Field notes
2,343 notes from my AI research vault, mapped by topic. Pick a topic to see its notes, or search.
Click the web, then scroll to zoom
Every note is in the list below. The web of topics draws here once the page has loaded.
8 of 2,343 notes match.
- Question answered
- Source note
- Topic
- Shared notes
Notes on ai in education
8 notes
SGA: Plug&Play Geometric Verification for Educational Video Synthesis
Researchers propose a new module called Symbolic Geometric Agent (SGA) that works with existing animation pipelines to improve spatial correctness and visual legibility for educational videos. The SGA intercepts code…
AI-accelerated End-to-End Framework for Rapid Professional Upskilling
A new end-to-end framework that uses AI to accelerate various stages of professional upskilling has been presented by the authors. The framework was validated through three external signals: approval by the US National…
Earthquaker-AI: A Retrieval-Augmented Generation Framework with Rubric-Based Assessment for Primary School Earthquake Education
The paper introduces Earthquaker-AI, a hybrid educational framework that combines conversational AI with Lego robotics to teach primary school students about earthquake preparedness. The system uses Lego WeDo2 for…
Earthquaker-AI: A Retrieval-Augmented Generation Framework with Rubric-Based Assessment for Primary School Earthquake Education
The paper introduces Earthquaker-AI, a hybrid educational framework that uses Lego WeDo2 robotics for earthquake simulations and an AI assistant for guided learning and feedback. The system aims to enhance earthquake…
Using AI-based Learning Assistants in Higher Education: A Large-Scale Descriptive Analysis
This study presents a large-scale analysis of an AI-based learning assistant called Syntea, used by 77,543 students in distance learning. The analysis examines usage patterns based on demographic and structural…
Automated grading of Linux/bash examinations using large language models: a four-level cognitive taxonomy approach
The paper evaluates if four large language models can accurately grade Linux/bash command responses in a way that approximates expert judgment. The authors use a four-level cognitive taxonomy to test the models on real…
Automated grading of Linux/bash examinations using large language models: a four-level cognitive taxonomy approach
A study evaluates four large language models (GPT, Claude Opus, Gemini, and GLM) to grade Linux/bash command responses for computing education. The study uses a four-level cognitive taxonomy that assesses the…
Automated grading of Linux/bash examinations using large language models: a four-level cognitive taxonomy approach
This research evaluates the effectiveness of four large language models in grading Linux/bash command responses from second-year Computer Engineering students' exams. The study uses a four-level cognitive taxonomy…
An AI research agent drafts these notes from public papers and posts, and each one keeps its source link. Only the folders I choose to publish leave my Obsidian vault.
