Official course description:

Full info last published 6/09-21
Course info
Language:
English
ECTS points:
7.5
Course code:
BSTECOM1KU
Participants max:
59
Offered to guest students:
yes
Offered to exchange students:
yes
Offered as a single subject:
yes
Price for EU/EEA citizens (Single Subject):
10625 DKK
Programme
Level:
Bachelor
Programme:
BSc in Data Science
Staff
Course manager
Assistant Professor
Teacher
Part-time Lecturer
Course semester
Semester
Efterår 2021
Start
30 August 2021
End
31 January 2022
Exam
Exam type
ordinær
Internal/External
ekstern censur
Grade Scale
7-trinsskala
Exam Language
GB
Abstract
This course gives an introduction to technical communication. It focuses on designing different forms of communication correctly, effectively, and convincingly. There will be a theoretical introduction to the importance and principles of technical communication together with several individual and group based practical exercises.
Description

To succeed in life, you need to be able to communicate in an efficient and convincing manner. Your ability to communicate technical topics will play a deciding role whether you get a job, a promotion, win a grant, or whether your start-up succeeds. Research shows that no matter what job you have, whether you are a manager in a big company, a researcher, or a data-scientist, you will spend at least 20 percent of your time on communication. Much of this time will be spent on communicating technical insights to non-technical audiences (e.g. team members, upper management, investors, journalists, policy makers). As such, poor communication can lead to major financial losses or even to serious catastrophes costing human lives.

In this course the student will gain an understanding of why technical communication is important, and how to communicate technical information clearly, efficiently, and convincingly to different audiences and through different formats. We will focus on communicating verbally and through written text. In particular, the course will cover the following subjects:

  1. Challenges and failures of communication 
  2. Importance and principles of technical communication
  3. Rhetoric principles
  4. Team-based communication
  5. Audience analysis and subject research
  6. Communicating correctly, effectively, and convincingly
  7. Designing and delivering persuasive technical presentations
  8. Text design and reviewing, evaluating, testing documents and websites
  9. Summarizing research findings, communication for web and social media
  10. Translating research findings for a general audience
  11. Writing definitions, documentation and instructions

Formal prerequisites
This is a mandatory course for BSc Data Science students, however, the course is open for all Bsc students. Students must have done a research project (first, second year project or something comparable, including projects in courses like Machine Learning or Network Analysis).
Intended learning outcomes

After the course, the student should be able to:

  • Write correctly and efficiently a technical/professional document for a specific audience.
  • Apply the right rhetorical techniques to convince the audience.
  • Design a persuasive technical presentation for a specific audience.
  • Communicate collaboratively in a team setting.
Learning activities

14 weeks of teaching consisting of lectures and exercises

  1. Challenges and failures of communication
  2. Importance and principles of technical communication
  3. Rhetoric principles
  4. Team-based communication
  5. Audience analysis and subject research
  6. Communicating correctly, effectively, and convincingly
  7. Designing and delivering persuasive technical presentations
  8. Text design and reviewing, evaluating, testing documents and websites
  9. Summarizing research findings, communication for web and social media
  10. Translating research findings for a general audience
  11. Information design with figures, tables, and graphs

Mandatory activities
Completion of 3 exercise submissions are required to be entitled for taking the final exam.

The student will receive the grade NA (not approved) at the ordinary exam, if the mandatory activities are not approved and the student will use an exam attempt.

Course literature

The course literature is published in the course page in LearnIT.

Student Activity Budget
Estimated distribution of learning activities for the typical student
  • Preparation for lectures and exercises: 10%
  • Lectures: 25%
  • Exercises: 25%
  • Assignments: 20%
  • Exam with preparation: 10%
  • Other: 10%
Ordinary exam
Exam type:
C: Submission of written work, External (7-point scale)
Exam variation:
C1G: Submission of written work for groups
Exam submission description:
The submission will consist of summaries of research findings, interview materials, and slides of presentations targeted at particular audiences including graphics or figures.
Group submission:
Group
  • 4 students - 3 can be accepted if a group of 4 is not possible.

Time and date