Effects Of The Single-Factor Physical Environment On Learning Performance Of Undergraduates By The Electroencephalogram Technology

College students spend a great deal of time studying in the classroom and their learning efficiency and physical health are directly affected by the quality of the indoor environment.Improving the quality of the environment is thus likely to assist students’ academic performance.The acoustic,luminous,and thermal characteristics of classroom environments are the main factors affecting learning,and these appropriate parameters should be extremely considered when constructing university classrooms to facilitate learning and ensure physical and psychological health.This study used the concentration,fatigue,and learning efficiency of college students to evaluate performance.Subjective questionnaires,physiological measurements,and behavioral tests were used to explore the influence of the acoustic,luminous,and thermal environmental parameters on learning performance from the perspectives of neurobiology and psychology,thus providing an assessment of the optimal environment for students.The main contents and results of the study are as follows:(1)The associations between college students’ learning performance and the physiological and psychological regulatory mechanisms of the body under environmental stress were analyzed.This was followed by a systematic and comprehensive evaluation of the effects of environmental parameters using subjective questionnaires(including the assessment of environmental comfort,quality of the indoor physical environment,and perceptions of concentration and fatigue),physiological measurements(including assessments of concentration and fatigue by EEG and heart rate variability),and evaluations of learning-associated behaviors(including reactivity,attention,memory,and calculation).(2)In terms of the acoustic environment,the influence of different sound sources(ambient sound,traffic noise,speech sound,music,and natural sound)and sound pressure levels(30 dB,40 dB,50 dB,60 dB)on learning performance were investigated.The results showed a decreasing trend in learning performance when exposed to music,natural sound,ambient sound,speech sounds,and traffic noise,respectively.Compared with concentration in the presence of ambient sound(0.55),concentration with music was the highest(0.65),while concentration with traffic noise was the lowest(0.47).Fatigue showed the opposite trend.At the same sound pressure level,the concentration levels and behavioral test scores when exposed to music were consistently better than those with traffic noise,and the fatigue level with music was consistently lower than that with traffic noise.Combining the measures of concentration,fatigue,and behavioral test scores,it was found that the optimal sound pressure level for music was 36 dB-40 dB,and the appropriate sound pressure level for traffic noise was 30 dB.(3)In terms of the luminous environment,the influence of illuminance(100 lx,300 lx,500 lx,700 lx,and 900 lx)and color temperature(3000 K,3700 K,4400 K,5100 K,5800 K,and 6500 K)on learning performance was investigated.The results showed that concentration gradually increased as the amount of illumination increased,while fatigue showed a U-shaped trend of first decreasing and then increasing,with the lowest value under 500 lx.The behavioral test scores initially increased and then decreased slowly,with the highest score under 500 lx.The effect of color temperature was similar to that of illuminance.Concentration increased gradually in response to increasing color temperature,while the amount of fatigue was lowest and the behavioral test scores were the highest when the color temperature was 4400 K.Combining the measures of concentration,fatigue,and behavioral test scores,it was concluded that the optimal illumination and color temperature ranges were 600 lx-700 lx and 4400 K-4750 K,respectively.(4)In terms of the thermal environment,the influence of air temperature(18℃,21℃,24℃,27℃,and 30℃)and relative humidity(40%,50%,60%,70%,and 80%)on learning performance were investigated.The results showed that as the temperature increased,the levels of concentration and the behavioral test scores first increased and then decreased,while fatigue showed a U-shaped trend of first decreasing and then increasing.The highest concentration levels and behavioral test scores were observed at 21℃,while the lowest levels of fatigue were observed at 24℃.The effect of humidity was essentially the same as that of temperature.At 60% humidity,both the concentration and the behavioral test scores were highest while the level of fatigue was lowest.Considering the measures of concentration,fatigue,and behavioral test scores in relation to learning performance,it was concluded that the optimal temperature and humidity were 21℃-23℃ and 55.00%-60.00%,respectively.(5)To integrate the effects of sound,light,and heat on learning performance,the existing classroom was used as the reference and the physical environment was optimized according to the above experimental results.The environment thus included 40 dB of music,illumination of 700 lx,color temperature of 4700 K,air temperature of 22.5℃,and humidity of 55%.This resulted in an increase of 47.1% in the students’ concentration compared with the former conditions,together with a reduction of 10.0%in fatigue,and an increase in the behavioral test scores of 13.2%.These findings thus verified the positive effects of appropriate acoustic,light,and thermal environmental parameters on learning performance.The system verifies the effect of appropriate acoustic,luminous and thermal environment parameters on the improvement of learning performance.Using subjective questionnaires,measurement of physiological indices,and behavioral tests,this study demonstrated the ways in which the physical environment influences the concentration,fatigue,and learning abilities of college students.This led to the identification of the optimal classroom conditions that promote learning and concentration in university environments.The application of these findings will improve college students’ learning performance and reduce their study fatigue.The conclusions are supported by practical and effective data,providing a theoretical foundation and potential engineering applications.