335 citations · 535 across the 88 of their papers we have counts for
15 papers · 1 filter
Toward LLM-Supported Automated Assessment of Critical Thinking Subskills
Marisa C. Peczuh, Nischal Ashok Kumar, Ryan Baker +11
As the world becomes increasingly saturated with AI-generated content, disinformation, and algorithmic persuasion, critical thinking - the capacity to evaluate evidence, detect unr…
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…
Interpretable Mnemonic Generation for Kanji Learning via Expectation-Maximization
Jaewook Lee, Alexander Scarlatos, Andrew Lan
Learning Japanese vocabulary is a challenge for learners from Roman alphabet backgrounds due to script differences. Japanese combines syllabaries like hiragana with kanji, which ar…
Pattern-based Knowledge Component Extraction from Student Code Using Representation Learning
Muntasir Hoq, Griffin Pitts, Tirth Bhatt +4
Personalized instruction aims to provide learners with support that adapts to their individual knowledge and progress toward learning objectives. Discovering and tracing Knowledge…
Exploring LLMs for Predicting Tutor Strategy and Student Outcomes in Dialogues
Fareya Ikram, Alexander Scarlatos, Andrew Lan
Tutoring dialogues have gained significant attention in recent years, given the prominence of online learning and the emerging tutoring abilities of artificial intelligence (AI) ag…
PhoniTale: Phonologically Grounded Mnemonic Generation for Typologically Distant Language Pairs
Sana Kang, Myeongseok Gwon, Su Young Kwon +4
Vocabulary acquisition poses a significant challenge for second-language (L2) learners, especially when learning typologically distant languages such as English and Korean, where p…
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…
Reasoning and Sampling-Augmented MCQ Difficulty Prediction via LLMs
Wanyong Feng, Peter Tran, Stephen Sireci +1
The difficulty of multiple-choice questions (MCQs) is a crucial factor for educational assessments. Predicting MCQ difficulty is challenging since it requires understanding both th…
From Text to Visuals: Using LLMs to Generate Math Diagrams with Vector Graphics
Jaewook Lee, Jeongah Lee, Wanyong Feng +1
Advances in large language models (LLMs) offer new possibilities for enhancing math education by automating support for both teachers and students. While prior work has focused on…
The StudyChat Dataset: Analyzing Student Dialogues With ChatGPT in an Artificial Intelligence Course
Hunter McNichols, Fareya Ikram, Andrew Lan
The widespread availability of large language models (LLMs), such as ChatGPT, has significantly impacted education, raising both opportunities and challenges. Students can frequent…
Training LLM-based Tutors to Improve Student Learning Outcomes in Dialogues
Alexander Scarlatos, Naiming Liu, Jaewook Lee +2
Generative artificial intelligence (AI) has the potential to scale up personalized tutoring through large language models (LLMs). Recent AI tutors are adapted for the tutoring task…
Learning Code-Edit Embedding to Model Student Debugging Behavior
Hasnain Heickal, Andrew Lan
Providing effective feedback for programming assignments in computer science education can be challenging: students solve problems by iteratively submitting code, executing it, and…
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…
Whose story is it? Personalizing story generation by inferring author styles
Nischal Ashok Kumar, Chau Minh Pham, Mohit Iyyer +1
Personalization is critical for improving user experience in interactive writing and educational applications, yet remains understudied in story generation. We study the task of pe…