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.
Using mobile technology for reading assessment
Taxitari, L.;Cappa, C.;Ferro, M.;Marzi, C.;Nadalini, A.;Pirrelli, V.
2020
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.| Campo DC | Valore | Lingua |
|---|---|---|
| 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.authority.project | ReadLet | en |
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| dc.date.issued | 2020 | - |
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| 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. | - |
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| dc.description.allpeopleoriginal | Taxitari, L.; Cappa, C.; Ferro, M.; Marzi, C.; Nadalini, A.; Pirrelli, V. | en |
| dc.description.fulltext | restricted | en |
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| dc.identifier.doi | 10.1109/CiSt49399.2021.9357173 | en |
| dc.identifier.isbn | 978-1-7281-6646-9 | en |
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| dc.language.iso | eng | en |
| dc.relation.allauthors | Loukia Taxitari, Claudia Cappa, Marcello Ferro, Claudia Marzi, Andrea Nadalini, Vito Pirrelli | en |
| dc.relation.conferencename | 6th IEEE Congress on Information Science and Technology (CiSt) | en |
| dc.relation.firstpage | 302 | en |
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| dc.relation.medium | ELETTRONICO | en |
| dc.relation.numberofpages | 6 | en |
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| dc.relation.projectAwardTitle | ReadLet | en |
| dc.relation.projectFunderName | MUR | en |
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| dc.relation.volume | 2020-June | en |
| dc.subject.keywordseng | reading assessment, reading research, mobile technology, NLP, cloud computing, special education needs | - |
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| 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 |
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| Appare nelle tipologie: | 04.01 Contributo in Atti di convegno | |
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