1 citations · 2 across the 7 of their papers we have counts for
7 papers
Evaluating Feedback Focus and Pedagogical Adaptivity in LLM-Generated Feedback on Student Writing
Norah Almousa, Shayan Peyghambari Oskoui, Raquel Coelho +3
We investigate whether state-of-the-art large language models (LLMs) generate feedback that reflects the pedagogical practices of expert teachers in terms of feedback focus and ada…
SEFORA: Student Essays with Feedback Corpus and LLM Feedback Evaluation Framework
Shayan Peyghambari Oskoui, Norah Almousa, Zhaoyi Joey Hou +5
Effective writing feedback is among the strongest drivers of student learning, yet producing it at scale is labor-intensive. LLMs offer a natural path to scaling writing support, b…
Intention-Adaptive LLM Fine-Tuning for Text Revision Generation
Zhexiong Liu, Diane Litman
Large Language Models (LLMs) have achieved impressive capabilities in various context-based text generation tasks, such as summarization and reasoning; however, their applications…
Efficient Layer-wise LLM Fine-tuning for Revision Intention Prediction
Zhexiong Liu, Diane Litman
Large Language Models (LLMs) have shown extraordinary success across various text generation tasks; however, their potential for simple yet essential text classification remains un…
eRevise+RF: A Writing Evaluation System for Assessing Student Essay Revisions and Providing Formative Feedback
Zhexiong Liu, Diane Litman, Elaine Wang +4
The ability to revise essays in response to feedback is important for students' writing success. An automated writing evaluation (AWE) system that supports students in revising the…
Analyzing Large Language Models for Classroom Discussion Assessment
Nhat Tran, Benjamin Pierce, Diane Litman +2
Automatically assessing classroom discussion quality is becoming increasingly feasible with the help of new NLP advancements such as large language models (LLMs). In this work, we…
Enhancing Knowledge Retrieval with Topic Modeling for Knowledge-Grounded Dialogue
Nhat Tran, Diane Litman
Knowledge retrieval is one of the major challenges in building a knowledge-grounded dialogue system. A common method is to use a neural retriever with a distributed approximate nea…