Data input for a Generative AI LLM.
The Professional Law Institute (part of the Dickson Poon School of Law) is looking for a research assistant who can input data into a Generative AI LLM that has been built to provide feedback to students on a Land Law formative answer. This is part of a trial to see whether Generative AI can provide appropriate, and useful feedback, on that formative assessment for the Land Law module on the MSc in Law and Professional Practice course (which is a post-graduate course for non-law students).
The LLM needs to be run offline (for ethics approval reasons) and therefore the students cannot access the LLM to put their formative answers through this. As such, we need a research assistant who will take the formative answers from KEATS (as they are submitted online through KEATS), save them into a Sharepoint folder and anonymise the answers by giving them a number instead of the student?s name, details etc. The anonymised answer will then be run through the LLM, and the feedback generated should be copied and pasted onto the bottom of the student?s formative answer. This feedback will then be checked by a member of the research team, and then the research assistant will email the feedback back to each of the relevant students (using a proforma email produced by the research team). A detailed flowchart will be provided for the research assistant to follow that will list all these processes.
QualificationsWe are looking for a third year undergraduate or masters? level student to undertake this work. The subject of you degree, or masters, does not matter, but if you have any interest in Generative AI and computing then that would be useful.
SkillsAttention to detail, ability to work well with the wider research team, ability to work quickly yet accurately. Good computing skills required, and an ability to work with Excel.
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