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Marking Rubric

Marking Rubric

Description

Integrating large language models into the creation of marking rubrics in higher education can assist you by making it easier to generate one. The use of artificial intelligence in this context streamlines the rubric development process and introduces a new dimension of efficiency and effectiveness.

Didactic benefits

Crafting a comprehensive and precise rubric that aligns with learning objectives and standards will assist you as an educator when assessing the students; furthermore, it will assist students in their learning process by making it transparent for them to see how learning goals are transferred and understood. Sharing the rubric with the students makes it possible for them to direct their learning.

Prompt

"Construct a comprehensive rubric for evaluating exam hand-ins in the [course name] at [graduate or undergraduate] level. The rubric should cover key criteria, including but not limited to thesis clarity, evidence quality, and critical analysis. Ensure the rubric is detailed and applicable for assessing the written work of students in the specified course."

The prompt is designed for ChatGPT (3.5). The prompt might work with other large language models, but you will need to test it.

Bloom's Taxonomy & Principles for digitally supported PBL

For this use case, it is not described how it aligns with Bloom’s Taxonomy and the principles for digitally supported PBL as it is highly contextual to the examination and goals.