Business Research and Development Methods II (5cr)

Evaluation scale

Hylätty/Hyväksytty

Objective

Student will learn the methods how to use, handle, analyze and interpret both qualitative and quantitative data. She/he will learn how to combine qualitative and quantitative data, i.e. use mixed methods/triangulation.

Execution methods

Lectures and online lectures

Accomplishment methods

Lectures
Online lectures
Active participating
Group discussions
Course assigment

Content

Qualitative data analyses
Quantitative data analyses

Location and time

The lectures will take place on campus during the period of 12 January - 30 April. The exact schedule will be released prior to the start of the course.

Materials

To be announced later on Reppu

Teaching methods

The lectures will take place on campus. The course also includes course work (both group work and individual) on qualitative methods. The course also includes exercises and homework on quantitative methods. Evaluation will be based on the course work (qualitative methods) and an exam and survey task (quantitative methods).

Employer connections

None.

Exam schedules

The exam will take place during the last quantitative methods class on campus. There will be two opportunities for retakes. The retakes will have to be taken before the end of the calendar year of 2026. Register for the retake at least 10 days prior to the exam date. Exam dates can be found on KAMK intra page Exams and retakes.

International connections

None.

Completion alternatives

There is no optional completion method for the course.

Student workload

The course requires approximately 135 hours of student work.
Lectures account for approximately 33 hours. The remaining 102 hours are dedicated to assessed project works and the course exam.
Of these, approximately 51 hours will be dedicated to qualitative research, and 51 hours to quantitative research.
These figures are indicative, and the actual workload depends on the amount of time each student chooses to spend on their studies.

Assessment criteria, approved/failed

Pass:
Student knows the requirements of quantitative and qualitative data analyses and can apply different analysis methods in his/her research process. Students is able to collect and analyse both qualitative and quantitative data and further interpret the results in a critical way.

Assessment criteria, approved/failed

Pass
Student knows the requirements of quantitative and qualitative data analyses and can apply different analysis methods in his/her research process. Students is able to collect and analyse both qualitative and quantitative data and further interpret the results in a critical way.

Further information

Guidelines for the use of AI—including its possibilities and limitations—will be reviewed during the first session in relation to the course assignments (based on Arene's AI recommendations).

Failure to follow the given instructions may result in the rejection of the course. If this is the case only with a single assignment, the student will be required to redo the task to receive a passing grade.

As with all the courses, it is possible to apply for credit transfer or recognition of prior learning (RPL) for the course, including the opportunity to integrate prior experience through a process of learning validation.

Mandatory attendance: students must attend at least 50% of the classes. Attendance will be recorded separately for qualitative and quantitative methods.

For both course assignments and exams there will be two opportunities for retakes (3 attempts overall). If a student does not pass after 3 attempts, they will have to retake the course.