Applies ToMicrosoft Teams Microsoft Teams for Education

What is rubric generation?

Rubric generation drastically simplifies the rubric creation process by allowing the teacher to describe a rubric and use generative AI to create a rubric tailored to their scenario. The teacher will then be presented with the generated rubric for them to review and finetune by adjusting characteristics such as the target age range, length of generated content, and rubric details. Once the teacher has approved and saved the rubric, they can then attach it to an assignment to be used while grading the students' work.

What can rubric generation do?

Rubric generation supports the following generative AI operations:

  • Rubric criteria suggestions – Suggestions are generated for rubric criteria based off the provided rubric title and description.

  • Rubric generation – A rubric is generated based off the provided rubric title, rubric description, age range, grading levels, and rubric criteria.

  • Rubric rewrite – A rubric is rewritten based off revised values for rubric description, age range, sentence count, grading levels, and rubric criteria.

What is rubric generation's intended use(s)?

Rubric generation is intended for teacher in the loop where the feature is only available to educators/teachers, and the teacher must review/approve the generated content before the rubric is shown to students.

How was rubric generation evaluated? What metrics are used to measure performance?

Rubric generation was validated through direct testing with teachers to assess the relevancy and usefulness of the generated rubrics.

Validation was done to ensure that rubric generation is resilient against malicious content

How are Standards used in rubric generation?

The system provides the ability to add standards as part of Rubric Generation. The Standards are used when generating the suggested Rubric Criteria for the Rubric. Learn more about standards here Add educational standards in Microsoft tools

Educator should always validate the Rubric Criteria before they generate the Rubric

What are the limitations of rubric generation? How can users minimize the impact of rubric generation’s limitations when using the system?

Rubrics Generation is not grounded in factual knowledge and while it writes in a fluent, grammatically correct way, the content it generates can be inaccurate or inappropriate. It can’t understand meaning or evaluate accuracy, so educators need to review what it writes, and use their best judgment. Educators must validate and review all generated rubrics to ensure accuracy and relevance.

What operational factors and settings allow for effective and responsible use of rubric generation?

Effective and responsible use of Rubric Generation requires thoughtful implementation of operational factors and careful configuration of settings. Key considerations include:

  1. Clear and Detailed Evaluation Goals

    • Provide precise rubric evaluation goals, correct rubric criteria instructions, and appropriate rubric scale to guide the AI in generating contextually relevant rubrics.

  2. Educator Review and Validation

    • Always review and validate AI-generated rubrics to confirm accuracy, relevance, and alignment with the specific needs of the student.

    • Avoid over-reliance on AI; use it as a complement to human judgment, not a replacement.

  3. Educator Training

    • Provide educators with training on how to effectively input data and interpret AI-generated outputs.

    • Share best practices for integrating AI-generated rubrics into teaching strategies.

Supported Languages

AI-generated rubrics have been validated and supported for the following languages: English (United States) en-US, German (Germany) de-DE, Spanish (Spain) es-ES, Norwegian Bokmål (Norway) nb-NO, French (France) fr-FR, French (Canada) fr-CA, Spanish (Mexico) es-MX, Portuguese (Brazil) pt-BR, Japanese (Japan) ja-JP, Dutch (Netherlands) nl-NL, and Swedish (Sweden) sv-SE.

For other locals in English are used as input, e.g EN-UK, or EN-AU, the system will output in EN-US

Other languages may be available but they have not been tested.

The system hasn't been specifically evaluated for the wide variety of dialects and sociolects represented in these languages  

Generative AI models are trained using vast amounts of data, and that data is most often in English. This can sometimes result in better performance in English as compared to non-English languages. As with any deployment of generative AI models, we encourage users to be mindful of the limitations of these systems for their specific use case, and cultural and linguistic contexts.   

Microsoft is planning to add more supported languages and locals to Rubrics Generation. This Transparency Document will be updated as additional languages are supported. 

Learn more

Getting started creating rubrics with Generative AI

Create and manage grading rubrics in Microsoft Teams

Troubleshooting AI rubrics

Regenerating AI rubrics

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