Degradation of Passive Thermal Performance in Colonial School Buildings Under Climate Change: Implications for Cognitive Function

1. Introduction

Educational buildings in tropical regions increasingly face challenges in maintaining acceptable indoor environmental quality due to rising ambient temperatures and urban climate change. As a result, numerous Dutch colonial buildings were established throughout the city. Dutch colonial buildings were constructed with adaptations to Indonesia’s tropical climate to ensure both thermal and lighting comfort for their occupants [1]. Climatic adaptations included the incorporation of large and numerous openings to facilitate air circulation and natural lighting [2], high ceilings to allow the accumulation of warm air, and double-layered roofs with ventilated cavities to enable the inflow and outflow of hot air, among other features [3]. To this day, several of these colonial buildings remain in use, with some functioning as educational facilities. In the context of building engineering, these features represent passive design strategies intended to support indoor environmental performance.

In educational buildings, maintaining adequate indoor environmental performance is essential to support occupants’ activities, including learning performance. However, due to the impacts of climate change, the effectiveness of these architectural adaptations in maintaining thermal comfort has increasingly come into question. The National Oceanic and Atmospheric Administration (NOAA) reported a continuous increase in global temperatures. Similarly, Meteorology, Climatology, and Geophysical Agency (Indonesian: Badan Meteorologi, Klimatologi, dan Geofisika) stated that the average temperature in Indonesia has increased by 0.6℃ every 30 years [4]. The continuous rise in ambient temperatures and the increasing thermal stress associated with climate change indicate that these historical architectural designs may no longer be fully adequate for maintaining comfort under current environmental conditions.

Thermal and lighting environments are essential factors that support occupants’ activities within a building, in this case, students’ learning activities in schools [5]. During learning activities, a series of cognitive processes occur in the human brain, commonly referred to as human information processing. This process describes how individuals perceive, think, and respond to various stimuli from their surrounding environment [5]. Within this process, attention helps sustain the information processing cycle by ensuring clearer understanding, more accurate responses, and better-controlled behavior [6]. Additionally, working memory plays a role in the formation of new concepts and the level of attentional control [7]. Therefore, when students’ attention and working memory are not optimal during the learning process, human information processing can be disrupted, leading to learning difficulties, misinterpretations, and inappropriate responses.

A study conducted at Yonsei University found that an individual’s attention ability is highly influenced by the room’s thermal conditions. The highest level of attention was observed at a PMV value of +1, while the lowest levels of attention occurred at PMV values of +2 and +3 [8]. Furthermore, research conducted at North Dakota State University revealed that attention ability is influenced not only by temperature but also by lighting conditions. The study indicated that the highest attention performance occurred at temperatures ranging from 26 to 29 ℃ with illuminance levels between 600 and 900 lux [9]. It was also noted that lighting has a significant interactive effect on attention ability; brighter lighting can enhance students’ attention across various temperature conditions [9]. In addition to that, previous research found that subjects in a hyperthermic condition experienced a significant decrease in working memory performance by 12.22% (t = 4.675, p = 0.002) compared to those in a normothermic condition [10].

Therefore, this study aims to evaluate the environmental performance of a colonial educational building in a tropical climate and examine its implications for occupant comfort under current environmental conditions. The study assesses indoor thermal and visual environmental parameters, occupants’ subjective comfort responses, and cognitive performance to provide a comprehensive understanding of the current performance of colonial educational architecture. The findings are expected to contribute to the development of adaptive retrofitting and climate-responsive improvement strategies for existing colonial educational buildings in tropical regions.

2. Materials and Methods

2.1. Participants

A total of 30 high school students (15 students in each class) with the distribution of 16 males (53.33%) and 14 females (46.67%) participated as respondents in this study. This field study was conducted in classrooms of colonial building high school located on the first and second floors in Semarang City, Central Java (6°58’32.402” S, 110°25’7.173” E), as can be seen in Figure 1. Purposive sampling technique was implemented in order to select participants based on specific criteria. The mentioned criteria include students currently engaged in classroom learning activities, students without Congenital Insensitivity to Pain with Anhidrosis (CIPA) disease, students with no prior caffeine intake, and students who are willing to participate and follow the research procedures as respondents.

2.2. Instruments

Data collection involved measuring several physical environmental factors including air temperature, relative humidity, air velocity, mean radiant temperature, and illuminance. The utilized instruments are shown in Table 1. Indoor air temperature (T_a) and relative humidity (Rh) were measured using an Elitech GSP-6, air velocity (V_a) was measured using a Hot Wire Anemometer GM89003, and illuminance (lux) was measured using a Lux-29 Digital Light Meter with Data Logging. In addition, outdoor air temperature and relative humidity were also recorded using a Wireless Weather Station and MISOL-2320 instruments. Except for the wireless weather station, all of the physical parameters measuring-instruments were placed in the center of the classroom at the height of 1.1 meter [11] as can be seen in Figure 2. Instruments utilized in this study has been calibrated before the installation.

2.3. Research Design

The classes used in this study are located in the center of the building and each had dimensions of 8×7.5×5 meters as can be seen in Figure 3. According to Putra[12], rooms situated in the central part of a building tend to have a more uniform temperature distribution, making them more representative of the building’s overall thermal characteristics. Therefore, these classrooms were selected to represent the indoor environmental performance of the building. The study was carried out from 20^th of January to 17^th of February 2025, excluding national holidays and weekends. Prior to data collecting procedure, the purpose of this study was explained to the participants. In this study, the students had an 8-hour school time starting from 7 a.m. to 3.30 p.m.

Data collection procedures included the physical parameter measurements, subjective responses, and cognitive performances. The environmental parameters were measured continuously during school hours, from morning until dismissal, to obtain a comprehensive overview of indoor thermal and lighting condition fluctuations in the classroom. Meanwhile, questionnaire and cognitive test data were collected periodically at three time-intervals: morning, noon, and afternoon. This time division aimed to avoid students’ break periods, ensuring that the measurements accurately represented classroom learning activities, and because each time interval exhibited different environmental characteristics.

2.4. Thermal Comfort

This study used both objective and subjective parameters to evaluate thermal conditions as part of indoor environmental performance. ASHRAE questionnaires such as thermal sensation votes (TSV) (-3: cold to +3: hot), thermal comfort votes (TC) (-3: very uncomfortable to +3: very comfortable), thermal acceptability votes (TA) (+1: unacceptable and 0: acceptable), and thermal preference votes (TP) (-1: prefer cooler to +1: prefer warmer) were given out to participants at the designated measurement time to evaluate their subjective thermal comfort levels [11].

In addition to that, physical measurement results were used to further support the thermal comfort level evaluation. To compare subjective responses with objective environmental conditions, predicted mean vote (PMV) and predicted percentage of dissatisfied (PPD) developed by Fanger[13] were calculated at the same time intervals. PMV and PPD equation used in this study is explained in (1) and (2). All of the respondents were students who wear the same school uniform. Therefore, for the PMV calculations, clothing insulation level was assumed to be 0.6 [11].

$$\mathrm{PMV}=(0.303{\mathrm{e}}^{-0.036\mathrm{M}}+0.028) \text{{}\mathrm{M} - \mathrm{W}) - 3.05\times {10}^{-3}\times [5733 - 6.99 (\mathrm{M} - \mathrm{W}) - {\mathrm{P}}_{\mathrm{a}}] - 0.42\times \text{{}(\mathrm{M} - \mathrm{W}) - 58.15] - 1.7 \times 10{-}^5\mathrm{M} (5867 - {\mathrm{P}}_{\mathrm{a}}) - 0.0014\mathrm{M} (34 - {\mathrm{t}}_{\mathrm{a}}) \text{–} 3.96\times 10(-8) {\mathrm{F}}_{\mathrm{cl}}\times [{\left({\mathrm{T}}_{\mathrm{c}\mathrm{l}}\mathrm{+}273\right)}^4-{\left({\mathrm{M}}_{\mathrm{R}\mathrm{T}}\mathrm{+}273\right)}^4]-{\mathrm{F}}_{\mathrm{c}\mathrm{l}}{\mathrm{H}}_{\mathrm{c}}({\mathrm{T}}_{\mathrm{c}\mathrm{l}}-{\mathrm{T}}_{\mathrm{a}})\}$$

(1)

$$\mathrm{PPD}=100 \text{–} 95\times e^{-0.3353\times PM{V}^4}+0.2179\times {\mathrm{PMV}}^2$$

(2)

where PMV is the predicted mean votes which scales from cold (-3) to hot (+3), M is the metabolic rate (W/m²), W is the effective mechanical power which is 0 for most activities (W/m²), F_cl is the clothing surface area factor, T_a is the air temperature (℃), T_MRT is the mean radiant temperature (℃), is the partial water vapor pressure (Pa), H_c is the convective heat transfer (W/m²K), and T_cl is the clothing surface temperature (℃). T_MRT in the PMV formula was calculated using globe temperature formula [14] elaborated in (3).

Where PMV is the predicted mean votes which scales from cold (-3) to hot (+3), M is the metabolic rate (W/m²), W is the effective mechanical power which is 0 for most activities (W/m²), F_cl is the clothing surface area factor, T_a is the air temperature (℃), T_MRT is the mean radiant temperature (℃), is the partial water vapor pressure (Pa), H_c is the convective heat transfer (W/m²K), and T_cl is the clothing surface temperature (℃). T_MRT in the PMV formula was calculated using globe temperature formula [14] elaborated in (3).

$${\mathrm{T}}_{\mathrm{M}\mathrm{R}\mathrm{T}}={\left[{\left({\mathrm{T}}_{\mathrm{g}}+273.15\right)}^4+{\displaystyle \frac{1.1\times {10}^8{V}_a^{0.6}}{\epsilon D^{0.4}}}\times \left({\mathrm{T}}_{\mathrm{g}}-T_a\right)\right]}^{0.25}-273.15$$

(3)

where T_g is the globe temperature (℃), V_a is the air velocity (m/s), $\epsilon$ is the black globe emissivity (0.95), D is the diameter of the black globe (0.15), and T_a is the air temperature (℃). Additionally, heat strain score index (HSSI) questionnaires, which is developed by Dehghan[15] to assess heat strain level subjectively, was used in this study to determine the heat strain levels of the respondents.

2.5. Lighting Comfort

Lighting comfort level in this study was based on illuminance measurement and perceived lighting comfort level votes. The perceived lighting comfort was evaluated using lighting comfort vote (LCV) (-3: very uncomfortable to +3: very comfortable) and lighting sensation vote (LSV) (-3: very dark to +3: very bright) [16]. Moreover, measured illuminance level would be compared to Ministry of Health of Indonesian Republic standards for classrooms (200 – 300 lux) [17].

2.6. Cognitive Test

Learning performance in this study was evaluated from the respondents’ attention and working memory performances. Attention ability was evaluated using Stroop Task. The Stroop test measures selective visual attention, which helps individuals prioritize relevant information while ignoring irrelevant stimuli [9]. In this test, participants are instructed to press the corresponding key on the keyboard that matches the color of the displayed word. The written word itself differs from the font color, serving as a distractor or irrelevant information.

Working memory in this study was evaluated using N-back test. Previous studies have concluded that assessing working memory performance using the N-back test in an online-setting yields results comparable to those obtained in an experimental laboratory environment [18]. Similar research has also concluded that the N-back test is one of the reliable methods for measuring working memory capacity [19]. Correct percentage was recorded for both tests as dependent variables in this study. Additionally, cognitive tests in this study were conducted using web-based software (Psytoolkit) developed by Stoet[20,21].

3. Ethical Considerations

All of the research procedures were approved by Health Research Ethics Committee, Faculty of Public Health, Diponegoro University (Ethics Code: 76/EA/KEPK-FKM/2025). Before the study began, necessary explanations about this study were given to the teaching staffs and students. The students were also assured that their personal information would be kept confidential for privacy purposes.

4. Results

4.1. Physical Environment

A total of 18 measuring days data were able to be used in the analysis. This is due to missing data and unpredicted event such as electricity blackout occurred during the research duration. During the measurement period, the maximum and minimum air temperature, relative humidity, and air velocity can be seen in Table 2. Outdoor physical measurement was affected by unpredictable weather, hence the wide gap between maximum and minimum value.

Indoor environment measurement results can be seen in Figure 4. The indoor physical measurement results shows that the average air temperature, relative humidity, and illuminance exceeded the regulated threshold. The air temperature threshold is regulated at 23 – 26℃; relative humidity is regulated at 40 – 60% [22]; and illuminance is regulated at 200 – 300 lux [17]. In contrast, the air velocity measurement results were still in compliance of the threshold regulated by the government, which is at 0.15 – 0.5 m/s [23].

Analysis of variance (ANOVA) results revealed a significant effect of time of day on air temperature (F (2, 48) = 3.515, p < 0.05), indicating that temperature varied across different periods. However, no significant differences were observed between floors (p > 0.05). Similar patterns were found for relative humidity, where time of day had a significant effect (F (2, 48) = 4.839, p < 0.05), but floor level did not (p > 0.05). Post hoc comparisons test indicated that relative humidity at noon and in the afternoon was significantly lower than in the morning (p < 0.05). In contrast, air velocity showed no significant variation across times of day (p > 0.05), but there was a significant difference between floors (F (1, 48) = 6.628, p < 0.05), suggesting spatial rather than temporal variation. Finally, illuminance exhibited significant differences between floors (F (1, 48) = 6.670, p < 0.05), while no significant differences were detected across times of day (p > 0.05).

This study found that the sample classrooms in this colonial building, based on physical measurements, were not capable of providing adequate thermal and lighting comfort. However, this finding still needs to be compared to subjective responses of the respondents since acclimatization factors could affect the perceived thermal comfort of occupants.

The calculation of PMV and PPD in this study is represented by scatter plot points on the graph in Figure 5. PMV calculations showed that the average of PMV of the respondents in the first and second floor are 1.493 and 1.593, respectively. Additionally, the average PPD of the respondents in the first and second floor are 51.71% and 54.05%, respectively. Although the differences in PMV and PPD values between the two floors were not statistically significant (p > 0.05), the obtained values indicate a deviation from the thermal comfort range defined by ASHRAE Standard 55. According to this standard, thermal comfort is achieved when PMV values range between −0.5 and +0.5 and PPD values remain below 10% [11]. Therefore, the findings suggest that the occupants were likely to feel warm and dissatisfied with the classroom’s thermal environment.

4.2. Subjective Thermal Comfort

Subjective thermal comfort in this study was evaluated using TSV, TA, TC, and TP based on ASHRAE scales. A total of 810 data points were collected for this study. The mean value for each parameter on each floor can be seen in Figure 6. When compared, the TSV values of respondents on the first floor in the morning indicate a higher percentage of those feeling warm (39.34%) than respondents on the second floor (30.84%). A similar pattern is observed at noon, where 78% of first-floor respondents tend to feel warm compared to 70.84% on the second floor. In the afternoon, 86.67% of respondents on the first floor also tend to feel warmer than those on the second floor (65.01%). Respondents on the first floor generally perceived the thermal condition to become hotter over time, in line with the increasing temperature (Morning temperature: 27.48℃; Noon: 28.69℃; Afternoon: 29.06℃). Meanwhile, respondents on the second floor felt that the thermal condition became warmer until noon but tended to feel cooler in the afternoon relative to their TSV at noon.

A total of 40.67% of respondents on the first floor reported feeling thermally uncomfortable in the morning, while 38.33% of those on the second floor felt the same. At noon, 54% of respondents on the first floor and 60% on the second floor tended to feel uncomfortable. In the afternoon, 71.33% of respondents on the first floor and 52.51% on the second floor reported feeling thermally uncomfortable. The number of respondents on the first floor who felt thermally uncomfortable continued to increase with the rise in average indoor air temperature. Although the majority of respondents on the second floor also tended to feel uncomfortable, their number decreased by 7.49%.

The TP values of respondents on both the first and second floors, whether it is in the morning, noon, or afternoon, show that the majority preferred a cooler temperature inside the classroom. In the morning, 70.67% of first-floor respondents and 52.5% of second-floor respondents preferred a cooler temperature. At noon, 64% of first-floor respondents and 58.33% of second-floor respondents expressed the same preference. In the afternoon, 74% of respondents on the first floor and 58.33% on the second floor preferred a cooler temperature. It can be observed that, on both floors, the number of respondents preferring a cooler temperature increased over time.

The TA values of respondents on both floors generally indicate that most participants could still tolerate the thermal environment. However, it can be observed that the number of respondents who could tolerate the thermal condition decreased as the indoor air temperature increased.

In addition to subjective thermal comfort responses, perceived heat strain level data also collected in this study. Perceived heat strain level data in this study was evaluated using HSSI questionnaires. The results can be seen in Figure 7. An HSSI final score below 13.5 indicates a very minimal or no risk of heat strain. Scores ranging from 13.6 to 18 suggest a potential risk of heat strain that may lead to heat-related illnesses (HRIs) and require immediate further assessment. Meanwhile, an HSSI score above 18 indicates a high likelihood of an ongoing HRI, necessitating prompt action to reduce the level of heat strain [15]. Analysis of variance (ANOVA) result shows that there is a significant difference of HSSI across the times of day (F (2, 48) = 7.301; p < 0.05), while none was found between different floors. Post hoc comparisons test indicated that HSSI at noon and in the afternoon was significantly higher than in the morning (p < 0.05). Thus, the finding shows that there was no potential risk of heat strain experienced by the classroom occupants during the study period. Although, it can also be noted that the HSSI value for both floors had an increasing trend except for the occupants in the second floor in the afternoon.

4.3. Subjective Lighting Comfort

As shown in Figure 8, the analysis of subjective responses through the LSV and LCV questionnaires revealed that students on the second floor perceived the classroom as darker and less comfortable compared to those on the first floor. This contrast with the measured illuminance results, which show that the second floor had higher light intensity. This perception mismatch may be attributed to visual adaptation, where occupants’ eyes adjust to dim environments and thus maintain a lower brightness perception even under increased illuminance [24]. Overall, both classrooms exhibited illuminance levels below the recommended standard, which likely contributed to reduced visual sensation and comfort among the respondents.

4.4. Learning Performance

The learning performance evaluated in this study consisted of attention and working memory abilities, with accuracy level used as the main performance parameter. A total of 810 data were collected with the measurement results of each learning performance parameter on each room can be seen in the Figure 9 and Figure 10. For attention ability, the accuracy in both classrooms showed decline as indoor temperature increased throughout the day. In the morning, both classrooms showed the highest attention ability the average of accuracy 95.13%. At noon, the first floor recorded a slightly higher accuracy (94.48%) compared to the second floor (94.17%). In the afternoon, attention accuracy was higher on the second floor (94.33%) than on the first floor (94.22%). However, the overall average showed that the first floor achieved a slightly higher accuracy (94.61%) than the second floor (94.54%).

The analysis of variance for attention performance indicated no significant differences between floors. In contrast, a significant effect of time of day was observed (F (2, 48) = 6.031, p < 0.05), suggesting that attention performance varied across different times of the day. Post hoc analysis further revealed that attention performance in the morning was significantly higher than during both noon and afternoon sessions (p < 0.05), while no significant difference was found between the noon and afternoon results. In addition to that, the working memory performance results shows that the respondents’ average accuracy in the morning was the highest across the times of day at 86.99% and 86.69% for the first and second floor classroom, respectively. Additionally, the first-floor classroom shows higher accuracy (84.26%) than the second floor (83.39%) at noon time. However, the first-floor classroom shows lower accuracy (83.31%) than the second (84.68%) in the afternoon. The analysis of working memory performance revealed no significant differences between floors. In contrast, a significant effect of time of day was observed (F (2, 48) = 13.264, p < 0.001). Post hoc comparisons further showed that performance in the morning was significantly higher than in both noon and afternoon sessions (p < 0.001), whereas no significant difference was found between the noon and afternoon results. The classroom with higher air temperature and relative humidity, which also resulted in higher PMV values, showed lower attention and working memory ability. These results are supported with the correlation analysis presented in Table 3.

Figure 11 further illustrates the overall relationship between PMV and cognitive performance across all respondents. The regression plots demonstrate a consistent decline in both attention and working memory accuracy as PMV values increased. The negative regression trends indicate that warmer thermal conditions were associated with reduced cognitive accuracy, supporting the correlation analysis results presented in Table 3. Compared to attention performance, working memory showed a steeper decline as PMV increased, suggesting that working memory may be more sensitive to thermal discomfort under classroom conditions.

5. Discussion

This study assessed the indoor environmental performance of a colonial-era educational building and examined its implications for occupant comfort and cognitive performance under current climatic conditions. The findings indicate that the environmental performance of the building under current climatic conditions may no longer fully reflect the effectiveness originally intended by its historical passive design strategies. The physical measurements provide strong evidence of this inadequacy. Both the classroom air temperature (T_a) and relative humidity (Rh) were considerably higher than the regulated thresholds for classroom environments. Additionally, although the building’s colonial design features such as high ceilings and large openings were originally intended to enhance natural ventilation, the measured air velocity (V_a) remained low and did not approach the upper limit of the recommended range. This indicates that the existing passive ventilation system was insufficient to provide effective air circulation and convective heat removal. As a result, the average PMV values on the first and second floors classified both classrooms as thermally warm, falling outside the recommended comfort range. Furthermore, the PPD values were extremely high, suggesting that more than half of the occupants were likely to feel thermally dissatisfied.

The objective thermal assessments were further validated by the students’ subjective responses. Most respondents perceived the indoor environment as warm and reported feeling uncomfortable. This discomfort intensified throughout the day, corresponding to the gradual increase in indoor temperature. Consequently, many students expressed a preference for a cooler indoor environment. Similar results were found in previous studies. A study conducted to examine the influence of environmental conditions on students’ thermal comfort in three primary schools in Brazil [25] reported that in the first school, with an average temperature of 26.79°C, the majority of respondents (31.25%) felt thermally neutral. In the second school, where the average temperature was 26.49°C, most respondents (38.65%) reported feeling slightly cool. Meanwhile, in the third school, which had a slightly different average temperature of 26.9°C, the majority of respondents (33.46%) also reported feeling neutral. Interestingly, although most students still considered the classroom conditions tolerable, their acceptance declined as temperatures continued to rise. Similarly, a study conducted in an underground railway station in China reported that 91.69% of respondents found the thermal environment acceptable at a temperature of 25°C, 86.46% at 27°C, and 70.10% at 29°C [16]. This difference between discomfort and tolerance suggests a notable degree of thermal acclimatization among students accustomed to warm-humid climates. These responses further reinforce the building’s limitations in maintaining acceptable indoor environmental performance during classroom occupancy.

However, such adaptation does not necessarily imply the absence of physiological strain or cognitive consequences. The statistical analysis revealed a strong and significant negative relationship between both the PMV and HSSI with student’s cognitive performance, specifically in attention and working memory ability. This finding indicates that as thermal conditions became warmer and perceived heat strain increased, cognitive accuracy declined. The correlation analysis showed that higher PMV and HSSI values were associated with lower attention and working memory scores, confirming that excessive thermal load can impair concentration and short-term information processing. These results are consistent with previous studies reporting that thermal discomfort and physiological heat stress can reduce cognitive performance. This finding is consistent with previous research, which reported that working memory performance increases as thermal conditions approach the neutral range (–0.5 < PMV < 0.5), with the highest working memory accuracy observed at PMV 0 (p < 0.05) [26]. Another study found that working memory performance decreases with rising air temperature and humidity within the range of 26.88°C to 31.92°C [27]. The strong magnitude of correlation observed in this study emphasizes that even mild heat strain in classroom environments can substantially affect short-term cognitive performance.

As a secondary environmental parameter, lighting conditions analysis showed a positive but statistically insignificant relationship with cognitive performance. Although higher illuminance tended to correspond with slightly better attention and memory accuracy, the effect was too weak to reach statistical significance. This finding differs from [9] that has reported statistically significant effect of illuminance on both attention and working memory ability. This may be due to the uniformly low illuminance levels in both classrooms, which limited the variation necessary to detect an effect, or because the influence of thermal discomfort dominated over the contribution of lighting. Although lighting did not show statistically significant cognitive effects, the consistently low illuminance suggests a need for further assessment of daylighting adequacy within the existing building configuration.

Future studies should therefore include classrooms with a wider range of lighting conditions or implement controlled illumination interventions to isolate the effect of light on cognition under tropical conditions. In addition, this study faced several limitations, including a relatively small sample size, a short observation period, and the use of only two classroom settings within one building.

The lack of statistical significance between illuminance and cognitive performance may be further explained by the occupants' subjective perceptions. Based on the Lighting Sensation Vote (LSV) and Lighting Comfort Vote (LCV), the lighting conditions in the colonial building of SMA Negeri 1 Semarang were generally perceived as neutral to slightly bright, despite the recorded intensity being relatively low. In the morning, respondents on the first floor reported a slightly bright sensation (+1) at 28.966 lux, while the second-floor majority remained neutral (0) at 33.869 lux. Interestingly, a temporal divergence was observed where first-floor occupants reported a decreasing sensation of brightness toward the evening, while those on the second floor felt the environment became increasingly bright as the day progressed. This finding presents a notable contrast with prior research in subway environments, where significant portions of respondents perceived the environment as dark even at much higher illuminance (100–300 lux) [16]. This suggests that the building's specific architectural features or the occupants' adaptation to natural light may lower the threshold for neutral brightness sensations.

Furthermore, the Lighting Comfort Vote (LCV) data indicates that comfort levels did not consistently align with higher illuminance. On the first floor, comfort significantly declined throughout the day, with slight discomfort (-1) peaking in the evening at 46.67%. Conversely, the second floor exhibited an inverse trend, where comfort peaked during midday and the percentage of uncomfortable occupants gradually decreased toward the afternoon. This suggests that the optimal lighting comfort for the first floor is achieved in the morning, while the second floor reaches its peak comfort during midday. The prevalence of neutral to uncomfortable votes at these low illuminance levels might explain why lighting did not serve as a strong catalyst for cognitive improvement. Although the lighting sensation was adequate for basic tasks, the physiological comfort remained insufficient to significantly boost mental performance.

These constraints may reduce the generalizability of the results and highlight the need for larger-scale and longitudinal studies to confirm the observed relationships between thermal comfort, lighting, and cognitive performance. Furthermore, the HSSI measurements in this field study did not include quantitative assessments of participants’ physiological responses. Therefore, future studies should incorporate quantitative physiological measurements to capture the phenomenon more objectively and strengthen the interpretation of heat strain effects on learning performance.

From a building engineering perspective, the findings highlight the need for adaptive retrofitting strategies in colonial educational buildings operating in tropical climates. While preserving historical architectural identity remains important, passive design systems may require enhancement to maintain acceptable indoor environmental quality under future climate conditions. Potential interventions include improving cross-ventilation effectiveness, integrating hybrid ventilation systems, optimizing shading strategies, reducing internal heat accumulation, and improving daylight distribution without increasing solar heat gain. Such interventions may help preserve the functional relevance of colonial educational buildings while improving occupant comfort and cognitive performance.

6. Conclusions

This research found that the colonial-era school building demonstrates limited capability in maintaining acceptable indoor environmental conditions under current climatic conditions to support effective learning. Findings suggest a decline in the effectiveness of the building’s passive environmental control strategies. Both objective measurements and students’ subjective perceptions consistently indicated thermal discomfort and inadequate illumination levels. Although no direct heat strain risks were detected, the observed rise in HSSI values alongside increasing PMV points to accumulating physiological stress under warmer indoor conditions. Statistical analysis further revealed significant negative correlations between PMV, HSSI, and students’ cognitive performance, particularly in attention and working memory, showing that higher thermal discomfort and perceived heat strain lead to reduced cognitive accuracy. In contrast, lighting conditions showed a positive but nonsignificant effect on cognitive outcomes, likely due to the uniformly low illuminance across both classrooms.

In summary, the findings highlight that even moderate but continuous heat exposure in tropical learning environments can impair student’s learning performance without necessarily triggering measurable heat strain. The results also highlight the need to re-evaluate passive environmental control performance in existing colonial educational buildings and consider adaptive improvement strategies to maintain acceptable indoor environmental quality. Future research should incorporate quantitative physiological indicators and controlled lighting experiments to better understand these interactions. Expanding the study to include a larger sample size, longer observation period, and diverse building types would also improve the generalizability and robustness of the conclusions.