Abstract:

Educational innovation has traditionally focused on pedagogy, curriculum development, and digital technologies as the main drivers of learning improvement. However, increasing evidence indicates that the physical environment also plays a crucial role in shaping how students learn. Rather than being neutral settings, classrooms function as dynamic spaces that interact with cognitive and emotional processes.

The field of neuroarchitecture offers a useful framework for understanding how environmental variables influence brain activity and behavior. From this perspective, sensory inputs such as lighting, noise, odors, and visual stimuli are not merely contextual factors but active components that can facilitate or hinder cognitive functioning. These inputs directly affect attention, emotional regulation, and cognitive load, which are fundamental processes for learning.

The objective of this study was to investigate the impact of contrasting sensory classroom environments on students’ cognitive performance and subjective well-being.

The study was conducted through an experimental workshop involving secondary education students (n=45), designed to evaluate the impact of environmental conditions on cognitive performance. Participants were divided into two groups:
- Group HSE (homeostatic sensory environment), were assigned to a classroom designed to support cognitive balance. This included adequate lighting (approximately 630 lux), lavender scent, biophilic elements (plants), natural ambient sounds (46 dB), and the absence of visual distractions.
- Group DSE (dissonant sensory environment) were assigned to a classroom characterized by disruptive stimuli. This included insufficient lighting (approximately 210 lux), an aversive odor (vinegar), the absence of natural elements, noise levels ranging from 65 to 75 dB, and the presence of visual distractions such as dynamic digital content.

Following an initial habituation period (10 min) to their respective environments, all participants completed the same sequence of cognitive tasks. These included an image recognition task (real vs AI-generated images), Stroop Color-Word Test, Task-switching paradigm, Remote Associates Test and a questionnaire assessing their subjective perception of the environment. Since the data did not satisfy the assumptions required for parametric analyses, data was analyzed using the non-parametric Kruskal–Wallis test.

The results revealed clear differences between the two classroom conditions in both cognitive performance and subjective perception. In the Stroop task students in the DSE demonstrated lower accuracy (p = 0.05) and significantly longer reaction times (p < 0.001) compared to those in the HSE. In the task-switching paradigm, students in the DSE showed approximately 18% lower accuracy than those in the homeostatic classroom (p = 0.037). In the Remote Associates Test, no statistically significant differences were found between groups (p = 0.25). In the questionnaire students in the HSE reported lower levels of stress and described the environment as favorable for concentration. In contrast, students in the DSE reported higher stress levels and greater difficulty maintaining focus.

These findings suggest that classroom design should be considered an active component of the learning process. Environments that provide balanced sensory input can support concentration and efficiency, while poorly designed environments may hinder cognitive functioning.

Keywords:

Neuroeducation, Neuroarchitecture, Learning environments, Cognitive performance, Attention, Educational design, Sensory processing, Student well-being.