Admission requirements
This course is only available for Bachelor Public Administration students (DDG). (From sept 2025 onwards the DDG specialization is changing to DBM: Digitalisering, Bestuur en Maatschappij.)
Description
This course integrates knowledge and skills from two first year DDG courses: The Digital State and Data Science Skills and Applications 1. The course achieves this by guiding students to develop their own group project/research. During the development of their projects, students will approach the concepts, theories, and challenges associated with the development of the digital state, and how data analytics can be used to showcase the problems and help the government work better. In other words, students will explore real-life societal problems of the digital state, understand the causes, and investigate how can the problem and potential solutions be better understood via an evidence-based approach. Students will team up to develop their projects to demonstrate timely digital state issues, justify the importance of their project, project questions, the theoretical grounds, the data evidence, and analytical skills.
Course objectives
By the end of the course, through project-based learning, students are expected to increase their academic knowledge, practical perspectives, and teamwork ability. Objectives include:
Use scholarly literature and policy information to approach a research problem about the digital state.
Plan and deliver a data-driven project by teamwork, leveraging project collaboration and communication skills.
Understand the practical implications on the public sector of digital programs and manage to identify ongoing policy problems and navigate positive changes.
Effectively communicate the design, data, results, and conclusions of the project, to both specialized and non-specialized audiences.
Timetable
On the right side of the programme front page of the studyguide you will find links to the website and timetables, uSis and Brightspace.
Mode of instruction
The course has a mixed lecture approach, with a highly practical orientation. A part of the course will be based on lectures and working groups, that will guide the students in integrating the knowledge and skills from The Digital State and Computational/Digital skills 1: Data - uses and opportunities courses to craft their research/projects. But a very important part of the course will rely on self-study and group teamwork.
Total study load: 140 hours, of which:
Lecture, tutorials & working groups: 14 hours
(Lecture: 6 hour, working group 8 hours)
Self/Group-study: 126 hours
Assessment method
Individual assignment:
Observation memo & literature review (30%)
Group assignments:- Project proposal (20%)
Project presentation (two times, pass/fail)
Final project report (50%)
There will be individual assignments regarding observation memos and literature reviews. Most assignments are group-based to conduct a team project. Students should attend all lectures and working group meetings (mandatory). Students must show that they have participated actively in their group. All assignments must be submitted on time on Brightspace.
To pass the course, students must present their group project in class and the grade for the final paper must be at least 5.5. Retake for the final paper assignment is allowed but the resubmission will receive a score with a maximum grade of 7 due to the principle of fairness.
Partial grades are only valid in the current academic year.
Reading list
This course builds on literature, knowledge, and toolkits learnt from the first year courses, in particular: the Digital State and Computational/Digital skills 1. Additional articles may be shared in the course guide and on Brightspace. Articles should be studied before the sessions.
Registration
Register yourself via MyStudymap for each course, workgroup and exam (not all courses have workgroups and/or exams). Do so on time, before the start of the course; some courses and workgroups have limited spaces. You can view your personal schedule in MyTimetable after logging in.
Registration for this course is possible from Tuesday 12 December, 13:00 h.
Leiden University uses Brightspace as its online learning management system. After enrolment for the course in MyStudymap you will be automatically enrolled in the Brightspace environment of this course.
More information on registration via MyStudymap can be found on this page.
Please note: guest-/contract-/exchange students do not register via MyStudymap but via uSis.
Contact
Dr. Hsini Huang: h.i.huang@fgga.leidenuniv.nl