Assessing and Tracking Students’ Wellbeing through an Automated Scoring System: School Day Wellbeing Model

Xin Tang, Katja Upadyaya, Toyama Hiroyuki, Mika Kasanen, Katariina Salmela-Aro

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Sammanfattning

The assessment of student wellbeing has been often static and lagged behind for the intervention/diagnostic purpose. In this chapter, we aim to introduce an automated school wellbeing scoring dynamic real-time system, School Day Wellbeing Model. With Artificial Intelligence (AI)-based item sampling methods and answers scoring and reporting systems, the School Day Wellbeing Model can collect wellbeing data at low cognitive cost, track wellbeing real time at multiple levels (e.g., individual-, class-, school-level), and give immediate feedback. The model is constructed on the basis of the School Wellbeing Model, Study Demand-Resource Model, and OECD Social-Emotional Skill Model. In the book chapter, the wellbeing assessments, including AI-based assessments, are reviewed so that the strengths of the School Day Wellbeing Model are highlighted. User experiences are collected to show the utility of the model. During the COVID-19 pandemic, the need for such a model is imperatively high as students’ wellbeing has been largely dampened. As a result, the model has been appreciated by users and has served about 55,000 students so far in the globe. The future development of the model is also discussed.
Originalspråkengelska
Titel på värdpublikationAI in Learning: Designing the Future
RedaktörerH. Niemi, R.D. Pea, Y. Lu
Antal sidor17
UtgivningsortCham
FörlagSpringer
Utgivningsdatum2023
Sidor55–71
ISBN (tryckt)978-3-031-09686-0
ISBN (elektroniskt)978-3-031-09687-7
DOI
StatusPublicerad - 2023
MoE-publikationstypA3 Del av bok eller annan forskningsbok

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  • 516 Pedagogik

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