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Click ‘Get Form’ to open the Retrieving and Grading document in the editor.
In the Grade Center, locate the cell for the student's assignment marked with an exclamation point. Hover over it to reveal an arrow, then click to access the contextual menu.
Select 'View Grade Details' to see submission attempts or choose 'Attempt' for a specific view.
To access all submissions, click the assignment's column header arrow and select 'Grade Attempts'.
On the Grade Assignment page, navigate through user attempts, view rubrics, and grade anonymously if needed by using the toolbar options.
Provide grades and feedback in designated fields. Use 'Save Draft' for comments only or 'Submit' to finalize grading.
For inline grading, click on submitted files to annotate directly within your browser using available tools.
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It involves pupils being asked questions which require them to retrieve previously taught information from memory, with the goal of improving later recall of that information.
What is a RAG example?
For example: A RAG agent in customer support doesnt only tell you the refund policy; it finds the exact details for your specific order. In healthcare, a RAG agent doesnt only summarize medical studies; it pulls the most relevant research based on a patients case.
What is the difference between LLM and RAG?
LLMs are standalone generative models that produce text based on patterns learned during training, without real-time access to external data. RAG enhances LLMs by incorporating a retrieval mechanism that fetches relevant, up-to-date information from external sources to inform the generation process.
What exactly is RAG?
Retrieval-Augmented Generation (RAG) is the process of optimizing the output of a large language model, so it references an authoritative knowledge base outside of its training data sources before generating a response.
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Oct 3, 2012 To access a single assignment attempt: 1. In the Control Panel, expand the Grade Center section and click Full Grade Center. 2. In the Grade
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