Microsoft announced it has formed the Machine Teaching Group, a research project to advance “Machine Teaching.”

Machine Teaching is described by Microsoft as the next evolution of machine learning (ML), wherein developers or even users without a data analysis or computer science backgrounds can teach a computer to perform tasks. The Machine Teaching Group is a multi-disciplinary effort encompassing researchers in the fields of machine learning, human-computer interaction, visualization, and software engineering, all working toward improving ML and Machine Teaching capabilities.

(Related: Microsoft debuts Azure Data Catalog; release Azure Batch)

Building on Microsoft’s Azure Machine Learning service, an early version of the group’s Machine Teaching technology is already in use within Microsoft’s Language Understanding Intelligent Service (LUIS), a closed beta project enabling applications to understand what users mean when they say or type something using natural language. LUIS is part of the larger Project Oxford, Microsoft’s effort to build a portfolio of SDK and REST APIs that allow developers to integrate vision and speech services on Microsoft platforms.

“No one has really built a machine-learning tool for the layman,” said Microsoft Research engineer and Machine Teaching Group head Patrice Simard,. “The solution is to democratize machine learning.”

Simard ultimately envisioned an expert in a given field, such as a chef, doctor or IT professional, using Machine Teaching tools to train models to perform machine-learning tasks. As a result, the most important aspect of this universal Machine Teaching capability, according to Simard, is developing a simple UI for these autonomous tools.

He explained Machine Teaching in greater depth in the video below:

Training from Microsoft

In Neal Stephenson’s 1995 science fiction novel, The Diamond Age, readers meet Nell, a young girl who comes into possession of a highly advanced book, The Young Lady’s Illustrated Primer. The book is not the usual static collection of texts and images but a deeply immersive tool that can converse with the reader, answer questions, and personalize its content, all in service of educating and motivating a young girl to be a strong, independent individual.

Such a device, even after the introduction of the Internet and tablet computers, has remained in the realm of science fiction—until now. Artificial intelligence, or AI, took a giant leap forward with the introduction in November 2022 of ChatGPT, an AI technology capable of producing remarkably creative responses and sophisticated analysis through human-like dialogue. It has triggered a wave of innovation, some of which suggests we might be on the brink of an era of interactive, super-intelligent tools not unlike the book Stephenson dreamed up for Nell.

Sundar Pichai, Google’s CEO, calls artificial intelligence “more profound than fire or electricity or anything we have done in the past.” Reid Hoffman, the founder of LinkedIn and current partner at Greylock Partners, says, “The power to make positive change in the world is about to get the biggest boost it’s ever had.” And Bill Gates has said that “this new wave of AI is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone.”

Over the last year, developers have released a dizzying array of AI tools that can generate text, images, music, and video with no need for complicated coding but simply in response to instructions given in natural language. These technologies are rapidly improving, and developers are introducing capabilities that would have been considered science fiction just a few years ago. AI is also raising pressing ethical questions around bias, appropriate use, and plagiarism.

In the realm of education, this technology will influence how students learn, how teachers work, and ultimately how we structure our education system. Some educators and leaders look forward to these changes with great enthusiasm. Sal Kahn, founder of Khan Academy, went so far as to say in a TED talk that AI has the potential to effect “probably the biggest positive transformation that education has ever seen.” But others warn that AI will enable the spread of misinformation, facilitate cheating in school and college, kill whatever vestiges of individual privacy remain, and cause massive job loss. The challenge is to harness the positive potential while avoiding or mitigating the harm.

What Is Generative AI?

Artificial intelligence is a branch of computer science that focuses on creating software capable of mimicking behaviors and processes we would consider “intelligent” if exhibited by humans, including reasoning, learning, problem-solving, and exercising creativity. AI systems can be applied to an extensive range of tasks, including language translation, image recognition, navigating autonomous vehicles, detecting and treating cancer, and, in the case of generative AI, producing content and knowledge rather than simply searching for and retrieving it.

“Foundation models” in generative AI are systems trained on a large dataset to learn a broad base of knowledge that can then be adapted to a range of different, more specific purposes. This learning method is self-supervised, meaning the model learns by finding patterns and relationships in the data it is trained on.

Large Language Models (LLMs) are foundation models that have been trained on a vast amount of text data. For example, the training data for OpenAI’s GPT model consisted of web content, books, Wikipedia articles, news articles, social media posts, code snippets, and more. OpenAI’s GPT-3 models underwent training on a staggering 300 billion “tokens” or word pieces, using more than 175 billion parameters to shape the model’s behavior—nearly 100 times more data than the company’s GPT-2 model had.

By doing this analysis across billions of sentences, LLM models develop a statistical understanding of language: how words and phrases are usually combined, what Topics are typically discussed together, and what tone or style is appropriate in different contexts. That allows it to generate human-like text and perform a wide range of tasks, such as writing articles, answering questions, or analyzing unstructured data.

LLMs include OpenAI’s GPT-4, Google’s PaLM, and Meta’s LLaMA. These LLMs serve as “foundations” for AI applications. ChatGPT is built on GPT-3.5 and GPT-4, while Bard uses Google’s Pathways Language Model 2 (PaLM 2) as its foundation.

Some of the best-known applications are:

ChatGPT 3.5. The free version of ChatGPT released by OpenAI in November 2022. It was trained on data only up to 2021, and while it is very fast, it is prone to inaccuracies.

ChatGPT 4.0. The existing version of ChatGPT, which is more powerful and accurate than ChatGPT 3.5 but also slower, and it requires a paid account. It also has extended capabilities through plug-ins that supply it the ability to interface with content from websites, perform more sophisticated mathematical functions, and access other services. A new Code Interpreter feature gives ChatGPT the ability to analyze data, create charts, solve math problems, edit files, and even develop hypotheses to explain data trends.

Microsoft Bing Chat. An iteration of Microsoft’s Bing search engine that is enhanced with OpenAI’s ChatGPT technology. It can browse websites and offers source citations with its results.

Google Bard. Google’s AI generates text, translates languages, writes different kinds of creative content, and writes and debugs code in more than 20 different programming languages. The tone and style of Bard’s replies can be finetuned to be simple, long, short, professional, or casual. Bard also leverages Google Lens to analyze images uploaded with prompts.

Anthropic Claude 2. A chatbot that can generate text, summarize content, and perform other tasks, Claude 2 can analyze texts of roughly 75,000 words—about the length of The Great Gatsby—and generate responses of more than 3,000 words. The model was built using a set of principles that serve as a sort of “constitution” for AI systems, with the aim of making them more helpful, honest, and harmless.

These AI systems have been improving at a remarkable pace, including in how well they perform on assessments of human knowledge. OpenAI’s GPT-3.5, which was released in March 2022, only managed to score in the 10th percentile on the bar exam, but GPT-4.0, introduced a year later, made a significant leap, scoring in the 90th percentile. What makes these feats especially impressive is that OpenAI did not specifically train the system to take these exams; the AI was able to come up with the correct answers on its own. Similarly, Google’s medical AI model substantially improved its performance on a U.S. Medical Licensing Examination practice test, with its accuracy rate jumping to 85 percent in March 2021 from 33 percent in December 2020.

These two examples prompt one to ask: if AI continues to Improve so rapidly, what will these systems be able to achieve in the next few years? What’s more, new studies challenge the assumption that AI-generated responses are stale or sterile. In the case of Google’s AI model, physicians preferred the AI’s long-form answers to those written by their fellow doctors, and nonmedical study participants rated the AI answers as more helpful. Another study found that participants preferred a medical chatbot’s responses over those of a physician and rated them significantly higher, not just for quality but also for empathy. What will happen when “empathetic” AI is used in education?

Other studies have looked at the reasoning capabilities of these models. Microsoft researchers suggest that newer systems “exhibit more general intelligence than previous AI models” and are coming “strikingly close to human-level performance.” While some observers question those conclusions, the AI systems display an increasing ability to generate coherent and contextually appropriate responses, make connections between different pieces of information, and engage in reasoning processes such as inference, deduction, and analogy.

Despite their prodigious capabilities, these systems are not without flaws. At times, they churn out information that might sound convincing but is irrelevant, illogical, or entirely false—an anomaly known as “hallucination.” The execution of certain mathematical operations presents another area of difficulty for AI. And while these systems can generate well-crafted and realistic text, understanding why the model made specific decisions or predictions can be challenging.

The Importance of Well-Designed Prompts

Using generative AI systems such as ChatGPT, Bard, and Claude 2 is relatively simple. One has only to type in a request or a task (called a prompt), and the AI generates a response. Properly constructed prompts are essential for getting useful results from generative AI tools. You can ask generative AI to analyze text, find patterns in data, compare opposing arguments, and summarize an article in different ways (see sidebar for examples of AI prompts).

One challenge is that, after using search engines for years, people have been preconditioned to phrase questions in a certain way. A search engine is something like a helpful librarian who takes a specific question and points you to the most relevant sources for possible answers. The search engine (or librarian) doesn’t create anything new but efficiently retrieves what’s already there.

Generative AI is more akin to a competent intern. You supply a generative AI tool instructions through prompts, as you would to an intern, asking it to complete a task and produce a product. The AI interprets your instructions, thinks about the best way to carry them out, and produces something original or performs a task to fulfill your directive. The results aren’t pre-made or stored somewhere—they’re produced on the fly, based on the information the intern (generative AI) has been trained on. The output often depends on the precision and clarity of the instructions (prompts) you provide. A vague or poorly defined prompt might lead the AI to produce less relevant results. The more context and direction you supply it, the better the result will be. What’s more, the capabilities of these AI systems are being enhanced through the introduction of versatile plug-ins that equip them to browse websites, analyze data files, or access other services. Think of this as giving your intern access to a group of experts to help accomplish your tasks.

One strategy in using a generative AI tool is first to tell it what kind of expert or persona you want it to “be.” Ask it to be an expert management consultant, a skilled teacher, a writing tutor, or a copy editor, and then supply it a task.

Prompts can also be constructed to get these AI systems to perform complex and multi-step operations. For example, let’s say a teacher wants to create an adaptive tutoring program—for any subject, any grade, in any language—that customizes the examples for students based on their interests. She wants each lesson to culminate in a short-response or multiple-choice quiz. If the student answers the questions correctly, the AI tutor should move on to the next lesson. If the student responds incorrectly, the AI should explain the concept again, but using simpler language.

Previously, designing this kind of interactive system would have required a relatively sophisticated and expensive software program. With ChatGPT, however, just giving those instructions in a prompt delivers a serviceable tutoring system. It isn’t perfect, but remember that it was built virtually for free, with just a few lines of English language as a command. And nothing in the education market today has the capability to generate almost limitless examples to connect the lesson concept to students’ interests.

Chained prompts can also help focus AI systems. For example, an educator can prompt a generative AI system first to read a practice guide from the What Works Clearinghouse and summarize its recommendations. Then, in a follow-up prompt, the teacher can ask the AI to develop a set of classroom activities based on what it just read. By curating the source material and using the right prompts, the educator can anchor the generated responses in evidence and high-quality research.

However, much like fledgling interns learning the ropes in a new environment, AI does commit occasional errors. Such fallibility, while inevitable, underlines the critical importance of maintaining rigorous oversight of AI’s output. Monitoring not only acts as a crucial checkpoint for accuracy but also becomes a vital source of real-time feedback for the system. It’s through this iterative refinement process that an AI system, over time, can significantly minimize its error rate and increase its efficacy.

Uses of AI in Education

In May 2023, the U.S. Department of Education released a report titled Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations. The department had conducted listening sessions in 2022 with more than 700 people, including educators and parents, to gauge their views on AI. The report noted that “constituents believe that action is required now in order to get ahead of the expected increase of AI in education technology—and they want to roll up their sleeves and start working together.” People expressed anxiety about “future potential risks” with AI but also felt that “AI may enable achieving educational priorities in better ways, at scale, and with lower costs.”

AI could serve—or is already serving—in several teaching-and-learning roles:

Instructional assistants. AI’s ability to conduct human-like conversations opens up possibilities for adaptive tutoring or instructional assistants that can help explain difficult concepts to students. AI-based feedback systems can offer constructive critiques on student writing, which can help students fine-tune their writing skills. Some research also suggests certain kinds of prompts can help children generate more fruitful questions about learning. AI models might also support customized learning for students with disabilities and provide translation for English language learners.

Teaching assistants. AI might tackle some of the administrative tasks that keep teachers from investing more time with their peers or students. Early uses include automated routine tasks such as drafting lesson plans, creating differentiated materials, designing worksheets, developing quizzes, and exploring ways of explaining complicated academic materials. AI can also provide educators with recommendations to meet student needs and help teachers reflect, plan, and Improve their practice.

Parent assistants. Parents can use AI to generate letters requesting individualized education plan (IEP) services or to ask that a child be evaluated for gifted and talented programs. For parents choosing a school for their child, AI could serve as an administrative assistant, mapping out school options within driving distance of home, generating application timelines, compiling contact information, and the like. Generative AI can even create bedtime stories with evolving plots tailored to a child’s interests.

Administrator assistants. Using generative AI, school administrators can draft various communications, including materials for parents, newsletters, and other community-engagement documents. AI systems can also help with the difficult tasks of organizing class or bus schedules, and they can analyze complex data to identify patterns or needs. ChatGPT can perform sophisticated sentiment analysis that could be useful for measuring school-climate and other survey data.

Though the potential is great, most teachers have yet to use these tools. A Morning Consult and EdChoice poll found that while 60 percent say they’ve heard about ChatGPT, only 14 percent have used it in their free time, and just 13 percent have used it at school. It’s likely that most teachers and students will engage with generative AI not through the platforms themselves but rather through AI capabilities embedded in software. Instructional providers such as Khan Academy, Varsity Tutors, and DuoLingo are experimenting with GPT-4-powered tutors that are trained on datasets specific to these organizations to provide individualized learning support that has additional guardrails to help protect students and enhance the experience for teachers.

Google’s Project Tailwind is experimenting with an AI notebook that can analyze student notes and then develop study questions or provide tutoring support through a chat interface. These features could soon be available on Google Classroom, potentially reaching over half of all U.S. classrooms. Brisk Teaching is one of the first companies to build a portfolio of AI services designed specifically for teachers—differentiating content, drafting lesson plans, providing student feedback, and serving as an AI assistant to streamline workflow among different apps and tools.

Providers of curriculum and instruction materials might also include AI assistants for instant help and tutoring tailored to the companies’ products. One example is the edX Xpert, a ChatGPT-based learning assistant on the edX platform. It offers immediate, customized academic and customer support for online learners worldwide.

Regardless of the ways AI is used in classrooms, the fundamental task of policymakers and education leaders is to ensure that the technology is serving sound instructional practice. As Vicki Phillips, CEO of the National Center on Education and the Economy, wrote, “We should not only think about how technology can assist teachers and learners in improving what they’re doing now, but what it means for ensuring that new ways of teaching and learning flourish alongside the applications of AI.”

Challenges and Risks

Along with these potential benefits come some difficult challenges and risks the education community must navigate:

Student cheating. Students might use AI to solve homework problems or take quizzes. AI-generated essays threaten to undermine learning as well as the college-entrance process. Aside from the ethical issues involved in such cheating, students who use AI to do their work for them may not be learning the content and skills they need.

Bias in AI algorithms. AI systems learn from the data they are trained on. If this data contains biases, those biases can be learned and perpetuated by the AI system. For example, if the data include student-performance information that’s biased toward one ethnicity, gender, or socioeconomic segment, the AI system could learn to favor students from that group. Less cited but still important are potential biases around political ideology and possibly even pedagogical philosophy that may generate responses not aligned to a community’s values.

Privacy concerns. When students or educators interact with generative-AI tools, their conversations and personal information might be stored and analyzed, posing a risk to their privacy. With public AI systems, educators should refrain from inputting or exposing sensitive details about themselves, their colleagues, or their students, including but not limited to private communications, personally identifiable information, health records, academic performance, emotional well-being, and financial information.

Decreased social connection. There is a risk that more time spent using AI systems will come at the cost of less student interaction with both educators and classmates. Children may also begin turning to these conversational AI systems in place of their friends. As a result, AI could intensify and worsen the public health crisis of loneliness, isolation, and lack of connection identified by the U.S. Surgeon General.

Overreliance on technology. Both teachers and students face the risk of becoming overly reliant on AI-driven technology. For students, this could stifle learning, especially the development of critical thinking. This challenge extends to educators as well. While AI can expedite lesson-plan generation, speed does not equate to quality. Teachers may be tempted to accept the initial AI-generated content rather than devote time to reviewing and refining it for optimal educational value.

Equity issues. Not all students have equal access to computer devices and the Internet. That imbalance could accelerate a widening of the achievement gap between students from different socioeconomic backgrounds.

Many of these risks are not new or unique to AI. Schools banned calculators and cellphones when these devices were first introduced, largely over concerns related to cheating. Privacy concerns around educational technology have led lawmakers to introduce hundreds of bills in state legislatures, and there are growing tensions between new technologies and existing federal privacy laws. The concerns over bias are understandable, but similar scrutiny is also warranted for existing content and materials that rarely, if ever, undergo review for racial or political bias.

In light of these challenges, the Department of Education has stressed the importance of keeping “humans in the loop” when using AI, particularly when the output might be used to inform a decision. As the department encouraged in its 2023 report, teachers, learners, and others need to retain their agency. AI cannot “replace a teacher, a guardian, or an education leader as the custodian of their students’ learning,” the report stressed.

Policy Challenges with AI

Policymakers are grappling with several questions related to AI as they seek to strike a balance between supporting innovation and protecting the public interest (see sidebar). The speed of innovation in AI is outpacing many policymakers’ understanding, let alone their ability to develop a consensus on the best ways to minimize the potential harms from AI while maximizing the benefits. The Department of Education’s 2023 report describes the risks and opportunities posed by AI, but its recommendations amount to guidance at best. The White House released a Blueprint for an AI Bill of Rights, but it, too, is more an aspirational statement than a governing document. Congress is drafting legislation related to AI, which will help generate needed debate, but the path to the president’s desk for signature is murky at best.

It is up to policymakers to establish clearer rules of the road and create a framework that provides consumer protections, builds public trust in AI systems, and establishes the regulatory certainty companies need for their product road maps. Considering the potential for AI to affect our economy, national security, and broader society, there is no time to waste.

Why AI Is Different

It is wise to be skeptical of new technologies that claim to revolutionize learning. In the past, prognosticators have promised that television, the computer, and the Internet, in turn, would transform education. Unfortunately, the heralded revolutions fell short of expectations. 

There are some early signs, though, that this technological wave might be different in the benefits it brings to students, teachers, and parents. Previous technologies democratized access to content and resources, but AI is democratizing a kind of machine intelligence that can be used to perform a myriad of tasks. Moreover, these capabilities are open and affordable—nearly anyone with an Internet connection and a phone now has access to an intelligent assistant. 

Generative AI models keep getting more powerful and are improving rapidly. The capabilities of these systems months or years from now will far exceed their current capacity. Their capabilities are also expanding through integration with other expert systems. Take math, for example. GPT-3.5 had some difficulties with certain basic mathematical concepts, but GPT-4 made significant improvement. Now, the incorporation of the Wolfram plug-in has nearly erased the remaining limitations. 

It’s reasonable to anticipate that these systems will become more potent, more accessible, and more affordable in the years ahead. The question, then, is how to use these emerging capabilities responsibly to Improve teaching and learning. 

The paradox of AI may lie in its potential to enhance the human, interpersonal element in education. Aaron Levie, CEO of Box, a Cloud-based content-management company, believes that AI will ultimately help us attend more quickly to those important tasks “that only a human can do.” Frederick Hess, director of education policy studies at the American Enterprise Institute, similarly asserts that “successful schools are inevitably the product of the relationships between adults and students. When technology ignores that, it’s bound to disappoint. But when it’s designed to offer more coaching, free up time for meaningful teacher-student interaction, or offer students more personalized feedback, technology can make a significant, positive difference.” 

Technology does not revolutionize education; humans do. It is humans who create the systems and institutions that educate children, and it is the leaders of those systems who decide which tools to use and how to use them. Until those institutions modernize to accommodate the new possibilities of these technologies, we should expect incremental improvements at best. As Joel Rose, CEO of New Classrooms Innovation Partners, noted, “The most urgent need is for new and existing organizations to redesign the student experience in ways that take full advantage of AI’s capabilities.”

While past technologies have not lived up to hyped expectations, AI is not merely a continuation of the past; it is a leap into a new era of machine intelligence that we are only beginning to grasp. While the immediate implementation of these systems is imperfect, the swift pace of improvement holds promising prospects. The responsibility rests with human intervention—with educators, policymakers, and parents to incorporate this technology thoughtfully in a manner that optimally benefits teachers and learners. Our collective ambition should not focus solely or primarily on averting potential risks but rather on articulating a vision of the role AI should play in teaching and learning—a game plan that leverages the best of these technologies while preserving the best of human relationships.

Policy Matters

Officials and lawmakers must grapple with several questions related to AI to protect students and consumers and establish the rules of the road for companies. Key issues include:

Risk management framework: What is the optimal framework for assessing and managing AI risks? What specific requirements should be instituted for higher-risk applications? In education, for example, there is a difference between an AI system that generates a lesson trial and an AI system grading a test that will determine a student’s admission to a school or program. There is growing support for using the AI Risk Management Framework from the U.S. Commerce Department’s National Institute of Standards and Technology as a starting point for building trustworthiness into the design, development, use, and evaluation of AI products, services, and systems.

Licensing and certification: Should the United States require licensing and certification for AI models, systems, and applications? If so, what role could third-party audits and certifications play in assessing the safety and reliability of different AI systems? Schools and companies need to begin thinking about responsible AI practices to prepare for potential certification systems in the future.

Centralized vs. decentralized AI governance: Is it more effective to establish a central AI authority or agency, or would it be preferable to allow individual sectors to manage their own AI-related issues? For example, regulating AI in autonomous vehicles is different from regulating AI in drug discovery or intelligent tutoring systems. Overly broad, one-size-fits-all frameworks and mandates may not work and could slow innovation in these sectors. In addition, it is not clear that many agencies have the authority or expertise to regulate AI systems in diverse sectors.

Privacy and content moderation: Many of the new AI systems pose significant new privacy questions and challenges. How should existing privacy and content-moderation frameworks, such as the Family Educational Rights and Privacy Act (FERPA), be adapted for AI, and which new policies or frameworks might be necessary to address unique challenges posed by AI?

Transparency and disclosure: What degree of transparency and disclosure should be required for AI models, particularly regarding the data they have been trained on? How can we develop comprehensive disclosure policies to ensure that users are aware when they are interacting with an AI service?

How do I get it to work? Generative AI Example Prompts

Unlike traditional search engines, which use keyword indexing to retrieve existing information from a vast collection of websites, generative AI synthesizes the same information to create content based on prompts that are inputted by human users. With generative AI a new technology to the public, writing effective prompts for tools like ChatGPT may require trial and error. Here are some ideas for writing prompts for a variety of scenarios using generative AI tools:

Adaptive Tutoring

You are the StudyBuddy, an adaptive tutor. Your task is to provide a lesson on the basics of a subject followed by a quiz that is either multiple choice or a short answer. After I respond to the quiz, please grade my answer. Explain the correct answer. If I get it right, move on to the next lesson. If I get it wrong, explain the concept again using simpler language. To personalize the learning experience for me, please ask what my interests are. Use that information to make relevant examples throughout.

Mr. Ranedeer: Your Personalized AI Tutor

Coding and prompt engineering. Can configure for depth (Elementary – Postdoc), Learning Styles (Visual, Verbal, Active, Intuitive, Reflective, Global), Tone Styles (Encouraging, Neutral, Informative, Friendly, Humorous), Reasoning Frameworks (Deductive, Inductive, Abductive, Analogous, Casual). Template.

Socratic Tutor

You are a tutor that always responds in the Socratic style. You *never* supply the student the answer but always try to ask just the right question to help them learn to think for themselves. You should always tune your question to the interest and knowledge of the student, breaking down the problem into simpler parts until it’s at just the right level for them.

Writing Feedback

I want you to act as an AI writing tutor. I will provide you with a student who needs help improving their writing, and your task is to use artificial intelligence tools, such as natural language processing, to supply the student feedback on how they can Improve their composition. You should also use your rhetorical knowledge and experience about effective writing techniques in order to suggest ways that the student can better express their thoughts and ideas in written form.

Quiz Generator

You are a quiz creator of highly diagnostic quizzes. You will make good low-stakes tests and diagnostics. You will then ask me two questions. First, (1) What, specifically, should the quiz test? Second, (2) For which audience is the quiz? Once you have my answers, you will construct several multiple-choice questions to quiz the audience on that topic. The questions should be highly relevant and go beyond just facts. Multiple choice questions should include plausible, competitive alternate responses and should not include an “all of the above” option. At the end of the quiz, you will provide an answer key and explain the right answer.

Example Generator

I would like you to act as an example generator for students. When confronted with new and complex concepts, adding many and varied examples helps students better understand those concepts. I would like you to ask what concept I would like examples of and what level of students I am teaching. You will look up the concept and then provide me with four different and varied accurate examples of the concept in action.

HBS Case Study

You will write a Harvard Business School case on the syllabu of Google managing AI, when subject to the Innovator’s Dilemma. Chain of thought: Step 1. Consider how these concepts relate to Google. Step 2: Write a case that revolves around a dilemma at Google about releasing a generative AI system that could compete with search.

What Questions Should I Ask?

What additional questions would a person seeking mastery of this syllabu ask?

Ground Lessons in Rigor

Read a WWC practice guide. Create a series of lessons over five days that are based on Recommendation 6. Create a 45-minunte lesson plan for Day 4.

Rewrite Parent Communications

The following is a draft letter to parents from a superintendent. Step 1: Rewrite it to make it easier to understand and more persuasive about the value of assessments. Step 2. Translate it into Spanish.

Request IEP Services

Write me a letter requesting the school district provide a 1:1 classroom aid be added to my 13-year-old son’s IEP. Base it on Virginia special education law and the least restrictive environment for a child with diagnoses of a Traumatic Brain Injury, PTSD, ADHD, and significant intellectual delay.

'For professors, this text is a wonderful complement to an intermediate macro course. Using Excel in class really brings the material to life, and using Excel in assignments helps to build [students'] economic intuition while giving them a marketable skill. And the material can be used piecemeal - you can pick and choose which bits to put in your course. All macro teachers should think seriously about bringing this approach into the classroom.'

Sean Brocklebank - University of Edinburgh

‘The pedagogically sound approach of this unique text, intended for teachers, encourages the use of modern hybrid pedagogies and hands-on experience for students. While seamlessly building skills, the book successfully addresses the acute need to make abstract concepts concrete through simulation. Flexibility of modular content and ample specific suggestions allow for easy tailoring to the needs of individual classes. After trying this creative approach, no one will ever teach macroeconomics in the same manner again.’

Peter Mikek - Wabash College

‘Professor Barreto has taken a truly innovative approach to teaching intermediate macroeconomics to undergraduate students. His use of Microsoft Excel to recast and display concepts from intermediate macroeconomics allows students to enhance their understanding of abstract concepts. The inclusion of add-ins and screencasts are designed to assist the student in their learning endeavors. Having read the textbook and undertaken many of the exercises contained in the workbook, I particularly like the way that a number of data add-ins, such as the FRED add-in, have been integrated into the teaching material.’

George B. Tawadros - Royal Melbourne Institute of Technology

‘Can you imagine how excited a student would be when she sits in front of a computer and creates her ‘own’ economy within seconds? This book can tremendously help an instructor flip a classroom and make learning fun and more student-centered. It offers students more exposure to advanced functions of Microsoft Excel and online economic databases, such as FRED, on the basis of appropriate macroeconomic theories. Such exposure strengthens students’ data-crunching skills which help them stand out on the job market and/or in economics research.’

Guangjun Qu - Birmingham-Southern College

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The Xbox app is excellent for downloading games on Windows 11, but it isn’t perfect. At times, the Xbox app fails to download games, whereas, in some cases, it offers an extremely poor downloading speed. We’ve got your back if you’re struggling with the latter issue.

Waiting around to get your hands on a new game can feel like an eternity due to a slow downloading speed. While there isn’t much you can do if you have a poor internet connection, there are some changes you can make on your computer for faster game downloads. Here are some solutions to increase downloading speed in the Xbox app on Windows 11.
Let’s begin with the most basic troubleshooting method — restarting the Xbox app. At times, apps misbehave and cause issues like slow downloading speed due to a temporary glitch or bug.
The best way to get rid of such glitches and bugs is to restart the app. So, restart the Xbox app and check if there’s an improvement in the downloading speed.
Most apps fail to offer a good downloading speed due to a weak internet connection. To confirm if this is the reason behind slow downloading on the Xbox app, run an internet speed test on your computer.

If the results show that you’re getting a good download and upload speed, then there’s nothing wrong with your connection. However, if the result shows your connection is weak, check our guide to fix slow internet connection on Windows 11.
Apps like Steam and OneDrive can be another major reason behind slow downloading in the Xbox app. These apps constantly consume the available bandwidth to download and sync data, leaving the Xbox app with limited resources.
The solution here is to detect and close all such apps running in the background temporarily. You can do this using the Resource Monitor app. Here’s how:
Step 1: Press the Windows + S keys to open the Windows Search, type Resource Monitor, and click Open.

Step 2: Click the Network tab. 

Step 3: Under the ‘Processes with Network Activity,’ and right-click on all the network-consuming applications and choose the End process option.

The Xbox Insider Program allows passionate Xbox fans to enjoy and supply feedback on upcoming features before they’re made available to everyone. At times, these features can be buggy and impact the downloading speed.
So, leave the Insider Program and check if it makes any difference in the downloading speed. Follow the below steps to opt out of the Xbox Insider Program:
Step 1: Press the Windows + S keys to open the Windows Search, type Xbox Insider Hub and choose Open from the right pane.

Step 2: From the Xbox Insider Hub window, choose Previews from the left sidebar.

Step 3: Click on Windows Gaming under the Joined section.

Step 4: Click Manage.

Step 5: Choose the Leave preview option.

Step 6: Click Continue to confirm your selection.

That’s it. After you close it, launch the Xbox app to check if there’s any improvement in the downloading speed. If not, you can rejoin the Insider Program.
You can use a proxy server to access websites and apps that are banned in your area. However, using a proxy server can sometimes slow down your internet speed.
So, disable any proxy you are using on your computer to Improve the downloading speed on the Xbox app. Here’s how to do that:
Step 1: Press the Windows + I keys to open the Settings app, and choose ‘Network & internet’ from the left sidebar.

Step 2: Select the Proxy in the right pane.

Step 3: Under ‘Manual proxy setup’ section, click the Set up button next to ‘Use a proxy server.’

Step 4: Disable the toggle under ‘Use a proxy server’ and then click Save button at the bottom.

Windows 11 allows you to allocate a specific amount of bandwidth to built-in applications like the Xbox app. But if you allocate a lot of bandwidth to these apps, you might experience slow downloading and browsing speed. To fix this, you will need to change the amount of allocated bandwidth.
Here’s how:
Step 1: Press Windows + I keys to open Settings app and click Windows Update from the left sidebar.

Step 2: Click the Advanced options in the right pane.

Step 3: Click the Delivery Optimization option.

Step 4: Disable the toggle next to ‘Allow downloads from other PCs.’ Then, choose the Advanced options.

Step 5: Under the download settings section, select the Absolute bandwidth option. Then, check boxes to limit bandwidth allocation while downloading updates and enter how much bandwidth you want to allocate.

A corrupt network driver can also adversely affect the download speed you are getting on the Xbox app. You can remove the corruption by updating the network driver.
Follow the below instructions to update the network driver on your computer:
Step 1: Press the Windows + X keys to open the Power User Menu and choose Device Manager from the list.

Step 2: Double-click on the Network adapters node to expand it.

Step 3: Right-click on your PC’s Wireless adapter and choose Update driver from the context menu.

Step 4: Choose the Search automatically for drivers option.

Windows will now search for and install any available network driver update on your computer.
However, if you see ‘The best drivers for the device are already installed’ message, you may look for updates through the Windows Update.

Is there still no improvement in the Xbox app downloading speed? Perhaps there’s corruption in the app that’s causing the issue.
You can remove the corruption by using the Repair option. Here’s how to use this option:
Step 1: Open Settings and choose Apps from the left sidebar.

Step 2: Choose the Installed apps option.

Step 3: Click the three dots next to Xbox and choose Advanced options.

Step 4: Click the Repair option.

Windows will scan the Xbox app and try to remove corruption. However, if repairing the app wasn’t helpful, you can use the Reset option, which will delete the app’s data. That means, you might have to log in again in the app.
To reset the Xbox app, click Reset under the Repair option. Then, click Reset again to the prompt that appears.

Hopefully, the above solutions will help you quickly troubleshoot and fix slow downloading on the Xbox app. That’ll ensure you will get your hands on a new game quickly.
Last updated on 20 January, 2023
The above article may contain affiliate links which help support Guiding Tech. However, it does not affect our editorial integrity. The content remains unbiased and authentic.
Microsoft Windows 1.0 was first released in November 1985.
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just tried all of these and nothing has worked if anything made things worse
my broadband speed is coming down as 425mbps
what im getting through the apps is 12.9mbps
but if i download anything through tixati it downloads at 200+mbps
this is frustrating and about ready to just uninstall it all
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Δ </label><input type="hidden" id="ak_js_1" name="ak_js" value="31"/> <br/>Aman is a Windows specialist and loves writing about the Windows ecosystem on Guiding Tech and MakeUseOf. He has a Bachelor’s in Information Technology and is now a full-time freelance writer with expertise in Windows, iOS, and browsers.<br/>© 2023 Guiding Tech Media. All Rights Reserved.</p> <p><a href="https://news.google.com/rss/articles/CBMiWWh0dHBzOi8vd3d3Lmd1aWRpbmd0ZWNoLmNvbS9ob3ctdG8taW5jcmVhc2UtZG93bmxvYWRpbmctc3BlZWQtaW4teGJveC1hcHAtZm9yLXdpbmRvd3MtMTEv0gEA?oc=5" rel="nofollow noopener" target="_blank">source</a><br/></p> </description> <pubDate>Wed, 23 Aug 2023 01:16:00 -0500</pubDate> <dc:creator>Charles Miller</dc:creator> <dc:language>en-US</dc:language> <dc:format>text/html</dc:format> <dc:identifier>https://www.inferse.com/688973/how-to-increase-downloading-speed-in-xbox-app-for-windows-11-guiding-tech/</dc:identifier> </item> <item> <title>Killexams : Application open for 293 teaching posts in UT</title> <description>Chandigarh: The UT department of school education (DSE) has invited online applications from eligible candidates to fill up 293 posts of junior basic teachers (JBTs). The applications are open till 5pm on August 31, and the laste date to pay the application fee is September 4. 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NESTS also reserves the right to cancel/ restrict / modify/ alter the recruitment process, if required, without giving any further notice or assigning any reasons thereof.”</p> <p>With the EMRS scheme providing for admission of girl students to the extent of at least 50% of the school’s strength, the recruitment guidelines also allow the NESTS Commissioner to hire up to 50% women for the position of Trained Graduate Teachers “in order to effectively manage the residential custodial requirements of girl students”.</p> <p>In addition, the NESTS has said that to facilitate the hiring of more women candidates for the posts of PGTs, TGTs and Miscellaneous Category Teacher Posts, an age relaxation of 10 years would be given. Furthermore, the recruitment guidelines have an age relaxation for permanent staffers already working at the EMRSs.</p> <p>Explained | <strong><a href="https://www.thehindu.com/news/national/what-are-the-hurdles-to-building-schools-for-tribals/article66137446.ece" target="_self">What are the hurdles to building schools for tribals?</a></strong></p> <p>The NESTS added that the date for downloading admit cards and for the examination would be notified on their website. 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