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Curricular information is subject to change
– 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
– 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 Type | Hours |
---|---|
Seminar (or Webinar) | 6 |
Autonomous Student Learning | 218 |
Total | 224 |
In order to take the module, students are expected to have attended at least one module on Introduction to Statistics.
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Group Project: A 6,000-word research paper | Week 12 | n/a | Graded | No | 60 |
Presentation: Conference-style presentation of the research question, data, methods, initial results, and progress on the project | Week 7 | n/a | Graded | No | 20 |
Seminar: Attending the Connected_Politics Lab seminar in spring term and writing response papers on presentations (pass/fail; at least 5 response papers must receive a “pass” grade) | Throughout the Trimester | n/a | Pass/Fail Grade Scale | No | 20 |
Remediation Type | Remediation Timing |
---|---|
In-Module Resit | Prior to relevant Programme Exam Board |
• Group/class feedback, post-assessment
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.