The overall aims of this module are to give students the necessary backgrounds and practical skills in the following areas:

• Key works and ideas in computational social science (methodological and topical)
• Planning and designing code for social science purposes and practices
• Fundamental programming concepts
• Applying those fundamentals in the form of small-scale social-science-relevant projects

In overview, students on this module will be able to:

• Demonstrate a working knowledge of the fundamentals of computer programming to meet the needs of a small-scale social scientific research project
• Collaborate with others on project work involving computer programming
• Connect the work of computer programming to the methodologies and topics of social science in the form of a written report
• Reflect on the ways in which PaSS, as a distinctive form of d igital social enquiry, helps open up understandings of the situation of digital technologies of various kinds within social life.

(LO1) Demonstrate a knowledge of key works and ideas in computational social science (methodological and topical)

(LO2) Plan and design code for social science purposes and practices

(LO3) Demonstrate skills and techniques with fundamental programming concepts

(LO4) Execute their plans and designs in code, using fundamental programming concepts to build small-scale social-science-relevant projects

(S1) Methodological Reflexivity: The module will teach students how to frame the work of doing computation and computer programming in relation to broader methodological concerns of the social sciences.

(S2) Technical Skills: The module will provide introduction to fundamental concepts in computer programming, and support students in building these up into small-scale social-science-relevant projects.

(S3) Research Skills: The module will teach students how to conceive, conduct and reflect on the import of empirical studies.

(S4) Analytical Skills: The module will use the lens of ‘design’ (of code/software) to teach students how to think critically and analytically about digital research materials.

(S5) Intellectual Creativity: By allowing students to explore independent research interests in their assessments, the module will help students foster their intellectual creativity.

While this module will explore the role and purpose of computer programming within the social sciences broadly, it will also provide a hands-on introduction to computer programming using PaSS (Brooker, 2019) as a distinctive approach within the broader field of computational social science. Among other things, then, this module will cover the following core areas of enquiry:

• Key works and ideas in computational social science (methodological and topical)
• Planning and designing code for social science purposes and practices
• Fundamental programming concepts
• Applying those fundamentals in the form of small-scale social-science-relevant projects

Readings and tutorial exercises will be supplied (via Canvas) in relation to every topic covered and will form the basis of the content of lectures, workshops and support sessions. Students will be expected to engage with resources (e.g. key readings) on a weekly basis, as well as complete short programming exercises as a collaborator in small groups of fellow students – online resources (e.g. discussion boards) will be provided by the module leader to facilitate this, though independent activity (e.g. meeting up to work on problems together outside of scheduled sessions) will be strongly encouraged. As the assessments will require students to develop a topical interest to which their programming methods can be usefully applied, students will be expected to undertake independent reading in those topical areas for the purposes of their written report assessments – support sessions and office hours will, therefore, be advertised as a forum for supporting students with these aspects.

Teaching Method 1: 6x Lectures/Demonstrations

Scheduled Directed Student Hours: 12

Unscheduled Directed Student Hours: 0

Description: Lectures will form a key part of the way in which this module is delivered. Running over a two-hour session, in the first half of the module there will be 6 lectures covering core foundational learning in computational social science methodology and related relevant issues. The lecture will also comprise a short introduction to and demonstration of the students’ weekly coding exercise, with time for Q&A thereafter. This is to give students as much support as possible with regards undertaking these coding exercises independently; an objective which is furthered also by other teaching methods of the module (e.g. the weekly Workshops). For these reasons, the Lectures/Demonstrations should take place within a computer lab setup, where each student can access a university PC with the necessary programming tools already inst alled.

Attendance Recorded: Yes

Teaching Method 2: 6x Coding Clinics

Scheduled Directed Student Hours: 12

Unscheduled Directed Student Hours:

Description: Once the first six weeks of foundational content is covered, the lectures as outlined above will continue (in the same computer lab setup) as Coding Clinics. Rather than these being optional drop-in sessions, the Coding Clinics become a fundamental dynamic platform for the tutor to provide class-wide instruction and guidance on issues arising as students’ independent work progresses, and for students to begin and continue work on their independent projects in a supervised setting. The sessions will provide a space for the tutor to introduce students to more advanced coding concepts, and to support students in moving from “dependent learning” to “independent doing” for the purposes of completing their assessed work.

Attendance Recorded: Yes

Teaching M ethod 3: 11x Workshops

Scheduled Directed Student Hours: 11

Unscheduled Directed Student Hours: 11

Description: This module will be make extensive use of weekly workshops, though the nature of the content of those workshop sessions will shift according to the topics and activities at hand. Workshop sessions may, then, variously comprise a set of components including seminar sessions with readings and/or other materials to discuss, technical sessions (e.g., guided walkthroughs of programming libraries and techniques) and collaborative sessions where students present their coding exercises and project work to one another in small groups.

Attendance Recorded: Yes

Teaching Method 4: Independent Study

Self-Directed Learning Hours: 115

Description: Independent study, including reading, preparing and writing assessments, and any coding work required for the assessments that could not be completed within class.

Attendance Recorded: No