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.

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

Chiara Alzetta
Primo
;
2025

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.
Campo DC Valore Lingua
dc.authority.ancejournal JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY en
dc.authority.orgunit Istituto di linguistica computazionale "Antonio Zampolli" - ILC en
dc.authority.people Chiara Alzetta en
dc.authority.people Ilaria Torre en
dc.collection.id.s b3f88f24-048a-4e43-8ab1-6697b90e068e *
dc.collection.name 01.01 Articolo in rivista *
dc.contributor.appartenenza Istituto di linguistica computazionale "Antonio Zampolli" - ILC *
dc.contributor.appartenenza.mi 918 *
dc.contributor.area Non assegn *
dc.date.accessioned 2025/06/16 17:07:39 -
dc.date.available 2025/06/16 17:07:39 -
dc.date.firstsubmission 2025/06/04 12:21:10 *
dc.date.issued 2025 -
dc.date.submission 2025/06/04 12:21:10 *
dc.description.abstracteng 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. -
dc.description.allpeople Alzetta, Chiara; Torre, Ilaria -
dc.description.allpeopleoriginal Chiara Alzetta; Ilaria Torre en
dc.description.fulltext open en
dc.description.international no en
dc.description.numberofauthors 2 -
dc.identifier.doi 10.1002/asi.24992 en
dc.identifier.isi WOS:001427490400001 -
dc.identifier.scopus 2-s2.0-85218265677 en
dc.identifier.source orcid *
dc.identifier.uri https://hdl.handle.net/20.500.14243/545881 -
dc.identifier.url https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24992?af=R en
dc.language.iso eng en
dc.relation.firstpage 1 en
dc.relation.lastpage 22 en
dc.relation.numberofpages 22 en
dc.subject.keywordseng Annotation, Annotation Tool, Prerequisite Relations, User Evaluation, Usability, -
dc.subject.singlekeyword Annotation *
dc.subject.singlekeyword Annotation Tool *
dc.subject.singlekeyword Prerequisite Relations *
dc.subject.singlekeyword User Evaluation *
dc.subject.singlekeyword Usability *
dc.title Prerequisite Relations Annotation Tool: Annotation and analysis of educational relations in texts en
dc.type.driver info:eu-repo/semantics/article -
dc.type.full 01 Contributo su Rivista::01.01 Articolo in rivista it
dc.type.miur 262 -
iris.isi.extIssued 2025 -
iris.isi.extTitle Prerequisite Relations Annotation Tool: Annotation and analysis of educational relations in texts -
iris.mediafilter.data 2025/06/17 04:06:16 *
iris.orcid.lastModifiedDate 2025/06/16 17:07:39 *
iris.orcid.lastModifiedMillisecond 1750086459870 *
iris.scopus.extIssued 2025 -
iris.scopus.extTitle Prerequisite Relations Annotation Tool: Annotation and analysis of educational relations in texts -
iris.sitodocente.maxattempts 1 -
iris.unpaywall.bestoahost publisher *
iris.unpaywall.bestoaversion publishedVersion *
iris.unpaywall.doi 10.1002/asi.24992 *
iris.unpaywall.hosttype publisher *
iris.unpaywall.isoa true *
iris.unpaywall.journalisindoaj false *
iris.unpaywall.landingpage https://doi.org/10.1002/asi.24992 *
iris.unpaywall.license cc-by *
iris.unpaywall.metadataCallLastModified 20/06/2025 04:51:03 -
iris.unpaywall.metadataCallLastModifiedMillisecond 1750387863928 -
iris.unpaywall.oastatus hybrid *
isi.authority.ancejournal JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY###2330-1635 *
isi.authority.sdg Goal 4: Quality education###12084 *
isi.category NU *
isi.category ET *
isi.contributor.affiliation Consiglio Nazionale delle Ricerche (CNR) -
isi.contributor.affiliation University of Genoa -
isi.contributor.country Italy -
isi.contributor.country Italy -
isi.contributor.name Chiara -
isi.contributor.name Ilaria -
isi.contributor.researcherId KVX-9760-2024 -
isi.contributor.researcherId GCR-9224-2022 -
isi.contributor.subaffiliation ItaliaNLP Lab -
isi.contributor.subaffiliation Dept Informat Bioengn Robot & Syst Engn -
isi.contributor.surname Alzetta -
isi.contributor.surname Torre -
isi.date.issued 2025 *
isi.description.abstracteng 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. *
isi.description.allpeopleoriginal Alzetta, C; Torre, I; *
isi.document.sourcetype WOS.SCI *
isi.document.type Article *
isi.document.types Article, Early Access *
isi.identifier.doi 10.1002/asi.24992 *
isi.identifier.eissn 2330-1643 *
isi.identifier.isi WOS:001427490400001 *
isi.journal.journaltitle JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY *
isi.journal.journaltitleabbrev J ASSOC INF SCI TECH *
isi.language.original English *
isi.publisher.place 111 RIVER ST, HOBOKEN 07030-5774, NJ USA *
isi.title Prerequisite Relations Annotation Tool: Annotation and analysis of educational relations in texts *
scopus.authority.ancejournal JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY###2330-1635 *
scopus.category 1710 *
scopus.category 1705 *
scopus.category 1802 *
scopus.category 3309 *
scopus.contributor.affiliation Istituto di Linguistica Computazionale “Antonio Zampolli” -
scopus.contributor.affiliation University of Genoa -
scopus.contributor.afid 60008941 -
scopus.contributor.afid 60121711 -
scopus.contributor.auid 57192938832 -
scopus.contributor.auid 57220754587 -
scopus.contributor.country Italy -
scopus.contributor.country Italy -
scopus.contributor.dptid 114087935 -
scopus.contributor.dptid -
scopus.contributor.name Chiara -
scopus.contributor.name Ilaria -
scopus.contributor.subaffiliation ItaliaNLP Lab;CNR; -
scopus.contributor.subaffiliation Department of Informatics;Bioengineering;Robotics and Systems Engineering; -
scopus.contributor.surname Alzetta -
scopus.contributor.surname Torre -
scopus.date.issued 2025 *
scopus.description.abstracteng 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. *
scopus.description.allpeopleoriginal Alzetta C.; Torre I. *
scopus.differences scopus.relation.lastpage *
scopus.differences scopus.relation.firstpage *
scopus.differences scopus.description.allpeopleoriginal *
scopus.differences scopus.relation.issue *
scopus.differences scopus.relation.volume *
scopus.document.type ar *
scopus.document.types ar *
scopus.funding.funders 501100000780 - European Commission; 501100004462 - Consiglio Nazionale delle Ricerche; *
scopus.identifier.doi 10.1002/asi.24992 *
scopus.identifier.eissn 2330-1643 *
scopus.identifier.pui 2033395185 *
scopus.identifier.scopus 2-s2.0-85218265677 *
scopus.journal.sourceid 21100307484 *
scopus.language.iso eng *
scopus.publisher.name John Wiley and Sons Inc *
scopus.relation.firstpage 1006 *
scopus.relation.issue 7 *
scopus.relation.lastpage 1027 *
scopus.relation.volume 76 *
scopus.title Prerequisite Relations Annotation Tool: Annotation and analysis of educational relations in texts *
scopus.titleeng Prerequisite Relations Annotation Tool: Annotation and analysis of educational relations in texts *
Appare nelle tipologie: 01.01 Articolo in rivista
File in questo prodotto:
File Dimensione Formato  
Asso for Info Science Tech - 2025 - Alzetta - Prerequisite Relations Annotation Tool Annotation and analysis of.pdf

accesso aperto

Licenza: Creative commons
Dimensione 4.3 MB
Formato Adobe PDF
4.3 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/545881
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact