GV2ASD-Analysing Social Data

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 Steve Musson

Email: s.musson@reading.ac.uk

Type of module:

Summary module description:
I have met hundreds of students during my career who told me they 'couldn't do statistics'. This view was often based on a lack of confidence in their mathematical ability to follow through the technical steps required to complete a statistics test, and confusion over how to interpret statistical results. As a consequence, large numbers of students are switched off from using numerical data because they aren't sure they can handle it. This module takes a different approach to analysing social data. Rather than seeing data as a set of numbers that need to be subjected to complex mathematical processes, it sees such data as political and social ammunition. In this module, we will use social data to persuade, argue, illustrate and deceive. The emphasis will NOT be on developing your statistical ability. Instead, I want you to become a better informed, more confident and critical user of social data. I hope that these skills will be useful both in the remainder of your degree and in your life after university.

1. To encourage students to understand social data as a socio-political product and to enable them to reflect on the epistemological and methodological implications of this perspective;
2. To empower students to become critical users of social data, with particular reference to the relative strengths and weaknesses of a range of data sources;
3. To develop students' confidence in finding and using social data for research purposes, including the development of a range of analytical and visualisation techniques that allow them to understand the possibilities of different types of social data;

Assessable learning outcomes:

By the end of this module, students will be able to: 1. Identify different sources of social data and think critically about their potential utility 2. Demonstrate their ability to manipulate social data, conduct appropriate analysis and display their results in an appropriate way 3. Use social data to make a compelling and evidenced argument  4. Reflect on their use of social data in a way that demonstrates a critical understanding of socio-political processes of data production

Additional outcomes:
Students will become more confident users of social data and develop a range of transferable skills, in sourcing, manipulating, analysing, visualising and reporting social data. These skills will be invaluable in subsequent academic modules (especially the undergraduate dissertation) and are highly sought after by prospective graduate employers. The ability to think critically about data and to argue in an evidenced way are important life skills and this module gives students an opportunity to develop their abilities in this respect.

Outline content:
This module begins with seminars that introduce students to key features of social data, research applications and critical interpretation of its role in the creation of knowledge. Students will encounter, manipulate and analyse a range of social data. This will initially take the form of teaching data sets, but students will later be expected to obtain their own data in an informed and critical manner. Towards the end of the module, students will work on a small data analysis task, in which they will be expected to demonstrate their ability as a critical user of social data.

Brief description of teaching and learning methods:

This module will be delivered through a mixture of lectures and practical classes. A companion website will support learning with supplimentary material including sample datasets and worked through exercises.

Contact hours:
  Autumn Spring Summer
Seminars 4
Practicals classes and workshops 16
Guided independent study 80
Total hours by term 100.00
Total hours for module 100.00

Summative Assessment Methods:
Method Percentage
Set exercise 100

Summative assessment- Examinations:
No examination.

Summative assessment- Coursework and in-class tests:

Students will complete five set exercises, each worth 20% of the marks for the module. These excercises will each relate to a different area of learning on the module.

Formative assessment methods:

Students will be able to check their learning each week, following set practical exercises online and bringing their work to the practical sessions for discussion / further clarification.

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:
    Re-submission of relevant item(s) of coursework in August/September.

    Additional Costs (specified where applicable):
    1) Required text books:
    2) Specialist equipment or materials:
    3) Specialist clothing, footwear or headgear:
    4) Printing and binding:
    5) Computers and devices with a particular specification:
    6) Travel, accommodation and subsistence:

    Last updated: 20 April 2018


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