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

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

Abstract

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.
Original languageEnglish
Title of host publicationAI in Learning: Designing the Future
EditorsH. Niemi, R.D. Pea, Y. Lu
Number of pages17
Place of PublicationCham
PublisherSpringer
Publication date2023
Pages55–71
ISBN (Print)978-3-031-09686-0
ISBN (Electronic)978-3-031-09687-7
DOIs
Publication statusPublished - 2023
MoE publication typeA3 Book chapter

Fields of Science

  • 516 Educational sciences
  • Students’ wellbeing
  • Automated scoring system
  • Social-emotional skills
  • Artificial Intelligence

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