SLMs achieve competitive performance with LLMs on pedagogically grounded metrics for assessment design but exhibit biases in model-based evaluation versus experts, supporting bounded AI use with human oversight.
arXiv preprint arXiv:2402.12702 (2024)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Small, Private Language Models as Teammates for Educational Assessment Design
SLMs achieve competitive performance with LLMs on pedagogically grounded metrics for assessment design but exhibit biases in model-based evaluation versus experts, supporting bounded AI use with human oversight.