Assessing Students' Aptitude in Analysing 3D Scanned Women's Body Shapes to Improve Fashion Curriculum Design

Abstract

Unisa emphasises responsive student-centredness, recognising the role of an engaged student for future career success and lifelong learning. This research adopted a learner-centred approach, integrating point cloud scans from a 3D full-body scanner into a module for third-year fashion and textile undergraduates. Traditionally, the fashion sector designs apparel for an hourglass woman’s body type. However, South African researchers report that this shape does not represent the majority of women in the country. This research aimed to assess the competence of undergraduate fashion students in visually assessing women’s body shapes to develop cognitive skills for the workplace. Twenty-nine students visually assessed 31 3D scans provided as 2D black and white images. The experts and students identified the dominant shapes of spoon, hourglass and rectangle. In addition, the students reported the triangle, inverted triangle and diamond. Of the 31-point cloud images, 52% of the student’s classifications correlated with those of the clothing industry experts; 48% of the students experienced challenges in accurately assessing asymmetrical body shapes with varying frame sizes across different classifications. The findings suggest that fashion students demonstrate a degree of skill in visually assessing women’s body shapes. Recommendations include using 3D printed models and interactive 360° videos to enhance cognitive abilities. Integrating 3D scanning technology into the curriculum offers sustainable benefits by streamlining processes, improving digital competence and standardising body measurements to SANS 8559-1. This integration not only develops essential workplace skills but also educates students on minimising waste throughout the design-to-garment construction process, thereby aligning academic instruction with industry norms.