📚 SAT Prep Module – Topic Selection & AI Content Generation

 

SAT Prep Module – Topic Selection & AI Content Generation

Overview

This module enables users to navigate and select SAT preparation topics based on a well-defined hierarchical structure. It supports dynamic content generation using AI, tailored to the selected topic, and is designed to help students prepare for the SAT with personalised, targeted study material.

This module is via our AI learning platform www.skilld.ai

🏗️ Feature Structure

1. Hierarchical Topic Tree

The SAT syllabus is modelled in a structured hierarchy with the following levels:

• Section (e.g., Reading and Writing, Math, Optional Essay)

o Domain (e.g., Craft and Structure, Algebra)

▪ Subtopic (e.g., Words in Context, Linear Equations)

▪ Subdivision (e.g., Vocabulary in prose and poetry)

This allows for granular topic targeting, so students can focus precisely on the areas where they need the

most help.

Example:

Section: Math

└── Domain: Algebra

└── Subtopic: Linear Equations and Inequalities

└── Subdivision: Solving single-variable equations

🤖 AI-Powered Content Generation

📥 Input Parameters

The system accepts user selections at any level (topic, subtopic, or subdivision), and uses that input to dynamically generate instructional content.

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🎯 Key Benefits

1. Personalised Prep: Learners can focus on micro-topics, helping them improve in specific areas.

2. Efficient Navigation: The hierarchy allows users to drill down to exact content without feeling overwhelmed.

3.  Expert-Like Guidance: AI responses simulate one-on-one SAT tutoring with clear explanations, examples, and test strategies.

4. Scalable: Easily extendable for new topics or other exams (e.g., GRE, GMAT).

🛠️ Use Case Flow

1. User Journey:

o Student selects a Section (e.g., Math)

o Picks a Domain (e.g., Advanced Math)

o Chooses a Subtopic (e.g., Exponential Functions)

o Optionally picks a Subdivision (e.g., Growth and decay models)

o Receives a full-length, AI-generated explanation tailored to the chosen topic.

2. Under the Hood:

o The system maps user input to the satData structure.

o Constructs the final prompt.

o Sends it to an LLM using a consistent system + user prompt structure.

o Displays the response in a student-friendly UI.

🔒 Extensibility & Maintenance

• Modular Structure: New sections, topics, or subdivisions can be added directly in the satData object.

• Prompt Logic Decoupled: Prompt template and SAT hierarchy are independent, allowing easy tweaks to tone, strategy, or format.

• Localisation Potential: The structure supports international versions of the SAT or translations

What’s Coming Next ?

🔍 Topic Selection with AI-Powered Explanations

Students can choose what to study through a structured topic hierarchy (Section → Domain → Subtopic

→ Subdivision).

Once a topic is selected, an AI tutor generates an intuitive explanation—including examples, common mistakes, strategies, and test-taking tips.

🤖 Interactive AI Practice

After reading a topic, students are taken to a practice page where an AI asks relevant questions to reinforce learning—turning passive reading into active learning.

💬 Ask-AI: Content-Based Doubt Clarification

An integrated AI chatbot is available throughout the learning experience. Students can ask questions about the topic they’re studying, and the AI responds with helpful, context-aware explanations.

📄 Previous Year Question Papers + AI Help

There’s a dedicated section where students can browse past SAT questions. Here too, the AI chatbot is available to explain or break down any question, just like a real tutor.