The enormous potential of Information and Communication Technologies (ICT) for addressing critical educational issues is generally acknowledged, but its use in the assessment of the complex skills of reading and understanding a text has been very limited to date. The paper contrasts traditional reading assessment protocols with ReadLet, an ICT platform with a tablet front-end, designed to support online monitoring of silent and oral reading abilities in early graders. ReadLet makes use of cloud computing and mobile technology for large-scale data collection and allows the time alignment of the child's reading behaviour with texts tagged using Natural Language Processing (NLP) tools. Initial findings replicate established benchmarks from the psycholinguistic literature on reading in both typically and atypically developing children, making the application a new ground-breaking approach in the evaluation of reading skills. Index Terms--reading assessment, reading research, mobile technology, NLP, cloud computing, special education needs.

Using mobile technology for reading assessment

Taxitari L
Primo
;
Cappa C
Secondo
;
Ferro M;Marzi C;Nadalini A;Pirrelli V
Ultimo
2021

Abstract

The enormous potential of Information and Communication Technologies (ICT) for addressing critical educational issues is generally acknowledged, but its use in the assessment of the complex skills of reading and understanding a text has been very limited to date. The paper contrasts traditional reading assessment protocols with ReadLet, an ICT platform with a tablet front-end, designed to support online monitoring of silent and oral reading abilities in early graders. ReadLet makes use of cloud computing and mobile technology for large-scale data collection and allows the time alignment of the child's reading behaviour with texts tagged using Natural Language Processing (NLP) tools. Initial findings replicate established benchmarks from the psycholinguistic literature on reading in both typically and atypically developing children, making the application a new ground-breaking approach in the evaluation of reading skills. Index Terms--reading assessment, reading research, mobile technology, NLP, cloud computing, special education needs.
Campo DC Valore Lingua
dc.authority.orgunit Istituto di Fisiologia Clinica - IFC en
dc.authority.orgunit Istituto di linguistica computazionale "Antonio Zampolli" - ILC en
dc.authority.people Taxitari L en
dc.authority.people Cappa C en
dc.authority.people Ferro M en
dc.authority.people Marzi C en
dc.authority.people Nadalini A en
dc.authority.people Pirrelli V en
dc.collection.id.s 71c7200a-7c5f-4e83-8d57-d3d2ba88f40d *
dc.collection.name 04.01 Contributo in Atti di convegno *
dc.contributor.appartenenza Istituto di Fisiologia Clinica - IFC *
dc.contributor.appartenenza Istituto di linguistica computazionale "Antonio Zampolli" - ILC *
dc.contributor.appartenenza.mi 885 *
dc.contributor.appartenenza.mi 918 *
dc.date.accessioned 2024/02/21 06:26:16 -
dc.date.available 2024/02/21 06:26:16 -
dc.date.firstsubmission 2024/09/26 16:35:43 *
dc.date.issued 2021 -
dc.date.submission 2024/09/26 16:35:43 *
dc.description.abstracteng The enormous potential of Information and Communication Technologies (ICT) for addressing critical educational issues is generally acknowledged, but its use in the assessment of the complex skills of reading and understanding a text has been very limited to date. The paper contrasts traditional reading assessment protocols with ReadLet, an ICT platform with a tablet front-end, designed to support online monitoring of silent and oral reading abilities in early graders. ReadLet makes use of cloud computing and mobile technology for large-scale data collection and allows the time alignment of the child's reading behaviour with texts tagged using Natural Language Processing (NLP) tools. Initial findings replicate established benchmarks from the psycholinguistic literature on reading in both typically and atypically developing children, making the application a new ground-breaking approach in the evaluation of reading skills. Index Terms--reading assessment, reading research, mobile technology, NLP, cloud computing, special education needs. -
dc.description.affiliations ILC; IFC; ILC; ILC; ILC; ILC -
dc.description.allpeople Taxitari, L; Cappa, C; Ferro, M; Marzi, C; Nadalini, A; Pirrelli, V -
dc.description.allpeopleoriginal Taxitari, L.; Cappa, C.; Ferro, M.; Marzi, C.; Nadalini, A.; Pirrelli, V. en
dc.description.fulltext open en
dc.description.international si en
dc.description.numberofauthors 6 -
dc.identifier.isbn 9781728166469 en
dc.identifier.uri https://hdl.handle.net/20.500.14243/423945 -
dc.identifier.url http://www.ieee.ma/cist20/component/content/?id=26&Itemid=185 en
dc.language.iso eng en
dc.miur.last.status.update 2024-12-18T15:02:42Z *
dc.relation.conferencedate 05/06/2021 en
dc.relation.conferencename 6th IEEE Congress on Information Science & Technology (IEEE CIST'20) en
dc.relation.conferenceplace online en
dc.relation.firstpage 1 en
dc.relation.ispartofbook Proceedings of the 6th IEEE Congress on Information Science and Technology (CiSt) en
dc.relation.lastpage 6 en
dc.relation.numberofpages 6 en
dc.subject.keywordseng reading assessment -
dc.subject.keywordseng reading research -
dc.subject.keywordseng mobile technology -
dc.subject.keywordseng NLP -
dc.subject.keywordseng cloud computing -
dc.subject.keywordseng special education needs -
dc.subject.singlekeyword reading assessment *
dc.subject.singlekeyword reading research *
dc.subject.singlekeyword mobile technology *
dc.subject.singlekeyword NLP *
dc.subject.singlekeyword cloud computing *
dc.subject.singlekeyword special education needs *
dc.title Using mobile technology for reading assessment en
dc.type.driver info:eu-repo/semantics/conferenceObject -
dc.type.full 04 Contributo in convegno::04.01 Contributo in Atti di convegno it
dc.type.miur 273 -
dc.type.referee Esperti anonimi en
dc.ugov.descaux1 441870 -
iris.mediafilter.data 2025/04/15 04:19:47 *
iris.orcid.lastModifiedDate 2024/11/29 18:59:28 *
iris.orcid.lastModifiedMillisecond 1732903168401 *
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