domains like science and medicine.

Agentic Large Language Models

This book provides a comprehensive introduction to the foundations of Large Language Models (LLMs). It outlines the core concepts and techniques driving modern NLP, starting with pre-training paradigms and architectures like BERT. It explores generative models, scaling laws, and long-sequence modeling. Key sections detail prompting strategies such as chain-of-thought, alongside alignment methods including instruction fine-tuning and Reinforcement Learning from Human Feedback (RLHF). The text also covers efficient inference techniques, decoding algorithms, and optimization strategies, serving as an educational resource for understanding the mechanisms behind intelligent language systems.

Large Language Model

The process of teaching and receiving instruction to facilitate learning knowledge, skills, behaviors, values, beliefs.

San Jose State University

University of Michigan - Ann Arbor

The act of imparting knowledge on those who wish to learn through systematic steps.  

Teaching/Instruction

Learning is defined as a relatively permanent change in behavior or knowledge that results from experience. This process of acquiring new knowledge and skills allows an organism to adapt to its environment. Unlike innate behaviors such as instincts and reflexes, which are genetically predetermined, learning involves change and is dependent on experience.

Definition of Learning

Wikipedia

- curriculum is inflexible
- reliance on assessment
- allows certain students to fail

Cons of Teaching/Instruction

- easily standardizable
- methods of teaching are often uniform between teachers
- information is easily broken down into parts

Pros of Teaching/Instruction

Roles of a Teacher/Instructor

- **Lesson Planning**
- **Classroom Management**
- **Instruction Delivery**
- **Assessment and Evaluation**
- **Individualized Instruction**
- **Curriculum Development**
- **Professional Development**
- **Student Engagement**
- **Communication with Parents/Guardians**
- **Classroom Environment Maintenance**
- **Student Mentorship**
- **Adaptation to Educational Technologies**
- **Cultural Competence**
- **Collaboration with Colleagues**
- **Student Well-being and Safety**
- **Ethical and Legal Responsibility**
- **Documentation and Record Keeping**
- **Support for Extracurricular Activities**
- **Continuous Improvement**

Responsibilities of Teacher/Instructor

Education

IGI Global

The materials that help teachers and learners reach their goals are called learning content.

Learning Content

Disorders of Learning

A central inquiry in psychology is understanding the precise mechanisms of learning. Key questions explore the specific processes at work that enable individuals to acquire knowledge and skills, transforming experience and information into understanding.

Fundamental Questions about the Learning Process

Both learned behaviors and innate behaviors, such as instincts and reflexes, are crucial for an organism's adaptation to its environment. The fundamental difference lies in their origin: innate behaviors are genetically predetermined and do not require experience, whereas learned behaviors are acquired through experience, resulting in a relatively permanent change in behavior or knowledge.

Learned vs. Innate Behaviors as Adaptive Mechanisms

Complex learning, such as mastering a new skill or academic discipline, is not a monolithic process. It involves a sophisticated interplay between both conscious and unconscious mental activities.

Conscious and Unconscious Processes in Learning

Associative learning is a form of learning where connections or associations are made between events that occur together in the environment. Both classical conditioning and operant conditioning are classified as forms of associative learning.

Associative Learning

The three fundamental types of learning are classical conditioning, operant conditioning, and observational learning. These processes are distinguished by the nature of the associations formed and the level of consciousness involved. Classical conditioning typically involves unconscious processes, operant conditioning involves conscious processes, and observational learning incorporates social and cognitive dimensions into the associative processes.

Comparison of the Three Basic Forms of Learning

While the approaches within behaviorism are fundamental to understanding learning, they do not encompass the entire field. Separate and distinct traditions for studying learning have developed within other areas of psychology, such as those focused on memory and cognition. A comprehensive understanding of learning requires considering these alternative perspectives, which often converge with behaviorist principles over time.

Learning Perspectives Beyond Behaviorism

Albert Bandura's key contribution to learning theory was the concept of vicarious learning, more commonly known as observational learning. This process involves learning by observing the behavior of another person, or model, and the consequences of that behavior. Bandura proposed that this form of learning is crucial for personality development, as individuals acquire not just single actions but entire patterns of behavior by watching others. Unlike learning through direct experience, observational learning allows for the acquisition of complex behaviors without personal trial and error.

Observational Learning (Vicarious Learning)

A fundamental component of learning is the mind's natural tendency to automatically make connections between events that occur closely together or in sequence. This automatic association forms the basis for studying how learning occurs.

Learn Before

Related

Learn After