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BA Criminology

Year of entry: 2021

Course unit details:
Crime Mapping: an introduction to GIS and spatial analysis

Unit code CRIM31152
Credit rating 20
Unit level Level 3
Teaching period(s) Semester 2
Offered by School of Social Sciences
Available as a free choice unit? No

Pre/co-requisites

Students who have studied Data Analysis or a similar course such as The Survey Method in Social Research SoST20012.

 

Aims

This course unit aims to provide an introduction to the use of geographic information systems for crime analysis and research. The course combines the study of theory and research on crime and place with the development of practical skills in the use of geographic information systems and spatial data analysis using R and R Studio. Consequently, the course has a hybrid nature insofar as it combines the study of a subject area (crime and place) with the development of spatial visualisation and analysis skills.

The course will be of interest to both criminology students but also to social science students with a particular interest in learning GIS for the study of a variety of social or public health phenomena. The course responds to current calls from ESRC and the British Academy to improve the quantitative skills of social science graduates and fits within the Q-Step Manchester initiative.

The course assumes the student has already taken an introductory data analysis course using appropriate software such as SPSS, STATA or R such as Modelling Criminological Data, Making Sense of Criminological Data, or Data Analysis with R and R Studio, or the equivalent in other Departments across SOSS. In case of doubt about whether you meet this criteria do not hesitate to contact the course leader.

Learning outcomes

Students will be able to:

1. Identify main research traditions in the study of crime and place

2. Recognise key concepts on spatial data visualisation and analysis

3. Produce maps of crime and other social features in a professional manner

4. Carry out exploratory spatial data analysis of both points and area data

5. Produce hot spots maps using various approaches

6. Model spatial area data using regression

Teaching and learning methods

Teaching in academic year 20/21 will reflect both University policy and local and national lockdown restrictions operating at the time of delivery. We will offer face-to-face teaching where possible and provide a like for like on-line experience for those unable to be on campus. 

Our teaching models will be flexible and allow us to adapt to changing conditions, however, the common intention across units is to provide (1) media, activities and other learning material that should be engaged with before scheduled teaching; (2) a timetabled 2-hour online slot used for ‘practical lab sessions’; (3) a timetabled weekly 1-hour ‘discussion session’ that will be face-to-face if possible and ‘live’ online if not/preferred; (4) weekly opportunity for 1:1 support. In total, there will be the opportunity for up to 30 hours of contact time (UG; 20 for PGT).

Further details: In the Discussion Sessions, we will introduce the most substantive part of the course. These sessions will try to provide the context for what we are doing (the research and theory on the geography of crime) but also try to reinforce some of the methodological concepts that you will have the chance to apply in the labs.

In the Practical Lab Sessions you will work interactively with a PC or your own laptop and carry out a set of designated exercises to consolidate your understanding of GIS and spatial analysis.

Assessment methods

Method Weight
Other 20%
Portfolio 80%

The course is assessed by means of homework (20%) and a learning portfolio (80%). You will submit 8 pieces of homework. Mostly the homework activities will ask you to submit the maps that you will typically have the time to complete during the lab sessions. We mark timely submission rather than quality of the output. Then you will need to submit a learning portfolio (3000 words). As part of it, you will have to attach a selection of maps and analysis.

Recommended reading

We won’t require you to purchase a textbook for this course unit. Instead we will rely on reading material that is available for free or that can be obtained from the library on digital format. The main required text we will be following is: ‘Crime Mapping and Analysis using R: a Practical Introduction’ by Reka Solymosi and Juanjo Medina, available online here: https://maczokni.github.io/crime_mapping/ You will also need to obtain a copy of this report on "Mapping Crime: Understanding Hotspots" by John Eck and colleagues, that is available as a pdf file from the US Department of Justice in the provided hyperlink (https://www.ncjrs.gov/pdffiles1/nij/209393.pdf).

Study hours

Independent study hours
Independent study 0

Teaching staff

Staff member Role
Reka Solymosi Unit coordinator

Additional notes

Students who have studied Modelling Criminological Data, Making Sense of Criminological Data, or Data Analysis with R and R Studio, or the equivalent in other Departments across SOSS such as The Survey Method in Social Research SoST20012. In case of doubt about whether you meet this criteria do not hesitate to contact the course leader.

  Resticted to: Final year students University wide who have met the pre-requisites.

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