IN5610 ¨C Advanced Topic in Digital Innovation

Course content

This course goes in-depth on selected topics in digital business and innovation from within the research field of information systems. Key topics are business analytics, data-driven innovation, and decision support. The aim is to enable the students to both practically and theoretically engage with current practices of digital business and innovation, as covered by the selected topics. The course syllabus will continuously be updated with current research literature, and the selected topics may therefore change from year to year. The course aims to both give the students a basis for writing a master thesis tied to the selected topics and to introduce them to practically relevant methods and practices in digital innovation.

Learning outcome

After taking?this course, the student will be able to:

• have insight into state-of-the-art research on digital business and innovation

• have knowledge on the opportunities and technologies of data-driven innovation

• understand the role of business analytics in the digital organization

• be able to plan, implement, and evaluate a project covered by the course topics, like business analytics, data-driven innovation, and decision support

• have skills in using a business analytics tool in practice

• have the competence to reflect on the organizational, ethical, and legal aspects of data-driven innovation and decision support

• assess and evaluate managerial implications of data-driven innovation

Admission to the course

Students who are admitted to study programmes at UiO must each semester register which courses and exams they wish to sign up for?in Studentweb.

If you are not already enrolled as a student at UiO, please see our information about?admission requirements and procedures.

Students in the?Master`s program Informatics: Digital Economics and Leadership will be prioritized.

Recommended previous knowledge

It is recommended to have taken at least 20 credits in business courses prior to?this course, such as INEC1800, INEC1810, INEC1820/INEC1821, INEC1831

Teaching

2 hours of lectures and?2 hours of exercises per week.

Teaching is based on a mixture of theory lectures, lab exercises and active discussions in class.

Submission of mandatory assignments is required.?Read more about requirements for submission of assignments, group work and legal cooperation under guidelines for mandatory assignments.

Examination

The course grade is based on the following assessments:

• a term paper to be written in groups of two or three, on a self-chosen topic decided in collaboration with the course leader: 60%
• two individual assignments in analytics: 20% each

All parts of the exam and the attendance must be passed, and passed?in the same semester, to pass the course.

Mandatory assignments must be approved prior to the exam.

Grading scale

Grades are awarded on a scale from A to F, where A is the best grade and F?is a fail. Read more about?the grading system.

More about examinations at UiO

• Use of sources and citations
• Special exam arrangements due to individual needs
• Withdrawal from an exam
• Illness at exams / postponed exams
• Explanation of grades and appeals
• Resitting an exam
• Cheating/attempted cheating

You will find further guides and resources at the web page on examinations at UiO.