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Human comfort in indoor environments—particularly in schools, universities, and other learning institutions—is a critical determinant of student well-being, cognitive performance, and productivity. Indoor comfort is typically evaluated using parameters such as thermal comfort, air quality, lighting, humidity, acoustics, and ventilation (ASHRAE, 2019). Sick Building Syndrome (SBS) is a condition recognized by the World Health Organization (WHO, 1984), where building occupants experience acute health symptoms such as headaches, fatigue, eye irritation, and respiratory discomfort without a clearly identifiable cause, which improve upon leaving the building. The study aims to find out various parameters that determine the optimum levels of basic human comfort in the learning space. The methodology involves the spatial analysis w.r.t daylighting and ventilation. Environmental simulation softwares- Grasshopper for Rhino and Lightstanza were used to get data and questionnaire surveys were conducted among the user groups involving teachers and students. Teachers who have spent more than 2 years said that for most of them, symptoms do not ease when they leave college. Almost 90% of the students feel their symptoms happened when they were in college. Stress was also a contributing factor for SBS seen in the users. The study proved that students and teachers were affected by SBS symptoms.
Keywords:
Sick building Syndrome, Learning spaces, Environmental simulation, Daylight, Ventilation, Work stress, Spatial Analysis.
Cite Article:
"Assessing Human Comfort Levels in Learning Environments- The Role of Sick Building Syndrome", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 7, page no.a795-a806, July-2025, Available :http://www.ijrti.org/papers/IJRTI2507087.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator