REVIEW 6 cited by
EduChat: A Large-Scale Language Model-based Chatbot System for Intelligent Education
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
EduChat (https://www.educhat.top/) is a large-scale language model (LLM)-based chatbot system in the education domain. Its goal is to support personalized, fair, and compassionate intelligent education, serving teachers, students, and parents. Guided by theories from psychology and education, it further strengthens educational functions such as open question answering, essay assessment, Socratic teaching, and emotional support based on the existing basic LLMs. Particularly, we learn domain-specific knowledge by pre-training on the educational corpus and stimulate various skills with tool use by fine-tuning on designed system prompts and instructions. Currently, EduChat is available online as an open-source project, with its code, data, and model parameters available on platforms (e.g., GitHub https://github.com/icalk-nlp/EduChat, Hugging Face https://huggingface.co/ecnu-icalk ). We also prepare a demonstration of its capabilities online (https://vimeo.com/851004454). This initiative aims to promote research and applications of LLMs for intelligent education.
Forward citations
Cited by 6 Pith papers
-
SCOPE and SCION: A Benchmark and an Auditable Reference Pipeline for Schema Induction and Fusion from Text
A 24-dataset benchmark for inducing schema graphs from raw text, plus an auditable LLM-based pipeline that reports the highest scores on the benchmark's four schema-similarity metrics.
-
Investigating Student Interaction Patterns with Large Language Model-Powered Course Assistants in Computer Science Courses
A deployed LLM course assistant served 589 students across three CS courses; logs show heavy evening use and homework questions, while only about 11% of responses included AI follow-ups that students mostly ignored.
-
How to Make Museums More Interactive? Case Study of Artistic Chatbot
A field deployment of a RAG-based voice chatbot at an art exhibition shows that retrieval-grounded answers stay on-topic (60% relevant) despite most user questions being off-topic.
-
PAPPL: Personalized AI-Powered Progressive Learning Platform
PAPPL, an LLM-powered tutoring platform that generates progressive hints from student attempt history, was linked to fewer attempts and higher second-attempt success in a small pavement-engineering pilot, but the evid...
-
InqEduAgent: Adaptive AI Learning Partners with Gaussian Process Augmentation
InqEduAgent fits a Gaussian process to simulated collaboration gains and then uses a Pareto front to pick learning partners, reporting small average gains over random pairing on six CMMLU domains.
-
Robust pid sliding mode control for dc servo motor speed control
An abstract-only claim that SMC-PID outperforms PID for DC servo motor speed on the CE110 trainer; the submitted body text is an unrelated paper, so the result is unverifiable.
Discussion (0). Continue with ORCID to comment.