NDAK17000U CHANGED: Collaborative Computing (CollComp)
MSc Programme in Computer Science.
The course in Collaborative Computing introduces research on Computer Supported Cooperative Work (CSCW) and has two main focuses 1) to study collaboration and 2) to design collaborative technologies. Collaboration is everywhere and techniques and methods can be used for several domains including open source development, open hardware collaboration, healthcare, gaming, research & development etc.
The course contains advanced research-based themes and topics from contemporary CSCW research and includes (but not limited to) articulation work, dependencies, coordination, awareness, common information spaces, information infrastructures, and knowledge sharing.
The course has three parts:
- Theoretical understanding of the CSCW research domain.
- Practical investigation of cooperative technologies for collaboration (e.g. wikipedia, GitHub, AMTurk etc.)
- Design of collaborative technologies utlizing makerspace methodologies.
Knowledge
- Explain central concepts in CSCW research.
- Discuss and argue theoretical concepts and insights from computer supported cooperative work (CSCW) research related to examinating collaborative work arrangement and designing cooperative technologies.
Skills
- Analyse a collaborative practice and the use of collaborative technologies by applying the theoretical concepts from CSCW.
- Design (Re-design) collaborative technologies and suggest how experienced challenges can be addressed in new designs of collaborative technologies based upon theoretical as well as practical arguments.
- Identify and discuss challenges for the design of collaborative technologies and work practices based upon CSCW foundations.
Competences
- Participate competently in globally distributed collaboration by acting pro-actively in terms of making the collaboration function and using collaborative technologies.
- Design and evaluate collaborative technologies.
Research papers. See Absalon.
- Category
- Hours
- Exam
- 1
- Exercises
- 24
- Lectures
- 12
- Preparation
- 32
- Project work
- 125
- Total
- 194
As
an exchange, guest and credit student - click here!
Continuing Education - click here!
PhD’s can register for MSc-course by following the same procedure as credit-students, see link above.
- Credit
- 7,5 ECTS
- Type of assessment
- Oral examination, 20 minThe oral exam is without preparation and is based on the qualifying group project report.
- Exam registration requirements
To qualify for the exam, student must hand in a report based on their project.
- Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners
- Re-exam
Oral exam without preparation, 20 min, based upon (possibly revised) project report.
For the student to qualify for the re-exam, the report must be resubmitted no later than two weeks before the re-exam date.
Criteria for exam assesment
In order to obtain the grade 12 the student should convincingly and accurately demonstrate the knowledge, skills and competences described under Learning Outcome.
Course information
- Language
- English
- Course code
- NDAK17000U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 2 And Autumn
- Schedule
- A
- Course capacity
- no limit
- Continuing and further education
- Study board
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Computer Science
Contracting faculty
- Faculty of Science
Course Coordinators
- Pernille Bjørn (pernille.bjorn@di.ku.dk)