POL42350 Connected_Politics

Academic Year 2021/2022

The Connected_Politics module trains you to conduct research projects relating to computational social science in small teams under the supervision of an assigned project coordinator and the module coordinator. You will address social science research questions by applying cutting-edge methods, such as quantitative text analysis, machine learning, image recognition, and network analysis. You will learn how to collaborate on research projects with your peers, set out short-term and longer-term goals, and divide up various tasks within groups. At the end of the module, you will have gained significant experience in designing and executing a collaborative academic research project.

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Curricular information is subject to change

Learning Outcomes:

– Execute a demanding research project using methods relating to computational social science
– Collaborate with peers and academic faculty on an academic research project
– Evaluate and compare a variety of research methods, sources, data, and analysis
– Critically and thoroughly examine a research question through independent, data-driven research
– Effectively communicate methods and findings

Indicative Module Content:

– Working on collaborative projects
– Research design(s) and the role of theory in the “digital age”
– Formulating and designing a research question
– Case-selection strategies
– Operationalisation and measurement
– Open science practices, research transparency in groups
– Replicability and reproducibility of research
– Presentation of progress

Student Effort Hours: 
Student Effort Type Hours
Seminar (or Webinar)

15

Autonomous Student Learning

235

Total

250

Approaches to Teaching and Learning:
This project will train you how to comment critically and constructively on working papers during research seminars, and how to conduct a demanding research project using methods relating to computational social science. To reach these goals, you will attend the Connected_Politics Lab seminar series, work in groups, allocate tasks, present your progress, and write a research paper. The module centres on active and task-based learning in groups and seminar discussions. In addition, we will have check-in meetings (up to 30 minutes) after each seminar to discuss the progress and open questions. 
Requirements, Exclusions and Recommendations
Learning Requirements:

In order to take the module, students are expected to have attended at least one module on Introduction to Statistics.


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Presentation: Conference-style presentation of the research question, data, methods, initial results, and progress on the project Week 6 n/a Graded No

20

Assignment: A blog post for the Connected_Politics Lab that describes the research question, data, analysis, and results for a broader audience. Week 12 n/a Graded No

20

Assignment: Attending the Connected_Politics Lab seminar series; writing two response papers on the research projects presented by the external speakers (~500 words for each response paper) Throughout the Trimester n/a Pass/Fail Grade Scale No

10

Group Project: A 4,000-5,000-word research paper Week 12 n/a Graded No

50


Carry forward of passed components
No
 
Remediation Type Remediation Timing
In-Module Resit Prior to relevant Programme Exam Board
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Feedback will be provided by the project coordinator and the module coordinator on a continuous basis throughout the module. The module coordinator will grade the progress report, presentations, participation, and research paper.