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Found 10 papers, 3 papers with code
Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language Models
Multiple-choice questions (MCQs) are ubiquitous in almost all levels of education since they are easy to administer, grade, and are a reliable format in assessments and practices.
Improving the Validity of Automatically Generated Feedback via Reinforcement Learning
Second, we propose a framework for feedback generation that optimizes both correctness and alignment using reinforcement learning (RL).
Novice Learner and Expert Tutor: Evaluating Math Reasoning Abilities of Large Language Models with Misconceptions
We propose novel evaluations for mathematical reasoning capabilities of Large Language Models (LLMs) based on mathematical misconceptions.
Automated Distractor and Feedback Generation for Math Multiple-choice Questions via In-context Learning
Multiple-choice questions (MCQs) are ubiquitous in almost all levels of education since they are easy to administer, grade, and are a reliable form of assessment.
NeurIPS Competition Instructions and Guide: Causal Insights for Learning Paths in Education
In this competition, participants will address two fundamental causal challenges in machine learning in the context of education using time-series data.
Simultaneous Missing Value Imputation and Structure Learning with Groups
Learning structures between groups of variables from data with missing values is an important task in the real world, yet difficult to solve.
CoRGi: Content-Rich Graph Neural Networks with Attention
Graph representations of a target domain often project it to a set of entities (nodes) and their relations (edges).
Contextual HyperNetworks for Novel Feature Adaptation
While deep learning has obtained state-of-the-art results in many applications, the adaptation of neural network architectures to incorporate new output features remains a challenge, as neural networks are commonly trained to produce a fixed output dimension.
Instructions and Guide for Diagnostic Questions: The NeurIPS 2020 Education Challenge
In this competition, participants will focus on the students' answer records to these multiple-choice diagnostic questions, with the aim of 1) accurately predicting which answers the students provide; 2) accurately predicting which questions have high quality; and 3) determining a personalized sequence of questions for each student that best predicts the student's answers.
Educational Question Mining At Scale: Prediction, Analysis and Personalization
Online education platforms enable teachers to share a large number of educational resources such as questions to form exercises and quizzes for students.
