dc.contributor.author | Jääskelä, Päivikki | |
dc.contributor.author | Heilala, Ville | |
dc.contributor.author | Kärkkäinen, Tommi | |
dc.contributor.author | Häkkinen, Päivi | |
dc.date.accessioned | 2020-04-21T12:55:51Z | |
dc.date.available | 2020-04-21T12:55:51Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Jääskelä, P., Heilala, V., Kärkkäinen, T., & Häkkinen, P. (2021). Student agency analytics : learning analytics as a tool for analysing student agency in higher education. <i>Behaviour and Information Technology</i>, <i>40</i>(8), 790-808. <a href="https://doi.org/10.1080/0144929X.2020.1725130" target="_blank">https://doi.org/10.1080/0144929X.2020.1725130</a> | |
dc.identifier.other | CONVID_34610505 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/68635 | |
dc.description.abstract | This paper presents a novel approach and a method of learning analytics to study student agency in higher education. Agency is a concept that holistically depicts important constituents of intentional, purposeful, and meaningful learning. Within workplace learning research, agency is seen at the core of expertise. However, in the higher education field, agency is an empirically less studied phenomenon with also lacking coherent conceptual base. Furthermore, tools for students and teachers need to be developed to support learners in their agency construction. We study student agency as a multidimensional phenomenon centring on student-experienced resources of their agency. We call the analytics process developed here student agency analytics, referring to the application of learning analytics methods for data on student agency collected using a validated instrument. The data are analysed with unsupervised and supervised methods. The whole analytics process will be automated using microservice architecture. We provide empirical characterisations of student-perceived agency resources by applying the analytics process in two university courses. Finally, we discuss the possibilities of using agency analytics in supporting students to recognise their resources for agentic learning and consider contributions of agency analytics to improve academic advising and teachers' pedagogical knowledge. | en |
dc.format.mimetype | application/pdf | |
dc.language | eng | |
dc.language.iso | eng | |
dc.publisher | Taylor & Francis | |
dc.relation.ispartofseries | Behaviour and Information Technology | |
dc.rights | In Copyright | |
dc.subject.other | student agency | |
dc.subject.other | learning analytics | |
dc.subject.other | robust statistics | |
dc.title | Student agency analytics : learning analytics as a tool for analysing student agency in higher education | |
dc.type | article | |
dc.identifier.urn | URN:NBN:fi:jyu-202004212844 | |
dc.contributor.laitos | Koulutuksen tutkimuslaitos | fi |
dc.contributor.laitos | Informaatioteknologian tiedekunta | fi |
dc.contributor.laitos | Finnish Institute for Educational Research | en |
dc.contributor.laitos | Faculty of Information Technology | en |
dc.contributor.oppiaine | Human and Machine based Intelligence in Learning | fi |
dc.contributor.oppiaine | Koulutuksen tutkimuslaitos | fi |
dc.contributor.oppiaine | Koulutusteknologia ja kognitiotiede | fi |
dc.contributor.oppiaine | Digitalization in and for learning and interaction | fi |
dc.contributor.oppiaine | Monitieteinen oppimisen ja opetuksen tutkimus | fi |
dc.contributor.oppiaine | Human and Machine based Intelligence in Learning | en |
dc.contributor.oppiaine | Finnish Institute for Educational Research | en |
dc.contributor.oppiaine | Learning and Cognitive Sciences | en |
dc.contributor.oppiaine | Digitalization in and for learning and interaction | en |
dc.contributor.oppiaine | Multidisciplinary research on learning and teaching | en |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | |
dc.type.coar | http://purl.org/coar/resource_type/c_2df8fbb1 | |
dc.description.reviewstatus | peerReviewed | |
dc.format.pagerange | 790-808 | |
dc.relation.issn | 0144-929X | |
dc.relation.numberinseries | 8 | |
dc.relation.volume | 40 | |
dc.type.version | acceptedVersion | |
dc.rights.copyright | © 2020 Taylor & Francis | |
dc.rights.accesslevel | openAccess | fi |
dc.subject.yso | koneoppiminen | |
dc.subject.yso | oppiminen | |
dc.subject.yso | opiskelijat | |
dc.subject.yso | toimijuus | |
dc.format.content | fulltext | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p21846 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p2945 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p16486 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p2335 | |
dc.rights.url | http://rightsstatements.org/page/InC/1.0/?language=en | |
dc.relation.doi | 10.1080/0144929X.2020.1725130 | |
jyx.fundinginformation | No funding information. | |
dc.type.okm | A1 | |