GV2POP-Population Geography

Module Provider: Geography and Environmental Science
Number of credits: 10 [5 ECTS credits]
Terms in which taught: Spring term module
Non-modular pre-requisites:
Modules excluded:
Current from: 2018/9

Module Convenor: Dr Sylvie Dubuc

Email: s.dubuc@reading.ac.uk

Type of module:

Summary module description:

This module provides an introduction to population geography topics and a methodological analytical foundation for the study of populations. This encompasses the analysis of population data and measures, contemporary dynamics of population growth, composition, spatial distribution and processes associated to population change. The module will introduce students to a secondary data analysis approach to population key topics. We will explore how demographic trends link with social inequality, urbanization and development. The module addresses issues at the regional, national and global levels.

The module design associates lectures, practical and project-based learning activities. Students will encounter a range of quantitative data and, in addition to developing their conceptual appreciation of population-related topics and contemporary issues, they will gain practical skills associated with secondary data analysis and interpretation.


1. To learn fundamental concepts in population geography, critically examine key geographic and historical processes of population changes and relate spatial patterns to the 3 major demographic processes: mortality, fertility and migration;

2. To develop students’ awareness of global challenges of population change linked with broader geographical topics like social inequality, social justice, development and the environment and to particularly gain an understanding of the complex links between population dynamics and development, drawing on a range of academic literature from human geography and broader population studies fields;

3. To gain knowledge and understanding of some of the essential sources of demographic data and their limitations; use basic demographic and quantitative techniques to analyse population and social data and interpret population measures;

4. To enable students to use quantitative analytical techniques to interrogate secondary data from a range of sources relating to demographic change, social inequality and development and develop students’ appreciation of their role in understanding population dynamics and social processes in a global context.

Assessable learning outcomes:

By the end of the module, students will be able to:

1. Apply geographical concepts like space, place and scale to population-related social and environmental issues;

2. Critically evaluate the significance of concepts including mortality, fertility, migration, urbanization, demographic transition, overpopulation, population structure and gender to understandings of socio-spatial inequality and development;

3. Source and apply demographic and secondary quantitative data analysis to appropriately describe population dynamics;

4. Produce written arguments citing supporting evidence and data in a clear and well-structured way;

5. Illustrate their understanding of population dynamics and the links between population, social processes and development, using a range of international examples and exploring the reasons for the differences observed across space.

Additional outcomes:

Students will develop transferable skills in the application of secondary data analysis to research questions. This will be invaluable for subsequent dissertation work and is an important employability skill in its own right.

Outline content:

Students will be introduced to a range of population-related themes in the lecture program, including demographic and health transitions in link with poverty, family, gender and development, spatial distribution, urbanization, migration (over)population and environmental pressure. The lectures’ material will be reinforced through practical activities using secondary data to learn basic demographic methods and quantitative skills. The students will further develop skills in data analysis and interpretation using quantitative techniques, including statistics, through their assessed individual project.

Brief description of teaching and learning methods:

Lectures and practical classes.

Contact hours:
  Autumn Spring Summer
Lectures 10
Seminars 10
Guided independent study 80
Total hours by term 100.00
Total hours for module 100.00

Summative Assessment Methods:
Method Percentage
Project output other than dissertation 100

Summative assessment- Examinations:

Summative assessment- Coursework and in-class tests:

Formative assessment methods:

Students will be given opportunities to complete small, practical tasks in every lecture and seminar. They can check their understanding of key concepts and techniques through these tasks and through their guided individual project.

Penalties for late submission:
The Module Convener will apply the following penalties for work submitted late:

  • where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day[1] (or part thereof) following the deadline up to a total of five working days;
  • where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

  • The University policy statement on penalties for late submission can be found at: http://www.reading.ac.uk/web/FILES/qualitysupport/penaltiesforlatesubmission.pdf
    You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

    Assessment requirements for a pass:

    A mark of 40% overall

    Reassessment arrangements:

    Resubmission of coursework and/or re-examination

    Additional Costs (specified where applicable):

    Last updated: 20 April 2018


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