dc.contributor.author | Heilala, Ville | |
dc.contributor.author | Jääskelä, Päivikki | |
dc.contributor.author | Saarela, Mirka | |
dc.contributor.author | Kärkkäinen, Tommi | |
dc.contributor.editor | Lv, Zhihan | |
dc.date.accessioned | 2024-02-07T12:00:22Z | |
dc.date.available | 2024-02-07T12:00:22Z | |
dc.date.issued | 2024 | |
dc.identifier.citation | Heilala, V., Jääskelä, P., Saarela, M., & Kärkkäinen, T. (2024). Adapting Teaching and Learning in Higher Education Using Explainable Student Agency Analytics. In Z. Lv (Ed.), <i>Principles and Applications of Adaptive Artificial Intelligence</i> (pp. 20-51). IGI Global. Advances in Computational Intelligence and Robotics. <a href="https://doi.org/10.4018/979-8-3693-0230-9.ch002" target="_blank">https://doi.org/10.4018/979-8-3693-0230-9.ch002</a> | |
dc.identifier.other | CONVID_202885473 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/93293 | |
dc.description.abstract | This chapter deals with the learning analytics technique called student agency analytics and explores its foundational technologies and their potential implications for adaptive teaching and learning. Student agency is vital to consider as it can empower students to take control of their learning, fostering autonomy, meaningful experiences, and improved educational outcomes. Beginning with an overview of the technique, its underlying educational foundations, and analytical approaches, the chapter demonstrates the synergy between computational psychometrics, learning analytics, and educational sciences. Considering adaptive artificial intelligence in the context of adaptive learning and teaching, the chapter underscores the potential of these approaches in education. The chapter serves as a brief guide for educators, researchers, and stakeholders interested in the convergence of AI and education. | en |
dc.format.extent | 316 | |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | |
dc.publisher | IGI Global | |
dc.relation.ispartof | Principles and Applications of Adaptive Artificial Intelligence | |
dc.relation.ispartofseries | Advances in Computational Intelligence and Robotics | |
dc.rights | In Copyright | |
dc.title | Adapting Teaching and Learning in Higher Education Using Explainable Student Agency Analytics | |
dc.type | bookPart | |
dc.identifier.urn | URN:NBN:fi:jyu-202402071779 | |
dc.contributor.laitos | Koulutuksen tutkimuslaitos | fi |
dc.contributor.laitos | Informaatioteknologian tiedekunta | fi |
dc.contributor.laitos | Kasvatustieteiden laitos | fi |
dc.contributor.laitos | Finnish Institute for Educational Research | en |
dc.contributor.laitos | Faculty of Information Technology | en |
dc.contributor.laitos | Department of Education | en |
dc.contributor.oppiaine | Koulutuksen tutkimuslaitos | fi |
dc.contributor.oppiaine | Monitieteinen oppimisen ja opetuksen tutkimus | fi |
dc.contributor.oppiaine | Koulutusteknologia ja kognitiotiede | fi |
dc.contributor.oppiaine | Human and Machine based Intelligence in Learning | fi |
dc.contributor.oppiaine | Digitalization in and for learning and interaction | fi |
dc.contributor.oppiaine | Finnish Institute for Educational Research | en |
dc.contributor.oppiaine | Multidisciplinary research on learning and teaching | en |
dc.contributor.oppiaine | Learning and Cognitive Sciences | en |
dc.contributor.oppiaine | Human and Machine based Intelligence in Learning | en |
dc.contributor.oppiaine | Digitalization in and for learning and interaction | en |
dc.type.uri | http://purl.org/eprint/type/BookItem | |
dc.relation.isbn | 979-8-3693-0230-9 | |
dc.type.coar | http://purl.org/coar/resource_type/c_3248 | |
dc.description.reviewstatus | peerReviewed | |
dc.format.pagerange | 20-51 | |
dc.relation.issn | 2327-0411 | |
dc.type.version | publishedVersion | |
dc.rights.copyright | © 2024 IGI Global | |
dc.rights.accesslevel | openAccess | fi |
dc.relation.grantnumber | 356314 | |
dc.subject.yso | tekoäly | |
dc.subject.yso | analyysi | |
dc.subject.yso | oppiminen | |
dc.subject.yso | korkeakouluopetus | |
dc.subject.yso | toimijuus | |
dc.subject.yso | opiskelijat | |
dc.format.content | fulltext | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p2616 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p6851 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p2945 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p1246 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p2335 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p16486 | |
dc.rights.url | http://rightsstatements.org/page/InC/1.0/?language=en | |
dc.relation.doi | 10.4018/979-8-3693-0230-9.ch002 | |
dc.relation.funder | Suomen Akatemia | fi |
dc.relation.funder | Research Council of Finland | en |
jyx.fundingprogram | Akatemiatutkija, SA | fi |
jyx.fundingprogram | Academy Research Fellow, AoF | en |
jyx.fundinginformation | M. S. research was supported by Otto A. Malm, the Finnish Foundation for Share Promotion, and the Academy of Finland (project no. 356314). | |
dc.type.okm | A3 | |