Optimizing Furniture Design for Junior Secondary School Students Using Predictive Analytics of Growth Patterns

EasyChair Preprint 14344

Abstract

The design of ergonomic classroom desks for junior secondary school students poses significant challenges due to the diverse and evolving physical dimensions of this age group. This study investigates the development of comprehensive anthropometric databases and the application of predictive models to create desks that accommodate students' growth and provide optimal ergonomic support. By compiling extensive anthropometric data, including height, weight, and body proportions, the research aims to build a detailed database reflecting the physical dimensions of students across different age groups and demographics. Predictive models will then be employed to analyze growth trends and forecast future dimensions, enabling the design of desks that are adjustable and adaptable to changing needs. The application of these models ensures that the desks not only fit current dimensions but also anticipate future growth, promoting long-term comfort and usability. This approach aims to enhance the ergonomic design of classroom furniture, contributing to improved student posture, reduced discomfort, and a more supportive learning environment.

Keyphrases: 1. **Predictive Models**, 10. **Design Adaptability**, 11. **User-Centric Design**, 12. **Furniture Usability**, 13. **Ergonomic Support**, 14. **Data-Driven Design**, 15. **Predictive Analytics**, 2. **Anthropometric Data**, 3. **Ergonomic Desk Design**, 4. **Classroom Furniture**, 5. **Growth Forecasting**, 6. **Adjustable Furniture**, 7. **Student Ergonomics**, 8. **Longitudinal Data**, 9. **Machine Learning**

@booklet{EasyChair:14344,
  author    = {Elizabeth Henry},
  title     = {Optimizing Furniture Design for Junior Secondary School Students Using Predictive Analytics of Growth Patterns},
  howpublished = {EasyChair Preprint 14344},
  year      = {EasyChair, 2024}}