Designing Collaborative Technologies (DesignCoTech)
Course content
In this course we will explore and experiment with applying new technologies (such as Blockchain, Augmented Reality and the Internet of Things) to support social interaction and collaboration in new ways. Students will start by learning how to study diverse workplaces, drawing on established theories of computer supported cooperative work (CSCW). The goal here will be to learn how to study users and their practices, and to learn from how technologies are used in 'real world’ organisations. Students will then bring these new insights into the Makerspace and start a design process learning how to develop and apply novel technologies in a user-centred way. The overall goal will be to help students to rethink and innovate the future of workplace, and build new collaborative technologies that fit with real users needs.
The course has three parts:
- Ethnographic empirical study of a selected workplace drawing on theoretical theories of computer supported cooperative work
- Design and prototyping collaborative technologies in the Makerspace using user-centred approaches
- Re-thinking and innovating the future workplace creating design fictions
Knowledge of
- Theories in computer supported cooperative work (CSCW)
- Ethnographic field methods for design
- User centred design in Makerspaces
Skills to
- Analyse the complexities of workplace using CSCW theories
- Design collaborative technologies for the future workplace
- Innovate through iterative prototyping in a Makerspace
Competences to
- Analyse work practices in real life organisations
- Design workplace technologies supporting people needs
- Innovate the future of work
Learning activities include seminars, workshops, explorative exercises, empirical data collection, where students will work theoretically and experimentally with CSCW concepts for analysis and design. Some learning activities will take place in a Makerspace. Moreover, there will be assignments which will require collaboration with students located at University of Maryland, Baltimore, USA - allowing students real-life experiences with globally distributed work.
Research papers. See Absalon.
Academic qualifications equivalent to a BSc degree is recommended.
The course is similar to the discontinued course NDAK17000U Collaborative Computing (CollComp) and students can only take (and get credit for) one of the courses.
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.
- ECTS
- 7,5 ECTS
- Type of assessment
-
Oral exam on basis of previous submission, 20 minutes (no preparation time)
- Type of assessment details
- Specifically, the exam consists of two parts:
1. A group report (written assignment) based on the project.
2. An individual oral examination (without preparation) based on the report.
The written and oral examination are not weighted, why only one overall assessment is provided for the two parts of the exam. - Aid
- All aids allowed
The use of Large Language Models (LLM)/Large Multimodal Models (LMM) – such as ChatGPT and GPT-4 - is permitted. The finite list of allowed AI-tools will be announced in Absalon.
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners
- Re-exam
-
Same as the ordinary exam.
For the re-exam the student must submit a new individual report or resubmit an edited version of the group report no later than 3 weeks before the re-exam.
Criteria for exam assessment
See Learning Outcome
Single subject courses (day)
- Category
- Hours
- Lectures
- 24
- Preparation
- 32
- Exercises
- 24
- Project work
- 125
- Exam
- 1
- English
- 206
Kursusinformation
- Language
- English
- Course number
- NDAK23007U
- ECTS
- 7,5 ECTS
- Programme level
- Full Degree Master
- Duration
-
1 block
- Placement
- Block 3
- Schedulegroup
-
A
- Capacity
- No limitation – unless you register in the late-registration period (BSc and MSc) or as a credit or single subject student.
- Studyboard
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Computer Science
Contracting faculty
- Faculty of Science
Course Coordinator
- Pernille Bjørn (14-7d727f7b767979723b6f777c7f7b4d71763b78823b7178)
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Kursusinformation for indskrevne studerende