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Analyzing Special Needs Support through Networks and Learning Analytics in Primary Education
Mid Sweden University, Faculty of Human Sciences, Department of Education. (HEEL: Higher Education and E-Learning)ORCID iD: 0000-0002-9803-3358
2022 (English)In: Networked Learning 2022: Proceedings for the Thirteenth International Conference on Networked Learning (NLC2022) / [ed] Jimmy Jaldemark, Marcia Håkansson Lindqvist, Peter Mozelius, Lena-Maria Öberg, Maarten De Laat, Nina Bonderup Dohn, Thomas Ryberg, Sundsvall, 2022, p. 331-334Conference paper, Published paper (Refereed)
Abstract [en]

In this short paper, analytical issues of networked learning are related to special needs support and learning analytics research in primary education. Very brief suggestions for these analytical issues are discussed for the networked learning research field to continue to expand upon. In part, the discussion is intended to form the underpinnings of a work-in-progress research project with cross-disciplinary networked connections across multiple universities.

Currently, teachers are faced with an expansion of their professional role that may be too economically demanding, which may result in consequences that is not beneficial for children with special needs. Researchers that aim to study inclusive education face the challenge to represent findings in a way that does not increase workload for teachers in primary education. Any failings in this regard may strengthen the intertwining of educational results and economical interest, which to a large extent could be considered as opposed to networked learning theory, dualistically separated from pedagogical concerns.

The inclusive goal of addressing diversity for children with special needs may be promoted by providing an educational setting with networked connections that enhances variation to modes of behavior, by addressing specific and contextual strengths and challenges of students appropriately. With learning analytics, specific and contextual strengths and challenges of students might be easier to highlight with new database schemas, algorithms, and user interfaces to represent networked data. Radical behaviorist methodology may further emphasize specific contextual findings from primary education through strictly defined events of behavior, which may be of interest to the networked learning research community to further expand upon.

Thus, this paper proposes suggestions for networked learning research of primary education, with approaches commonly implemented in special education, such as radical behaviorist methodology. The suggestions are based on networked consequences from three social dimensions: political, economic, and technology-developmental.

1    The political dimension is discussed through the notion of inclusive education for children with special needs and its current state,

2     the economic dimension is discussed through the 21st century role expansion of teachers,

3    the technology-developmental dimension is discussed through learning analytic research and its connection to bodily and biological associations. This dimension is especially noteworthy, as learning analytics is currently underutilized in primary education research as opposed to common higher education research.

Place, publisher, year, edition, pages
Sundsvall, 2022. p. 331-334
Keywords [en]
Behaviorism, Elementary education, Evaluation methodologies, Improving classroom teaching, Inclusive education, Learning analytics, Special educational needs
National Category
Pedagogy
Identifiers
URN: urn:nbn:se:miun:diva-46297ISBN: 978-87-974099-0-9 (print)OAI: oai:DiVA.org:miun-46297DiVA, id: diva2:1704466
Conference
Thirteenth International Conference on Networked Learning (NLC2022), Sundsvall, Sweden, May 16-18 2022.
Available from: 2022-10-18 Created: 2022-10-18 Last updated: 2024-06-19Bibliographically approved
In thesis
1. Smartbands, artificial intelligence, and special educational needs: Multifarious behaviorist design for primary education
Open this publication in new window or tab >>Smartbands, artificial intelligence, and special educational needs: Multifarious behaviorist design for primary education
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Exploring data from various disciplinary-linked methodologies with many different data types and many different data collection sources is common in multimodal learning analytics research. Such data nowadays include previously unobservable measurements that have the potential to expand our knowledge about student learning. Exploration and manipulation of such data are relevant alongside a complex shift in future education systems fueled by increasingly powerful digital technology that enables Artificial Intelligence (AI). These developments impact research on students with Special Educational Needs (SEN) in primary education. This thesis aims with a multimodal learning analytics approach and radical behaviorist emphasis to relate AI and SEN to educational design and research of primary education. Further, foundational aspects of methodological and scientific approaches are explored in related research fields. Beside in-depth philosophical explorations, three notable knowledge contributions for educational sciences methodological purposes include (a) the empirical study of biometrical understanding of students' stress as related to SEN and learning in primary education classrooms, (b) educational exploration of the management and manipulation of large amounts of data through complex sorting algorithms across databases, and (c) applied AI-related modeling and analysis with networked learning analytics visualizations related to the research of primary education. Potential aspects of the impact of AI on research are discussed, such as vast changes to literature review practices and beneficial aspects of mobile adaptive, behaviorist, and predictive digital technology. Ethical implications are also discussed, such as transparency risks that may contribute to large-scale misinformation and integrity-abusing means of control.

Place, publisher, year, edition, pages
Sundsvall: Mid Sweden University, 2024. p. 140
Series
Mid Sweden University doctoral thesis, ISSN 1652-893X ; 409
Keywords
Artificial intelligence, behaviorism, deployable wearable, digital technology, educational design, heart rate variability, multimodal learning analytics, special educational needs
National Category
Pedagogy
Identifiers
urn:nbn:se:miun:diva-51576 (URN)978-91-89786-70-7 (ISBN)
Public defence
2024-08-30, Fälldinsalen, Holmgatan 10, Sundsvall, 13:00 (English)
Opponent
Supervisors
Note

Vid tidpunkten för framläggandet av avhandlingen var samtliga delarbeten publicerade.

At the time of the PhD defence all of the papers were published.

Available from: 2024-06-19 Created: 2024-06-19 Last updated: 2024-06-19Bibliographically approved

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https://www.networkedlearning.aau.dk/digitalAssets/1274/1274674_proceedings-for-the-thirteenth-international-conference-on-networked-learning_.pdf

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Gunnars, Fabian

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