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Found 6 papers, 0 papers with code
A Comparative Study of AI-Generated (GPT-4) and Human-crafted MCQs in Programming Education
While there is a growing body of research in computing education on utilizing large language models (LLMs) in generation and engagement with coding exercises, the use of LLMs for generating programming MCQs has not been extensively explored.
Harnessing LLMs in Curricular Design: Using GPT-4 to Support Authoring of Learning Objectives
We evaluated 127 LOs that were automatically generated based on a carefully crafted prompt (detailed guidelines on high-quality LOs authoring) submitted to GPT-4 for conceptual modules and projects of an AI Practitioner course.
Can Generative Pre-trained Transformers (GPT) Pass Assessments in Higher Education Programming Courses?
We evaluated the capability of generative pre-trained transformers (GPT), to pass assessments in introductory and intermediate Python programming courses at the postsecondary level.
Large Language Models (GPT) Struggle to Answer Multiple-Choice Questions about Code
While questions requiring to fill-in a blank in the code or completing a natural language statement about the snippet are handled rather successfully, MCQs that require analysis and/or reasoning about the code (e. g., what is true/false about the snippet, or what is its output) appear to be the most challenging.
Intersectionality Goes Analytical: Taming Combinatorial Explosion Through Type Abstraction
HCI researchers' and practitioners' awareness of intersectionality has been expanding, producing knowledge, recommendations, and prototypes for supporting intersectional populations.
Linguistic Markers of Influence in Informal Interactions
There has been a long standing interest in understanding `Social Influence' both in Social Sciences and in Computational Linguistics.
