Artificial Intelligence in Education as Lifelong Learning: What Should be Learnt?
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| Title: | Artificial Intelligence in Education as Lifelong Learning: What Should be Learnt? |
|---|---|
| Authors: | Mozelius, Peter1 Peter.Mozelius@miun.se, Cleveland-Innes, Martha1 Martha.Clevelandinnes@miun.se, Lindqvist, Marcia Håkansson1 Marcia.HakanssonLindqvist@miun.se, Jaldemark, Jimmy1 Jimmy.Jaldemark@miun.se |
| Source: | Proceedings of the European Conference on e-Learning (ECEL). 2025, p281-288. 8p. |
| Subject Terms: | *Artificial intelligence, *Generative artificial intelligence, *Learning, *Adult education, *Professional employee training, *Teacher training |
| Abstract: | The rapid development of tools and techniques in the field of Generative AI (GenAI) has affected many sectors. One of these sectors is definitely education, where teaching, learning, assessment, curricula and policy document need to be revised and updated. Many research studies also highlight the necessity for teacher professional development regarding Artificial Intelligence in Education (AIED), as AIED is also a field under constant development and will need continuous upskilling during the coming years. There are now teacher training courses in fundamental AIED available, and more are under development. There seems to be a consensus regarding what an introduction course in AIED should comprise, but not regarding which topics continuation courses should follow-up related to continuous lifelong learning. With the heutagogical idea of asking the learners about what to learn, this question was posted to participants in a course on fundamental AIED. In a discussion forum, course participants gave their suggestions and commented on other course participants' postings. Moreover, the forum postings were supplemented with suggestions and comments from email conversations between the authors and course participants. According to the concept of Open Coding, forum postings and email conversations were analysed and divided into the categories of: AI didactics, GenAI tools for teaching, Prompt engineering, Audio generation and Voice cloning, Customisation of AI models, AI and disinformation, Applicable takeaways and AI sustainability and ethics. All of the categories were found to be relevant in a second Axial coding reanalysis. The category Applicable takeaways was found to b e t he axial category t hat ti es a ll o f t he categories t ogether for a m eaningful course d esign. T he conclusion is that a continuation course, as in introductory courses on AIED, must contain both theoretical parts with themes such as AI sustainability and ethics, but also concrete applications such as AI didactics to fulfil the aim of Applicable takeaways. Finally, it could be difficult to involve all the categories in just one or two continuation courses. However, as mentioned earlier, AIED should to be seen as continuous lifelong learning. [ABSTRACT FROM AUTHOR] |
| Copyright of Proceedings of the European Conference on e-Learning (ECEL) is the property of Academic Conferences & Publishing International Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 189744814 AccessLevel: 6 PubType: Conference PubTypeId: conference PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Artificial Intelligence in Education as Lifelong Learning: What Should be Learnt? – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Mozelius%2C+Peter%22">Mozelius, Peter</searchLink><relatesTo>1</relatesTo><i> Peter.Mozelius@miun.se</i><br /><searchLink fieldCode="AR" term="%22Cleveland-Innes%2C+Martha%22">Cleveland-Innes, Martha</searchLink><relatesTo>1</relatesTo><i> Martha.Clevelandinnes@miun.se</i><br /><searchLink fieldCode="AR" term="%22Lindqvist%2C+Marcia+Håkansson%22">Lindqvist, Marcia Håkansson</searchLink><relatesTo>1</relatesTo><i> Marcia.HakanssonLindqvist@miun.se</i><br /><searchLink fieldCode="AR" term="%22Jaldemark%2C+Jimmy%22">Jaldemark, Jimmy</searchLink><relatesTo>1</relatesTo><i> Jimmy.Jaldemark@miun.se</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Proceedings+of+the+European+Conference+on+e-Learning+%28ECEL%29%22">Proceedings of the European Conference on e-Learning (ECEL)</searchLink>. 2025, p281-288. 8p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Learning%22">Learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Adult+education%22">Adult education</searchLink><br />*<searchLink fieldCode="DE" term="%22Professional+employee+training%22">Professional employee training</searchLink><br />*<searchLink fieldCode="DE" term="%22Teacher+training%22">Teacher training</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The rapid development of tools and techniques in the field of Generative AI (GenAI) has affected many sectors. One of these sectors is definitely education, where teaching, learning, assessment, curricula and policy document need to be revised and updated. Many research studies also highlight the necessity for teacher professional development regarding Artificial Intelligence in Education (AIED), as AIED is also a field under constant development and will need continuous upskilling during the coming years. There are now teacher training courses in fundamental AIED available, and more are under development. There seems to be a consensus regarding what an introduction course in AIED should comprise, but not regarding which topics continuation courses should follow-up related to continuous lifelong learning. With the heutagogical idea of asking the learners about what to learn, this question was posted to participants in a course on fundamental AIED. In a discussion forum, course participants gave their suggestions and commented on other course participants' postings. Moreover, the forum postings were supplemented with suggestions and comments from email conversations between the authors and course participants. According to the concept of Open Coding, forum postings and email conversations were analysed and divided into the categories of: AI didactics, GenAI tools for teaching, Prompt engineering, Audio generation and Voice cloning, Customisation of AI models, AI and disinformation, Applicable takeaways and AI sustainability and ethics. All of the categories were found to be relevant in a second Axial coding reanalysis. The category Applicable takeaways was found to b e t he axial category t hat ti es a ll o f t he categories t ogether for a m eaningful course d esign. T he conclusion is that a continuation course, as in introductory courses on AIED, must contain both theoretical parts with themes such as AI sustainability and ethics, but also concrete applications such as AI didactics to fulfil the aim of Applicable takeaways. Finally, it could be difficult to involve all the categories in just one or two continuation courses. However, as mentioned earlier, AIED should to be seen as continuous lifelong learning. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Proceedings of the European Conference on e-Learning (ECEL) is the property of Academic Conferences & Publishing International Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.34190/ecel.24.1.3895 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 8 StartPage: 281 Subjects: – SubjectFull: Artificial intelligence Type: general – SubjectFull: Generative artificial intelligence Type: general – SubjectFull: Learning Type: general – SubjectFull: Adult education Type: general – SubjectFull: Professional employee training Type: general – SubjectFull: Teacher training Type: general Titles: – TitleFull: Artificial Intelligence in Education as Lifelong Learning: What Should be Learnt? Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mozelius, Peter – PersonEntity: Name: NameFull: Cleveland-Innes, Martha – PersonEntity: Name: NameFull: Lindqvist, Marcia Håkansson – PersonEntity: Name: NameFull: Jaldemark, Jimmy IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: 2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 20488637 Titles: – TitleFull: Proceedings of the European Conference on e-Learning (ECEL) Type: main |
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