6 papers
Decomposing the Doer Effect in Programming Practice: Code Writing Stands Out Among Active Practice
Arun Balajiee Lekshmi Narayanan, Gillian Gold, Jordan Barria-Pineda +3
The "doer effect" suggests that actively doing practice activities is more strongly associated with learning outcomes than passively viewing content. In the doer effect literature,…
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…
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…
A Survey of LLM-Based Applications in Programming Education: Balancing Automation and Human Oversight
Griffin Pitts, Anurata Prabha Hridi, Arun-Balajiee Lekshmi-Narayanan
Novice programmers benefit from timely, personalized support that addresses individual learning gaps, yet the availability of instructors and teaching assistants is inherently limi…
A Pre-Trained Graph-Based Model for Adaptive Sequencing of Educational Documents
Jean Vassoyan, Anan Schütt, Jill-Jênn Vie +3
Massive Open Online Courses (MOOCs) have greatly contributed to making education more accessible. However, many MOOCs maintain a rigid, one-size-fits-all structure that fails to ad…
Towards Scalable Automated Grading: Leveraging Large Language Models for Conceptual Question Evaluation in Engineering
Rujun Gao, Xiaosu Guo, Xiaodi Li +3
This study explores the feasibility of using large language models (LLMs), specifically GPT-4o (ChatGPT), for automated grading of conceptual questions in an undergraduate Mechanic…