Work

Prerequisite Relations Annotation Tool: Annotation and analysis of educational relations in texts

Year: 2025

Type: article

Abstract: Relations between terms in texts have long been studied in linguistics and specialized knowledge domains, especially when occurring in educational materials like textbooks, where they play a crucial role in guiding instructional design and learning. Prerequisite relations (PR), which determine the sequence of presentation of domain terms, are particularly crucial for effective learning. Therefore, the authors consider them carefully when writing instructional texts. The reverse process of identifying PR within texts aims to extract the inherent knowledge structure they are based on and is a key task in the field of corpora annotation for educational knowledge modeling. Although there are tools for manual annotation, there is a need for specialized tools tailored to the unique properties of PR, enabling easy creation, analysis, and sharing of annotated datasets. In this paper, we introduce Prerequisite Relations Annotation Tool (PRAT), a novel tool designed for annotating PR based on a validated protocol. PRAT simplifies the process of capturing, analyzing, and visualizing prerequisite structures in educational texts. We outline PRAT's architecture and functionalities, emphasizing its unique features compared to existing corpora annotation tools. Through a user study involving users with diverse backgrounds, we show PRAT's effectiveness in real‐world scenarios.

Source: Journal of the Association for Information Science and Technology

DOI: 10.1002/asi.24992

Authors: Chiara Alzetta, Ilaria Torre

Institutions: Institute for Computational Linguistics “A. Zampolli”, University of Genoa

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: hybrid

Estimated APC paid: $3,310