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Predicting Gaps in Usage in a Phone-Based Literacy Intervention System
Educational technologies may help support out-of-school learning in contexts where formal schooling fails to reach every child, but children may not persist in using such systems to learn at home. Prior research has developed methods for predicting learner dropout but primarily for adults in formal...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334192/ http://dx.doi.org/10.1007/978-3-030-52237-7_8 |
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author | Chatterjee, Rishabh Madaio, Michael Ogan, Amy |
author_facet | Chatterjee, Rishabh Madaio, Michael Ogan, Amy |
author_sort | Chatterjee, Rishabh |
collection | PubMed |
description | Educational technologies may help support out-of-school learning in contexts where formal schooling fails to reach every child, but children may not persist in using such systems to learn at home. Prior research has developed methods for predicting learner dropout but primarily for adults in formal courses and Massive Open Online Courses (MOOCs), not for children’s voluntary ed tech usage. To support early literacy in rural contexts, our research group developed and deployed a phone-based literacy technology with rural families in Côte d’Ivoire in two longitudinal studies. In this paper, we investigate the feasibility of using time-series classification models trained on system log data to predict gaps in children’s voluntary usage of our system in both studies. We contribute insights around important features associated with sustained system usage, such as children’s patterns of use, performance on the platform, and involvement from other adults in their family. Finally, we contribute design implications for predicting and supporting learners’ voluntary, out-of-school usage of mobile learning applications in rural contexts. |
format | Online Article Text |
id | pubmed-7334192 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-73341922020-07-06 Predicting Gaps in Usage in a Phone-Based Literacy Intervention System Chatterjee, Rishabh Madaio, Michael Ogan, Amy Artificial Intelligence in Education Article Educational technologies may help support out-of-school learning in contexts where formal schooling fails to reach every child, but children may not persist in using such systems to learn at home. Prior research has developed methods for predicting learner dropout but primarily for adults in formal courses and Massive Open Online Courses (MOOCs), not for children’s voluntary ed tech usage. To support early literacy in rural contexts, our research group developed and deployed a phone-based literacy technology with rural families in Côte d’Ivoire in two longitudinal studies. In this paper, we investigate the feasibility of using time-series classification models trained on system log data to predict gaps in children’s voluntary usage of our system in both studies. We contribute insights around important features associated with sustained system usage, such as children’s patterns of use, performance on the platform, and involvement from other adults in their family. Finally, we contribute design implications for predicting and supporting learners’ voluntary, out-of-school usage of mobile learning applications in rural contexts. 2020-06-09 /pmc/articles/PMC7334192/ http://dx.doi.org/10.1007/978-3-030-52237-7_8 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Chatterjee, Rishabh Madaio, Michael Ogan, Amy Predicting Gaps in Usage in a Phone-Based Literacy Intervention System |
title | Predicting Gaps in Usage in a Phone-Based Literacy Intervention System |
title_full | Predicting Gaps in Usage in a Phone-Based Literacy Intervention System |
title_fullStr | Predicting Gaps in Usage in a Phone-Based Literacy Intervention System |
title_full_unstemmed | Predicting Gaps in Usage in a Phone-Based Literacy Intervention System |
title_short | Predicting Gaps in Usage in a Phone-Based Literacy Intervention System |
title_sort | predicting gaps in usage in a phone-based literacy intervention system |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334192/ http://dx.doi.org/10.1007/978-3-030-52237-7_8 |
work_keys_str_mv | AT chatterjeerishabh predictinggapsinusageinaphonebasedliteracyinterventionsystem AT madaiomichael predictinggapsinusageinaphonebasedliteracyinterventionsystem AT oganamy predictinggapsinusageinaphonebasedliteracyinterventionsystem |