COMPLEX SOCIAL SYSTEMS - 2020/1

Module Overview

Complexity social science represents an important new suite of methods that moves researchers beyond the traditional reliance on quantitative or qualitative approaches.

This module introduces students to complex social systems and the challenges of complexity social science and policy research. The course introduces students to a range of methods to tackle these challenges, in particular focussing on methods to understand complex causality. Two methods are covered in particular: Qualitative Comparative Analysis (QCA) and Process Tracing/Bayesian Updating. Both methods will be introduced through real world case studies and situated within the research and policy process.

Module provider

Sociology

Module Leader

ELSENBROICH Corinna (Sociology)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 7

Module cap (Maximum number of students): N/A

Module Availability

Semester 2

Prerequisites / Co-requisites

None

Module content

Indicative content includes:

• Introduction to Complex Social Systems


• Causality in Complex Systems


• Deep uncertainty and “wicked” problems


• Qualitative Comparative Analysis (QCA)


• Process Tracing


• Bayesian Updating


• Narratives and Evidence


• Social Science and Policy Research

Assessment pattern

Alternative Assessment

Video Presentation

Assessment Strategy

The assessment strategy is designed to:

Provide students with the opportunity to demonstrate their knowledge, analytical capacity and practical skills of the relevant methods to tackle complexity in the social sciences. A focus on applying methods to relevant case studies is mirrored in the assessment strategy consisting of a presentation on the challenges to understanding Complex Social Systems and a written assignment applying the methods to a case study.

Thus, the summative assessment for this module consists of:

• Student presentation (30%): Students will do a presentation in a workshop. The presentation is a group effort and students are asked to show their understanding of the challenges of complex social science problems and methods to tackle them.


• Case study (70%): Students will prepare a case study on a complex policy problem using QCA or Process Tracing/Bayesian Updating. The case study should contain a specific social science or applied policy problem, a discussion why it is a complex problem, a detailed assessment of the data available, an assessment of the appropriate methods to analyse the data, and a critical assessment as to how and how far the results can support policy decision-making.

Formative assessment and feedback

The group representation will have formative verbal and written feedback. Written feedback will also be provided for the case study and students are invited to one-to-one sessions to discuss the feedback and how to learn from it for the future. Further formative feedback is provided in the workshop sessions in which students will receive peer feedback as well as feedback from the module leader.

Module aims

• Introduce students to challenges of Complex Social Systems in social science and policy research
• Provide students with an understanding of the problems of causality in complex systems
• Introduce students to QCA and Process Tracing/Bayesian Updating
• Make students confident in applying the methods to relevant case studies

Learning outcomes

Methods of Teaching / Learning

The learning and teaching strategy is designed to:

Introduce the students to the challenges of complexity in the social sciences and policy research, and methods to tackle those problems. The intensive course will give students the conceptual background and methodological skills. The follow on workshop will consist of student group presentations.

The learning and teaching methods include:

• Lectures


• Practical workshops


• Group discussion

This module is taught intensively during one-week. Days 1-3 will consist of a combination of lectures and hands on practical sessions. Day 4 is devoted to independent study, allowing students to undertake preparatory work on their assignment. Finally, on day 5 students will get the opportunity to receive formative feedback on their initial assignment plans and peer feedback during group discussion. Students will then complete their practical assignment.

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: SOCM066

Other information

None

Programmes this module appears in

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2020/1 academic year.