AI-Powered Degree Progress Auditor using Google Sheets - n8n Workflow

Academic Advisors & Registrars: Who need to quickly check large cohorts of students for graduation readiness.
Higher Education IT Staff: Looking to deploy scalable, automated advising tools.
Automation Specialists: Seeking advanced examples of using LangChain Agents within an n8n node for structured data analysis.
Users of n8n templates: Who need to integrate complex AI logic with Google Sheets data operations.

Manually auditing degree progress for hundreds of graduating seniors is time-consuming and prone to human error. This specialized n8n workflow solves this by transforming standard academic data into actionable insights instantly. The workflow reads student records (including completed courses and program intent) from a Google Sheet. It then passes this data to an AI agent, leveraging a powerful n8n node setup, which compares the student's history against hard-coded program requirements (stored within the prompt). The output is structured JSON, ensuring high data integrity. This n8n template drastically reduces the advisory load, providing accurate, consistent degree summaries and identifying missing requirements, which is then written back directly to the Google Sheet. This makes this n8n workflow a critical tool for scaling academic operations.

This automation begins with a manual n8n trigger.

1. Trigger Data Retrieval: The execution is started using the 'When clicking Execute workflow' n8n trigger. The workflow immediately proceeds to the first action.


2. Retrieve Student Data: The 'Get Student Data1' n8n node connects to Google Sheets to read all student records from the specified 'Senior_data' tab. Each student record is processed individually.


3. AI Degree Audit: The 'Degree Audit Agent' n8n node (a LangChain Agent) takes the student's StudentID, Program, and CompletedCourses as input. It utilizes a detailed, hard-coded system message containing the requirements for various university programs (e.g., Computer Science BS, Business Administration BBA).


4. Structured AI Processing: The agent uses the connected 'OpenAI Chat Model1' (using a powerful model like gpt-5) and the 'Structured Output Parser1' n8n node. This setup forces the AI to return the audit results in a specific JSON format, including a list of Missing courses and a concise Summary of what to prioritize.


5. Write Results Back: The final 'Add Student Degree Summary' n8n node connects back to the original Google Sheet. Using the appendOrUpdate operation and matching on the StudentID, it inserts the AI-generated audit summary into the designated 'AI Degree Summary' column. This completes the data flow for this robust n8n workflow.

To deploy this powerful n8n workflow, follow these setup steps:

1. Import the n8n Workflow: Copy the provided JSON and import it directly into your n8n instance using the 'Import Workflow' option.


2. Google Sheets Credentials Setup: You must configure a Google Sheets (OAuth2) credential. In n8n, navigate to Credentials -> New -> Google Sheets (OAuth2). Sign in with your Google Account and grant the necessary access.


3. Configure Google Sheets Nodes: In both the 'Get Student Data1' and 'Add Student Degree Summary' n8n nodes, select your newly created Google Sheets credential, specify the Spreadsheet ID, and confirm the Senior_data worksheet.


4. OpenAI Credentials Setup: Create an OpenAI API credential. In n8n, navigate to Credentials -> New -> OpenAI API. Paste your API key.


5. Configure AI Node: In the 'OpenAI Chat Model1' n8n node, select your OpenAI credential. Ensure the selected model is capable of handling complex reasoning (like GPT-4 or GPT-5).


6. Test: Run the n8n trigger manually to ensure the flow reads, processes, and writes the data correctly.

When clicking ‘Execute workflow’ (Manual Trigger): This serves as the starting n8n trigger for the workflow execution, ideal for manual batch processing of student data.
Get Student Data1 (Google Sheets n8n node): Reads all rows from the target Google Sheet (Senior_data tab). It gathers input data points like StudentID, Program, and CompletedCourses that are fed into the AI agent.
OpenAI Chat Model1 (OpenAI n8n node): Defines the Large Language Model used for the audit. The workflow is configured to use a powerful model (e.g., gpt-5) for accurate analysis against the degree rules.
Structured Output Parser1 (LangChain Output Parser n8n node): Crucial for ensuring data quality. This n8n node enforces a strict JSON schema for the AI's response, making it reliable for subsequent data writing.
Degree Audit Agent (LangChain Agent n8n node): The core intelligence of this n8n workflow. It contains the complete set of program requirements in its system message. It processes the input student data, runs the analysis using the LLM, and calculates the missing courses and summarizes the student's standing.
Add Student Degree Summary (Google Sheets n8n node): Performs the final action. This n8n node uses the appendOrUpdate operation to write the AI's structured Summary back into the appropriate column of the Google Sheet, matched by StudentID.