Education Copilot Review

Introduction

For as long as I can remember, people have been predicting the demise of computer programming. The main reason is that programming is an art form as much as a science or engineering discipline, which is why it has yet to happen.

Beyond the conventional lesson plan, Education Copilot is a comprehensive AI-powered system that simplifies teaching. It makes it possible to quickly create flexible lesson plans, assisting educators in fulfilling their primary responsibility of promoting the education and growth of their students. Its ability to support multiple languages increases its usefulness in various educational settings.

Copilot is a cloud service that provides interfaces to JetBrains IDEs, including IntelliJ IDEA, Neovim, and Visual Studio Code (which can run on your computer or in the cloud on Codespaces).

Operating on billions of lines of public code, OpenAI Codex is a language model that powers the code prediction engine in the cloud service.

How Does Copilot Work?

OpenAI Codex can comprehend programming and human languages with open-source code and natural language training. The Copilot editor extension transmits your remarks and code to the Copilot service, synthesizing and suggesting specific lines and functions using OpenAI Codex. Additionally, the service makes better recommendations in the future by using user choices.

Features

The following are some of Education Copilot’s salient characteristics and benefits:

1.    AI-Generated Content

Education Copilot is ideal for educators working with diverse student populations because it uses artificial intelligence (AI) to create educational handouts, lesson plans and  PowerPoints in seconds. It also supports both English and Spanish.

2.    Comprehensive Toolkit

With more than ten tools, such as project outlines, writing prompts, student reports, and lesson planners, Education Copilot provides educators with a comprehensive toolkit to assist them in producing high-quality teaching and learning materials.

3.    Time-Saving

By cutting down on planning and material creation time, Education Copilot frees teachers to concentrate on their students, resulting in more effective instruction and improved learning outcomes.

Getting The Most Out Of Copilot

Naming is difficult; we should know since “Code” is the name of our product. But “GitHub Copilot” is a cool name. Instead of using terms like “autopilot,” “pair programmer,” or even “chat,” “Copilot” expresses several key ideas in one word. Thus, by considering yourself to be the Pilot of GitHub Copilot and VS Code as well as Copilot, you begin to understand how to approach the service and engage with it to get the most out of your seatmate.

As the Pilot, you hold the authority. You choose which code to incorporate into your workspace and which suggestions to follow. The primary responsibility of Copilot is to help you by handling tedious or repetitive duties. Allow it to create sample data, write test cases, or build code scaffolding based on preexisting patterns. Greater context allows Copilot to perform more. While quick keyword-based web searches are all too common, you will get better results if you include more information.

Cases

Applications in Education Copilot are perfect for a range of educators, such as

• Teachers who want to focus on student performance and engagement by streamlining lesson planning and material generation.
• Academic establishments strive to enhance the efficacy and distribution of resources, augmenting student education’s general caliber.
• To improve the effectiveness and efficiency of their instruction, tutors, and trainers should concentrate on student engagement rather than spending time creating content.

Real-Life Examples

1.    GPT-4 Turbo

You will soon be able to take on longer and more complex tasks with Copilot because it will soon be able to generate responses using OpenAI’s most recent model, GPT-4 Turbo. In the upcoming weeks, Copilot will widely integrate this model, which is currently undergoing testing with a small group of users.

2.    New DALL-E 3 Model

An upgraded DALL-E 3 model means you can now use Copilot to produce even higher-quality images that are more accurate to the prompt. You can now access these features by going to bing.com/create or telling Copilot to create an image.

3.    Inline Compose With Rewrite Menu

Users of Microsoft Edge can easily write on most websites when they use Copilot. Choose the text you wish to modify, then request that Copilot rewrite it. Soon available to all Edge users.

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• Multi-Modal with Search Grounding: To improve image understanding for your queries, we are fusing the vision of GPT-4 with Bing image search and web search data. This new feature will soon be accessible.
• Code Interpreter: We are working on a new feature that will let you handle more complicated tasks like coding, data analysis, math, visualization, and more. We intend to make these capabilities generally available shortly after receiving input from a small group of users.
• Deep Search: Deep Search will soon be available on Bing and uses GPT-4 to optimize search results for difficult-to-understand subjects. By turning on Deep Search, you can get more relevant results by expanding your search queries into more detailed descriptions.

Inspired by our community of fans and preview testers, we’ve compiled a list of some of our favorite use cases for you to try right now to give you an idea of the scope of what Copilot can do for you.

Copilot Capabilities

Besides deducing function bodies from function names and summary comments, Copilot can also learn from variable names and other code within your editing file. In TypeScript, for instance, Copilot will attempt to determine the type if I type a colon after a variable name. Copilot will detect the word “test” and produce a runnable test for the preceding function if I type “var test1 =.” Copilot will attempt to produce more examples of the same pattern if I type multiple lines that repeat.

Copilot is compatible with many different languages and frameworks. It is most compatible with Python, JavaScript, TypeScript, Ruby, Go, and, more recently, Java. Plans call for support for the C family of languages, which includes C, C++, and C#. Others have told me it works incredibly well with well-known JavaScript frameworks like React.

Copilot Limitations

To begin with, Copilot only sometimes produces well-written code. It only produces accurate code sometimes. It only sometimes produces executable code, which is even worse. You must go over the code that Copilot produces. Handle it as if it were written by an intern green programmer who knows how to use Google but requires careful supervision.

Using the “Open Copilot” option from its context menu or the Ctrl-Enter key combination to open the Copilot suggestions window in a separate tab are two ways to avoid accepting the first snippet that Copilot offers. Examine the ten proposed solutions, then select the most closely resembles your desired outcome. After that, you should make minor edits to the generated code to strengthen it.

Although 43% right is an impressive achievement for a new code generation technology, it could be a better (or even acceptable) correctness score for production use. However, you are an adept code reviewer.

In that case, you can significantly reduce the time it takes to edit Copilot-generated code to make it accurate and reliable compared to writing it from scratch, mainly if you’re using a new library or framework.

Embracing the Chat View

An increasing number of external and internal extensions with customized Chat views emerged with the growing buzz surrounding ChatGPT.

We were concerned that these would not scale because it is difficult to support the fundamentals in a web view, such as critical bindings and themes, and because scaling to hundreds of instances of the Monaco editor is very difficult for those who use it for code blocks—not to mention that those editor instances do not support extensions.

Thus, we worked closely with the GitHub Copilot team to integrate a Chat view into the heart of Visual Studio Code.

The primary advantage of an integrated experience over a chat window in a browser is that we can give the model context, which helps to anchor the discussion and produce more insightful responses. For instance, requesting the browser-based ChatGPT to optimize code spanning multiple files is complex.

Since this is how you can perform file-to-file refactorings, Find All References, Go to Definition, and other operations, Visual Studio Code is already familiar with the workspace. To help the model provide more pertinent responses, it is possible to embed critical information into the prompt responsibly. This allows you to ask Copilot to optimize or refactor code with dependencies across multiple files.

Responsible AI

Such truly remarkable technological advances are sporadic. They also think that artificial intelligence (AI) will be the next big thing, changing how we design, develop, and use developer tools. In the end, it will improve every facet of the development process in ways that are currently unimaginable.

Although they don’t claim to be the first to say it, customers will soon question how we developed, debugged, implemented, and maintained systems and applications without AI-powered tools.

While AI is not flawless—nor are we—it will improve with time. To ensure that your experience using the service is appropriate, enjoyable, and helpful, Microsoft and GitHub Copilot implement controls and adhere to the principles of Responsible AI.

Conclusion

In its current technical preview stage of development, Copilot is helpful. With its current performance, it will continue to save even more time.