SPOL10030 Understanding Social Problems and Policies

Academic Year 2023/2024

This module seeks to equip you with basic research and analytical skills that are needed to understand and respond to social policy problems. Its main focus is on statistical data available in online databases that are widely used to describe such problems and design policy solutions to them. You will learn about major relevant databases for Ireland and the EU and will receive guidance and hands-on experience on how to access those databases, search through them for data on specific social policy topics, select and extract particular relevant indicators into Excel spreadsheets, present the data in graphs and tables, and write brief descriptive commentaries on what the data reveal. For illustrative purposes, the module will focus on unemployment as a representative social problem and will concentrate on analysing that problem and policy responses to it in Ireland and in the EU. A special focus will be on the impact of Covid-19 on the labour market and its effects on employment and unemployment among younger cohorts in particular.

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Curricular information is subject to change

Learning Outcomes:

What will I learn?
On completion of this module, you should be able to:
1. Identify the key social policy data sources that are available online for Ireland and the EU;
2. Understand what kinds of information those sources contain;
3. Access these sources and locate information within them on particular social policy topics;
4.Extract and download data on these topics;
5. Use Excel spreadsheets to organise the data and present them in graphs and tables;
6. Apply basic descriptive statistics in Excel;
7. Write short descriptive accounts of what the data reveal.

How will I learn?
The course delivery is a mix of lectures and hands-on computer workshops in small groups. In the blended format live sessions are supported with in-depth pre-recorded lectures and tutorials online.

Indicative Module Content:

The key aim of the module is to introduce students to social science data analysis. Throughout the module the main example are drawn from analysing the labour market which includes unemployment, education level, gender pay gap, occupational segregation, female managers and the effects of Covid-19 on employment levels. With a focus on Ireland all data analysis has a European perspective.

Student Effort Hours: 
Student Effort Type Hours


Computer Aided Lab


Specified Learning Activities


Autonomous Student Learning




Approaches to Teaching and Learning:
The module consists of lectures and data analysis workshops.
1. The lectures will introduce the module and examine basic aspects of social policy data, with reference especially to data on unemployment. The lectures also discuss the practical data analysis and introduce you to critically assess tables, graphs and results.
2. In six weeks of data analysis workshops you will learn how to put into practice some of what you have learned in the lectures. The class will be divided into small groups for these workshops. Each student will have one workshop per week for this six-week period. The computer labs are practical and hands-on sessions where you can explore and familiarise yourself with social data. 
Requirements, Exclusions and Recommendations
Learning Recommendations:

To learn about the power of stats watch this video:

Module Requisites and Incompatibles
Social Policy Research (SPOL1903)

Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment: Mid-trimester assignment Week 8 n/a Graded No


Assignment: End-of-trimester assignment Week 12 n/a Graded No


Carry forward of passed components
Resit In Terminal Exam
Spring No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

The mid-term assignment will develop your analytical and writing skills with detailed feedback to improve data analysis. The final assignment asks for a more comprehensive and advanced data analysis and the previous feedback should be considered. In the data analysis workshops oral feedback is provided, but there will be no feedback on the submission of workshop outcomes.

Quirk, Thomas J. (2016) Excel 2016 for Social Science Statistics. A Guide to Solving Practical Problems. Cham: Springer. DOI:10.1007/978-3-319-39711-5
Guerrero, Hector (2014 or 2019) Excel Data Analysis. Modeling and Simulation. Heidelberg: Springer. DOI:10.1007/978-3-642-10835-8
Name Role
Dr Maria Pierce Lecturer / Co-Lecturer
Ausra Cizauskaite Tutor
Patrick Mulvaney Tutor
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Lecture Offering 1 Week(s) - 2, 3, 4, 5, 6, 7, 9, 10, 11, 12 Mon 16:00 - 16:50
Lecture Offering 1 Week(s) - 2, 3, 4, 5, 6, 7, 9, 10, 11, 12 Wed 14:00 - 14:50
Computer Aided Lab Offering 1 Week(s) - 5, 6, 7, 9, 10 Thurs 11:00 - 11:50
Computer Aided Lab Offering 2 Week(s) - 5, 6, 7, 8, 9, 10, 11 Tues 13:00 - 13:50
Computer Aided Lab Offering 3 Week(s) - 5, 6, 7, 9, 10 Thurs 10:00 - 10:50
Computer Aided Lab Offering 4 Week(s) - 5, 6, 7, 8, 9, 10, 11 Tues 14:00 - 14:50
Computer Aided Lab Offering 5 Week(s) - 5, 6, 7, 9, 10 Thurs 12:00 - 12:50
Computer Aided Lab Offering 6 Week(s) - 5, 6, 7, 9, 10 Thurs 13:00 - 13:50
Computer Aided Lab Offering 7 Week(s) - 5, 6, 7, 9, 10 Thurs 14:00 - 14:50