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Found 6 papers, 2 papers with code
An Automatic Question Usability Evaluation Toolkit
Evaluating multiple-choice questions (MCQs) involves either labor intensive human assessments or automated methods that prioritize readability, often overlooking deeper question design flaws.
Automated Generation and Tagging of Knowledge Components from Multiple-Choice Questions
This research advances the automation of KC generation and classification for assessment items, alleviating the need for student data or predefined KC labels.
Generative AI for Education (GAIED): Advances, Opportunities, and Challenges
This survey article has grown out of the GAIED (pronounced "guide") workshop organized by the authors at the NeurIPS 2023 conference.
Assessing the Quality of Multiple-Choice Questions Using GPT-4 and Rule-Based Methods
We demonstrated the effectiveness of the two methods in identifying common item-writing flaws present in the student-generated questions across different subject areas.
Learnersourcing in the Age of AI: Student, Educator and Machine Partnerships for Content Creation
Engaging students in creating novel content, also referred to as learnersourcing, is increasingly recognised as an effective approach to promoting higher-order learning, deeply engaging students with course material and developing large repositories of content suitable for personalized learning.
fAIlureNotes: Supporting Designers in Understanding the Limits of AI Models for Computer Vision Tasks
To design with AI models, user experience (UX) designers must assess the fit between the model and user needs.
