This survey provides a comprehensive overview of AQG using LLMs, focusing on educational applications, and includes a taxonomy of question types by response openness, an analysis of AQG efforts across knowledge fields, educational levels, evaluation strategies, and difficulty control.
Roberto Oliveira, A. Hernández, M. Garbin et al.· ACM Computing Surveys· 1 citation
This investigation proposes the NORKE framework, a structure-aware solution for constructing KGs from normative documents that leverages the inherent normative hierarchy, to extract and formalize rules as semantically cohesive RDF triples.
E. D. de Souza, A. Gomes, J. D. dos Reis et al.· 0 citations
Test-based learning is effective in fostering knowledge retention, but manually creating assessment questions remains time-consuming and limits personalized student practice. The advent of Large Language Models (LLMs) has introduced new possibilities for Automatic Question Generation (AQG). Motivated by this context, t...
Roberto Oliveira, A. Hernández, M. Garbin et al.· ACM Computing Surveys· 0 citations
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