Buildings (Oct 2024)

Influence of Thermal Environment on College Students’ Learning Performance in Hot Overhead Spaces in China

  • Wanying Wang,
  • Yang Zhao,
  • Jiahao Yang,
  • Meng Du,
  • Xinyi Luo,
  • Ziyu Zhong,
  • Bixue Huang

DOI
https://doi.org/10.3390/buildings14103225
Journal volume & issue
Vol. 14, no. 10
p. 3225

Abstract

Read online

With the popularization of informal learning styles in universities, building overheads in hot and humid regions of China has become one of the main spaces for informal learning among college students in the region due to their improved thermal environmental conditions relative to outdoor spaces. However, the effects of thermal environmental changes on students’ learning performance on the overhead floors are not yet clear. Therefore, we recruited volunteers to conduct several tests, including the Stroop test, the Go/No-go test, the 2-back test, and the 3-back test, in the overhead space of a building in September and October. This was followed by a questionnaire survey, which yielded a total of 500 samples. Learning performance was quantified as a total of accuracy, response time, and final performance metrics. The results show that in hot and humid regions of China, the thermal perception of college students in the overhead was mainly related to Ta and Tmrt, and the relationship with Va was not significant; the maximum acceptable physiological equivalent temperature of college students in the overhead space was 30.3 °C; the change in the thermal environment had an effect on the learning performance of the four tests, and under neutral to slightly warm temperature (22.1–31.2 °C physiological equivalent temperature), the learning performance of the perceptually oriented and short-term memory task types increased by 2.5% and 1.1%, and the relationship between thermal environment and learning performance was not significant when the short-term memory task became more difficult. Attention-oriented learning had a relationship between the spatial thermal environment and learning performance in overhead spaces in hot and humid regions and suggests a basis for future overhead retrofitting.

Keywords