160 citations · 168 across the 13 of their papers we have counts for
13 papers
KASER: Knowledge-Aligned Student Error Simulator for Open-Ended Coding Tasks
Zhangqi Duan, Nigel Fernandez, Andrew Lan
Open-ended tasks, such as coding problems that are common in computer science education, provide detailed insights into student knowledge. However, training large language models (…
RADAR: Reasoning-Ability and Difficulty-Aware Routing for Reasoning LLMs
Nigel Fernandez, Branislav Kveton, Ryan A. Rossi +2
Reasoning language models have demonstrated remarkable performance on many challenging tasks in math, science, and coding. Choosing the right reasoning model for practical deployme…
SMART: Simulated Students Aligned with Item Response Theory for Question Difficulty Prediction
Alexander Scarlatos, Nigel Fernandez, Christopher Ormerod +2
Item (question) difficulties play a crucial role in educational assessments, enabling accurate and efficient assessment of student abilities and personalization to maximize learnin…
LookAlike: Consistent Distractor Generation in Math MCQs
Nisarg Parikh, Nigel Fernandez, Alexander Scarlatos +2
Large language models (LLMs) are increasingly used to generate distractors for multiple-choice questions (MCQs), especially in domains like math education. However, existing approa…
Automated Knowledge Component Generation for Interpretable Knowledge Tracing in Coding Problems
Zhangqi Duan, Nigel Fernandez, Arun Balajiee Lekshmi Narayanan +5
Knowledge components (KCs) mapped to problems help model student learning, tracking their mastery levels on fine-grained skills thereby facilitating personalized learning and feedb…
Test Case-Informed Knowledge Tracing for Open-ended Coding Tasks
Zhangqi Duan, Nigel Fernandez, Alexander Hicks +1
Open-ended coding tasks, which ask students to construct programs according to certain specifications, are common in computer science education. Student modeling can be challenging…
DiVERT: Distractor Generation with Variational Errors Represented as Text for Math Multiple-choice Questions
Nigel Fernandez, Alexander Scarlatos, Wanyong Feng +2
High-quality distractors are crucial to both the assessment and pedagogical value of multiple-choice questions (MCQs), where manually crafting ones that anticipate knowledge defici…
Interpreting Latent Student Knowledge Representations in Programming Assignments
Nigel Fernandez, Andrew Lan
Recent advances in artificial intelligence for education leverage generative large language models, including using them to predict open-ended student responses rather than their c…
SyllabusQA: A Course Logistics Question Answering Dataset
Nigel Fernandez, Alexander Scarlatos, Andrew Lan
Automated teaching assistants and chatbots have significant potential to reduce the workload of human instructors, especially for logistics-related question answering, which is imp…
3HAN: A Deep Neural Network for Fake News Detection
Sneha Singhania, Nigel Fernandez, Shrisha Rao
The rapid spread of fake news is a serious problem calling for AI solutions. We employ a deep learning based automated detector through a three level hierarchical attention network…
Improving Reading Comprehension Question Generation with Data Augmentation and Overgenerate-and-rank
Nischal Ashok Kumar, Nigel Fernandez, Zichao Wang +1
Reading comprehension is a crucial skill in many aspects of education, including language learning, cognitive development, and fostering early literacy skills in children. Automate…
Automated Scoring for Reading Comprehension via In-context BERT Tuning
Nigel Fernandez, Aritra Ghosh, Naiming Liu +4
Automated scoring of open-ended student responses has the potential to significantly reduce human grader effort. Recent advances in automated scoring often leverage textual represe…
Synthesizing Tasks for Block-based Programming
Umair Z. Ahmed, Maria Christakis, Aleksandr Efremov +4
Block-based visual programming environments play a critical role in introducing computing concepts to K-12 students. One of the key pedagogical challenges in these environments is…