Often, they were doing this work with little cognitive and emotional support.

Dr. Carmen Garcia, president of CCSS, Superintendent of Morgan Hill Unified School District and an incredibly thoughtful and kind leader, welcomed the group with one sentiment; “being a superintendent is lonely.” No matter how big your team is, the high-pressure, highly-public, and highly responsible role of superintendent has little room for mistakes. 

In the education world, we’ve seen the ways educators can use AI to produce lesson plans, quizzes, and report cards. But I would argue the most important potential of AI isn’t to enhance human productivity. It’s to enhance and support human thinking. 

So at CCSS, I chose to prepare our Superintendents to use AI as the thought partner they’ve always wanted, in a world where leading is a lonely job. 

This 2-part article is about AI’s cognitive abilities as a thought partner.

The first part differentiates the competencies of AI from humans. It identifies what humans can double down on as their unique advantage, while also identifying a new standard for quality of thought using AI.

The second part (coming next week) provides ideas for how leaders can train an AI thought partner to represent whoever they want – a critic, a twin, a mentor, a philosopher, or a guide. 

The Cognitive Dance of AI

In the last year, we’ve seen a rapid improvement in the abilities of generative AI. It can take millions of pieces of data and reconfigure them into billions of pieces of content. However, shortcomings with data validity, misinformation, and algorithmic bias have deterred some educators from considering it a reliable tool.

When writing my keynote, I wondered if understanding AI’s cognitive abilities could help advocate for its utility. A familiar framework came to mind: Bloom’s Taxonomy. 

When I was a teacher, Bloom’s played an important role in lesson planning and assessing the competencies of my learners. Recent critics have appropriately recognized that these cognitive levels shouldn’t be stacked linearly, but should be more of a spiral that volleys between levels as learning is happening. Either way, it’s been the most accessible representation of learning in the last 70 years.

I thought that mapping AI’s abilities to Bloom’s Taxonomy would group at the top, bottom, or even perhaps swallow all of Bloom’s. In reality, it was much more spotty and varied, revealing a keen representation of human and robot capabilities.

Mapping AI to Bloom’s

Here’s my evaluation. Remember that the purpose was to set our superintendents up for understanding when and how AI is most powerful. As you read this, keep in mind how you’ve been thinking about AI.

Remembering: The Relentless Recaller 

• Bloom’s Level: Remembering
• AI’s abilities: Highly competent. 
• Key actions: Retrieving information such as facts, dates, definitions, or answers.

How well does AI recall data or information?

This first one is obvious. AI can simultaneously access millions of pieces of information across large databases. It will always be able to retrieve data more quickly, accurately, and with more abundance, than humans ever will. 

Understanding: The Illusionist 

• Bloom’s Level: Understanding 
• AI’s abilities: Not competent. 
• Key actions: Recognizing, discussing, or explaining the meaning behind information.

How well does AI make meaning of information? 

When I evaluated this level, I didn’t expect AI to fail so soon on Bloom’s. AI can recognize patterns, categorize data, and extract pattern-based meaning from large datasets, but it doesn’t truly “understand” in the human sense. Its comprehension is based on patterns and data, not on consciousness or intuition.

During my keynote at CCSS, the very thoughtful leader Dr. Tom McCoy, Superintendent at Oxnard Union HS District, chimed in with an incredible example. He explained how his son, when completing a homework assignment that asked him to write a goodbye letter to racism, used ChatGPT for ideas. ChatGPT replied with an opening line to the letter: “Dear Racism, We’ve had such great times in the past…”. AI used pattern recognition to identify how great letters hook the reader but didn’t make meaning of the purpose of the letter and the weight of racism. AI did not understand the assignment. 

AI possesses an uncanny ability to generate responses that, at face value, seem informed and profound. This is because it excels in pattern-matching, recognizing and mimicking structures, sequences, and commonalities within data. But it’s not making meaning.

Applying: The Patterned Practitioner

• Bloom’s Level: Applying 
• AI’s abilities: Somewhat competent.
• Key actions: Using information in new contexts to predict, interpret, solve for, execute, or implement. 

How well does AI use information in new situations? 

AI, especially machine learning models, excels in applying learned patterns to new data. At the heart of AI’s application skills is a concept called “transfer learning”, which enables an AI model trained on one task to be repurposed for a second related task without starting from scratch. This is akin to a human leveraging their knowledge of cycling to quickly learn motorcycle riding.

However, humans possess an innate ability to make intuitive leaps. If faced with an unfamiliar problem, we draw from our varied experiences, even if they seem unrelated, to find solutions. AI, on the other hand, relies heavily on patterns it has seen. It struggles in scenarios where data is sparse or where intuitive, out-of-the-box thinking is required.

So the effectiveness of AI at this bloom’s level is somewhat competent and really depends on the data it has along with the complexity of the problem.

Analyzing: The Connection King

• Bloom’s Level: Analyzing
• AI’s abilities: Highly competent.
• Key actions: Identifying trends, differentiating, comparing, relating, and questioning. 

How well does AI draw connections among ideas?

Traditionally, Bloom’s illustrates that if a student isn’t able to remember, understand or apply, they probably won’t be able to move up on the taxonomy. But seeing AI fail at the lower levels and excel at this one further helps to make the case for Bloom’s Taxonomy as a spiral construct, not a linear progression. 

AI can analyze vast and multidimensional datasets with superhuman speed, identifying subtle patterns and relationships. For instance, in genetics, AI tools can sift through enormous genomic data to spot potential markers or mutations linked to diseases. AI can predict potential future patterns based on historical data, which makes it highly competent at this level.

Evaluating: The Emotionless Evaluator

• Bloom’s Level: Evaluating
• AI’s abilities: Minimally competent
• Key actions: Making a judgment, critiquing, depending, or providing an informed opinion.

How well does AI make judgments?

The act of evaluation is not merely about decision-making based on data; it is a complex cognitive process that often demands judgment, ethics, and contextual understanding. AI falls apart at this level. It does not operate with ethical judgment, it does not have cultural nuance, and it certainly does not have emotions. It over-relies on quantifiable metrics and although this perspective is important and can be used to evaluate our own blindspots, it is not the full picture.

We know that the instinct-based decisions leaders need to make in difficult situations are sometimes the best decisions. Steve Jobs is famously known for using his instinct to launch the iPad when tablets were failing in the market. 

This level is where humans can shine and have a serious advantage over the machine. I gave this one a “minimally competent” because although AI cannot make judgments, it can provide us with the right information and recommendations so we can make judgments.

Creating: The Copy-Cat Composer

• Bloom’s Level: Creating 
• AI’s abilities: Somewhat competent
• Key actions: Producing, designing, assembling, constructing, formulating.

How well does AI produce new or original work?

AI can create new content by merging patterns it has observed, but it isn’t original. It doesn’t have original thoughts, emotions, or consciousness. Even when AI creates music, artwork, or narratives, it does so by identifying and combining patterns in its training data. The result may sound or look unique to our ears or eyes, especially when the AI blends seemingly disparate styles. But at its core, AI is not inventing; it’s remixing.

And because of this, AI’s creative capacity is tethered to data. It cannot make the cognitive leaps across variable experiences even if the sheer vastness of combinations it generates seems groundbreaking. The permutations are just regurgitations in many forms. 

Human creativity often springs from emotions, personal experiences, cultural contexts, and epiphanies. It’s organic, nuanced, risky, and sometimes serendipitous and unintuitive. These elements are currently beyond AI’s grasp. So although AI is highly competent at creating remixed content, it is not competent at creating original content. 

How Learning Blooms

Mapping AI on Bloom’s taxonomy opened several cognitive and presentation pathways for me. 

• It helped me explain the human advantage over AI 
• It depicted AI as a cognitive partner
• It identified the ways learners might use AI and be duped by AI
• It allowed me to narrate how AI will elevate our standards in education for the production of content, ideas, and discourse

This last point is particularly important. One of the superintendents mentioned that using AI feels like cheating. She didn’t want people to think her thoughts and her work were not her own. That made perfect sense to me and it was difficult to justify AI’s IP leaching algorithm. 

Instead, I shared that the calculator gave us the shortcuts we needed for quick and generic mathematics, but what we put in the calculator — how we used and contextualized the answer, and how we reasoned through the validity of the response — is what made the output our own. The use of the calculator also enabled educators to level up their expectations for students. Getting an answer was no longer the sole outcome. Now, students had to show their work and reason through more difficult questions. 

Although a simplistic analogy, AI will similarly create new standards of productivity for us. The more ubiquitous AI is, the more we will use it to produce higher-quality content. When everyone is using it, we’ll think of new ways to assess student competencies.

The next article in this two-part series will dive into how AI can be a cognitive partner to leaders. In the meantime, check out my newsletter for more thoughts on AI + Web3. Join our community at Ed3 DAO to continue the conversation and to access AI courses for educators.

The post What Bloom’s Taxonomy Can Teach Us About AI appeared first on Getting Smart.

Focus.

Focus is an essential component of learning and yet it is something that eludes almost everyone at one point or another.

Think back to a time when you were listening to a lecture or reading a book. Despite your best efforts to pay attention, your mind inevitably drifted off to something completely unrelated. You may not have even realized it at first, and the people around you likely didn’t either. The next time you’re having a casual conversation, notice how often your thoughts switch to something else. Your mind might even be wandering as you are reading this now.

Such instances of being internally off task are often referred to as “mind wandering,” and it can be a significant barrier to learning for some students. But what if it didn’t have to be?

What we’ve learned about this “off task,” mind-wandering phenomenon is striking. First, it happens all the time and to everyone (up to 50 percent of our waking lives!), and students are no exception, regardless of their age. What is of concern, however, is that students’ whose minds wander off task may struggle to understand the material they are learning because they are missing key bits and pieces of information along the way.

This leads to a question: Can we offer support to mitigate this kind of disengagement? The answer may start with data and technology – specifically machine learning.

Recent work by the University of Minnesota and the University of Pennsylvania, funded by The Tools Competition and the Bill & Melinda Gates Foundation, hopes to address the need for more research around mind-wandering and explore potential solutions that can help teachers and others manage it better.

Let’s delve into the importance of data first. Why is it so vital in deducing whether or not we can fine tune our focus? Because there is still much to learn and understand about how detrimental – or beneficial – our internal distractions can be. After all, some types of mind-wandering may indeed help with creativity and problem solving, according to some research. But at what point does it become an impediment to learning? Are certain populations more at risk of negative consequences than others?

To address these questions, we need more data and we need it from more diverse groups of people.

Most of the research in this area has used relatively small samples and in primarily WEIRD (western educated industrialized rich democratic) populations. This makes it difficult for us to make generalizations—particularly in terms of understanding why students’ minds drift off task in the first place. Some students may use their internal distractions as a helpful escape from boredom or a time to come up with creative ideas. However, if some groups of students have more stress in their lives, one theory suggests they may end up distracted in their own minds more often. In this way, it’s easy to see how mind wandering could impede, rather than support, their learning. We need more data from more students to understand the difference and design effective interventions.

And while teachers certainly have umpteen tips and tricks to keep hold their students’ attention, overworked educators could always use more tools in their toolbox to ensure that distracted students don’t slip between the cracks.

Data can provide greater insight into the benefits and risks of mind wandering. And technology may also help us better manage this phenomenon. There is initial evidence that—using machine learning—we can actually detect when students’ minds wander and offer support in real-time.

A real-time intervention system, called the EyeMind Reader, can read a student’s gaze to determine if they are off-task. The system can then intervene at critical points to ensure that students get a chance to re-focus and re-engage with the lesson.

Such interventions can help ensure that students understand key concepts, plot points and information as they progress in their studies, rather than creating gaps in their understanding. After all, a student whose mind wanders at a key point in To Kill A Mockingbird won’t grasp why Boo Radley is the real hero of the story.

Now, to criticize my own work, any tech-based solution for mind wandering is nowhere near scalable to all students. The machine learning models I referenced were based on data collected from a few hundred (primarily White) students and the equipment cost thousands of dollars, a price that is likely out of reach for most schools.

As an analogy, consider how luxury cars were early adopters of built-in eye-tracking technology to help jolt inattentive drivers back to reality, while most cheaper models do not offer this feature. Do we want to perpetuate similar class distinctions in education? Probably not. But more data, along with more scalable technologies, can close any potential gaps.

We are creating a large-scale dataset that will be free and publicly available to any researcher interested in this topic. The dataset will include data streams that both are affordable and scalable, such as webcam-based eye-tracking (that does not store any student videos). Our hope is that easy access to diverse data will allow the research and education community to understand this ubiquitous phenomenon better, while also enabling better measurement and intervention methods to enable short- and long-term student success.

After all, we want our students to be dreamers, but ensuring that they absorb the necessary information – without distraction – will enable and equip them to be “doers” as well.

Caitlin Mills is an Assistant Professor at the University of Minnesota where she researches the intersection of cognitive psychology, computer science, and education. She is particularly interested in mind wandering: its neural correlates, relationship to affect, and impact on learning. 

The post Can Edtech Be Used to Better Serve Daydreamers? appeared first on Getting Smart.

Maybe when you hear the word “critical,” you think of negative stuff: to be critical must mean that you dislike something, right? Not always! “Critical” can be used in a variety of ways, including thinking carefully about something (critical thinking), asking questions of something (critical inquiry), and practicing media literacy (critical media literacy).

So, what’s critical about critical media literacy (CML)? Trust us, this is not an order to “eat your spinach!” or to ignore media that bring you joy and happiness. Instead, what’s critical about CML is taking a bit of distance from our media choices to examine them more thoroughly. Instead of looking only at our screens, we want to look behind the screens (or behind the scenes) to understand how the content got to us.  

Many U.S. schools teach media through a protectionist position—that is, teaching us that the media are bad for us. Protectionists are often concerned with media content they find dangerous, such as representations that glamorize violence, sex, or drug and alcohol use. They assume that once you learn that the media are bad, you will choose to turn them off.

Another way of studying the media in the United States is the celebratory position. In this view, you are considered an active agent and your knowledge and media use are rewarded. In practice, advocates of a celebratory approach to media literacy have focused mainly on interactive media, such as computer games, or material you may create for your social media profiles.

The protectionist and celebrationist positions seem like opposites of each other, but they actually have a fair amount in common. Both expend a lot of energy on the content of the media—what’s on the screen—without much attention, if any, on how that content came to be. Both believe that young people ought to make “better” media choices—but each position offers only a partial story about the media you use. Both are missing a serious investigation into the means of production—that is, how that media content came to be. Neither position addresses the political economy of media analysis—the study of media ownership, production, and distribution.

Despite their differences, protectionism and celebration share an important commonality: they both focus primarily on content and representation.

For both protectionism and celebration, media content is often approached as individual products, and these are often explored in isolation. For example, you might be involved in a discussion about a particular scene in a movie where you may talk about the dialogue between the characters or the lighting or sound effects. While that is important, it should not be the entire conversation. Critical media literacy will ask you to think about how that scene fits into the movie as a whole. It will also ask how you accessed that movie (did you watch it in a movie theater? on a streaming service? on a particular device?). CML will also ask you to think about when the movie was originally released, which may include a discussion of current events. CML will ask who wrote, produced, and distributed the movie—and, by extension, might ask what else those people and production companies had written, produced, and distributed. CML, therefore, fills in the gaps in representation.

As you can see from all these questions, CML is inquiry-based. What we do in CML is ask a lot of questions about our media use. We ask questions about many topics, including gender, race, class, and sexuality. Most importantly, we ask questions about power: Who has it and what they do with it, as well as who does not have it and why not. That is one reason why we ask questions about ownership, production, and distribution: because that’s where much of the power of media originates.

One of the many inquiries that CML urges us to take up involves analyzing stereotypes, which are overgeneralizations or fixed beliefs about a certain group. These include xenophobic stereotypes, such as the “Arab terrorist”; sexist ones, such as the “dumb blonde girl”; and racist ones, such as the “Black criminal,” to name a few obvious examples. The contemporary use of this term tracks back to Walter Lippmann, a giant of twentieth-century journalism and a pioneer of contemporary media studies. Looking at stereotypes critically can help us realize how media shape our perception of others and the of the world. Consider the following questions.

• What types of stereotypes have you encountered, online or in real life?
• Are there any stereotypes that affect you as an in individual?
• Can you think of any stereotypes that are beneficial or positive?
• Whom do these stereotypes benefit?
• Who do you think is in charge of producing these messages?
• How do you think the messages end up taking so much space online?

CML is a liberatory approach to making sense of the world. CML seeks to equip people with the tools to be independent media users, free from oppression or restrictions by others. We recognize that misinformation, disinformation, stereotypes, and problematic representations exist, but as media users we do not have to accept or internalize them. Instead, we can expose, question, and oppose them.

The post Looking Behind the Screen: Critical Media Literacy Gives Us Tools to Understand How Media Shapes Our Perception of Others and the World appeared first on Getting Smart.

There are big trends for this year about how AI will impact the world of work and the skills needed. It has been predicted that artificial intelligence will automate the production of 30% of all the content available on the ​Internet this year. With the creation of smart machines and new technologies and automation, humans will be replaced with machines, which means that students need to be able to develop skills that enable them to be flexible enough to adapt as these technologies and workplace needs change over time. According to Mark Cuban, “AI will dominate the workplace and to be successful, people are going to have to understand it.” In 2019 he launched a foundation that provides AI bootcamps for free to students to learn about AI. More recently, he has been working with the Penn State Readiness Institute with the Executive Director, Dr. Justin Aglio to provide more opportunities for high school students.

AI in the world

Students are learning about AI in amazing and innovative ways. Students in Winston-Salem had an experience with AI by working with the first AI Woman of color named C.L.Ai.R.A (acronym for Create Labs Artificial Intelligence Rendered Assistant). The purpose of C.L.Ai.R.A, which has been called “most powerful AI out there” is to “help communities with their needs while representing people of color.” C.L.Ai.R.A is being developed for use in the metaverse.

Chatbots are being created and provided to middle and high school students to help with the mental health crisis. As students increasingly experienced mental health challenges such as depression during Covid, there was a heightened awareness of the need for more services for students as well as adults. Alison Darcy, a psychologist and founder of Woebot Health created a chatbot to help make mental healthcare services more accessible via an app and chatbot in 2017. A high school student used the app for a week and felt positive effects from the experience.

Although there are many benefits offered by this technology, it is still important to consider the potential negative impacts or concerns as a result.  Natural language processing (NLP) is being used to work with people diagnosed with bipolar disorder. The research being done indicated that “language analysis could help aid the provision of care for those with the condition.” However, there is a continued reminder to focus on the ethics behind the use of these technologies and also the importance of privacy.  

In education, AI is making it possible to provide more personalized learning experiences for students. By automating tasks that take teachers more time, AI facilitates these tasks so that time can be spent with students providing one-to-one feedback. Digital tools with AI integrations like Quizizz for example create a personalized learning path in response to each student’s responses and based on their needs, these benefit student learning. There are many platforms that have AI which helps to automate tasks, and provide adaptive learning and more personalized experiences for students. Students would also have access to intelligent tutoring systems through AI.

Some examples include Knewton for higher education, Nuance’s Dragon Speech recognition promotes accessibility for students because it can transcribe up to 160 words per minute and has voice commands for navigating documents with a 99% accuracy rate. Knowji is an audio-visual vocabulary app for language learners which uses algorithms to track learner progress and can anticipate when a learner is going to forget a word and can provide repetition.

Can we all teach about AI?

While we all have our areas of certification or specific grade levels that we teach, artificial intelligence is something that should and can be taught at all levels, regardless of a teacher’s experience in this field. We don’t have to be the expert. It’s important that we learn from our students and give them a chance to become the creators and thrive in a way that meets their specific interests and needs which leads to more authentic and meaningful learning. There are many resources available that make it easier for any educator regardless of experience or familiarity with artificial intelligence. We can provide learning activities for students, even on a short-term basis, without worrying about having specific equipment or spending a lot of money on different programs.

While it can feel uncomfortable to not necessarily know the answer to a question that students may have, especially in an area that can be quite complex like AI, we simply need to know enough to get our students started. Bringing AI into our classrooms and getting the conversation started is the most important step. From there, we have a lot of options to explore.

I have been teaching about AI in my eighth grade STEAM Emerging Technology course for the past five years. When I started, I did not know that much about AI at all. However, because I first wrote a blog about AI for Getting Smart, and dove into some research, it piqued my interest so much that I wanted to continue to learn more. Also by enrolling in the ISTE AI course provided in partnership with General Motors, I was able to build my knowledge and skillset and provide more for my students the following school year. Just having some guidance and hands-on materials helps to give us a push to take some risks and bring new learning experiences to our students and ourselves.

With so much out there to explore, it’s great to do this in partnership with our students. To get started, there are some organizations that provide everything that an educator would need to begin teaching about AI in the classroom. With topics ranging from the basics about what AI is and how it works, to definitions and examples of AI, to more complex areas like creating AI or designing a chatbot, for example.

Getting started

The first step should be in helping students to define and understand what artificial intelligence is. By reviewing the resources available through AI4ALL or AI4K12, educators can find a wealth of information. There are videos from Crash Course AI that can be shown and discussed, which is a great way to get students thinking about AI. Or we can simply start with a question to ask students how they would define AI or what they think of when they hear “AI”? We can also exchange ideas about where we see AI being used in everyday life and where is AI making an impact and how. Beyond covering the basics, it is important to also open the conversation to any concerns that may exist around AI whether related to bias and ethics or safety.

Six Resources to Explore

AIClub offers a variety of courses for students as well as a lot of free resources for educators to choose from to get started. There are also PD sessions for teachers to sign up to learn more.

AI4K12 is a great resource to spark curiosity for learning about AI and has resources and is developing guidelines for AI curriculum for use in grades K through 12.

DayofAI org launched the first-ever Day of AI on May 13th. It was a day for classrooms around the world to participate in learning about AI through a variety of resources provided for teachers from MIT. Teachers can receive lesson plans and videos for all grade levels.

Google AI Experiments Google offers a lot of wonderful experiments based on AI and machine learning that students can interact with. Students also can create their own experiments and submit them to Google for possible inclusion on the site.  

Human vs AI Test A fun activity to try with students that have you decide whether art, music, writing or photos were created by a human or AI.

Wombo Dream With this site, you can create art that is generated through artificial intelligence by choosing a prompt and art style, and a work of art is created which can also be purchased. With Wombo AI, an AI-powered Lip Sync, you take a selfie, it scans your face and merges your face with that of the singer. Even if students are wearing a mask, it still layers your face onto the singer with facial expressions and movements.

There are also virtual summer camps available for students that vary depending on length and cost of the program. Code Connects has summer camps available on topics like Emerging Tech and AI and Big Data. AICamp has a three-week summer camp available for students ages 13-18 which is focused on AI and a one-week camp on data science. AIClub also offers summer camps for students in grades 4 through 12.

Preparing means starting today

Students need to explore AI and develop their own understanding of what it is and how it works. We also need to encourage students to become creators and brainstorm ideas for how AI can benefit society. Students as young as pre-K can begin learning about AI through the resources listed above. Giving students access to hands-on learning activities or engaging in conversations about AI and then coming up with their own ideas will have many benefits. We need to give students the chance to try something, fail at it, adapt, and then set new goals.

The post Teaching AI to All Students appeared first on Getting Smart.

If you are worried about plagiarism, things just got a lot more complicated with developments in Natural Language Processing (NLP), a branch of artificial intelligence that enables computers to understand, process, and generate language.  

AI, and particularly NLP, is changing the way humans create, consume, and evaluate content. Financial reports, sports news, and legal briefs are increasingly computer drafted. NLP is changing the nature of employment and will increasingly show up in classrooms–welcomed and otherwise.  

Language Processing

Natural language processing is a branch of computer science, specifically artificial intelligence, that enables computers to understand human language, process it and create language to interact with humans to communicate. Computers have been trained to process large quantities of data and language and then generate communication in return. It’s highly likely that everyone is interacting with NLP every single day because of all the places it is found.

Some examples include the use of chatbots, voice assistance, translation tools, and search engines. In my eighth grade STEAM course on emerging technologies, a good part of our year is focused on artificial intelligence and its various components. We explore a variety of materials such as AI4K12, ISTE U AI Course Materials, and have recently come across AIClub which has activities for students to see NLP in action and also work with some of the projects. They offer many free activities to explore AI. We want to move students from consumers to creators, especially in these areas, and with AI, it is impressive to see what students create, especially with chatbots. A group of sixth-grade students created the Calmzilla app to help middle school students deal with stress through a chatbot, showing a great way to focus on SEL through the use of chatbots and having students create.

How does NLP work?

NLP is possible through machine learning. Through algorithms, it is able to understand the meaning and structure of human language, analyze text, and even respond. The system stores all data whether that’s words, sentences, books, or any information that is loaded into the system. The computer then uses its data to find patterns to analyze.

Chatbots or messaging systems read the language that we use and can learn over time.

NLP can be used for different processes such as in documents for correcting spelling, translation of words, it can also respond to human language and react based on the information that it receives. Computers interpret what humans say, process human speech and then respond or react. It can evaluate speech based on context and intonation and then respond. We often use it for machine translation, text to speech, image description, and speech recognition.

Developments in NLP for accessibility and language creation

There have been many developments in NLP that promote accessibility and language uses from a variety of providers including Facebook, Google and Microsoft. For promoting accessibility, with NLP, companies can leverage the technology to provide more language capabilities.

Launched in 2020 by San Francisco R&D shop OpenAI, Generative Pre-trained Transformer 3 (GPT-3) is a third-generation model that demonstrated dramatic progress in creating human-like text.

Amazon Comprehend is NLP that locates insights and makes connections in text. There are many advances in large, “pre-trained transformer-based language models” such as BERT (Biodirectional Encoder Representations from Transformers). BERT, developed by Google is leveraged in its search engine and was trained on language modeling and next sentence prediction, and its use has continued to grow.

The use of NLP is expanding into all areas of work and life. There are some key trends with NLP to look out for in 2022 and here are some of the new developments (with thanks to Jack Clark for regular updates):

1. Facebook teaches language models to speak about 30 languages: These developments have been referred to as being “better than an equivalently sized GPT3 model…” To do this, Facebook trained a family of language models that are better at translation than GPT3. The XGLM ( an autoregressive language model) was trained on a mixture of 30 languages, varying from languages with a lot to very little data. They found that by training with more diverse language data than GPT3, the Facebook models performed better, especially when using ‘few-shot’ prompting. Few-shot prompting is where the model is fed a few examples of the target language, and then is asked to translate.
   
   
2. Facebook new AI supercomputer: Facebook introduced a new AI supercomputer to be used for AI research in what is called the AI Research SuperCluster (RSC). Facebook (Meta) believes it is one of the fastest AI supercomputers available. The use of this supercomputer will be for moderating the content on its platforms, creating new services for the metaverse and developing augmented reality tools.
   
   
3. Google’s big text model – LaMDA is a GPT-3 competitor which is part of a family of language models ranging in size from 2B to 137B parameters (GPT3: 175B), and that have been trained on a massive dataset of 1.56 trillion words. LaMDA is different from other big language models because it is centered around dialogue, with 50% of its data coming from “dialogues from public forums.” With this new capability, LaMDA can be used in a variety of useful applications that will be more practical and safe open-ended dialog, which is why we need people with the skills for the program to ensure the safety of these technologies.  
   
   
4. Microsoft makes MoEs easier to train: Microsoft is trying to scale-up mixture-of-experts (MoE) networks, which are one of the more promising routes for creating trillion-parameter-plus AI models. MoEs are more efficient to train than GPT3, which is a more dense model. MoEs work well for auto-regressive natural language generation tasks. With improved efficiency and training models, the result is great improvement in language accuracy. Beyond the efficiency, there is also a potential reduction in cost. Microsoft has stated that it can train 350M and 1.3B parameter MoE text models that have better (or the same) performance as GPT3 for a range of different tasks. What this means is that it nets out to models with the “same quality with 5X less training cost”. DeepSpeed-MoE offers massive MoE models with up to 4.5x faster and 9x cheaper inference when compared with quality-equivalent dense models.

NLP Applications

NLP has applicability in a variety of sectors of work and daily life.

• Sentiment analysis: NLP tools can “read” giant data sets to assess consumer brand sentiment and identify areas for improvement. It can detect negative comments as they are posted and can respond proactively.
• Chatbots: NLP streamlines communication in many areas of work and has been used to process customer requests because it is able to analyze the language and create a response to common requests. When a request is not understood, the message is sent to a human agent. There are many companies that are using virtual assistant technology to facilitate calls. For example, when you make a call to the electric company, airlines,  banks, or hotels, many of the most common requests can be responded to via chatbots or customers can manage their accounts using some of the voice commands. Companies often use the Alexa Skills Kit that is provided through Amazon.
• Reducing online bullying: detection of Cyberbullying is another way NLP is being utilized for good. On social media, classifiers are being developed to detect the usage of abusive and derogatory language, as well as hate speech.
• Fake news detection: While it may contribute to the problem, NLP has become a critical tool for detecting and reducing the spread of fake news and analyzing speech on social media. NLP is being used for automatic fake news identification this year, and this is an area we will likely see more of in 2022, with so much incorrect information about Covid-19 and other world issues circulating.
• World of Work: NLP is being used in various sectors such as finance, healthcare and human resources. In healthcare, NLP can analyze voice records and convert them into text to be added into patients’ records. NLP is being used to train algorithms on mental health disease which can then be used to provide cognitive behavior therapy or virtual therapy assistants to patients with PTSD, autism, or depression. In finance, NLP can extract data for credit scoring or combined with machine learning and predictive analytics to detect fraud. In human resources, NLP screens resumes and recruiting chatbots use NLP to schedule interviews, facilitate onboarding of candidates and more.

What NLP Means for Edu

Students should have an understanding of what AI is, the impact that it has on our lives and how it could shape the future–both good and bad. They should know that they are living through the first decade of widespread human-computer co-created content, art, and music–an amazing opportunity that will challenge historical views on intellectual property.  

Upper elementary school is a good time to teach digital literacy and critical consumption. Middle school is a good time to introduce AI ethics and begin the conversation about what it means to co-author with a machine.

High school should create opportunities for students to use machine learning tools to attack problems and create solutions. This could happen in a computer science course, a social studies and tech block, or an after school program (see AI4All).

And, keep an eye on student writing. Plagiarism detectors will be challenged by new content creation tools. Live performance assessment will remain the best way to determine if it was Robbie or robo-writer.

Finally, a real person wrote this post. But the next one you read, well, you may not be able to tell.

The post Robo-Writers, Translators, Chatbots: Developments in NLP and What it Means for Education appeared first on Getting Smart.

What are NFTs?

According to the Merriam-Webster definition, a nonfungible token (NFT) is a unique digital identifier which cannot be copied, substituted or subdivided. Once created, the NFT is then recorded in a blockchain which is used to certify its authenticity and ownership. An NFT is not a tangible object but rather a form of proof that shows ownership and purchase. These blockchain-based tokens can represent artwork, digital content, media or even event tickets. An NFT is an irrevocable digital certificate of ownership and authenticity for a digital or physical asset.

NFTs have unique digital identifiers and are stored on a blockchain, a system that is used to keep a record of transactions made in bitcoin or some type of cryptocurrency. NFT records are kept across multiple computers that are linked in a network and through the blockchain, can be sold or traded. NFTs are created through a process called “minting,” in which they convert digital files into a cryptocurrency collectible. The process of minting is how NFTs are uploaded to the blockchain.

A difference between bitcoin and NFTs is that bitcoin can be traded for another bitcoin, whereas NFTs are unique and cannot be traded as an equal value. In my eighth grade STEAM class, I shared this video explainer which provides some examples to help students and teachers better understand NFTs. One example shows how a $100 bill can be divided up into different amounts but keeps the same value. However, when it comes to NFTs, in art for example, you cannot take a painting like the Mona Lisa, divide it up, and equally distribute it because there is only one original Mona Lisa. That’s where the value of NFTs comes in, especially in areas like music and art. While you may be able to print a copy or take a picture of it, the value will not be the same as the original. Because of the ability to forge works of art or music, which makes it difficult to identify whether or not it is an authentic piece, this is where NFTs can be highly beneficial.

How are NFTs created?

NFTs are created by artists, designers or license holders through a process referred to as “minting.” Minting involves signing a blockchain transaction that provides the specifics or outline of the fundamental token details. NFTs can take various forms whether it is a photo, video, or even a GIF. The information is then sent to the blockchain to trigger a smart contract function which creates the token and assigns it to its owner. Each NFT has a unique identifier which is then stored on the blockchain. Once it is on the blockchain, it sets the authenticity and the ownership.

Where are NFTs being used in education?

In education, NFTs have become a topic of conversation. Over the past few months in my STEAM course on emerging technology, we have explored bitcoin, cryptocurrency, blockchain, and NFTs. Students are interested in learning about NFTs and discussing what it means for the future and for education, and even brainstorming what they would create. There are several universities that are using NFTs for credentialing and also for working in remote learning environments. One example is Duke University which has provided educational credentials in the form of NFTs for its Master of Engineering in Financial Technology degree.

Other universities are exploring some unique uses of NFTs. Seton Hall University held an Annual Entrepreneur Hall of Fame Dinner in February and alumni were presented with NFT awards. At Pepperdine University, one educator has been using NFTs in a personal finance course to award NFTs to the students. The NFTs represent academic tokens, without monetary value, that represents when a student has passed the course. The NFT contains unique details about student performance. MIT has done research and has been advocating for the use of blockchain for authenticating college certificates and transcripts.

NFT’s may also be used in the future in order to give people permission to events and to better manage which parts of the event people have access to. Over time, this may even become some kind of alumni status, i.e. special rewards or privileges to those who have attended SXSW EDU 5 years in a row, etc.

What does this look like in K-12?

At a high school level, think about times when we use assessments for learning or we share evidence of work that students have done whether that comes in the form of a certificate, maintaining student records, accessing results from a standardized test, or recording other academic achievements. These require time to obtain and to store and in some cases, can easily be forged. With so much technology available, we can make certificates and other documents look authentic. However, with NFTs and the inability to forge them, schools are likely going to consider using NFTs for a variety of reasons.  

When a student or teacher does well, to make it memorable, the academic sector can now create and design an NFT. The use of NFTs as diplomas and resumes could help better track and access what students have earned throughout their school careers. By using NFTs, it serves to stop students from falsifying their academic certifications because the token serves as a permanent, unchangeable and unique “transcript.” There are many ways NFTs are being used now and which can benefit various areas of work and life. Rabbi Michael Cohen, educator and author, has been doing a lot of work in the area of NFTs and even holds a Twitter Spaces chat on Tuesday nights about it. He sees the potential for using NFTs for creativity and in the arts.

Mark Cuban, a billionaire and investor on NFT platforms, believes that textbooks will become part of the NFT experience. Digital textbooks can be resold and royalties can be collected for each resale.

Preply, a global language learning platform founded in 2012, minted three NFTs on Open Sea as a way to reward tutors in 2021. Amy Pritchett, the Student Success Manager of Preply says: “We wanted to experiment with NFTs as a way to reward Preply tutors and the great education they provide our students. Once you have one of these tokens you can keep it or sell them. Pritchett added some ideas for using NFTs such as creating online ‘trophy cases’ of their NFTs as artifacts or perhaps creating digital portfolios, which can be shared with prospective employers or even college admissions. Teachers can also issue NFTs to represent when students successfully demonstrate learning the class material. Pritchett added, “We are only starting to see the beginning of how NFTs and education can come together. They are an emerging trend that we all continue to be curious about.”

What is the difference between NFTs and Verifiable Credentials?

Both NFTs and verifiable credentials (VC) offer ways to uniquely identify something in the digital space. NFTs are publicly displayed and VCs are a privately held digital fact, however, each of these spaces provides more security and authenticity, and are capable of being monetized. Each proves that something, whether a token or a piece of art, belongs to someone. However, there are differences. A VC uses link key infrastructure and has three entities: the issuer, the holder, and the verifier of the credential. Each party signs the license and gives it the authentication. An example would be a driver’s license. An NFT can only exist on the blockchain and as soon as it is created, everything is time-stamped which makes it easier to verify ownership. NFTs can be monetized by creating something new and then selling it whereas a VC cannot be tampered with and all information is verified cryptographically to prove the identity of the individual or entity. NFTs can be transferred, but VCs cannot, which means that the original owner remains the same.  

The value of NFTs

The value of NFTs are determined by the availability of a digital asset or what it represents. If few are in existence then the value will be greater. Earlier last year, digital artist Beeple sold Everydays, a collage of 5,000 images for $69.3 million and Jack Dorsey, Twitter CEO sold the first tweet he made as an NFT for $2.9 million. Podcast Host has launched the “world’s first-ever generative podcast NFT collection” under the branding of “The Curious Companion” introducing a new medium into the world of NFTs.  

NFTs create a unique way for artists and creators to express themselves by making digital art and artifacts that are collectible, sellable and authentic. When it comes to human expression and preparing students for the future, Tom Vander Ark says “We can no longer teach the expressive arts without introducing new modes of expression, new market platforms, and new business models with the opportunity to make a career in the arts sustainable. It’s time to teach creativity not just in the arts but in audience development and entrepreneurship.”

With NFTs and the potential for infusing creativity in the design and developing a plan for distribution, we are fostering essential skills such as entrepreneurship and agency in learning. Students are now creating artwork and maintaining ownership of their work as an NFT or they can develop entrepreneurial skills to build a business and make a profit.

As we seek to prepare students for the future, Vander Ark believes that schools and colleges can help by “Integrating the expressive arts with emerging technology and new business models so that more young people graduate ready for sustainable arts impact.”  We can expand access to careers in human expression while leveraging the emerging technologies in our future.

The post NFT in Edu: What Does the Future Hold? appeared first on Getting Smart.

Six years ago, Byron Auguste worked to support and grow TechHire, a White House initiative that focused on building career pathways and matching tech experiences to jobs. This helped to catalyze Opportunity@Work, an organization that focuses on supporting workers who do not have bachelor’s degrees but are Skilled Through Alternative Routes (STARs).  By engaging with corporate, philanthropic, and workforce partners, the organization has united efforts to directly address the barriers that STARs face in today’s labor market.

Opportunity@Work’s research aims to show employers the importance of the STARs talent pool. Through their STARs Insights Initiative, for the first time, there was dedicated research for employers to understand STARs values, skills, and opportunities for upward mobility.  

“We define STARs as individuals at least 25 years old who graduated from high school and have skills but don’t hold a bachelor’s degree. Many STARs enrolled in college but didn’t complete their degree due to family or financial circumstances. Others have a two-year community college degree or received technical training through workforce programs, online credentialing services, or certification programs. Still, others are self-taught or developed their skills on the job or through military service,” says the Opportunity@Work website.

Putting It Into Action

In order to better provide matchmaking capabilities, Opportunity@Work created Stellarworx, the STARs Talent Marketplace. Stellarworx is a faster way to match STARs with inclusive employers that are ready to hire, while uniquely integrating talent developers to validate candidates’ skills. This platform “hires people for their potential, not pedigree,” helping employers to identify diverse and growth-minded candidates more efficiently.

Recently, Opportunity@Work hired Bridgette Gray, a long-time advocate for alternative pathways and employment, as the Chief Customer Officer. Gray will work to grow Stellarworx’s reach and push the STARs brand to new heights. Gray joins Opportunity@Work after seven-and-a-half years at Per Scholas, where she was their first Chief Impact Officer, responsible for managing all training operations, and organizational impact for Per Scholas’ 17 campuses.

“Many companies desire diversifying their talent pool, but struggle to get outside their traditional pipelines,” says Gray. “This is where we come in.”

Gray says that she feels optimistic about the future and the fledgling momentum of skills-based hiring, however, it is not moving fast enough. “We have to also ensure that DEI is central to skills-based hiring and that workers are realizing their own value.”

Down the road, Opportunity@Work would like to see the STARs language widely known and used. Gray says that could be the STARs logo appearing on job applications, badges to indicate STARs hiring on websites,  career listing sites, and more. This hopeful signal has great potential to become adopted and spread throughout the workplace.

Opportunity@Work COO Shad Ahmed shared, “with employers across the country reporting talent shortages, while millions of STARs are sidelined from opportunity, we know the sky’s the limit with Bridgette on board.”

The post Among The STARs: The Rise of Skills-Based Hiring appeared first on Getting Smart.

What are some of the challenges in Career Technical Education today and how can AR/VR help to address them?

At its core, immersive learning is about giving students the opportunity to experience—in the truest sense of the word—what it’s like to perform certain tasks, whether that’s operating a multi-ton crane hoisting an 800,000-pound piece of equipment or learning on-the-job fundamentals of working at an industrial construction site. This level of immersion can be accomplished through virtual reality headsets, which provide trainees with a 360-degree view in all directions, and advanced simulations that enable learners to feel as though they are in a physical environment.

Immersive technology helps students gain exposure to well-paying, in-demand jobs. Simulations enable students to feel as though they are embedded in a factory, shop floor, or another workplace. With the headsets strapped on, they simulate tasks just as though they are performing real work with their hands, such as operating heavy machinery or using tools. They are seeing with their eyes the same environment they would see in a seven-story manufacturing facility or shop floor, for example, and practicing the same type of visual, physical, and decision-making skills they would be expected to use on the job. In this way, immersive technologies help solve one of the biggest challenges in Career Technical Education: providing learners with real insights into what tasks on the job look like, and understanding whether specific careers could be the right fit for them.  

What are some of the major trends you’ve seen in Career Technical Education?

The truth is we are still largely using the same paper processes to help students explore careers just as we did before the internet. It’s an archaic and limiting approach. When you ask a student what it’s like to be in manufacturing, they may picture big machines or heavy cranes; they may not make the connection that the operating crane isn’t so different from the video games they love to play. Moving Career Technical Education into this century requires bringing different careers alive for students, so we can help them see new possibilities for themselves.

How early should students begin career exploration processes?

Through our partnership with Coastal Bend College in Texas, we are bringing career exploration to students as young as 7th grade. If you ask any 7th grader what they want to be when they grow up, they will reference careers they have seen: firefighters, engineers, doctors, lawyers. The careers they dream about lead to which advanced classes they take in high school and influence their majors in college—and if they decide to pursue post-secondary education at all. It is crucial that we help students expand their understanding of what careers they can pursue and get their start early in career exploration.

What are some of the barriers students face to finding the right career?

You can’t be what you can’t see. Students don’t know the kinds of jobs that are out there–and that some of those jobs are closer to home than they think. Exposure and awareness is one barrier. Another is fighting the stigma around skilled trades–we need to help students understand that skilled trades are vital to our economy.

A Department of Education study showed that Black and Hispanic students benefit less often from classes connected to higher-paying careers and college degrees than their white peers. How can we help address this racial divide in career technical education?

Students of color across the country struggle to access Career Technical Education that sets them on paths toward higher-paying careers. Immersive learning technologies like TRANSFR help level the playing field. Low-cost but high-value, the tech is particularly helpful to students in under-resourced schools envision rewarding careers.

Why are you passionate about helping students explore careers?

Growing up, my family didn’t have money, social status, or connections, just lots of hopes and dreams—-like a lot of families across the country. I grew up in an era where people would say if you don’t have a plan for college then you will end up on the street. My first job was at Wendy’s-and it was an important stepping stone to entering the workforce and thinking about my future.

When I was 16 years old, I read a book about Warren Buffet and learned that his first job was delivering newspapers. Everyone has to get their start somewhere. What I want for students embarking on career exploration across the country is to get that first job–and also have an opportunity to see what is really possible for them.

What advice would you give to educators that want to help K-12 students with career exploration?

Make career exploration as interactive as possible. Let your students’ curiosity be their guide. That is where the best learning happens–when it’s driven by students.

Bharani Rajakumar is the CEO of TRANSFR Inc.

The post Expert Perspectives: How Virtual Reality Can Aid in Career Technical Education appeared first on Getting Smart.

Time. Arguably, it is the most valuable commodity anyone could have. For educators, time can be a sparkling prize held just out of reach. The chasm between is filled with deadlines, test requirements, homework to edit, meetings to attend, lessons to plan, a dog to feed, family to care for, and a positive mindset to maintain. Whew. Many calming breaths are needed when addressing the issues educators continue to face today.

One of the ways my team at Project Unicorn seeks to eliminate the workload in the life of a teacher, and school administrators, is by sharing the importance of data interoperability. Interoperability is a term that, while technical, underlies many commonplace applications and conveniences. Whether it’s the Bluetooth connection between a headset and a phone, or the ability to withdraw cash from a local ATM while traveling, interoperability helps things work when we need them to. When it comes to student data, educators often spend valuable time transferring data from system to system to complete everyday tasks, such as the simple goal of taking attendance. They’re faced with hours of additional work because the edtech systems and platforms available do not communicate with each other or enable the secure and easy transfer of student information.

Schools districts can start tackling this problem by taking action,  such as by signing the Project Unicorn School Network pledge. This pledge was created by the 16 diverse organizations that make up the Project Unicorn Steering Committee, which is invested in furthering the use of data interoperability. Signing the free pledge signals a district’s commitment to securing and leveraging interoperable data to improve student learning. Pledge signatories can access resources, technical assistance, events, and scholarships to support technology selection and procurement.

Ultimately, the increased demand for interoperability drives the edtech ecosystem to implement better interoperability practices. Pledge signatories commit to prioritizing the secure access, privacy, and interoperability of their edtech products, which empowers educators and families to engage more deeply in their students’ education. Meanwhile, they will improve access to that most valuable educator asset: time.

Two tips to consider:

Don’t ignore the capacity needs of educators in their efforts to provide the best quality education to students across the country.

Prioritize your time by signing the Project Unicorn School Network pledge and begin your journey towards seamless, secure data management.

Elise Hawthorne is the Technical Support and Implementation Lead for Project Unicorn at InnovateEDU.

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A few years ago we started with project-based learning (PBL) in my Spanish classes and part of our focus was on the United Nations Sustainable Development Goals. (SDGs) which are 17 goals set forth in 2015 with hopes to meet these goals by 2030. Some of the goals focus on helping to reverse damage done by climate change, work toward the elimination of poverty, facilitate the creation of healthy waterways, develop sustainable cities and communities, to name a few. With the SDGs as a focus, students can engage in meaningful real-world projects where they learn to identify a global problem and act locally.

The importance of giving students opportunities like this is to help them understand how they can effect change in the world that will benefit them and others in the future. I spoke with Steve Sostak, educator and founder of Inspire Citizens about the importance of bringing this type of learning into our classrooms. Steve said: “Education for sustainable development and global citizenship enables learners to build the future-focused cognitive skills and dispositions that shape a healthier self, society, and planet. When we take this transformative learning and combine it with imagining our schools as local community centers, students can purposefully apply interdisciplinary learning to co-create a wiser and more compassionate world together.”

When students truly care about an issue, make decisions about their learning path and reflect on that learning, they develop empathy and it also fosters the development of social-emotional learning (SEL) skills. As students build social awareness by connecting with community members and learning about challenges that impact the people and the world around them, they better understand the world they live in and the importance of working together to help others. As students design and work through their own projects, it helps them to develop SEL skills of self-awareness and self-management. Our students need to have an understanding of the world around them beyond their community and by connecting them with meaningful opportunities to make an impact, it will amplify their learning potential and prepare them for whatever the future holds.

Focusing on the SDGs is a way to help students and educators problem solve, communicate, and collaborate about ways that they can implement a project or take action for the world. Every teacher in any grade level or content area can find a way to bring learning about the SDGs into the classroom for the students. In my experience using project-based learning with my Spanish classes, looking at challenges faced in Spanish-speaking countries and finding those same challenges or similar challenges locally, made a tremendous impact on students. The phrase “Think global, act local” has become quite familiar around the world. When we look at these global issues it helps us to become more aware of the issues being faced by members of our own local community and take action.

We have the means between the technology available to us to do the research to explore ideas and to communicate with one another to bring in these real-world, purposeful learning experiences for our students.. Since we are helping to prepare students for the future, it makes sense that we prepare them to face challenges that exist in the world and come up with solutions for them. To find alternate ways of providing food to avoiding poverty to having sustainable cities for example.

Real-world learning in my school

At the start of this school year, my school, Riverview Junior-Senior High School in Oakmont, PA became involved in something that has been a truly meaningful learning experience that will benefit the community and offer authentic learning for students. A few years ago, we had a small hydroponics unit inside a classroom that students worked with. In 2019, the school applied for and received a grant to install a full hydroponic grow pod system outside of the school. One of our teachers, Mr. Michael MacConnell with the help of several students, works in the pod each day and takes care of the plants, cleaning and maintaining the pod.

With experiences such as these, students learn about sustainability through hands-on work. They learn about science and how what they are doing can impact their community and even the world. They are continuing to build on it and they have plans to grow a few thousand plants each month and potentially partner with a local food bank to donate produce. During this process students are learning about real world application of food production, working together on how to solve problems such as lack of food. Students are developing skills of collaboration, problem-solving, time management, critical thinking and engaging in something that is truly unique and more personalized to them. Principal Eric Hewitt is impressed by the work that students are doing. He adds “Work around sustainability is important to our society in general. Getting experience as a high school student puts young people in a great position to move into these careers.

Impact on learning

Educators may wonder why it is important to get kids involved in SDG projects and what the benefits are. MacConnell says that he “finds it very important that students learn about the food supply system. What they think is local and fresh can be from a different state or even country and has created so many greenhouse gasses to get to where it was located.” Looking at learning about the SDGS, MacConnell believes that the “sustainability goals set forth by the UN are a great guide for teachers to teach globalism.” He asks himself “What can I show my students that can make an impact on the world? It’s the small practices they can do in their everyday lives that will drive consumer spending and ultimately company practices.”

Principal Hewitt adds “When you work on a project in the classroom, you rarely get to see how that work is connected to anything else. The Grow-pod project allows students to see a bigger picture. They are not just growing plants but making connections to ensure that the food is being used—connecting with food service and seeing the fruits of their labor being served in our own cafeteria.  That experience expands their vision and helps them see how their work fits in the larger scale of a system.”

So what do students think?

Jacob Bennett, a ninth-grader – “I like working in the pod because I like planting.  I like to get my hands dirty”

Caden Smith, an eighth-grader– “I love being in the unit as much as I can.  I like working with my hands and am learning so much.”

Wendy Derry (Aide) – “The impact I see is when the students watch the seeds sprout, grow larger, care for the plant’s needs, and then harvest it for the school to use in the cafeteria.  The whole process is engaging, exciting, and educational for our students.”

Resources to learn more

MacConnell has some suggestions for schools looking to get started with a similar program. He says “We were excited to get a big project like this funded and implemented. Money is out there to help with sustainable spaces/practices. I think it’s important to start small…this year the ecology club and I will be starting a recycling program for the school that will eventually lead to composting and less waste.”

Sostak shared that for educators beginning to take first steps into understanding and using the SDGs, he highly recommends these resources: Flourish Project: SDGs for the Early Years, the Good Life Goals Pack of Actions and the Inspire Citizens Design Sprint which is an excellent tool to explore in designing learning experiences that embed concepts related to sustainability.

We can help students to look at some of the challenges that are faced in the world today and think about how they can be part of the solution. When we empower students to explore solutions, to think critically, to collaborate, and to engage in learning in which they can apply skills they’re learning from different classes, it promotes authentic, real-world experiences that will best prepare them for the future. It shows that we are all in this together.

Related Articles

United Nations Sustainable Development Goals Could Be Our Standards 

Think Global Act Local: How to Embed SDGs in Your School and Community

Green School Infuses Nature-based Learning for Sustainable Education

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