SGIA40G15: Full Stack Research Design

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• Learning to navigate research design in the social sciences, from formulating research questions, through data and method choices, to delivering the findings to a variety of audiences.

• Indicative content is listed below and will be taught with reference to problems/scenarios within the social sciences:
• Data types, sources and their relevance;
• Computational measurement designs;
• Surveys and sampling;
• Causal inference in experimental and observational studies;
• Simulation as a research design tool.

Subject-specific Knowledge:

• By the end of the module students will have a working knowledge and understanding of the following areas:
• Types of research objectives and designs;
• Data types and sources;
• Strengths and limitations of different methods in social science.

Subject-specific Skills:

• Critically appraising state of the art research in social science;
• Designing specialist research in social science;
• Communicating social science findings to a variety of audiences.

Key Skills:

• These include:
• Critical appraisal of research design and evidence in social science;
• Application of research designs for exploration, description, forecasting, and causal inferences;
• Ability to interpret and communicate findings from social science research to different audiences, including specialised and wider audiences;

• There are 10 Lecture-Seminar pairs with the seminar taking place later than its paired lecture.
• Lectures will demonstrate the conceptual foundations of applications of computational methods in social science. There are 10 lectures, 2-hour long.
• Seminars: enable students to explore and evaluate some of the key concepts discussed in the module. There are weekly seminars of 1-hour duration.
• Independent Reading: provides students with the opportunities to read widely, particularly in preparation for formative and summative assessments. Independent reading enables students to engage in debates within scholarly journals and research monographs, in ways that enhance a critical understanding and engagement with key issues in social data science.
• The formative essay requires students to discuss a social science topic and outline how they could contribute to the knowledge on this topic with an original research project.
• Summative research design proposal is designed to test the acquisition and articulation of knowledge and critical understanding, and skills of implementation and interpretation of classical and computational methods as applied to both synthetic and real social science data-related problems.

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