About this course

  • Create fundamental insight in and understanding of innovation and the meaning of innovation for value creation in bio-based industries.
  • Introduction to innovation. Innovation teams, creativity and innovation. Sources of innovation.
  • Decisions in situations with high uncertainty.
  • Sustainability and innovation.

Learning outcome

Knowledge

The student:

  • Has advanced knowledge of innovation processes, creativity in innovation, the role of creative teams, and decision-making under uncertain conditions.
  • Has in-depth understanding of the importance of interdisciplinary knowledge and learning for innovation processes.
  • Has insight into different types of innovation, innovation theories, and the relationship between research, innovation, and development in biologically based industries.
  • Understands how innovation in bio-based industries can contribute to increased sustainability.

Skills

The student:

  • Can develop ideas, as well as screen and test them in the early innovation phase.
  • Is capable of working effectively in interdisciplinary teams.

General Competence

The student:

  • Communicates effectively in interdisciplinary teams.
  • Has the ability to utilize interdisciplinary teams in problem-solving processes.

  • Learning activities

    The course is based on active participants by the students. The learning will take place in lectures, class discussions, individual activity, group projects and presentations. The groups will be cross functional.

  • Syllabus

    The Design-Thinking process is utilized.

    A variety of articles and videos are utilized throughout the course.

    The readings are published in Canvas prior to the course starts.

  • Assessment method

    Portfolio assessment, based on hand-ins and presentations of group projects. Individual lessons-learned submission.

    Students are graded as Passed / Failed.



    Portfolio Karakterregel: Passed / Not Passed

  • About use of AI

    Group Assignment and reflection report: K2 - Specified Use of AI in the group assignment and reflection report, AI may be used for brainstorming and language editing. The use of AI must be described with a brief explanation of which tools have been used and how they have been applied in the text. The group is responsible for the final content of the text after language editing has been completed.

    Use of AI is permitted, but must be in accordance with the guidelines for use of artificial intelligence (AI) at NMBU

    Descriptions of AI-category codes.

  • Examiner scheme

    External examiner will control the quality of syllabus, questions for the final examination, and principles for the assessment of the examination answers.

  • Mandatory activity

    Mandatory presence in the lectures.

  • Teaching hours

    12 hours of lectures per week, three days per week, for 3 weeks.

  • Reduction of credits

    The course overlaps 5 ECTS with INN301 Innovation

  • Admission requirements

    Students on the master´s program on Bioeconomy has priority access to this course.