Use Case

Generative AI models like Language Models (LLMs) and image generators can be a compelling tool for creating virtual mental arithmetic trainers. A LLM like ChatGPT can be programmed to generate a continuous stream of arithmetic problems of varying complexity, dynamically adjusting the difficulty level based on user performance. This ensures personalized learning and constant improvement. It can also provide detailed explanations for the solutions, enhancing understanding. Additionally, image generators can create visual aids and graphical representations of problems to facilitate learners who struggle with numerical representation alone. For instance, an image generator can generate pie charts for fractions or bar graphs for comparison sums. Furthermore, LLMs can aid in simulating an interactive classroom environment by adjusting the tone, language, and providing immediate feedback, making learning arithmetic engaging and less strenuous.

Ask the user to input the number of questions they want to practice

Prompt ChatGPT to generate a series of math problems based on the user's input

Ask the user to input their answer for each math problem

Fetch the correct answers for the math problems from an external API

Display the user's answers and the correct answers along with corresponding feedback for each problem

This is a description of how a potential AI application, built using Clevis, could function. The application is a virtual mental arithmetic trainer. Features similar to this can be built using Clevis for those wishing to do so.

In the first step, the application asks the user to input the number of arithmetic problems they want to practice. This is done through a Text Input step.

Next, using OpenAI's GPT-3 model (via the ChatGPT step), the application generates the specific number of math problems based on the user's request. For example, if the user inputs '10', the AI software generates 10 different arithmetic problems.

Subsequently, the application asks the user to input their answers for each math problem. Like the first step, this is done through a Text Input step.

Following this, the app makes an Http Request to an external API. This API returns the correct solutions for the arithmetic problems the user just solved.

Finally, the solutions given by the user and the correct solutions are displayed side by side. This is achieved by the Display Output step. Users can compare their responses against the correct solutions and receive feedback to improve their future performance.

The above steps showcase an example of an educational tool built with Clevis, helping users improve mental arithmetic skills with a seamless AI-driven interface.

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