Business Research and Development Methods II (5cr)

Evaluation scale

Hylätty/Hyväksytty

Content scheduling

Quantitative methods will be discussed in lectures during the time period of 24.3.-23.4, qualitative methods will be discussed in lectures 28.4.-26.5.

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 online lectures will take place during the time period of 24.3.-26.5.

Materials

To be announced later

Teaching methods

8 online lectures which will recorded.
Attendance is not mandatory. However, there may be an additional assignment if you are not present during certain lectures.
The course also includes course work (both group and individual assignments).

Employer connections

None.

Exam schedules

No exam.

International connections

None.

Completion alternatives

None.

Student workload

The course requires approximately 135 hours of student work.
Lectures account for approximately 18 hours. The remaining 117 hours are dedicated to assessed course assignments and individual study.
Of these, approximately 58 hours will be dedicated to qualitative research, and 58 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.

For course assignments 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.