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Model Code of Ethics for Educators (MCEE)

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How to Read Privacy Policies Like a Lawyer

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How to Read Privacy Policies Like a Lawyer

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How to read privacy policies like a lawyer

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This chapter is annotated every year as part of an undergraduate/graduate class on Teaching and Learning with Technology. To turn off the highlighted text, click on the “eye” icon in the top right corner of the browser screen.

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Creativity, Copyright, and Fair Use

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Lesson 2 - Helping our Heroes: How to be a Data Privacy Hero

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Five Quality Indicators for Edtech & AI Products

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Five Quality Indicators for Edtech & AI Products

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Easing the Burden on Schools: Five Quality Indicators for Edtech & AI Products

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Seven leading edtech organizations pledge to work together on behalf of educators, product developers, students, and their families to to identify quality...

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GenAI Chatbot Prompt Library for Educators

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GenAI Chatbot Prompt Library for Educators

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Prompt Library - Lesson Planning - AI for Education

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We have a variety of prompts to help you lesson plan and do administrative tasks with GenAI chatbots like ChatGPT, Claude, Bard, and Perplexity.

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Modify and Refine AI Image Prompts | Microsoft Copilot

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Modify your AI artwork prompts to get Designer in Copilot to produce fantastic results. Learn how to change colors, improve image quality, and more.

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AI Art Genres and Styles | Microsoft Copilot

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Create AI-generated images in any genre or style with Designer in Copilot. From AI photos and paintings to anime, create whatever you can imagine.

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Helping students understand the biases in generative AI

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Helping students understand the biases in generative AI

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Generative artificial intelligence has much potential in teaching and learning. It also has a dark side that students and faculty need to understand and explore. This includes biases in language, data, and algorithms; a tendency to fabricate; a potential to take on a threatening persona, and an origin story with disturbing elements. As with other technologies, these biases are amplified when an automated system replaces human judgment, as in such things as screening in job applications and college admission, and security screenings and searches.

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How to use AI responsibly EVERY time

EVALUATE the initial output to see if it meets the intended purpose and your needs.

VERIFY facts, figures, quotes, and data using reliable sources to ensure there are no hallucinations or bias.

EDIT your prompt and ask follow up questions to have the AI improve its output.

REVISE the results to reflect your unique needs, style, and/or tone. AI output is a great starting point, but shouldn't be a final product.

YOU are ultimately responsible for everything you create with AI. Always be transparent about if and how you used AI.
Developed in collaboration with Vera Cubero, Digital Teaching & Learning Consultant - North Carolina Dept. of Public Instruction

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How to Use AI Responsibly EVERY Time Infographic - AI for Education

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To ensure that AI serves as a valuable tool rather than a potential hazard, it's not only crucial to adopt a framework for responsible use, but acknowledge the key role we play as the users of that technology. Here's an acrostic (and infographic) we love to help guide responsible use of GenAI.

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Dive into this series of 4 student use cases for AI to discover how generative AI tools like ChatGPT can be used as a feedback generator, tutor, team coach, and learner. Get sample prompts and shareable guidelines to help students use AI tools effectively.

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Prompt Framework for Educators: The Five "S" Model

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Prompt Framework for Educators: The Five "S" Model

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The single most important new skill an educator or student can learn this year? Prompt Engineering

AI Chatbots can be a powerful tool for any educator - whether it's developing lesson plans, saving hours on administrative tasks, or brainstorming ideas for personalized learning.

We spend a lot of time crafting prompts for our prompt library, so we've distilled our framework to 5 S's to help you start getting the most out of your prompts.

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Prompt Framework for Educators: The Five "S" Model - AI for Education

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Prompt Framework for Educators: The Five "S" Model

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1  Introduction to artificial intelligence

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Public Awareness of Artificial Intelligence in Everyday Activities

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Public Awareness of Artificial Intelligence in Everyday Activities

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How AI works in everyday life | Google AI

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What's the Difference Between AI, Machine Learning, and Deep Learning?

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What's the Difference Between AI, Machine Learning, and Deep Learning?

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What's the Difference Between AI, Machine Learning, and Deep Learning?

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Generative AI Explainer - AI for Education

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Our Generative AI Explainer is a simple graphic organizer that defines Generative AI in the larger context of the field of Artificial Intelligence

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How Chatbots and Large Language Models Work

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How Chatbots and Large Language Models Work

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How Chatbots and Large Language Models Work

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Glossary of Artificial Intelligence Terms for Educators

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Glossary of Artificial Intelligence Terms for Educators

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by Pati Ruiz and Judi Fusco

This glossary was written for educators to reference when learning about and using artificial intelligence (AI). We will start with a definition of artificial intelligence and then provide definitions of AI-related terms in alphabetical order. This glossary was last updated on July 19, 2023

Artificial Intelligence (AI): AI is a branch of computer science. AI systems use hardware, algorithms, and data to create "intelligence" to do things like make decisions, discover patterns, and perform some sort of action. AI is a general term and there are more specific terms used in the field of AI. AI systems can be built in different ways, two of the primary ways are: (1) through the use of rules provided by a human (rule-based systems); or (2) with machine learning algorithms. Many newer AI systems use machine learning (see definition of machine learning below).

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Algorithm: Algorithms are the "brains" of an AI system and what determines decisions in other words, algorithms are the rules for what actions the AI system takes. Machine learning algorithms can discover their own rules (see Machine learning for more) or be rule-based where human programmers give the rules.

Artificial General Intelligence (AGI): Artificial general intelligence has not yet been realized and would be when an AI system can learn, understand, and solve any problem that a human can.

Artificial Narrow Intelligence (ANI): AI can solve narrow problems and this is called artificial narrow intelligence. For example, a smartphone can use facial recognition to identify photos of an individual in the Photos app, but that same system cannot identify sounds.

Chat-based generative pre-trained transformer (ChatGPT): A system built with a neural network transformer type of AI model that works well in natural language processing tasks (see definitions for neural networks and Natural Language Processing below). In this case, the model: (1) can generate responses to questions ( Generative); (2) was trained in advance on a large amount of the written material available on the web ( Pre-trained); (3) and can process sentences differently than other types of models ( T ransformer).

Transformer models: Used in ChatGPT (the T stands for Transformer), transformer models are a type of language model. They are neural networks and also classified as deep learning models. They give AI systems the ability to determine and focus on important parts of the input and output using something called a self-attention mechanism to help.

Self-attention mechanism: These mechanisms, also referred to as attention help systems determine the important aspects of input in different ways. There are several types and were inspired by how humans can direct their attention to important features in the world, understand ambiguity, and encode information.

Computer Vision: Computer Vision is a set of computational challenges concerned with teaching computers how to understand visual information, including objects, pictures, scenes, and movement (including video). Computer Vision (often thought of as an AI problem) uses techniques like machine learning to achieve this goal.

Critical AI: Critical AI is an approach to examining AI from a perspective that focuses on reflective assessment and critique as a way of understanding and challenging existing and historical structures within AI. Read more about critical AI.

Data: Data are units of information about people or objects that can be used by AI technologies.

Training Data: This is the data used to train the algorithm or machine learning model. It has been generated by humans in their work or other contexts in their past. While it sounds simple, training data is so important because the wrong data can perpetuate systemic biases. If you are training a system to help with hiring people, and you use data from existing companies, you will be training that system to hire the kind of people who are already there. Algorithms take on the biases that are already inside the data. People often think that machines are "fair and unbiased" but this can be a dangerous perspective. Machines are only as unbiased as the human who creates them and the data that trains them. (Note: we all have biases! Also, our data reflect the biases in the world.) ¹ ​​

Foundation Models: Foundation Models represent a large amount of data that can be used as a foundation for developing other models. For example, generative AI systems use large language foundation models. They can be a way to speed up the development of new systems, but there is controversy about using foundation models since depending on where their data comes from, there are different issues of trustworthiness and bias. Jitendra Malik, Professor of Computer Science at UC Berkeley once said the following about foundation models: " These models are really castles in the air, they have no foundation whatsoever. "

Human-centered Perspective: A human-centered perspective sees AI systems working with humans and helping to augment human skills. People should always play a leading role in education, and AI systems should not replace teachers.

Intelligence Augmentation (IA): Augmenting means making something greater; in some cases, perhaps it means making it possible to do the same task with less effort. Maybe it means letting a human (perhaps teacher) choose to not do all the redundant tasks in a classroom but automate some of them so they can do more things that only a human can do. It may mean other things. There's a fine line between augmenting and replacing and technologies should be designed so that humans can choose what a system does and when it does it.

Intelligent Tutoring Systems (ITS): A computer system or digital learning environment that gives instant and custom feedback to students. An Intelligent Tutoring System may use rule-based AI (rules provided by a human) or use machine learning under the hood. By under the hood we mean the underlying algorithms and code that an ITS is built with. ITSs can support adaptive learning.

Adaptive Learning: Subject or course material is adjusted based on the performance of the learner. The difficulty of material, the pacing, sequence, type of help given, or other features can be adapted based on the learner's prior responses.

Interpretable Machine Learning (IML): Interpretable machine learning, sometimes also called interpretable AI, describes the creation of models that are inherently interpretable in that they provide their own explanations for their decisions. This approach is preferable to that of explainable machine learning (see definition below) for many reasons including the fact that we should understand what is happening from the beginning in our systems, rather than try to "explain" black boxes after the fact.

Black Boxes: We call things we don't understand, "black boxes" because what happens inside the box cannot be seen. Many machine learning algorithms are "black boxes" meaning that we don't have an understanding of how a system is using features of the data when making their decisions (generally, we do know what features are used but not how they are used)There are currently two primary ways to pull back the curtain on the black boxes of AI algorithms: interpretable machine learning (see definition above) and explainable machine learning (see definition below).

Machine Learning (ML): Machine learning is a field of study with a range of approaches to developing algorithms that can be used in AI systems. AI is a more general term. In ML, an algorithm will identify rules and patterns in the data without a human specifying those rules and patterns. These algorithms build a model for decision making as they go through data. (You will sometimes hear the term machine learning model.) Because they discover their own rules in the data they are given, ML systems can perpetuate biases. Algorithms used in machine learning require massive amounts of data to be trained to make decisions.

It's important to note that in machine learning, the algorithm is doing the work to improve and does not have the help of a human programmer. It is also important to note three more things. One, in most cases the algorithm is learning an association (when X occurs, it usually means Y) from training data that is from the past. Two, since the data is historical, it may contain biases and assumptions that we do not want to perpetuate. Three, there are many questions about involving humans in the loop with AI systems; when using ML to solve AI problems, a human may not be able to understand the rules the algorithm is creating and using to make decisions. This could be especially problematic if a human learner was harmed by a decision a machine made and there was no way to appeal the decision.

Neural Networks (NN): Neural networks also called artificial neural networks (ANN) and are a subset of ML algorithms. They were inspired by the interconnections of neurons and synapses in a human brain. In a neural network, after data enter in the first layer, the data go through a hidden layer of nodes where calculations that adjust the strength of connections in the nodes are performed, and then go to an output layer.

Deep Learning: Deep learning models are a subset of neural networks. With multiple hidden layers, deep learning algorithms are potentially able to recognize more subtle and complex patterns. Like neural networks, deep learning algorithms involve interconnected nodes where weights are adjusted, but as mentioned earlier there are more layers and more calculations that can make adjustments to the output to determine each decision. The decisions by deep learning models are often very difficult to interpret as there are so many hidden layers doing different calculations that are not easily translatable into English rules (or another human-readable language).

Natural Language Processing (NLP): Natural Language Processing is a field of Linguistics and Computer Science that also overlaps with AI. NLP uses an understanding of the structure, grammar, and meaning in words to help computers "understand and comprehend" language. NLP requires a large corpus of text (usually half a million words).

NLP technologies help in many situations that include: scanning texts to turn them into editable text (optical character recognition), speech to text, voice-based computer help systems, grammatical correction (like auto-correct or grammarly), summarizing texts, and others.

Robots: Robots are embodied mechanical machines that are capable of doing a physical task for humans. "Bots" are typically software agents that perform tasks in a software application (e.g., in an intelligent tutoring system they may offer help). Bots are sometimes called conversational agents. Both robots and bots can contain AI, including machine learning, but do not have to have it. AI can help robots and bots perform tasks in more adaptive and complex ways.

User Experience Design/User Interface Design (UX/UI): User-experience/user-interface design refers to the overall experience users have with a product. These approaches are not limited to AI work. Product designers implement UX/UI approaches to design and understand the experiences their users have with their technologies.

Explainable Machine Learning (XML) or Explainable AI (XAI): Researchers have developed a set of processes and methods that allow humans to better understand the results and outputs of machine learning algorithms. This helps developers of AI-mediated tools understand how the systems they design work and can help them ensure that they work correctly and are meeting requirements and regulatory standards.

It is important to note that the term "explainable" in the context of explainable machine learning or explainable AI, refers to an understanding of how a model works and not to an explanation of how the model works. In theory, explainable ML/AI means that an ML/AI model will be "explained" after the algorithm makes its decision so that we can understand how the model works. This often entails using another algorithm to help explain what is happening as the "black box." One issue with XML and XAI is that we cannot know for certain whether the explanation we are getting is correct, therefore we cannot technically trust either the explanation or the original model. Instead, researchers recommend the use of interpretable models.

Thank you to Michael Chang, Ph.D., a CIRCLS postdoctoral scholar, for reviewing this post. We appreciate your work in AI and your work to bring educators and researchers together on this topic.

Educator CIRCLS posts are licensed under a Creative Commons Attribution 4.0 International License. If you use content from this site, please cite the post and consider adding: "Used under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/)."
Suggested citation format: [Authors] ([Year]). [Title]. Educator CIRCLS Blog. Retrieved from [URL]

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¹​​​​Fusco, J. (2020). Book Review: You Look Like a Thing and I Love You. CIRCLEducators Blog. Retrieved from https://circleducators.org/review-you-look-like-a-thing/

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Glossary of Artificial Intelligence Terms for Educators

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by Pati Ruiz and Judi Fusco This glossary was written for educators to reference when learning about and using artificial intelligence (AI). We will start with a definition of artificial intelligence and then provide definitions of AI-related terms in alphabetical order.

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GenAI Chatbot Prompt Library for Educators

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GenAI Chatbot Prompt Library for Educators

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Prompt Library - Lesson Planning - AI for Education

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We have a variety of prompts to help you lesson plan and do administrative tasks with GenAI chatbots like ChatGPT, Claude, Bard, and Perplexity.

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AI Art Genres and Styles | Microsoft Copilot

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Create AI-generated images in any genre or style with Designer in Copilot. From AI photos and paintings to anime, create whatever you can imagine.

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Modify and Refine AI Image Prompts | Microsoft Copilot

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Modify your AI artwork prompts to get Designer in Copilot to produce fantastic results. Learn how to change colors, improve image quality, and more.

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Yesterday we had the pleasure of working with leaders and teachers from L'Anse Creuse School District outside of Detroit for one of our Train-the-Trainer Institutes. We had a great time digging into all things GenAI!

Our 1-day institute focuses on two key PD sessions: Introduction to Generative AI for Educators and Prompting 101. We work to upskill the new trainers on foundational concepts of GenAI, before equipping them with strategies to turnkey this work in their school.

In our Prompting 101 session we focus on strategies for getting the best out of popular and powerful free GenAI tools like ChatGPT, Claude, and Gemini.

What's great is there are many different prompt frameworks out there for educators to use - including our 5S Framework: Set the scene (priming), be Specific, Simplify language, Structure output, and Share feedback.

We also break down a good prompting in the following four steps:

1. Clarity is Key

Explicitly state what you would like the model to do. The more specific your prompt, the more accurate and tailored the AI's response will be. General prompts will result in general responses

2. Pick the Right Prompting Technique

You may be able to get what you need from one well-structured prompt (one-shot prompting), but there are other techniques too. You can provide examples in your prompt to guide the AI's responses (few-shot prompting), or cut down your requests into steps (chain-of-thought prompting).

3. Provide Context

The chatbot is called a "context window" for a reason! Give AI as much necessary background information as possible. This will help it prepare a response that fits your needs.

4. Format Matters

A well-structured prompt guides the AI in understanding the exact nature of your request. Use clear and direct language, and structure your prompt logically.

So what does that look like in practice for a one-shot prompt? An OK prompt for educators might look like this:

"Create a lesson plan about multiplying fractions for 5th graders"

A better prompt would look like:

"Act as an expert mathematician and a teacher skilled in designing engaging learning experiences for upper elementary students. Design a lesson plan about multiplying fractions for 5th grade students."

And an even more effective prompt would be:

"You are an expert mathematician and teacher skilled in Universal Design for Learning. Design an accessible lesson plan about multiplying fractions for 5th grade students interested in soccer. The lesson should include a hands-on activity and frequent opportunities for collaboration. Format your response in a table."

We take this approach every time we create on of our more than 100 customizable prompts in our Prompt Library.

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Effective Prompting for Educators - AI for Education

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In our Prompting 101 session we focus on strategies for getting the best out of popular and powerful free GenAI tools like ChatGPT, Claude, and Gemini.What's great is there are many different prompt frameworks out there for educators to use - including our 5S Framework: Set the scene (priming), be S

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Prompt Framework for Educators: The Five "S" Model

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Prompt Framework for Educators: The Five "S" Model

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The single most important new skill an educator or student can learn this year? Prompt Engineering

AI Chatbots can be a powerful tool for any educator - whether it's developing lesson plans, saving hours on administrative tasks, or brainstorming ideas for personalized learning.

We spend a lot of time crafting prompts for our prompt library, so we've distilled our framework to 5 S's to help you start getting the most out of your prompts.

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Prompt Framework for Educators: The Five "S" Model - AI for Education

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Prompt Framework for Educators: The Five "S" Model

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Prompt literacy enables anyone to communicate with and direct generative AI systems without needing expertise in computer programming. Prompts are commands formulated in natural human language that unlock the capabilities of AI and guide its outputs. With prompt literacy, people can successfully interact with generative AI to achieve defined objectives, while exercising judgment and responsibility. Prompts serve as an accessible interface between users and automated systems, translating human intents into AI-compatible directives. Effectively crafted prompts are key to enabling generative AI to produce meaningful, targeted results. Just as traditional literacy involves mastering the written word, developing prompt literacy requires learning how to clearly formulate instructions for AI in its processing language. Command of this skill allows humans to reap benefits from AI, directing its open-ended potential to useful and ethical ends through targeted prompts.

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Teaching Responsible AI Use in Classrooms: Resources

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News and media literacy classroom resources for educators. Access lesson plans, classroom activities, posters and infographics, quizzes, training materials and videos for educators teaching news literacy.

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Artificial intelligence technology is not new, but dramatic advances in generative AI have captured the world's attention and are transforming the information landscape.

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In this lesson, students compare AI and human-generated texts to analyze the affordances and limitations of large language models. They'll score, guess origins, and discuss differences, then decide which aspects to adopt or avoid in their writing. The lesson culminates in a discussion of what aspects of the AI-generated writing students should emulate in their own writing and what aspects they should avoid.

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Descriptive and inferential statistics: What's the difference?

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A branch of mathematics, statistics, deals with the collection of data, its analysis and interpretation, and the ways of presenting numerical data. Statistics basically is a collection of data that is quantitative in nature. The subject of Statistics is broadly categorized as theoretical Statistics and Applied Statistics. Applied Statistics is further divided into descriptive statistics and inferential statistics. Let us understand what descriptive and inferential Statistics are and then delve down deeper to understand the differences between descriptive and inferential statistics.

1) What is descriptive statistics?

Descriptive Statistics is also referred to as samples and it determines multiple observations that you take through the research. It is defined as a finding group that fits the research parameters and the groups that are being tested and the use of graphs and stats to summarise the groups' findings. In simple words, descriptive Statistics pairs the findings from a group and reduces them to simple and small major points. In the case of descriptive Statistics, you only test for the results that you get from the relevant individuals. It needs you to test continuously if the result affects a larger population portion.

Conclusions that can be measured with descriptive Statistics are through:

The central tendency is the method of making use of the mean and the median to find the data location on the graph

Dispersion is a way to find the division of the data points from the graph centre. If the number is small then this tells that the dispersion is close to the centre. A large number means that there is a larger space from the graphs' epicentre.

Skewness basically highlights the data point separation that you have measured. It lets you conclude if the data points are skewed or symmetrical from the measurements.

2) What is inferential statistics?

Inferential Statistics is where you take the data got from a sample and make predictions if that influences the findings on a larger population. You can make use of random sampling in order to evaluate the ways in which the different variables lead to making generalizations to do experiments. To make an accurate analysis you will have to find out the population that is being measured and creates a population sample. You then need to incorporate analysis in order to find out the sampling error.

Some ways in which inferential Statistics can be measured is through:

Hypothesis test that determines if the population that is being measured has a high value as compared to the other data points in the analysis. It can also help to conclude if the population varies which is based on the results that you have earned from various experiments.

The confidence interval discovers the error margin in the research and finds out if it affects the testing. You will have to estimate the population range and if it falls under the median or means calculation.

Regression analysis is basically an association between the dependent and the independent variables of the experiment. You need to know the hypothesis test results in order to perform a regression analysis. This lets you know the relationship that is there between the subject matter. A few things that the regression analysis helps to test are the comparison between two sets of populations or maybe the comparison between height and weight of the different genders.

3) Difference between them

Here we list down the differences between descriptive and inferential statistics.

The descriptive analysis gives information about the raw data that describes the data in a particular manner. The inferential analysis makes the inference about a population which is done using the data that is drawn from a population.

Descriptive Statistics helps to organize, analyze, and present the data in a meaningful way. Inferential statistics allows comparing data and making predictions and hypotheses with it.

Descriptive Statistics is used in order to describe a situation whereas inferential Statistics is used to explain the chances of the occurrence of an event

Descriptive Statistics explains the data that is already known and is limited to a population or a sample of a small size. Inferential Statistics tries to reach out to a conclusion about the population.

Descriptive Statistics can be done using graphs, charts, and tables. Inferential Statistics is achieved through probability.

Descriptive Statistics has a tabular or diagrammatic representation of the final result whereas inferential Statistics represents the result in the probability form.

Descriptive Statistics describes the situation where inferential Statistics explains the likelihood if the event will occur.

Descriptive Statistics measures only the group that is assigned for the experiment which means that when you do the descriptive analysis you decide to not consider in the variables. In the case of inferential Statistics, you account for the sampling errors which may make you conduct additional tests that need to be on a large population depending on the amount of data that is required. In other words, you are likely to get a definite calculation when you use descriptive statistics.

Since you are testing the variables using inferential Statistics it is easy to arrive at conclusions when you use descriptive statistics.

Conclusion

Statistics has a very important role to play in the research field. It helps to collect, analyze, and present the data in a form that is measurable. It is difficult to understand if the research lies in descriptive or inferential statistics. This is because people may not really be aware of these two Statistics branches. Descriptive statistics as the name suggests describes the population. On the contrary inferential Statistics is used in order to make a generalization of the population based on the sample. This shows that there is a lot of difference between descriptive and inferential Statistics which basically lies in what you do with the data.

Descriptive statistics is about how you illustrate the current data set whereas inferential stats focus on making an assumption about the extra population which is more than the state of data that is under study. Descriptive Statistics provides a summary of the data that the researcher has studied. Inferential Statistics, however, makes a generalization which is on the data that you have not studied actually. These are the differences between descriptive and inferential statistics.

If you are interested in making it big in the world of data and evolve as a Future Leader, you may consider our Integrated Program in Business Analytics, a 10-month online program, in collaboration with IIM Indore!

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Descriptive and Inferential Statistics - A Comprehensive Guide For 2021

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Here we list down the differences between descriptive and inferential statistics.The descriptive analysis gives information about the raw data that describes the data in a particular manner. The inferential analysis makes the inference about a population which is done using the data that is drawn from a population.

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Want to try the easiest and most fun way to create animated movies ever invented?

This is how easy it is

1. Choose a scene

2. Create your own actors

3. Write your story and let Plotagon make it come to life

4. Save your masterpiece and share it with the world!

Plotagon is an award-winning storytelling tool for all ages. With this app, you essentially have an animation studio in the palm of your hand.

What's on your mind?

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In collaboration with NASA and the Artemis I Mission

Taking STEAM Learning to new heights! LEGO ® Education is teaming up with NASA and the Artemis I team to bring students and teachers an out-of-this-world STEAM learning series. Build to Launch is an exploration of the technology, STEAM concepts and careers behind the Artemis I mission to the Moon. Join the all new LEGO ® Space Team and their Artemis I team counterparts for a 10-week interactive digital learning adventure. Each episode students will find themselves in the shoes of NASA engineers, scientists, and of course astronauts. Through open ended lessons students will get hands-on and solve similar problems the Artemis I team faces as they build towards launch.

In collaboration with NASA and the Artemis I Mission

Taking STEAM Learning to new heights! LEGO ® Education is teaming up with NASA and the Artemis I team to bring students and teachers an out-of-this-world STEAM learning series. Build to Launch is an exploration of the technology, STEAM concepts and careers behind the Artemis I mission to the Moon. Join the all new LEGO ® Space Team and their Artemis I team counterparts for a 10-week interactive digital learning adventure. Each episode students will find themselves in the shoes of NASA engineers, scientists, and of course astronauts. Through open ended lessons students will get hands-on and solve similar problems the Artemis I team faces as they build towards launch.

PLAY

STEAM Practices

Based on STEAM practices and standards, the lessons are designed so each student can:

Ask questions and define problems

Plan and carry out investigations

Develop and use models

Meet design constraints

Evaluate competing design solution

Iteratively test and modify designs

Communicate best fit solutions

Explore cause and effects

Investigate systems and system models

Understand structure and function

...and more!

Kate: Command Pilot

Kate joined the LEGO Space Team in 2020. She likes to ride her motorcycle around the country visiting schools to talk about STEAM learning. Kate also wants to open a sushi and karaoke restaurant called Tunes and Tuna.

Next: Kyle: Mission Specialist

1 of 8 ARROW_RIGHT

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NASA's Artemis Mission: Taking STEAM to new heights!

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LEGO® Education is teaming up with NASA and the Artemis I Team to bring students and teachers an out of this world STEAM Learning series! Build to Launch is an exploration of the technology, STEAM concepts and careers behind the Artemis I mission to the moon!

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Creating Content Made Easy with Book Creator

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Read this free ebook by Tina Peji. Find thousands of free educational ebooks for classroom use at read.bookcreator.com

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Digital Escape Rooms in Google Apps - ISTE Educator Meet Up July 2022

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Technology can create opportunities for students to move beyond engagement in content, where the technology may simply be replacing a traditional method of instruction, but it is not actually doing anything different than the traditional method was doing. We call this the "value-added" aspect of technology. Value-added enhancement of learning through technology is when the tool is somehow aiding, assisting, scaffolding learning in a way that could not easily be done with traditional methods. This is the level where learning can become personalized and more relatable to the learner. This is when technology is really starting to change how learning occurs to make it more meaningful to the learner. Below are three questions that should be asked when measuring for enhancement of learning through technology tools.

Research to Support Enhanced Learning

The research below highlights the research that informs the Triple E component for enhancement.

Enhancement rarely occurs through applications that only use "drill and practice" methods

​"Drill and practice" software has not been successful in showing positive achievements for student learning outcomes (Wenglinsky, 1998).

Enhancement encourages the use of technology to add-value by allowing students to explore, create and problem-solve (higher-level thinking)

Digital technology use for creating and exploring rather than Drill and Practice, have been found to positively effect student achievement while drill and practice has had negative effects on student achievement scores (National Association of Educational Progress, NAEP via Wenglinsky, 2006).

Supporting or scaffolding technology that creates opportunities for children deepen their learning through social use (e.g., Hirsh-Pasek et al., 2015; Guernsey,2012; Takeuchi & Stevens, 2011).

Value-added strategies such as promoting student self-reflection, self-assessment, and self-explanation through technology can enhance learning outcomes (Means et al. 2009).

Enhancement encourages the quality of use over the quantity

Studies are finding that the quality of work done with computers is much more important to determining student achievement than the quantity of time spent with devices (Wenglinsky, 2006).

OECD Report found that of 70 countries, the top performing countries on the PISA exam (math and literacy), were not the countries that had students using technology the most often in their learning. In math, the top performances on the paper-based math exams were achieved by the students who had the very lowest use of computers in school learning (OECD, 2015).

Classroom Project that Enhances Learning

Enhancement Checklist

1. Does the technology tool aid students in developing or demonstrating a more sophisticated understanding of the content? (creates opportunities for creation/production over consumption) By students using technology to research their road trip (using authentic websites to reserve hotels, pay for meals, gas...etc), they are able to assess their understanding of rates, proportions, percents in mathematics with authentic data that connects to the real world (rather than a worksheet). They are using their higher order thinking cognitive skills of analysis, creativity and evaluation.

2. Does the technology create scaffolds to make it easier to understand concepts or ideas? The students were able to use technology to better see and experience the connections between math, geography, and social studies in everyday life. They are no longer isolated workbooks or class activities.

3. Does the technology create paths for students to demonstrate their understanding of the learning goals in a way that they could not do with traditional tools? There was a lot of choice available because the students could select where to go, what websites and digital resources to use to help aid in their development of the trip. Creation, critical thinking, and construction were all important skills that were enhanced with the aid of technology tools.

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Technology can create opportunities for students to move beyond engagement in content, where the technology may simply be replacing a traditional method of instruction, but it is not actually doing...

# data[].attributes.attachment_link.readable_text
Technology can create opportunities for students to move beyond engagement in content, where the technology may simply be replacing a traditional method of instruction, but it is not actually doing anything different than the traditional method was doing. We call this the "value-added" aspect of technology. Value-added enhancement of learning through technology is when the tool is somehow aiding, assisting, scaffolding learning in a way that could not easily be done with traditional methods. This is the level where learning can become personalized and more relatable to the learner. This is when technology is really starting to change how learning occurs to make it more meaningful to the learner. Below are three questions that should be asked when measuring for enhancement of learning through technology tools.

Research to Support Enhanced Learning

The research below highlights the research that informs the Triple E component for enhancement.

Enhancement rarely occurs through applications that only use "drill and practice" methods

​"Drill and practice" software has not been successful in showing positive achievements for student learning outcomes (Wenglinsky, 1998).

Enhancement encourages the use of technology to add-value by allowing students to explore, create and problem-solve (higher-level thinking)

Digital technology use for creating and exploring rather than Drill and Practice, have been found to positively effect student achievement while drill and practice has had negative effects on student achievement scores (National Association of Educational Progress, NAEP via Wenglinsky, 2006).

Supporting or scaffolding technology that creates opportunities for children deepen their learning through social use (e.g., Hirsh-Pasek et al., 2015; Guernsey,2012; Takeuchi & Stevens, 2011).

Value-added strategies such as promoting student self-reflection, self-assessment, and self-explanation through technology can enhance learning outcomes (Means et al. 2009).

Enhancement encourages the quality of use over the quantity

Studies are finding that the quality of work done with computers is much more important to determining student achievement than the quantity of time spent with devices (Wenglinsky, 2006).

OECD Report found that of 70 countries, the top performing countries on the PISA exam (math and literacy), were not the countries that had students using technology the most often in their learning. In math, the top performances on the paper-based math exams were achieved by the students who had the very lowest use of computers in school learning (OECD, 2015).

Classroom Project that Enhances Learning

Enhancement Checklist

1. Does the technology tool aid students in developing or demonstrating a more sophisticated understanding of the content? (creates opportunities for creation/production over consumption) By students using technology to research their road trip (using authentic websites to reserve hotels, pay for meals, gas...etc), they are able to assess their understanding of rates, proportions, percents in mathematics with authentic data that connects to the real world (rather than a worksheet). They are using their higher order thinking cognitive skills of analysis, creativity and evaluation.

2. Does the technology create scaffolds to make it easier to understand concepts or ideas? The students were able to use technology to better see and experience the connections between math, geography, and social studies in everyday life. They are no longer isolated workbooks or class activities.

3. Does the technology create paths for students to demonstrate their understanding of the learning goals in a way that they could not do with traditional tools? There was a lot of choice available because the students could select where to go, what websites and digital resources to use to help aid in their development of the trip. Creation, critical thinking, and construction were all important skills that were enhanced with the aid of technology tools.

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Technology can create opportunities for students to move beyond engagement in content, where the technology may simply be replacing a traditional method of instruction, but it is not actually doing...

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Choosing & Using Sources: A Guide to Academic Research - Open Textbook

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Engaging graphics, compelling examples, and easy-to-understand explanations make Choosing and Using Sources: A Guide to Academic Research , your most valuable, open access resource for completing research-based writing assignments and projects.

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Research validity in surveys relates to the extent at which the survey measures right elements that need to be measured. In simple terms, validity refers to how well an instrument as measures what it is intended to measure.

Reliability alone is not enough, measures need to be reliable, as well as, valid. For example, if a weight measuring scale is wrong by 4kg (it deducts 4 kg of the actual weight), it can be specified as reliable, because the scale displays the same weight every time we measure a specific item. However, the scale is not valid because it does not display the actual weight of the item.

Research validity can be divided into two groups: internal and external. It can be specified that "internal validity refers to how the research findings match reality, while external validity refers to the extend to which the research findings can be replicated to other environments" (Pelissier, 2008, p.12).

Moreover, validity can also be divided into five types:

1. Face Validity is the most basic type of validity and it is associated with a highest level of subjectivity because it is not based on any scientific approach. In other words, in this case a test may be specified as valid by a researcher because it may seem as valid, without an in-depth scientific justification.

Example: questionnaire design for a study that analyses the issues of employee performance can be assessed as valid because each individual question may seem to be addressing specific and relevant aspects of employee performance.

2. Construct Validity relates to assessment of suitability of measurement tool to measure the phenomenon being studied. Application of construct validity can be effectively facilitated with the involvement of panel of 'experts' closely familiar with the measure and the phenomenon.

Example: with the application of construct validity the levels of leadership competency in any given organisation can be effectively assessed by devising questionnaire to be answered by operational level employees and asking questions about the levels of their motivation to do their duties in a daily basis.

3. Criterion-Related Validity involves comparison of tests results with the outcome. This specific type of validity correlates results of assessment with another criterion of assessment.

Example: nature of customer perception of brand image of a specific company can be assessed via organising a focus group. The same issue can also be assessed through devising questionnaire to be answered by current and potential customers of the brand. The higher the level of correlation between focus group and questionnaire findings, the high the level of criterion-related validity.

4. Formative Validity refers to assessment of effectiveness of the measure in terms of providing information that can be used to improve specific aspects of the phenomenon.

Example: when developing initiatives to increase the levels of effectiveness of organisational culture if the measure is able to identify specific weaknesses of organisational culture such as employee-manager communication barriers, then the level of formative validity of the measure can be assessed as adequate.

5. Sampling Validity (similar to content validity) ensures that the area of coverage of the measure within the research area is vast. No measure is able to cover all items and elements within the phenomenon, therefore, important items and elements are selected using a specific pattern of sampling method depending on aims and objectives of the study.

Example: when assessing a leadership style exercised in a specific organisation, assessment of decision-making style would not suffice, and other issues related to leadership style such as organisational culture, personality of leaders, the nature of the industry etc. need to be taken into account as well.
My e-book, The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance offers practical assistance to complete a dissertation with minimum or no stress. The e-book covers all stages of writing a dissertation starting from the selection to the research area to submitting the completed version of the work within the deadline. John Dudovskiy

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Research validity in surveys relates to the extent at which the survey measures right elements that need to be measured. In simple terms, validity refers to how well an instrument as measures what it is intended to measure. Reliability alone is not enough, measures need to be reliable, as well as, valid.

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When you do quantitative research, you have to consider the reliability and validity of your methods and instruments of measurement.

Validity tells you how accurately a method measures something. If a method measures what it claims to measure, and the results closely correspond to real-world values, then it can be considered valid. There are four main types of validity:

Note that this article deals with types of test validity, which determine the accuracy of the actual components of a measure. If you are doing experimental research, you also need to consider internal and external validity, which deal with the experimental setup and the generalizability of results.

Construct validity

Construct validity evaluates whether a measurement tool really represents the thing we are interested in measuring. It's central to establishing the overall validity of a method.

What is a construct?

A construct refers to a concept or characteristic that can't be directly observed, but can be measured by observing other indicators that are associated with it.

Constructs can be characteristics of individuals, such as intelligence, obesity, job satisfaction, or depression; they can also be broader concepts applied to organizations or social groups, such as gender equality, corporate social responsibility, or freedom of speech.

Example

There is no objective, observable entity called "depression" that we can measure directly. But based on existing psychological research and theory, we can measure depression based on a collection of symptoms and indicators, such as low self-confidence and low energy levels.

What is construct validity?

Construct validity is about ensuring that the method of measurement matches the construct you want to measure. If you develop a questionnaire to diagnose depression, you need to know: does the questionnaire really measure the construct of depression? Or is it actually measuring the respondent's mood, self-esteem, or some other construct?

To achieve construct validity, you have to ensure that your indicators and measurements are carefully developed based on relevant existing knowledge. The questionnaire must include only relevant questions that measure known indicators of depression.

The other types of validity described below can all be considered as forms of evidence for construct validity.

Content validity

Content validity assesses whether a test is representative of all aspects of the construct.

To produce valid results, the content of a test, survey or measurement method must cover all relevant parts of the subject it aims to measure. If some aspects are missing from the measurement (or if irrelevant aspects are included), the validity is threatened.

Example

A mathematics teacher develops an end-of-semester algebra test for her class. The test should cover every form of algebra that was taught in the class. If some types of algebra are left out, then the results may not be an accurate indication of students' understanding of the subject. Similarly, if she includes questions that are not related to algebra, the results are no longer a valid measure of algebra knowledge.

Face validity

Face validity considers how suitable the content of a test seems to be on the surface. It's similar to content validity, but face validity is a more informal and subjective assessment.

Example

You create a survey to measure the regularity of people's dietary habits. You review the survey items, which ask questions about every meal of the day and snacks eaten in between for every day of the week. On its surface, the survey seems like a good representation of what you want to test, so you consider it to have high face validity.

As face validity is a subjective measure, it's often considered the weakest form of validity. However, it can be useful in the initial stages of developing a method.

Criterion validity

Criterion validity evaluates how closely the results of your test correspond to the results of a different test.

What is a criterion?

The criterion is an external measurement of the same thing. It is usually an established or widely-used test that is already considered valid.

What is criterion validity?

To evaluate criterion validity, you calculate the correlation between the results of your measurement and the results of the criterion measurement. If there is a high correlation, this gives a good indication that your test is measuring what it intends to measure.

Example

A university professor creates a new test to measure applicants' English writing ability. To assess how well the test really does measure students' writing ability, she finds an existing test that is considered a valid measurement of English writing ability, and compares the results when the same group of students take both tests. If the outcomes are very similar, the new test has a high criterion validity.

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The 4 Types of Validity | Explained with Easy Examples

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When you do quantitative research, you have to consider the reliability and validity of your methods and instruments of measurement. Validity tells you how accurately a method measures something. If a method measures what it claims to measure, and the results closely correspond to real-world values, then it can be considered valid.

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Reliability refers to whether or not you get the same answer by using an instrument to measure something more than once. In simple terms, research reliability is the degree to which research method produces stable and consistent results.

A specific measure is considered to be reliable if its application on the same object of measurement number of times produces the same results.

Research reliability can be divided into three categories:

1. Test-retest reliability relates to the measure of reliability that has been obtained by conducting the same test more than one time over period of time with the participation of the same sample group.

Example: Employees of ABC Company may be asked to complete the same questionnaire about employee job satisfaction two times with an interval of one week, so that test results can be compared to assess stability of scores.

2. Parallel forms reliability relates to a measure that is obtained by conducting assessment of the same phenomena with the participation of the same sample group via more than one assessment method.

Example: The levels of employee satisfaction of ABC Company may be assessed with questionnaires, in-depth interviews and focus groups and results can be compared.

3. Inter-rater reliability as the name indicates relates to the measure of sets of results obtained by different assessors using same methods. Benefits and importance of assessing inter-rater reliability can be explained by referring to subjectivity of assessments.

Example: Levels of employee motivation at ABC Company can be assessed using observation method by two different assessors, and inter-rater reliability relates to the extent of difference between the two assessments.

4. Internal consistency reliability is applied to assess the extent of differences within the test items that explore the same construct produce similar results. It can be represented in two main formats.

a) average inter-item correlation is a specific form of internal consistency that is obtained by applying the same construct on each item of the test

b) split-half reliability as another type of internal consistency reliability involves all items of a test to be 'spitted in half'.
My e-book, The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance offers practical assistance to complete a dissertation with minimum or no stress. The e-book covers all stages of writing a dissertation starting from the selection to the research area to submitting the completed version of the work within the deadline. John Dudovskiy

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Reliability refers to whether or not you get the same answer by using an instrument to measure something more than once. In simple terms, research reliability is the degree to which research method produces stable and consistent results. A specific measure is considered to be reliable if its application on the same object of measurement number of times produces the same results.

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The term reliability in psychological research refers to the consistency of a quantitative research study or measuring test. For instruments like questionnaires, reliability ensures that responses are consistent across times and occasions. Multiple forms of reliability exist, including test-retest, inter-rater, and internal consistency.

For example, if a person weighs themselves during the day, they would expect to see a similar reading. Scales that measured weight differently each time would be of little use.

The same analogy could be applied to a tape measure that measures inches differently each time it is used. It would not be considered reliable.

If findings from research are replicated consistently, they are reliable. A correlation coefficient can be used to assess the degree of reliability. If a test is reliable, it should show a high positive correlation.

Of course, it is unlikely the same results will be obtained each time as participants and situations vary. Still, a strong positive correlation between the same test results indicates reliability.

There are two types of reliability: internal and external.

Split-Half Method

The split-half method assesses the internal consistency of a test, such as psychometric tests and questionnaires.

There, it measures the extent to which all parts of the test contribute equally to what is being measured.

Here's how it works:

1. A test or questionnaire is split into two halves, typically by separating even-numbered items from odd-numbered items, or half half items vs second half.

2. Each half is scored separately, and the scores are correlated using a statistical method, often Pearson's correlation.

3. The correlation between the two halves gives an indication of the test's reliability. A higher correlation suggests better reliability.

4. To adjust for the test's shortened length (because we've split it in half), the Spearman-Brown prophecy formula is often applied to estimate the reliability of the full test based on the split-half reliability.

The reliability of a test could be improved by using this method. For example, any items on separate halves of a test with a low correlation (e.g., r = .25) should either be removed or rewritten.

The split-half method is a quick and easy way to establish reliability. However, it can only be effective with large questionnaires in which all questions measure the same construct. This means it would not be appropriate for tests that measure different constructs.

For example, the Minnesota Multiphasic Personality Inventory has sub scales measuring differently behaviors such as depression, schizophrenia, social introversion. Therefore the split-half method was not be an appropriate method to assess reliability for this personality test.

Test-Retest

The test-retest method assesses the external consistency of a test. Examples of appropriate tests include questionnaires and psychometric tests. It measures the stability of a test over time.

A typical assessment would involve giving participants the same test on two separate occasions. If the same or similar results are obtained, then external reliability is established.

Here's how it works:

1. A test or measurement is administered to participants at one point in time.

2. After a certain period, the same test is administered again to the same participants without any intervention or treatment in between.

3. The scores from the two administrations are then correlated using a statistical method, often Pearson's correlation.

4. A high correlation between the scores from the two test administrations indicates good test-retest reliability, suggesting the test yields consistent results over time.

This method is especially useful for tests that measure stable traits or characteristics that aren't expected to change over short periods. The disadvantage of the test-retest method is that it takes a long time for results to be obtained. The reliability can be influenced by the time interval between tests and any events that might affect participants' responses during this interval.

Beck et al. (1996) studied the responses of 26 outpatients on two separate therapy sessions one week apart, they found a correlation of .93 therefore demonstrating high test-restest reliability of the depression inventory.

This is an example of why reliability in psychological research is necessary, if it wasn't for the reliability of such tests some individuals may not be successfully diagnosed with disorders such as depression and consequently will not be given appropriate therapy.

The timing of the test is important; if the duration is too brief, then participants may recall information from the first test, which could bias the results.

Alternatively, if the duration is too long, it is feasible that the participants could have changed in some important way which could also bias the results.

The test-retest method assesses the external consistency of a test. This refers to the degree to which different raters give consistent estimates of the same behavior. Inter-rater reliability can be used for interviews.

Inter-Rater Reliability

Inter-rater reliability, often termed inter-observer reliability, refers to the extent to which different raters or evaluators agree in assessing a particular phenomenon, behavior, or characteristic. It's a measure of consistency and agreement between individuals scoring or evaluating the same items or behaviors.

High inter-rater reliability indicates that the findings or measurements are consistent across different raters, suggesting the results are not due to random chance or subjective biases of individual raters.

Statistical measures, such as Cohen's Kappa or the Intraclass Correlation Coefficient (ICC), are often employed to quantify the level of agreement between raters, helping to ensure that findings are objective and reproducible.

Ensuring high inter-rater reliability is essential, especially in studies involving subjective judgment or observations, as it provides confidence that the findings are replicable and not heavily influenced by individual rater biases.

Note it can also be called inter-observer reliability when referring to observational research. Here, researchers observe the same behavior independently (to avoid bias) and compare their data. If the data is similar, then it is reliable.

Where observer scores do not significantly correlate, then reliability can be improved by:

Training observers in the observation techniques and ensuring everyone agrees with them.

Ensuring behavior categories have been operationalized. This means that they have been objectively defined.

For example, if two researchers are observing 'aggressive behavior' of children at nursery they would both have their own subjective opinion regarding what aggression comprises.

In this scenario, they would be unlikely to record aggressive behavior the same, and the data would be unreliable.

However, if they were to operationalize the behavior category of aggression, this would be more objective and make it easier to identify when a specific behavior occurs.

For example, while "aggressive behavior" is subjective and not operationalized, "pushing" is objective and operationalized. Thus, researchers could count how many times children push each other over a certain duration of time.

Validity vs. Reliability In Psychology

In psychology, validity and reliability are fundamental concepts that assess the quality of measurements.

Validity pertains to the accuracy of an instrument. It addresses whether the test measures what it claims to measure. Different forms include content, criterion, construct, and external validity.

Reliability concerns the consistency of an instrument. It evaluates whether the test yields stable and repeatable results under consistent conditions. Types of reliability include test-retest, inter-rater, and internal consistency.

A pivotal understanding is that reliability is a necessary but not sufficient condition for validity.

It means a test can be reliable, consistently producing the same results, without being valid, or accurately measuring the intended attribute.

However, a valid test, one that truly measures what it purports to, must be reliable. In the pursuit of rigorous psychological research, both validity and reliability are indispensable.

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Reliability in Psychology Research: Definitions & Examples

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The term reliability in psychological research refers to the consistency of a quantitative research study or measuring test. For instruments like questionnaires, reliability ensures that responses are consistent across times and occasions. Multiple forms of reliability exist, including test-retest, inter-rater, and internal consistency.

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It's undeniable that the pandemic changed the way we teach, learn, work, and live, but when some people returned to in-person learning and their schools, it seemed they could use some advice on digital etiquette for the new, and extremely connected, world in which we are now operating. This is a world where at any time you may be meeting or teaching in-person, via video, phone, or a combination thereof at the same time.

While adapting was easier for some, others could use a bit of help. For those people, you may want to share or discuss these tips with them.

Digital Etiquette Tip 1: Use Earbuds / Headphones

There is never a time when you are in the company of others that you should listen to a device through the device. Lowering the volume also doesn't work. If you don't wear earbuds or headphones, you may come off as inconsiderate.

2: Multitask Mindfully if You Must

You may think that you are not captain obvious when you are doing something unrelated to the work at hand. However, usually, you are. If you must multitask on your phone, laptop, or other device, let the person in charge and those you are meeting with know, and give you feedback if it is okay or if it is better you don't participate.

3: Know How to Handle Hybrid

While remote was king in the first year or so of the pandemic, hybrid is now the norm. It's beneficial to know how to do this effectively. Learn to use your camera to livestream and even record meetings, lessons, conversations. If your district prioritizes this, there are products such as (opens in new tab), (opens in new tab), and (opens in new tab) that make this easy peasy. Having a backchannel for chat, insights, and feedback has many advantages. Have a moderator for this. They can bring any questions or comments to the attention of the presenter and/or participants as needed.

4: Ask If It's Okay to Pop On By

Whether it's a student or a staff member doing deep work it is important to respect their time. While some may not mind unexpected interruptions, others may. It's best to ask rather than just popping over to someone. If they're okay with that, great. If not, let them know when you plan to connect in advance and make sure that time works for them. This is true whether you're popping by in-person or connecting via video or phone conference. Respect the time and work schedule of others, know how to use digital calendars, and determine a time that is mutually convenient.

5: Courteous Calendaring

Calendaring technology, such as Calendly (opens in new tab), makes scheduling easy. Use calendars to coordinate and book meetings and events. Know how to read the calendars of others to know when they are free rather than asking. Don't book someone when they are already booked. Staff should also know how to share their calendar so it is visible to colleagues. This can also apply in school settings. Get rid of the bells and teach students and staff how to use a calendar to coordinate where they are going when.

6: People Over Phones

When you are in-person be with the persons you are with and put away the phones unless it is a part of what the group is doing together. If you think you must use your phone (relative in the hospital, sick child, etc.), then explain this to others and be discreet.

7: Conscious Camera Connecting

How do we find the right balance between Zoom fatigue (opens in new tab) and connection with cameras on? The answer is to choose consciously. If it's an ongoing meeting or class, you may want to discuss norms with participants. For example, you can acknowledge that having the camera on for everyone can be exhausting. Perhaps, you ask that cameras come on when folks speak. Or, cameras can be on in certain types of video conferencing and not others. Not talking about it can lead to discomfort. Instead, talk. Discuss. Create norms and figure out what makes sense for people. The organizer of the activity should share expectations up front, but be open if some folks have preferences or sensitivities.

Never attach files when sharing. Instead share links. Why? Attachments often have a variety of issues including version control, ability to access from any device, storage waste, and more. Additionally, if you mention a document when communicating, link to it. You can create links using a variety of platforms such as (opens in new tab), (opens in new tab), or (opens in new tab). Simply upload your file to the desired platform and access a copy of the link. Make sure you check visibility and share the file with the correct audience.

9: Interact

Learning and meetings are more effective when participants react and interact rather than sit back as passive participants. If you are leading the meeting or lesson, encourage the use of emojis or hand signals. Use polls to get reactions from those in attendance. Create time for whole and/or small group discussion. Use tools such as (opens in new tab) for folks to create and other tools to collaborate such as (opens in new tab) or a digital whiteboard.

As we move to a new normal that values digital teaching, learning, and working, it is more important than ever to integrate digital etiquette into our work, and into our students' work. Each of these tips will be crucial to ensure we all are as successful and effective as possible in the work we do with our colleagues and students.

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It's undeniable that the pandemic changed the way we teach, learn, work, and live, but when some people returned to in-person learning and their schools, it seemed they could use some advice on digital etiquette for the new, and extremely connected, world in which we are now operating.

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QR codes are a class of easy-to-read barcodes that can be read by your phone's camera to generate links. These can be a great way to easily distribute documents, quizzes, surveys, multimedia links, and all manner of handouts.

Though QR codes have been widely available for more than a decade, they have seen a surge in popularity in recent years, showing up everywhere from your local restaurant to TV commercials and, of course, in the classroom.

As any teacher will tell you, many students want to use their phones in class. Utilizing QR technology can help educators allow students to keep their phones in hand while also directing them to important educational material.

You can also have students create their own QR codes to gain tech skills as they share their work with you and with classmates.

Here are some of the best free sites for generating QR code links for teaching.

This free QR code generator lets users customize the color and design style of their QR codes. More ambitious users can also upload logos and pictures to be incorporated as part of their QR code. The code that is generated can be saved as a .PDF, .PNG, .EPS, or .SVG file.

Another free and easy-to-use dynamic QR code generator, Flowcode requires users to signup via their email or Facebook. While this adds a step to the process, the QR code generated is then emailed to the user, which is very convenient.

Graphics and multimedia giant Adobe offers a straightforward free QR generator that gives users the ability to choose the color and style of their QR code. You can't upload your own image or logo and may not be able to get as fancy as with some other QR code generators, but the stripped-down format of this QR code generator makes it even more user-friendly and quick to generate a QR code.

This free app allows Windows users to generate QR codes from their PCs and mobile devices. It is available for Android, iOS, and macOS M1. To find it, search 'CODEX QR' on the Play Store/App Store.

The free version of this QR generator is simple to use and allows you to upload an image or logo into the QR code you generate without needing to create an account. Simply copy and paste the desired URL, then click "generate QR code." Adding a logo is also easy and can be done straight from the home page. If you subscribe to QR Tiger, you can create dynamic QR codes that allow you to track data about time and location when a QR code is scanned, which could be helpful to teachers looking to track whether students are utilizing a specific resource.

Create customizable free QR codes in moments with this site. You can customize the look and feel of your code by choosing its color, design, and frame (the box around the QR code). The site also offers templates for generating QR codes that lead directly to Zoom meetings, calendar invites, or WiFi network logins, so there's plenty of options for educators to choose from.

Another free QR code-generating site that lives up to its name, Free-qr-code.net allows users to create QR codes in a fast and easy manner. The site also features several customizable elements such as the option to add a logo and choose a color, plus several QR code design templates.

The free version of this site allows you to create quick QR codes for all your initial needs. However, if you want to take your QR code a step further and create dynamic QR codes, you'll need to subscribe. Dynamic QR codes have features such as data tracking and the ability to send existing QR codes to new URLs, a great feature for an educator who wants to use the same printed materials but update resources for a class.

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QR codes are a class of easy-to-read barcodes that can be read by your phone's camera to generate links. These can be a great way to easily distribute documents, quizzes, surveys, multimedia links, and all manner of handouts.

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Matt:
Hello SEL education community, my name is Matt Pearsall. I am the community manager here in the SEL and education community and I am really excited to be able to share with you today at the beginning the inauguration of our of our new speaker series when we start- we're having a regular series of community members and other people coming in and talking to us giving brief talks around various different topics on social emotional learning and I am not only excited to be kicking off this event but also really excited to be able to kick off at this event featuring somebody who had a chance to meet here before A long time SEL champion in the SEL education community, Lynn Thomas. And so we're gonna be talking about supporting learner variability and without further ado I wanto kind of introduce you all to Lynn Lynn can you tell everybody a little bit about yourself before we jump in?

Lynn:
Hi I'm Lynn Thomas I'd love to Matt. I'm really happy to be here. Really excited about speaking to everybody I'm an ed secondary school english teacher from dunville ontario and I'm also an HP Teaching Fellow and I really advocate for mental health support and mental wellness and social emotional learning. I'm really excited to be here today.

Great! And so this topic of supporting learner variability one of the things on it that I really appreciated when I heard that you wanted to talk about this was that this is something that we all, we, every educator deals with every single day and so kind of hearing how you this connection you found in a little bit you were telling me about it before we started got me really excited. So can you tell us a little bit more about about this this this tool that you've been using and and why it's so exciting?

Well yes definitely. I'm really excited to share it with you so um it's a tool that was introduced to me through being an HP Teaching Fellow and it's something that has been created by Digital Promise who are a non-profit organization who research and try and fill the digital learning gap. And the wonderful thing about it is like learner variability as we all know our kids come to school with all kinds of stuff in their backpack and everybody learns different and we try to adjust and do everything in our programs to try and support all those students and that's a real feat how do you do it for you know 30 odd kids in a room and that kind of thing and a lot of times it can be overwhelming when we try and think about well but how do I account for trauma? How do I account for social emotional learning? how do I account for any cognitive issues? How do I account for background knowledge? You know English language learner, there's so many things that it can feel overwhelming.

And how do you put all that together so the really cool thing about it - and it's called the Learner Variability Navigator - is that it does put all those things together and I love the fact that a lot of times we often think about when we want to do a social emotional learning activity it's very explicit and what I love about this is it offers strategies that are based on research to support any of the different variables or factors that affect learning. And it gives you teaching strategies and methodologies that support those things so you can build it as a thread throughout your program, like every single day and every single lesson without feeling like you're adding more. You know it's switching to how you teach something as opposed to teaching one more thing. And I think that sometimes can really you know it's it's a hard thing to figure out how to do. And you know what are those things it supports so well.

Matt: I think we got you got muted there Lynn there we go you're back

Lynn: okay so I'm having trouble picking which screen I want. That's the one. I got it. Okay sharing. Okay is it right can you see the Learner Variability Navigator? Yep okay.

So this is the Digital Promise's Learner Variability Project. As I said, Digital Promise is an independent nonprofit and their mission is to accelerate innovation and improve opportunities for learning. So basically, what they've done is they've taken research and put it at our fingertips. This is open source and free for all educators. So, you can see as we move down through their research, they've defined basically four pillars that are the main areas that they look at.

So you know here we have social emotional learning, and but we also have content cognition and student background. And then what they did is created looked at those pillars and looked at them in these different models. So they've broken it down basically into kind of numeracy and literacy, which basically they can hit on every single subject. Right, so for ease and because it's the one I'm most familiar with. So you know we'll have a look at the grade 7-12 model and explore the factors. So the first time I saw this, I was blown away by this part so here you can see the four pillars divided in the columns and you can see the factors that they discovered affected learning the most what's really marvelous is when I hover over any one of these factors you can see how some fade out and highlight and it shows automatically right there visually how they're interconnected. And I thought that was just brilliant because sometimes we would forget like you know I wouldn't have thought reading fluency would be affected that much by social emotional learning right and it really emphasized the importance of integrating everything together to support the whole child. And you know you can see like hearing is a factor you know it. I thought it was marvelous, but it gets better.

So on any one of these I can click on and it will take me to a summary page. And then basically outlines what the factor is here it can go it goes into a little more deeper explanation about those connections you know critical literacy so it talks about why is emotion why does critical literacy get affected by emotion you know why does competition get affected so those it really helps. It's, it's like the best teacher PDA out there, I think also.

And again explains all the main ideas so in emotion and if you continue down the page it gives you lots of opportunities to learn more. And I like this - the view measures and references. And it's a little different on for each of the factors, but what's wonderful is one you could dig into the references if you wanted to, but it also gives you measures. So sometimes, these are specific sorts of assessments that you could use in the classroom sometimes they're more specialized where it might be your school psychologist or something like that would deliver and interpret these sorts of assessments but there's a lot of them that the classroom teacher could utilize to then give themselves a better base of understanding so then if we go back and as I said sometimes there's a couple of different measures in there and and then you can see it goes into what are the strategies for this factor and before we get into there I will go back up to the top and you'll notice here we have strategies. So I'll show you that and again here we can see all the different areas down the left hand side and on the right hand side we see all the various strategies again that have been extensively researched and you can see just by the color coding what ones support each of the different factors and for example we can look at annotating. And again like before when I click on annotating I'm taken to a summary page that gives me an overview of what is this strategy and what is it like. But it's really awesome because it then gives me a perfect like a lovely example of it in action in a classroom. It also on the right hand side gives me an example of a technology tool that does a really good job in supporting this specific factor, so you know if you want to need to want to etcetera integrate technology you can find out what ones are really good at supporting that factor.

And as before you there's a ton of examples so you can really learn how are people using this strategy in their classroom and find something that really works for you and learn about it better and even dig into more research if you want to go down rabbit hole, which I have you know so and you can really find out different strategies and what they look like and how successful they can be and work in the classroom.

And finally up here in explorers what's really cool is you can create your own workspace and I'm just gonna show you directly the workspace that I created and what it does. Basically, it's you can go and select five or six factors that maybe you want to focus in on. You know, your class needs etc and that's what I did with this where I was given a new course to start this year our whole board is shifting our grade english courses to indigenous literature and so looking at that coming into coming back to school this year obviously I had a lot of things that I had to think about so I selected specific factors that I thought were going to be really important. So background knowledge because it's kind of lacking critical literacy always important in the english classroom but I also looked at given the emotions and adverse experiences and it's great because this workspace you can give annotation notes so you know I thought okay there's a lot of things that might be triggering just because of the subject matter this year emotions are probably going to be a big factor because of coming out of you know isolation etc and you can share the workspace so you could collaborate with colleagues wow you can just share it straight as a view viewing piece and the strategies that it came up with now it gives me a really great panorama I guess strategies that I can use and build on in my classroom so I know I'm supporting those different factors throughout what I'm teaching, no matter what the content material is.

This is really cool. This is, it's amazing yeah - the depth and breadth has just been phenomenal and the learning possibilities like as a teacher to see how those things are connected and learn the strategies that can support so many different things at the same time is just phenomenal. Yeah I think I mean one of the most powerful things I think from this is I hear a lot, I hear people saying "Well how do we move social motion learning into the classroom?" and I think there's a lot of real there's a lot of high level ways that we talk about that a lot but this really makes it very concrete it's like here's this teaching strategy that that probably most educators will recognize They'll say "oh I already do that, yeah like a gallery walk." How many of us do gallery walks all the time? Well now it's like, "Oh look at that, it supports emotion and it supports motivation. Wow, I wouldn't have thought that." Yeah right - or a guided inquiry. Like, "oh it didn't occur to me that that could be a social emotional learning tool."

Lynn: Yeah and and when when when when we kind of are aware of that then we can be a lot more intentional about how we're approaching it and saying that I'm not just doing this as an academic exercise I'm doing it as a social emotional learning exercise at the same time.

Yeah. Yeah, and I thought it was really cool you know obviously we still need those explicit times where you know maybe we're looking at the vocabulary and the social emotional word wheel or you know and that check-in and that kind of thing but to then carry it throughout the day in the various ways that you teach I think is just phenomenal. Yeah, wow. I really appreciate you you sharing this with us. I think I'd like to ask just one one question here at the end before we before we wrap up and say that that for people approaching this for the first time, what's the what's the where should they start? What's the what's the what's the first place they should go to, you know, What I - just again - it's pretty straightforward how they have it set up is just go to the Learner Variability Project, and I believe you put that n the chat for people to grab and I also gave you a link to a slideshow. Oh yeah let me put that I I made surrounding the learner Navigator Yeah sorry the Learner Variability Navigator and there's a ton of links in there and one specific link at the end resources is basically kind of a one-pager of how to get started and how to create your own workspace. And it's like a one-pager and there's a ton more examples of workspaces that are really really helpful to see how people have utilized it like one teacher used it and sent the link home of her workspace because it explained to the parents all the different strategies and factors

That is a really cool yeah really neat idea because I feel like that's that's something that that's often a real that's a it's a gap in communication between families and educators about about why are we doing things what are the what are the reasons what are the reasons that we do this why does education look different than it used to that sort of those sort of conversations though yeah exactly exactly. So you know there's a wide array of ways that you can use it you know for for your own learning to improve your own practice but also to reach out and make connections with your parents and community

Matt: Well thank you so much for sharing this Lynn, I know the thing I'm going to dig into in this as soon as we get off of here is I'm going to go look at the assessment tools that are laid out in there because that is something that I come that comes up all the time about what are some different ways that we can assess things that are that are they can be done alongside academics. This would be is going to be really useful to a lot of people. That's where I'm headed, yeah for sure.

Lynn: And like I said you could get lost going down the rabbit hole in this Navigator, but it's well worth it.

Matt: Cool! Well again Lynn, thank you so much. I really appreciate you joining us, and for those of you watching at home, I just wanna remind everyone that this is the this is the first of our of our social emotional learning kind of speaker series we're having in the SEL and education community you can continue the conversation right here you see the link to our group. We'd love to see you there. We'll be doing more of these. We've got another one coming up a week from from today with JV Johnson talking about emotional motion management. So, without further ado thank you very much, and we will see you all next week take care everybody. Thank you, Lynn.

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Learner Variability Navigator | Learner Variability Project

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Matt: Hello SEL education community, my name is Matt Pearsall.

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The UDL Guidelines are a tool used in the implementation of Universal Design for Learning, a framework to improve and optimize teaching and learning for all people based on scientific insights into how humans learn. Learn more about the Universal Design for Learning framework from CAST. The UDL Guidelines can be used by educators, curriculum developers, researchers, parents, and anyone else who wants to implement the UDL framework in a learning environment. These guidelines offer a set of concrete suggestions that can be applied to any discipline or domain to ensure that all learners can access and participate in meaningful, challenging learning opportunities.

Reenvisioning the UDL Guidelines

Because the UDL Guidelines are meant to be informed by feedback from the field as well as new research, they have been updated several times in the past. We are in the process of updating the Guidelines once again in our UDL Rising to Equity initiative.

This update will focus specifically on addressing systemic barriers that result in inequitable learning opportunities and outcomes. CAST aims to develop a transparent, inclusive, and community-driven process. If you are interested in collaborating and staying updated on our progress, we invite you to complete a brief survey.

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The UDL Guidelines are a tool used in the implementation of Universal Design for Learning, a framework to improve and optimize teaching and learning for all people based on scientific insights into how humans learn. Learn more about the Universal Design for Learning framework from CAST. The UDL Guidelines can be used by educators, curriculum developers, researchers, parents, and anyone else who wants to implement the UDL framework in a learning environment. These guidelines offer a set of concrete suggestions that can be applied to any discipline or domain to ensure that all learners can access and participate in meaningful, challenging learning opportunities.

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(Image credit: Kathy Schrock)

An incredible tool to think about the integration of technology with instruction was developed in 2010 by Ruben Puentedera when he introduced what we now know as the SAMR model. The acronym stands for Substitution, Augmentation, Modification, and Redefinition, and the intention was to create a shared language across multiple disciplines so that teachers would be able to determine the best use of technology as an instructional tool.

Loui Lord Nelson and Andrew Churches inspired Kathy Schrock to create the image above of the model associating it with the levels of the new Bloom's Digital Taxonomy.

Many teachers successfully adopted the SAMR model to help them determine the best way to introduce a technology and scaffold learning to the redefinition level. In fact, the Technology Integration Matrix gives a nod to the model in the technology integration levels of the rubric.

However, all that order and intention went out the window for many teachers when the COVID-19 pandemic hit and they were thrust into a technology-required environment with sometimes little professional development or training in the use of digital tools. Additionally, many had minimal knowledge of how to develop lessons for learners who were not physically present. That said, more than 89% adopted technologies and moved into technology-rich environments, according to the Christensen Report Breaking the Mold.

So, it begs the question, "Is SAMR a fatality of COVID?" Have teachers successfully integrated technology to the degree that we can unanimously agree we have redefined learning?

Many teachers acknowledge they are not going to put away the technology they have now become accustomed to having it in their classrooms, but they are also asking for more PD and resources. Districts are continuing to implement a wide-scale digital curriculum and the 1:1 distribution of devices. Some districts are even implementing 2:1, with students having a device at home and school. However, even though technology is more available than ever, and this is truly an edtech leader's dream come true, can we be confident that instruction has changed?

There are two aspects that should be considered before determining SAMR is no longer necessary.

First, let's think in terms of Webb's Depth of Knowledge when compared with SAMR. When applied this way, SAMR is not linear but rather a continuum. A learner can step into any level of SAMR depending on the activity and where the learner is in their own learning process. An activity may be developed for a learner to recall or reproduce information, or an activity within a lesson could level up to extended thinking. Learners enter at various levels and SAMR acknowledges that variance and suggests the use of technology should adapt to the learner's needs.

(Image credit: Ruben R. Puentedura)

The second aspect to consider is the blended learning continuum, which may be the fastest way to get to the redefinition level of SAMR. Considering the agility of the model and the ability for learners and teachers to move from face-to-face to fully online enables the learning to be more dynamic and more intentional. Engagement increases when learners are exploring their own questions and using technology in a flexible manner to create and explore their own interests related to a particular standard. This certainly allows for a more personalized approach.

(Image credit: researchgate.net)

Adopting the blended learning continuum and developing lessons designed to expose learners to a continuous variety of activities while enabling them to explore many aspects of problems and approaches to complex problems is the essence of SAMR and it can improve student engagement with the content along the way!

So, SAMR is not dead but rather evolved. We once considered SAMR through the eyes of the teacher and how they used technology for instruction and to develop student activities. This is still true today with the exception that teachers are applying it to redesign whole units of study that incorporate the various levels of SAMR throughout the lesson. However, the real evolution is how SAMR could apply to the role of the student enabling the combination of teacher and technology to facilitate a personal learning pathway. This allows the student to identify whether they are substituting, augmenting, modifying, or redefining their learning tasks through the use of technology. It also encourages the student to be more reflective about the tool being used and how it best applies to a learning task.

We probably aren't at a complete redefinition level within SAMR because of the lack of PD, training, and time to genuinely reflect on instruction with technology. Students do need to continue learning in digitally rich environments, albeit a balance of print materials and manipulatives is necessary as is the need to have time in teacher and student schedules to attend to basic social and emotional needs. Creating more flexible learning pathways that incorporate the levels of SAMR while embracing the continuum of blended learning will give students the flexibility and freedom they need to create at a new level and redefine their learning experiences!

Dr. Kecia Ray is a strategic thinker and a proven leader in K12 transformation. She serves as Tech & Learning's Brand Ambassador and is the founder of the consulting service, K20Connect

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(Image credit: Kathy Schrock) An incredible tool to think about the integration of technology with instruction was developed in 2010 by Ruben Puentedera when he introduced what we now know as the SAMR model.

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ISTE20 #DigCitCulture/Media Literacy in the Online Blended Classroom

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Allows students to evaluate each other's work anonymously

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Peergrade - engaging student peer review

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Peergrade is a free online platform to facilitate peer feedback sessions with students

Get started

The teacher sets up an assignment

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Peergrade - engaging student peer review

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Peergrade is a free online platform to facilitate peer feedback sessions with students Get started You start by setting up your assignment. You pick a feedback rubric from our library or create your own, select an assignment template and you're ready to get started. Students submit their work to your assignment.

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Google Docs add- on, teachers can leave written comments, voice recordings, links, and rubric-based feedback using rubrics created inside the app.

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Kaizena - Fast, Personal Feedback on Student Work

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Give your students fast, high quality feedback on their work. Record voice comments to convey emotion, embed explainer videos, and track skills students demonstrate in their work.

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Feedback with a quicker turn around time (allows students to send photos of work in progress with questions)

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Students can gather photos, documents, and links into one space

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Create portfolio pages and organize them into collections

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bulb | Digital Portfolios | Online Portfolios for Education | ePortfolio

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With a bulb digital portfolios, showcase your skills through beautiful, multimedia content on an incredibly easy-to-use platform. Built for educators, professionals and anyone else who wants show what they know.

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Students can upload images of artwork into portfolios. Parents and view and comment, as well as buy items with the artwork on it (And 20% goes back to the classroom!)

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Artsonia is the world's largest collection of student art, published by teachers and students from around the world. Parents and family can view the art online, leave comments and order keepsakes featuring the artwork.

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Artsonia - The Largest Gallery of Student Art Portfolios in the World!

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Artsonia is the world's largest collection of student art, published by teachers and students from around the world. Parents and family can view the art online, leave comments and order keepsakes featuring the artwork.

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Webjets can contain images, embedded videos, Google Docs, attached files, even tables

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What our users say

I really like the concept of the boxes, to be able to nest them and combine them together.

Thomas Steiger
Software Engineer

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Webjets.io - The new way to collect, organize and share anything

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Lists & Grids Organize clusters of information using this, most simple type of presentation. Mindmaps & Diagrams Maximize your brain's abilities by displaying related information in form of a mindmap. Tables Use tables to make Kanban boards or visualize two-dimensional structures. Collect Collect any information from the Web.

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Visual bookmarking tool you create

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Symbaloo: Bookmarks & Favorites - The #1 Homepage for Educators

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Easily save, share, and organize your favorites with Symbaloo; the best online bookmark manager for educators. Use Symbaloo as a homepage on any browser or Internet-enabled device. Create a free account today!

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"Boards" to organize online items

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Pulls content from publications based on your interests and turns it into a webpage for you

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To build an active online presence. Content. Webpage. Social. Newsletter.

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If building your personal brand is your goal, choose content that represents all your layers - work, personal & passions. You decide what you want to be known for.

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Please enable Javascript to correctly display the content on Paper.li

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Build your digital presence with Paper.li

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To build an active online presence. Content. Webpage. Social. Newsletter. If building your personal brand is your goal, choose content that represents all your layers - work, personal & passions. You decide what you want to be known for. Build a presence on the topics you're passionate about.

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Virtual notebook site with tabs and subtabs

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Feed reader for your favorite sites

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Please try to reload https://feedly.com/ in case this is due to a networking or caching issue.

In some cases, some browser extensions can interfere with the loading of Feedly. If you have some browser extensions installed, try to load Feedly in an incognito window and see if that resolves the issue. If it does, you can try to disable extensions one by one to determine where the conflict is.

Finally, this could be caused by a bug in Feedly. If this is the case, please send an email to care@feedly.com and we will be happy to help.

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Please try to reload https://feedly.com/ in case this is due to a networking or caching issue. In some cases, some browser extensions can interfere with the loading of Feedly. If you have some browser extensions installed, try to load Feedly in an incognito window and see if that resolves the issue.

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Visual bookmarking tool to gather links

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Turn web links into visually appealing newsletters, web pages and website embeds

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elink is an all-in-one content marketing tool to curate and publish email newsletters and web pages in minutes. Grow your audience and increase engagement.

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Streaming videos that read popular children's books aloud to them

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Differentiated articles of current events, adapted for five different reading levels

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Differentiated articles of current events, adapted for five different reading levels

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Full texts of six of Shakespeare's most popular plays with modern English translations

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I have tried many film versions of to help my students understand the Bard, but this is a great supplement to their studies. It explores not only the language, but the motives and emotions of the characters, and does it in a satirical, talk-show format, with "commercials" and songs. The students really get it!

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I have tried many film versions of to help my students understand the Bard, but this is a great supplement to their studies. It explores not only the language, but the motives and emotions of the characters, and does it in a satirical, talk-show format, with "commercials" and songs.

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Collection of multicultural films, photo essays, and articles

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Experience Our Storytelling

Watch this short video to learn more about the stories we tell.

Student Artwork: Spirit of Reciprocity Contest

Inspired by the work of Robin Wall Kimmerer, this contest invited students to take a photograph or create an original illustration that reflects the spirit of reciprocity and kinship with the living world.

"I have found that my best photos of nature are taken when I practice patience. The forest never stops moving if I stand still enough to see it. The art of photography is seeing the smallest points of beauty and capturing it. This glimpse into beauty is a gift for pausing to notice it. It is reciprocity in the most wonderful and simplest sense."
Bre Ireland (18) - Wisconsin, U.S.

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Photo Essay

This series features tintype photographs of the remaining speakers of endangered Indigenous languages in North America.

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Film

Yup'ik fisherman Ray Waska, who lives on the Alaskan Yukon Delta, teaches his grandchildren how to fish during the summer salmon run.

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Photo Essay

These photos by Sheila Pree Bright share intimate moments of mourning and inspiration within the Black Lives Matter movement.

"These powerful photographs are ones we don't often see in the mainstream media. Sheila Pree Bright's work encourages students to foster empathy in a time when we need it most."

Cleary Vaughan-Lee, Executive Director, Global Oneness Project

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Watch this short video to learn more about the stories we tell. Inspired by the work of Robin Wall Kimmerer, this contest invited students to take a photograph or create an original illustration that reflects the spirit of reciprocity and kinship with the living world.

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Free for teachers, digital books and videos for kids for Pre-K through age 12

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Daily short written entry or podcast telling an interesting story in history of someone from a different ethnic or cultural background

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Brief stories on historical contributions.

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Free online library (grades 3-12)

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Large library of texts and videos for ELA, social studies, and science for grades 3-12

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Engage every student in every lesson with Actively Learn's award-winning ELA, science, and social studies curriculum platform.

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Team messaging platform that is more efficient than email

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Whiteboard brainstorming, digitally

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Templates for lesson planning, newsletters, and project management

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Kanbanchi #1 Task & Project Management app for G-Suite

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Hey, everyone is on a limited budget nowadays! Start a free trial, and then within the app click "purchase", select "make a deal" button to suggest pricing that is suitable for your circumstances. Your budget problem sorted!

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A central place to organize any project

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One place, not all over the place.

Because of COVID-19, your company is likely scrambling to figure out how to transition to remote work. It may feel daunting, but you're in the right place with Basecamp. We built Basecamp to run our entire remote company - and we've been working remotely for 20 years. We know what it takes, we do it every day, and we built those learnings into Basecamp. Tens of thousands of other companies rely on Basecamp every day.

Watch Basecamp's founders discuss working remotely in this livestream.

Remote work is especially challenging when stuff's spread out across emails, file services, task managers, spreadsheets, chats, meetings, etc. Things get lost, you don't know where to look for stuff, and people put the right information in the wrong place.

But when it's all together in Basecamp, you'll see where everything is, understand what everyone's working on, and know exactly where to put the next thing everyone needs to know about. Your team can access Basecamp from anywhere - on the web, on iOS, and Android. This is the modern way - The Basecamp Way to Work.
Basecamp is different - take a deeper look at how it works >

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Replace all over the place with ONE place.

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Because of COVID-19, your company is likely scrambling to figure out how to transition to remote work. It may feel daunting, but you're in the right place with Basecamp. We built Basecamp to run our entire remote company - and we've been working remotely for 20 years.

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Interactive, video-based brain breaks

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Get Your Kids Moving & Practicing Mindfulness with GoNoodle®. Start Watching Now & Get Access to Hundreds of Videos! Active Learning. Healthy Kids. Active Kids. Boost Learning.