Thermal comfort and indoor air quality (IAQ) of educational buildings can affect students’ academic performance and well-being and are closely related to ventilation energy consumption. Demands of the indoor environmental quality within the classroom generally vary with the education levels and result in ventilation energy consumption accounting for a considerable proportion of the total energy use in bulk educational buildings. Its huge energy-saving potential is attracting worldwide attention from scholars and governments. Therefore, appropriate operation strategies of ventilation systems should be adopted to effectively reduce energy consumption without sacrificing thermal comfort and IAQ. However, the absence of relevant standards and guidelines for designing a quality classroom environment considering the special features of educational buildings remains an important research question. This study conducts a comprehensive review to determine research gaps and identify future directions for the interaction between thermal comfort, IAQ and ventilation energy consumption for educational buildings. The review results show that: (1) The thermal comfort prediction model should consider the influences of genders, ages and socioeconomic backgrounds; (2) The mixed-mode ventilation coupling the natural and mechanical approaches is preferred given its advantage of lower energy consumption and improved thermal comfort, but its control strategies need further exploration; (3) Optimizing passive design parameters of buildings (e.g., window to wall ratios, window orientations and sun shading installations) can significantly reduce the ventilation demands while maintaining indoor thermal comfort; (4) More studies are required for investigating thermal comfort in educational buildings during the heating period; and (5) IAQ of university buildings clearly requires further studies, especially on bacterial and fungal aerosol pollutants, for a more comprehensive assessment of the built environment.

E-learning platforms are being used in higher education to liberate teaching and learning from the constraints of time, pace, and space. These platforms provide rich media content, collaborative assessment, and analytics tools and support learning through a variety of online possibilities. However, the focus of most of this research is on learning analytics inside e-learning platforms and does not cover other related institutional surveys and educator professional development activities. This paper outlines a novel conceptual approach for the creation of a teaching and learning data warehouse analytics system that utilizes a Multi-Dimensional Analysis approach to teaching and learning analytics across these e-learning platforms in combination with other institutional data sources, such as various institutional surveys, tracking of professional development activities, and analysis of the use of the learning management system. The novel teaching and learning data warehouse analytics system (TLDWAS) is being developed at Lingnan University, a leading liberal arts university in Hong Kong. The genesis of this project is analyzing large volumes of teaching and learning data and presenting a big picture for senior management to gain insight from massive amounts of student courses and teacher evaluation data, fill the research gaps mentioned above, and help educators identify problems and solutions more effectively. The TLDWAS provides a visual interface for identifying some indicators and storing, classifying, and analyzing teaching and learning data in various forms to generate statistics, analyze models, and identify meaningful patterns in the data in order to improve teaching and learning. The TLDWAS not only provides more evidence-based decision-making for senior management but is also capable of being applied to identify patterns and relations pertaining to students’ academic performance, usage of e-learning systems, and associated staff development activities.

Thermal comfort (TC) and CO₂ concentration significantly influence the overall indoor comfort sensations of building occupants. However, few studies have focused on educational buildings regarding both TC and CO₂ concentration in tropical regions, and they also lack guidelines for short-term evaluation, which is essential for university classrooms. In this study, a mechanically ventilated university classroom was selected to investigate the 5 min-averaged comfort ranges for indoor parameters and the impacts of TC and variation of CO₂ on student overall comfort. The real-time indoor environmental parameters were monitored, including indoor air temperature (T_a), mean radiant temperature (T_m), relative humidity (RH) and CO₂ and air velocity (v_a); the operative temperature (T_op) was calculated. Moreover, an online-based questionnaire survey related to thermal sensation (TS) and CO₂-related air sensation (AS) was carried out. Linear and nonlinear regression models of comfort sensation predictions were obtained based on the questionnaires and corresponding measured indoor environmental data. The 5 min-averaged comfort ranges for T_op, CO₂ and RH are 21.5–23.8 °C, <1095 ppm and 47–63.5%, respectively. The comfort range of the TS and AS are 2.3–3.1 and 1–1.55, respectively. The result shows that students prefer a relatively cold indoor environment, as this improves their ability to tolerate bad indoor air quality (IAQ) with high CO₂. A regression analysis indicated that AS is the most critical aspect, with a weight of 0.32, followed by TS, with 0.18. Finally, it was also found that individual weighting coefficients were not equivalent and differed across geographical locations and building types. Thus, obtaining the prediction models for a particular building is necessary. The results can give meaningful suggestions to adopt the appropriate operations for HVAC and improve indoor environmental quality in university buildings in tropical regions.

The COVID-19 pandemic has instigated considerable unprecedented challenges to tertiary education in the aftermath of the mass shutdown of universities across Hong Kong since early 2020. Accordingly, shifting the traditional modalities to the online model has been opted for as the only reasonable alternative in the breakout period. It is, then, essential for educators to perceive the extent to which students’ learning attainments and experiences have been negatively impacted by these educational changes in the post-pandemic era. With the aim of examining the abrupt changes which the freshmen students’ e-learning experiences and their learning environment have undergone before and after the pandemic, the present quantitative study was conducted at a Liberal Arts Institution in Hong Kong, whose data was collected via the web-based questionnaire FYSLES, or “first-year student learning experience survey”. Quantitative analysis of responses indicated that students’ impressions and experience of liberal arts education, and students’ personalities and skills development, presented a U-shaped trend during the COVID-19 pandemic. The underlying rationale of this study is addressed to higher education policymakers to orient and add value to their safety measures, pertinent recommendations, as well as in context strategies that could be established in view of the pandemic’s detrimental effects.

This study develops a model for buildings with a cooling roof, walls, and low-emissivity (Low-E) windows. This model is verified through experimental analysis. The cooling demands of standard buildings and cooling buildings are compared, and the energy-saving potentials of cooling buildings are analysed. It is found that compared to standard buildings, cooling buildings exhibit superior cooling performances attributable to the application of cooling materials. Considering Hong Kong’s weather data, the indoor temperature of cooling buildings can be sub-ambient. The cooling demands of cooling buildings are decreased from 75 W/m² to 30 W/m², indicating a 60% energy-saving potential. The nationwide cooling demand for a standard building across China is approximately 95.7 W/m², whereas the nationwide summer average cooling demand for cooling buildings is 52.7 W/m². Moreover, the cooling performance of a cooling roof is adversely affected by hot and humid weather conditions, resulting in lower temperature drops in southern regions compared to northern regions. However, the nationwide temperature drop across China can still be 1.6 °C, demonstrating promising cooling potentials. For the Low-E windows, the temperature can also be sub-ambient, with a nationwide average temperature drop of 1.7 °C. Therefore, the use of Low-E windows across China can also significantly contribute to energy savings for indoor cooling. Overall, the results of this study show that cooling buildings have high energy-saving potential under various climates. The proposed model can provide a reliable tool to facilitate relevant cooling evaluation by stakeholders, thereby benefiting the popularization of this technology.

Owing to an earlier miscommunication in the original publication (Li et al