Clickstream for learning analytics to assess students’ behavior with Scratch

The construction of knowledge through computational practice requires to teachers a substantial amount of time and effort to evaluate programming skills, to understand and to glimpse the evolution of the students and finally to state a quantitative judgment in learning assessment. The field of learn...

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Autores: Amo Filvá, Daniel, Alier Forment, Marc|||0000-0003-3922-1516, García Peñalvo, Francisco José, Fonseca Escudero, David, Casany Guerrero, María José|||0000-0002-5072-6745
Tipo de recurso: artículo
Fecha de publicación:2019
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/130122
Acceso en línea:https://hdl.handle.net/2117/130122
https://dx.doi.org/10.1016/j.future.2018.10.057
Access Level:acceso abierto
Palabra clave:Programming (Computers) -- Study and teaching (Higher)
Learning analytics
Clickstream
Scratch
Programming
Big data
Programació (Ordinadors) -- Ensenyament universitari
Àrees temàtiques de la UPC::Informàtica::Programació
Àrees temàtiques de la UPC::Ensenyament i aprenentatge::TIC's aplicades a l'educació
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oai_identifier_str oai:upcommons.upc.edu:2117/130122
network_acronym_str ES
network_name_str España
repository_id_str
spelling Clickstream for learning analytics to assess students’ behavior with ScratchAmo Filvá, DanielAlier Forment, Marc|||0000-0003-3922-1516García Peñalvo, Francisco JoséFonseca Escudero, DavidCasany Guerrero, María José|||0000-0002-5072-6745Programming (Computers) -- Study and teaching (Higher)Learning analyticsClickstreamScratchProgrammingBig dataProgramació (Ordinadors) -- Ensenyament universitariÀrees temàtiques de la UPC::Informàtica::ProgramacióÀrees temàtiques de la UPC::Ensenyament i aprenentatge::TIC's aplicades a l'educacióThe construction of knowledge through computational practice requires to teachers a substantial amount of time and effort to evaluate programming skills, to understand and to glimpse the evolution of the students and finally to state a quantitative judgment in learning assessment. The field of learning analytics has been a common practice in research since last years due to their great possibilities in terms of learning improvement. Both, Big and Small data techniques support the analysis cycle of learning analytics and risk of students’ failure prediction. Such possibilities can be a strong positive contribution to the field of computational practice such as programming. Our main objective was to help teachers in their assessments through to make those possibilities effective. Thus, we have developed a functional solution to categorize and understand students’ behavior in programming activities based in Scratch. Through collection and analysis of data generated by students’ clicks in Scratch, we proceed to execute both exploratory and predictive analytics to detect patterns in students’ behavior when developing solutions for assignments. We concluded that resultant taxonomy could help teachers to better support their students by giving real-time quality feedback and act before students deliver incorrectly or at least incomplete tasks.Peer ReviewedElsevier20192019-04-0120192019-03-07journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/130122https://dx.doi.org/10.1016/j.future.2018.10.057reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivs 3.0 Spainhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/1301222026-05-27T15:37:01Z
dc.title.none.fl_str_mv Clickstream for learning analytics to assess students’ behavior with Scratch
title Clickstream for learning analytics to assess students’ behavior with Scratch
spellingShingle Clickstream for learning analytics to assess students’ behavior with Scratch
Amo Filvá, Daniel
Programming (Computers) -- Study and teaching (Higher)
Learning analytics
Clickstream
Scratch
Programming
Big data
Programació (Ordinadors) -- Ensenyament universitari
Àrees temàtiques de la UPC::Informàtica::Programació
Àrees temàtiques de la UPC::Ensenyament i aprenentatge::TIC's aplicades a l'educació
title_short Clickstream for learning analytics to assess students’ behavior with Scratch
title_full Clickstream for learning analytics to assess students’ behavior with Scratch
title_fullStr Clickstream for learning analytics to assess students’ behavior with Scratch
title_full_unstemmed Clickstream for learning analytics to assess students’ behavior with Scratch
title_sort Clickstream for learning analytics to assess students’ behavior with Scratch
dc.creator.none.fl_str_mv Amo Filvá, Daniel
Alier Forment, Marc|||0000-0003-3922-1516
García Peñalvo, Francisco José
Fonseca Escudero, David
Casany Guerrero, María José|||0000-0002-5072-6745
author Amo Filvá, Daniel
author_facet Amo Filvá, Daniel
Alier Forment, Marc|||0000-0003-3922-1516
García Peñalvo, Francisco José
Fonseca Escudero, David
Casany Guerrero, María José|||0000-0002-5072-6745
author_role author
author2 Alier Forment, Marc|||0000-0003-3922-1516
García Peñalvo, Francisco José
Fonseca Escudero, David
Casany Guerrero, María José|||0000-0002-5072-6745
author2_role author
author
author
author
dc.subject.none.fl_str_mv Programming (Computers) -- Study and teaching (Higher)
Learning analytics
Clickstream
Scratch
Programming
Big data
Programació (Ordinadors) -- Ensenyament universitari
Àrees temàtiques de la UPC::Informàtica::Programació
Àrees temàtiques de la UPC::Ensenyament i aprenentatge::TIC's aplicades a l'educació
topic Programming (Computers) -- Study and teaching (Higher)
Learning analytics
Clickstream
Scratch
Programming
Big data
Programació (Ordinadors) -- Ensenyament universitari
Àrees temàtiques de la UPC::Informàtica::Programació
Àrees temàtiques de la UPC::Ensenyament i aprenentatge::TIC's aplicades a l'educació
description The construction of knowledge through computational practice requires to teachers a substantial amount of time and effort to evaluate programming skills, to understand and to glimpse the evolution of the students and finally to state a quantitative judgment in learning assessment. The field of learning analytics has been a common practice in research since last years due to their great possibilities in terms of learning improvement. Both, Big and Small data techniques support the analysis cycle of learning analytics and risk of students’ failure prediction. Such possibilities can be a strong positive contribution to the field of computational practice such as programming. Our main objective was to help teachers in their assessments through to make those possibilities effective. Thus, we have developed a functional solution to categorize and understand students’ behavior in programming activities based in Scratch. Through collection and analysis of data generated by students’ clicks in Scratch, we proceed to execute both exploratory and predictive analytics to detect patterns in students’ behavior when developing solutions for assignments. We concluded that resultant taxonomy could help teachers to better support their students by giving real-time quality feedback and act before students deliver incorrectly or at least incomplete tasks.
publishDate 2019
dc.date.none.fl_str_mv 2019
2019-04-01
2019
2019-03-07
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/130122
https://dx.doi.org/10.1016/j.future.2018.10.057
url https://hdl.handle.net/2117/130122
https://dx.doi.org/10.1016/j.future.2018.10.057
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301603

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