Raw LLM Responses

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Comment
Sabrina N. I don't think there is any one solution. I don't think bans and the use of AI detection are the way to go. They are not meaningfully enforceable or fit for purpose, respectively. It's clear at this stage that assessment needs to change. The days of relying on artefacts as stand-ins for learning are probably over (and that has been well overdue for some time, as someone who has been investigating contract cheating for years). If for some reason a university wants to use a report or an essay for the purposes of assessment, they can either, a) use it as a purely formative exercise (remove the value of cheating), b) watch the student write it, or c) make the assessment a face-to-face conversation about the document rather than the document itself. Ultimately, universities need to be spending more time having conversations with students about their learning, and these conversations should be the assessment.
LinkedIn General AI Discourse Integrity Investigator & Data Scientist | Assur… 2026-05-28T04:2…
Coding Result
DimensionValue
Primary valuehuman_autonomy
Secondary valuenone
Alignment targetindividual_users
Stancedemanding
Emotionapproval
Value justificationThe speaker emphasizes the need for universities to focus on conversations with students about their learning, implying a desire for human judgment and autonomy in the assessment process.
Target justificationThe speaker is primarily concerned with the impact of AI on individual students and their learning experience, as evident from their suggestions for alternative assessment methods.
Coded at2026-06-11T08:26:26Z
Raw LLM Response
```json { "value_primary": "human_autonomy", "value_secondary": "none", "target": "individual_users", "stance": "demanding", "emotion": "approval", "value_justification": "The speaker emphasizes the need for universities to focus on conversations with students about their learning, implying a desire for human judgment and autonomy in the assessment process.", "target_justification": "The speaker is primarily concerned with the impact of AI on individual students and their learning experience, as evident from their suggestions for alternative assessment methods." } ```