Gwybodaeth Modiwlau

This module is designed to provide students with a broad introduction to key concepts in Environmental Science, and to the techniques for the acquisition, analysis and presentation of Environmental Science data. The module comprises four sections (see section B2 for detail) which are linked together through the development of a prescribed research project, introduced at the start of the module.
The four sections are taught through a series of lectures (see detail below in B4). Broad-based training in various skills and competencies is provided in the lectures, while the assessments are designed to test key knowledge and skills.
Throughout the module, students will be developing appropriate practical skills and the conceptual framework to complete their own research project effectively. The research project topic is prescribed and appropriate datasets will also be provided for analysis. The aim of the project is to link the different elements of the module together and to provide a firm grounding in Environmental Science research but without the requirement of having to devise a research question. This next step is developed further in Year 2 through the Research Skills for Environmental Science module and through preparation for their independent dissertation project in Year 3.

The module comprises four sections which are linked together through the development of a prescribed research project, introduced at the start of the module:
Section 1: The first section considers the context for study in Environmental Sciences, discussing the history of the discipline including the application and relevance of academic knowledge from Geography, Biology and other related disciplines.
Section 2: The second section considers practical aspects of studying Environmental Science at university, including conducting literature searches, writing essays and reports, understanding assessment criteria and feedback, and ethical practice and health and safety issues in Environmental Science research.
Section 3: The third section outlines some of the key types and sources of data for Environmental Science and related disciplines, and the key techniques employed in data collection.
Section 4: The fourth section considers the analysis and presentation of both primary and secondary data in Environmental Science and related disciplines.

The module will be taught using 16 x 2 hour lectures. Topics to be covered are listed below (note: each lecture topic does not necessarily correspond to a distinct lecture). Additionally there will be 8 x 1 hour surgery sessions to help students plan their project.
Section 1
1. History of Environmental Science – the essential context of what Environmental Science is, and its development as an inter-disciplinary subject area (lecture).
2. Application and relevance of knowledge in Environmental Science (lecture).

Section 2

3. Literature searches and literature reviews (lecture).
4. Writing essays and reports – learning how to write in an academic style fit for university (lecture).
5. Introduction to projects: research design and research questions (lecture).
6. Understanding assessment criteria and feedback – learning from your mistakes and working toward better grades in the future (lecture).
7. Ethical practice and health & safety – how to undertake research in a professional manner and to ensure the safety of others and yourself (lecture).

Section 3

8. Primary data sources and collection I: Fieldwork, measurement and sampling – the scientific method, data collection, making observations and measurements in the field (lecture).
9. Primary data sources and collection II: questionnaires, interviews and participant observation – collecting data about people and their experiences (lecture).
10. Secondary data sources and collection: official and non-official sources (lecture).
11. Introduction to quantitative data analysis I: data types, distribution and descriptive statistics (lecture).
12. Introduction to quantitative data analysis II: data smoothing and modelling – extracting trends from datasets and understanding how and why we use models (lecture).
13. Introduction to qualitative data analysis: transcription and coding (lecture).

Section 4

14. Presentation of quantitative data: graphs and maps (lecture).
15. Statistical analyses: parametric and non-parametric tests (lecture).
16. Presentation of qualitative data: writing reports (lecture).