335 citations · 535 across the 88 of their papers we have counts for
13 papers · 1 filter
Generative AI May Reinforce Social Biases in Software Engineering Education
Erfan Entezami, Andrew Lan, Madeline Endres
Generative artificial intelligence (GenAI) is increasingly being deployed across a wide range of real-world applications. Without careful evaluation, reliance on these systems can…
Automated Recommendation of Programming Learning Content Using Pattern-based Knowledge Components
Muntasir Hoq, Griffin Pitts, Zhangqi Duan +5
Introductory programming instruction relies on hands-on practice and short learning activities to support mastery of foundational concepts. Although many such learning resources ex…
A Classroom Study of LLM-Generated Feedback Intervention in Introductory Programming
Hasnain Heickal, Andrew Lan
Large language models (LLMs) are increasingly used to provide automated feedback in introductory programming courses, yet empirical evidence from authentic classroom deployments co…
A Multi-Agent Approach to Validate and Refine LLM-Generated Personalized Math Problems
Fareya Ikram, Nischal Ashok Kumar, Junyang Lu +4
Students benefit from math problems contextualized to their interests. Large language models (LLMs) offer promise for efficient personalization at scale. However, LLM-generated per…
Should There be a Teacher In-the-Loop? A Study of Generative AI Personalized Tasks Middle School
Candace Walkington, Mingyu Feng, Itffini Pruitt-Britton +2
Adapting instruction to the fine-grained needs of individual students is a powerful application of recent advances in large language models. These generative AI models can create t…
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…
Evaluating GPT-4 at Grading Handwritten Solutions in Math Exams
Adriana Caraeni, Alexander Scarlatos, Andrew Lan
Recent advances in generative artificial intelligence (AI) have shown promise in accurately grading open-ended student responses. However, few prior works have explored grading han…
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…
Improving Automated Distractor Generation for Math Multiple-choice Questions with Overgenerate-and-rank
Alexander Scarlatos, Wanyong Feng, Digory Smith +2
Multiple-choice questions (MCQs) are commonly used across all levels of math education since they can be deployed and graded at a large scale. A critical component of MCQs is the d…
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…
Balancing Test Accuracy and Security in Computerized Adaptive Testing
Wanyong Feng, Aritra Ghosh, Stephen Sireci +1
Computerized adaptive testing (CAT) is a form of personalized testing that accurately measures students' knowledge levels while reducing test length. Bilevel optimization-based CAT…
GPT-based Open-Ended Knowledge Tracing
Naiming Liu, Zichao Wang, Richard G. Baraniuk +1
In education applications, knowledge tracing refers to the problem of estimating students' time-varying concept/skill mastery level from their past responses to questions and predi…
Personalized Education in the AI Era: What to Expect Next?
Setareh Maghsudi, Andrew Lan, Jie Xu +1
The objective of personalized learning is to design an effective knowledge acquisition track that matches the learner's strengths and bypasses her weaknesses to ultimately meet her…