AI Agents & Automation
Curriculum Science Agent
An AI copilot that maps education standards to matching curriculum lessons and exports a ready-to-use scope and sequence.
Live demo — click around
Matched 3 units spanning 10 lesson objectives across the molecular biology strand. Expand a unit to see the matched lesson objectives.
- DNA replication basics
- Transcription & translation
- Gene expression
- Mutations & variation
- Inheritance patterns
Interactive prototype with representative sample data.
The challenge
Aligning a lesson library to education standards is slow, manual cross-referencing work. A curriculum lead has to read a standard, hunt through units and lessons for anything that addresses it, and hand-assemble a scope and sequence document — repeating the process for every standard and every follow-up question.
Our approach
A conversational agent lets a curriculum lead paste or select a standard, then searches the lesson library and returns the matched units and lessons with objective counts. It keeps conversation history so follow-up questions build on prior context, and it assembles the results into a scope-and-sequence document the user can download as Markdown. It is built on an AWS Bedrock Agent driven from a Streamlit chat interface via boto3.
How it works
Select or paste a standard
The user picks a suggested standard chip or pastes standard text directly into the chat input to start a request.
The agent searches the lesson library
An AWS Bedrock Agent interprets the standard and searches the curriculum lesson library for units and lessons that address it.
Matched units and lessons come back
The assistant returns the matched units and lessons with objective counts, rendered as a rich, expandable response in the chat.
Follow-ups use conversation history
Conversation history is retained, so the user can ask follow-up questions and refine the mapping without restating context.
Scope and sequence is assembled
The matched results are compiled into a scope-and-sequence preview the curriculum lead can review in a side panel.
Export as Markdown
The user downloads the generated scope and sequence as a Markdown (.md) file to use or share.
Tech stack
Results
Turns a manual, standard-by-standard cross-referencing task into a conversational lookup that returns matched lessons and a downloadable scope-and-sequence draft in one flow. Concrete impact metrics were not measured for this case study.
Hours saved per scope-and-sequence
Standards mapped per session
Lesson library size covered
Curriculum leads using the tool
Metrics to be populated with the project owner’s real figures.
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