COURSEWORK OVERVIEW

Brief Module Description

The module aims to develop a foundational and applied understanding of Health, Well-being, and Comfort in buildings. You will evaluate your environment with the use of field-based data and the synthesis of scientific evidence. The learning objectives (Figure 1) among others include defining health and well-being in the built environment, interpreting standards, characterising exposure (through personal exposure measurements), and developing communication skills across disciplines (through exercises in groups). The module is thought through of a theoretical framework consisting of seminars by various experts and practical framework which are activities that lead to the coursework (See Figure 2). The exercises are encouraged to be done in groups. The coursework is assessed individually.

Figure 1. BENV0027 learning objectives based on Bloom Is Taxonomy.

Learning Outcomes

•     Making an understanding of health, well-being, and comfort definition using scientific and data-driven methods.

•     Making use of relevant standards to assess the Environmental Quality (EQ).

•     Understand EQ parameters (temperature, light, air quality, etc.) and what our personal exposures looks like in a daily life.

•     Apply methods to characterise exposure.

•     Link measured exposures to actigraphy data.

•     Explore use of subjective data ((Pittsburgh Sleep Quality Index (PSQI), sleep diaries, EQ comfort questionnaires(optional))

•     Applying field-based data and the synthesis of scientific using wearable techniques

•     Developing the ability to troubleshoot, adapt, and reflect on technical challenges is an essential skill for working with real-world data in the built environment.

Coursework

Aims & Context

This coursework is based on field data collection using wearable techniques and the synthesis of scientific evidence to characterise personal exposure to both indoor and outdoor environments.

You will assess how these exposures influence your activities and subjective responses, including sleep, comfort, and health. Particular emphasis will be placed on sleep quality, as a key indicator of health and wellbeing.

The context of the coursework is based on the framework shown in Figure 2. Drawing on the theoretical framework of the module and informed by literature review you are expected to develop a research question or hypothesis. Within the practical framework, you will then work towards answering your research question. During the monitoring phase, you will collect data, which will be pooled into an anonymised dataset created collaboratively by the class. From this dataset, a random allocation of data will be assigned to you for analysis. You will then investigate how environmental exposures may be linked to observed responses. Your evaluation should be based on statistical patterns identified in comfort ratings, questionnaire data, or sleep diary results. You will use data visualisation methods such as bar plots and boxplots to interpret your findings.

The final deliverable is a 3000-word individual report. Figure 2 illustrates the main elements of the module and how they are designed to enhance your theory and practical research for a better understanding of various exposure and their health effects. Check Appendix 1 for the timeline and details of each session.

Figure 2.The framework of the module help to shape the learning outcomes towards the final coursework deliverable

Coursework Structure

The coursework is built upon the theoretical framework of the module and the practical framework which together have been designed to enables you to make and understanding and evaluation of EQ exposure as (see Figure 2). As a first step, you will define a research question within the context and aims of the module. You will be provided with wearable sensors, including an activity monitor, light sensor, and air quality device, secured in a chest-mount pouch as shown in Figure 3. You will also receive a questionnaire, along with a sleep diary (fallback task uses only comfort questionnaire Appendix 7). In addition, you will be given an analysis cookbook, step-by-step instructions for analysis, monitoring and use of the wearables, and checklists to assist you. Based on these tools and methods, and within the context and aims of the module, you will explore:

•     What we, as individuals, are exposed to in our daily lives.

•     What these exposures mean when evaluated against existing standards and recommendations.

•     How they affect our wellbeing and comfort.

You will collect data over a defined monitoring period and upload it anonymously to a shared dataset pool. After the monitoring phase, you will be assigned a unique anonymised dataset(s) for your individual 3,000-word report.

Use of the wearable techniques will enhance your hands-on experience with use of sensors for a data-driven understanding of various EQ exposures. Moreover, you will use your ability to handle technical challenges and complication with research and scientific methods. Finally by using actigraphy data and psychological responses you will evaluate the effects personal daily exposure on well-being.

Please pay attention that:

All data collection must comply with ethical guidelines.

Share of your data for future research purposes is entirely optional.

If you opt out of actigraphy data collection or encounter data collection or technical issues, alternative options are available as detailed in Data Collection Issues and the Fallback task in Appendix 7.

Theoretical framework

The theoretical framework of the module including various seminars by different experts as well as the literature review exercise, will give you a head start to shape your research question.

Research question and data-driven investigation

While the emphasis on exposure effects on sleep quality, you are not given a fixed research hypothesis. Instead, you are expected to develop your niche research question based on the theoretical framework,  literature, your dataset or your interest within the context of the module.

For example, you might ask:

•      How does evening light exposure correlate with sleep quality?

•      Are there detectable patterns between temperature variability and comfort scores?

•      Do certain building types appear to buffer or worsen exposure impacts?

Hence as a starting point Formulate a clear hypothesis or guiding question. Clearly state the problem and the hypothesis you seek to explore in your report.

Practical framework

The practical framework is built upon monitoring and evaluation phases where in brief you will:

•     Monitor personal environmental exposures using wearable sensors across indoor and outdoor spaces.

•     Complete questionnaires.

•     Maintain a diary of activities.

Monitoring & Data Collection Phase

As part of the coursework, a range of wearable sensors is used to monitor and characterise the exposure to EQ factors in indoor and outdoor environments. Through this monitoring and data-driven approach, you will deepen your understanding of environmental quality in the built environment and how it affects well-being. You will gain hands-on experience with environmental monitoring and personal exposure assessment, while developing valuable fieldwork and analytical skills. These insights will enhance your ability to analyse data, reflect critically, and build a well-rounded understanding of health and comfort in the built environment. Figure 2 shows the devices and a chest mount pouch that you will be receiving for the data collection. Table 2 shows the data collection kit overview. Important for data upload instructions, refer to Appendix 6.

Figure 3. For data collection, you will be given a) a chest mount pouch, b) an actigraphy watch, b) a light sensor, and d) an air quality sensor, e) rigged as a wearable kit.

Table 2. Coursework data collection overview

Evaluation Phase

As part of this coursework, you are required to complete a structured set of “Standardised Analysis” using the environmental and actigraphy, as well as environmental comfort data that was collected during a 7 day period. This data collected by means of the wearable sensors capture air quality (e.g., CO₂), temperature, relative humidity, light exposure, and sleep quality.

The required standard analysis are outlined in a step-by-step instructions  which can be found in the Analysis Cookbook ( download here: link will be added). The standardised analysis  include generating time series plots, calculating key summary statistics (such as the 95th percentile), and comparing results to established standards like those from the National Sleep Foundation. You will use light level exposure measured in illuminance [lux] and melanopic illuminance light level (mEDI) [lux] from light data and explore links between environmental conditions and sleep outcomes.

These analyses provide a consistent foundation for comparing findings and help you develop a strong understanding of how environmental exposures affect comfort, health, and especially sleep quality. They will also form. the basis of your report and enable to explore and expand your proposed research question relevant to the context of this task as explained in the previous section.

Compiling the report

The coursework is marked based on your report as outlined in the Appendix 2. The report is a  a structured 3,000-word report including the sections below:

Introduction, Background (based on relevant literature review), Research Question & Objectives

Methods: Data Collection & Building Assessment

Data Analysis & Synthesis

Building Systems & EQ Evaluation

Interpretation and Conclusions, and Reflection

Presentation, Layout & Referencing

In the report based on your analysis you will make:

•     A comparison of exposure profiles: e.g., pollutant levels (especially CO₂, temperature, and light quality between indoor and outdoor spaces (or between the two buildings in case of opting to the fallback task (Appendix 7) )

•     Discussion of patterns such as peak exposure periods, exceedances of thresholds, or day/night or weekday/weekend variability.

•     A reflection on the implications of these exposures for comfort, health, well-being with direct physiological measures.

•     Where possible, comparison to relevant standards or guidelines (e.g., WHO, WELL Building Standard, CIBSE).

•     Reflect on implications for health, well-being, comfort.

Data Collection Issues

Data collection has to be checked on a regular basis to avoid any failure. The post-graduate teaching assistant (PGTA) has to be contacted immediately in case there are issues in data collection. All data must be collected within the given time. From the pool of data collected by all, a random set of data will be allocated to you for analysis.

In the case of your data collection failure, the following options can be considered to ensure learning continuity:

1)   Repeat the data collection

o The data collection and addition to the pool of data can be repeated till the Tutorial 2 session.

2) Partial Data  Analysis

o If at least two of the devices have collected data, a transition to the “fallback task” is recommended. See the section on the Fallback Task (Appendix 7).

o A critical review of the device and a reflection on the failure must be provided as an additional section to the report.

Important Notes

Students must notify the module lead or PGTA as soon as the issue is known to outline the continuation of the work and the report.

These options are designed to keep the assessment fair and focused on learning outcomes, not just technical success.

In such a data-driven approach, technical issues occur. The solution is to troubleshoot the issues and come up with alternative solutions.

Tutorials & Support

The two tutorials are designed to give you feedback on your progress and any questions that come along.  A data interpretation guidance will also take place on the first tutorial session on how to clean, visualize, and use data effectively. Beside the two tutorials, you will gain knowledge through the exercises on literature review, data handling and wearable techniques and sensor deployment guidance.

Statement on the use of artificial intelligence

This coursework follows UCL’s category 2 regulations of the use of artificial intelligence (AI), which states that AI tools can be used, but only in an assistive role. This includes, for example, occasionally improving sentences in English, Familiarising yourself with the topic or summarising text for better learning. If you use AI, you need to describe how you used it in your methods and/or acknowledgments section and specify the tools used and the version used. It would also be useful to provide further details in the appendix. IT IS IMPORTANT THAT YOU DO NOT UPLOAD ANY OF THE DATA AS SUCH TO ANY AI TOOL. If you upload the data, this means that you are uploading the data to the internet and thus to servers that may be located anywhere in the world. This may have serious consequences.