We report preliminary analyses from an ongoing study using performance-based tasks to assess science teachers’ generative AI (GenAI) literacy for classroom assessment and compare these scores with self-reported GenAI use and confidence. Preliminary findings indicate moderate correlation with use frequency but weak correlation with confidence, highlighting performance assessments’ value.

We use pretrained transformer-based language models in SemEval-2020 Task 7: Assessing the Funniness of Edited News Headlines. Inspired by the incongruity theory of humor, we use a contrastive approach to capture the surprise in the edited headlines. In the official evaluation, our system gets 0.531 RMSE in Subtask 1, 11th among 49 submissions. In Subtask 2, our system gets 0.632 accuracy, 9th among 32 submissions.