Spring 2020 will be distance education.

PA2566 Behavioural Software Engineering

Single subject course, 5 Higher education credits, Second cycle, autumn semester 2019

It is no longer possible to apply to this option

The purpose of this course is to better understand humans that are key in making software projects successful. It includes an understanding of behavior and social aspects of humans as individuals or groups that participate in and drive software engineering. This course complements the technology and process focus that dominates the software engineering area today. The focus is on the individuals and groups in software development and results at the organizational level are briefly covered. Those that participate in this course will gain knowledge that will help them to better cater to the needs of their colleagues as well as employees, build on their strengths as well as overcome their weaknesses, and in turn it helps increase the chances of running successful software projects.


  • Type of instruction: Distance, mixed-time, part-time 17%
  • Period : 2019-September-02 until 2020-January-19
  • Education level: A1N
  • Application: It is no longer possible to apply to this option
  • Language of instruction: The teaching language is English.
  • Location: Some or all of education and examination is held at distance.
  • No. of occasions: Mandatory: none, Voluntary: none
  • Main field of study: Software Engineering
  • Course syllabus: Download
  • Welcome letter: Download
  • Entry requirements: Admission to the course requires at least 120 credits of which 90 credits in a technical subject and a minimum of 2 years professional experience in software development (shown by, for example, a work certificate from an employer).


The course comprises six modules:
  • Introduction to Behavioural Software Engineering: Definitions, concepts, and motivations.
  • Individuals: Personality and cognitive biases, their effects, and related indicators / measures.
  • Individuals: Models for motivation and attitudes.
  • Individuals: Concepts for experience and emotion.
  • Groups: Norms and creativity within software development.
  • Politics, happiness, and freedom in software organisations for software engineers.

Learning outcomes

Knowledge and understanding
  • explain and discuss the importance of Behavioural Software Engineering and how it differs from classical software engineering,
  • explain and discuss the effects of personality and cognitive biases in relation to software engineering.

Competence and skills
  • discuss and apply models for norms and motivation in software development,
  • give examples of and discuss creativity, as well as creativity enhancement techniques, in software development.

Judgement and approach
  • critically reflect on their own experience with regards to behaviour and social aspects as individuals and within groups,
  • reflect on the emotions that software developers experience and how they impact a project,
  • identify, discuss, and critically reflect on political behaviour in their software organisation.

Course literature and other teaching material

A compilation of video lectures, written materials, and research reports are available on the course's online learning platform.

Course literature and other teaching material

A compilation of video lectures, written materials, and research reports are available on the course's online learning platform.

Learning methods

The teaching within each module is organised around research articles, pre-recorded lectures and written materials on key topics, and mandatory assignments. Two optional campus days with workshops and seminars will take place. Throughout the course, communication with teaching staff and fellow participants will take place through email and the course's online learning platform for discussions and feedback.

Work placement

No work placement is included in the planned learning activities. BTH is aiming for a close contact with the surrounding community when developing courses and programmes.


  1. Fabian Fagerholm
Course Manager
  1. Fabian Fagerholm

Time allocation

On average, a student should study 134 hours to reach the learning outcomes.
This time includes all the various available learning activities (lectures, self studies, examinations, etc.).
This estimation is based on the fact that one academic year counts as 60 ECTS credits,
corresponding to an average student workload of 1 600 hours. This may vary individually.


Component examinations for the course
Code Title ECTS credits Grade
1810 Assignments 5 G-U


The course will be graded G Pass, UX Insufficient, supplementation required, U Fail.


More information about exams are found in the Student's Portal, where you also enrolls for most exams.

There might be other scheduled examinations. Information regarding these examinations are available in the learning platform Canvas or at other places that the person who is responsible of the course will refer to.

Course Evaluation

The course manager is responsible for the views of students on the course being systematically and regularly gathered and that the results of the evaluations in various forms affect the form and development of the course.