Code of practice for learning analytics

Sclater, Niall - Bailey, Paul

Resumen:

Learning analytics should be used for the benefit of students. This might be to assist them individually or through using aggregated and anonymised data to help other students. Learning analytics might also be used to improve the educational experience more generally. It is distinct from assessment and should be used for formative rather than summative purposes. The effective use of learning analytics will initially involve the deployment of new systems along with changes to institutional policies and processes. New data may be collected about individuals and their learning activities. The data will be analysed and interventions may take place as a result. This presents opportunities for positive engagements and impacts on learningas well as misunderstandings, misuse of data and adverse impacts on students. Complete transparency and clear institutional policies are therefore essential regarding the purposes of learning analytics, the data collected, the processes involved and how they will be used to enhance the educational experience. This code of practice aims to set out the responsibilities of educational institutions to ensure that learning analytics is carried out responsibly, appropriately and effectively, addressing the key legal, ethical and logistical issues which are likely to arise. Educational institutions in the UK already have information management practices and procedures in place and have extensive experience of handling sensitive and personal data in accordance with the Data Protection Act 1998. They must now also comply with the General Data Protection Regulation (GDPR). By transferring and adapting this expertise to regulate the processing of data for learning analytics, institutions should establish the practices and procedures necessary to process the data of individuals lawfully and fairly.


Detalles Bibliográficos
2015
Learning Analytics
Education
Transparency
Accountability
Ciencias Sociales
Ciencias de la Educación
Análisis de datos
Procesamiento de datos
Ética
Privacidad
Inglés
Fundación Ceibal
Ceibal en REDI
https://hdl.handle.net/20.500.12381/318
Acceso abierto
Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional. (CC BY-NC-ND)
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author Sclater, Niall
author2 Bailey, Paul
author2_role author
author_facet Sclater, Niall
Bailey, Paul
author_role author
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7f26ba3bf5ac2249ea293f87030b9801
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
bitstream.url.fl_str_mv https://redi.anii.org.uy/jspui/bitstream/20.500.12381/318/2/license.txt
https://redi.anii.org.uy/jspui/bitstream/20.500.12381/318/1/Code_of_Practice_for_learning_analytics.pdf
collection Ceibal en REDI
dc.creator.none.fl_str_mv Sclater, Niall
Bailey, Paul
dc.date.accessioned.none.fl_str_mv 2018-11-26T14:41:52Z
2020-10-28T19:25:34Z
2021-09-07T18:02:09Z
dc.date.available.none.fl_str_mv 2018-11-26T14:41:52Z
2020-10-28T19:25:34Z
2021-09-07T18:02:09Z
dc.date.issued.none.fl_str_mv 2015-06-04
dc.description.abstract.none.fl_txt_mv Learning analytics should be used for the benefit of students. This might be to assist them individually or through using aggregated and anonymised data to help other students. Learning analytics might also be used to improve the educational experience more generally. It is distinct from assessment and should be used for formative rather than summative purposes. The effective use of learning analytics will initially involve the deployment of new systems along with changes to institutional policies and processes. New data may be collected about individuals and their learning activities. The data will be analysed and interventions may take place as a result. This presents opportunities for positive engagements and impacts on learningas well as misunderstandings, misuse of data and adverse impacts on students. Complete transparency and clear institutional policies are therefore essential regarding the purposes of learning analytics, the data collected, the processes involved and how they will be used to enhance the educational experience. This code of practice aims to set out the responsibilities of educational institutions to ensure that learning analytics is carried out responsibly, appropriately and effectively, addressing the key legal, ethical and logistical issues which are likely to arise. Educational institutions in the UK already have information management practices and procedures in place and have extensive experience of handling sensitive and personal data in accordance with the Data Protection Act 1998. They must now also comply with the General Data Protection Regulation (GDPR). By transferring and adapting this expertise to regulate the processing of data for learning analytics, institutions should establish the practices and procedures necessary to process the data of individuals lawfully and fairly.
dc.format.extent.es.fl_str_mv 6 p.
dc.identifier.citation.es.fl_str_mv Sclater, N., Bailey, P. (2015). Code of practice for learning analytics. Jisc [Website] https://www.jisc.ac.uk/guides/code-of-practice-for-learning-analytics (accessed November 26th, 2018).
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12381/318
dc.language.iso.none.fl_str_mv eng
dc.publisher.es.fl_str_mv JISC
dc.rights.es.fl_str_mv Acceso abierto
dc.rights.license.none.fl_str_mv Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional. (CC BY-NC-ND)
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.source.none.fl_str_mv reponame:Ceibal en REDI
instname:Fundación Ceibal
instacron:Fundación Ceibal
dc.subject.anii.none.fl_str_mv Ciencias Sociales
Ciencias de la Educación
dc.subject.ceibal.es.fl_str_mv Análisis de datos
Procesamiento de datos
Ética
Privacidad
dc.subject.es.fl_str_mv Learning Analytics
Education
Transparency
Accountability
dc.title.none.fl_str_mv Code of practice for learning analytics
dc.type.es.fl_str_mv Otro
dc.type.none.fl_str_mv info:eu-repo/semantics/other
dc.type.version.es.fl_str_mv Publicado
dc.type.version.none.fl_str_mv info:eu-repo/semantics/publishedVersion
description Learning analytics should be used for the benefit of students. This might be to assist them individually or through using aggregated and anonymised data to help other students. Learning analytics might also be used to improve the educational experience more generally. It is distinct from assessment and should be used for formative rather than summative purposes. The effective use of learning analytics will initially involve the deployment of new systems along with changes to institutional policies and processes. New data may be collected about individuals and their learning activities. The data will be analysed and interventions may take place as a result. This presents opportunities for positive engagements and impacts on learningas well as misunderstandings, misuse of data and adverse impacts on students. Complete transparency and clear institutional policies are therefore essential regarding the purposes of learning analytics, the data collected, the processes involved and how they will be used to enhance the educational experience. This code of practice aims to set out the responsibilities of educational institutions to ensure that learning analytics is carried out responsibly, appropriately and effectively, addressing the key legal, ethical and logistical issues which are likely to arise. Educational institutions in the UK already have information management practices and procedures in place and have extensive experience of handling sensitive and personal data in accordance with the Data Protection Act 1998. They must now also comply with the General Data Protection Regulation (GDPR). By transferring and adapting this expertise to regulate the processing of data for learning analytics, institutions should establish the practices and procedures necessary to process the data of individuals lawfully and fairly.
eu_rights_str_mv openAccess
format other
id CEIBAL_4baf69ea9bf9b92f02fafdc436606ef9
identifier_str_mv Sclater, N., Bailey, P. (2015). Code of practice for learning analytics. Jisc [Website] https://www.jisc.ac.uk/guides/code-of-practice-for-learning-analytics (accessed November 26th, 2018).
instacron_str Fundación Ceibal
institution Fundación Ceibal
instname_str Fundación Ceibal
language eng
network_acronym_str CEIBAL
network_name_str Ceibal en REDI
oai_identifier_str oai:redi.anii.org.uy:20.500.12381/318
publishDate 2015
reponame_str Ceibal en REDI
repository.mail.fl_str_mv mamunoz@fundacionceibal.edu.uy
repository.name.fl_str_mv Ceibal en REDI - Fundación Ceibal
repository_id_str 9421_1
rights_invalid_str_mv Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional. (CC BY-NC-ND)
Acceso abierto
spelling Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional. (CC BY-NC-ND)Acceso abiertoinfo:eu-repo/semantics/openAccess2018-11-26T14:41:52Z2020-10-28T19:25:34Z2021-09-07T18:02:09Z2018-11-26T14:41:52Z2020-10-28T19:25:34Z2021-09-07T18:02:09Z2015-06-04Sclater, N., Bailey, P. (2015). Code of practice for learning analytics. Jisc [Website] https://www.jisc.ac.uk/guides/code-of-practice-for-learning-analytics (accessed November 26th, 2018).https://hdl.handle.net/20.500.12381/318Learning analytics should be used for the benefit of students. This might be to assist them individually or through using aggregated and anonymised data to help other students. Learning analytics might also be used to improve the educational experience more generally. It is distinct from assessment and should be used for formative rather than summative purposes. The effective use of learning analytics will initially involve the deployment of new systems along with changes to institutional policies and processes. New data may be collected about individuals and their learning activities. The data will be analysed and interventions may take place as a result. This presents opportunities for positive engagements and impacts on learningas well as misunderstandings, misuse of data and adverse impacts on students. Complete transparency and clear institutional policies are therefore essential regarding the purposes of learning analytics, the data collected, the processes involved and how they will be used to enhance the educational experience. This code of practice aims to set out the responsibilities of educational institutions to ensure that learning analytics is carried out responsibly, appropriately and effectively, addressing the key legal, ethical and logistical issues which are likely to arise. Educational institutions in the UK already have information management practices and procedures in place and have extensive experience of handling sensitive and personal data in accordance with the Data Protection Act 1998. They must now also comply with the General Data Protection Regulation (GDPR). By transferring and adapting this expertise to regulate the processing of data for learning analytics, institutions should establish the practices and procedures necessary to process the data of individuals lawfully and fairly.6 p.engJISCLearning AnalyticsEducationTransparencyAccountabilityCiencias SocialesCiencias de la EducaciónAnálisis de datosProcesamiento de datosÉticaPrivacidadCode of practice for learning analyticsOtroPublicadoinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/otherRecursos y plataformasreponame:Ceibal en REDIinstname:Fundación Ceibalinstacron:Fundación CeibalSclater, NiallBailey, PaulLICENSElicense.txttext/plain4611https://redi.anii.org.uy/jspui/bitstream/20.500.12381/318/2/license.txt04900bda284772ac092f06dccc513e67MD52ORIGINALCode_of_Practice_for_learning_analytics.pdfapplication/pdf1933360https://redi.anii.org.uy/jspui/bitstream/20.500.12381/318/1/Code_of_Practice_for_learning_analytics.pdf7f26ba3bf5ac2249ea293f87030b9801MD5120.500.12381/3182024-04-15 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en REDI - Fundación Ceibalfalse
spellingShingle Code of practice for learning analytics
Sclater, Niall
Learning Analytics
Education
Transparency
Accountability
Ciencias Sociales
Ciencias de la Educación
Análisis de datos
Procesamiento de datos
Ética
Privacidad
status_str publishedVersion
title Code of practice for learning analytics
title_full Code of practice for learning analytics
title_fullStr Code of practice for learning analytics
title_full_unstemmed Code of practice for learning analytics
title_short Code of practice for learning analytics
title_sort Code of practice for learning analytics
topic Learning Analytics
Education
Transparency
Accountability
Ciencias Sociales
Ciencias de la Educación
Análisis de datos
Procesamiento de datos
Ética
Privacidad
url https://hdl.handle.net/20.500.12381/318