Advanced Research Methods (5 cr)

Objective

The purpose of the course is to strengthen the student’s competence in producing new knowledge and renewing ways of working in research and development projects aiming to predict the future. In addition, the purpose is to strengthen competence in the planning, execution and critical evaluation of customer-oriented, sustainable and high-quality research and development projects.

The student is able to select the qualitative or quantitative research methods that are suitable for the aims of a research and development project or the development methods suitable for its purpose (quantitative, qualitative or research-based development, literature reviews) and to justify the choices they make. The student masters the methods of systematic data search and collection, processing and analysis of data and is able to apply them in practice. The student has a good command of different stages, research ethics and data protection in research and development projects and is able to apply them in practice with each research and development method. The student is able to conduct qualitative and quantitative research and development work in practice. The student is able to report on their research and development projects.

Content

- Panning, execution and evaluation of research and development activities
- Methods of quantitative and qualitative research and development activities
- Data and data collection
- Statistical analyses of quantitative research, analysis of qualitative data
- Analysis of data for development activities
- Ethics, reliability and impact of research and development
- Various forms of expert communications in reporting on research and development work

Location and time

WEBINARS

14.1.2025 at 14-16 Orientation to the course
17.1.2025 9-12 Qualitative research: data description, quality assessment and content analysis
10.2.2025 9-12 Quantitative research: statistical description of data and statistical tests
11.2.2025 9-12 Development work: step-by-step progress and data
10.3.2025 9-12 Literature reviews
12.3.2025 10-11:30 Thesis presentation
13.3.2025, 9-12 Data management and planning

Course ends 13.4.2025

Materials

All course-related material can be found on Moodle when the course begins.

Teaching methods

Interactive teaching online (including exercises and discussion during the lessons)
Independent study and work in Moodle

Employer connections

-

Exam schedules

N/A

International connections

-

Completion alternatives

-

Student workload

135 hours of student work.
The work consists of attending lectures or watching recordings, independent online learning and eight smaller assignments and two larger assignments in Moodle.

Content scheduling

Themes:
Qualitative research
Quantitative research
Literature reviews
Developmental research
Data management
Ethics

Further information

-

Evaluation scale

0-5

Assessment criteria, satisfactory (1)

The student demonstrates that they understand the basic content of the course but there are shortcomings in their ability to independently acquire and interpret information and apply what they have learned.

Assessment criteria, good (3)

The student demonstrates that they have a good understanding of the content of the course. They actively acquire information and interpret the key connections between different pieces of information. The student has the ability to analyse what they have learned and to apply it in practice.

Assessment criteria, excellent (5)

The student demonstrates that they have a diverse and broad understanding of the content of the course. They possess excellent information acquisition skills that are suited to the purpose at hand. The student demonstrates independence and responsibility in the choices they make. They have a creative and broad-based ability to apply what they have learned in practice.

Assessment criteria, approved/failed

Approved: The student demonstrates that they understand the basic content of the course but there are shortcomings in their ability to independently acquire and interpret information and apply what they have learned in practice.

Assessment methods and criteria

EVALUATION

Exercises 1 to 7 and 10, pass - fail - fail to complete
Assignment 8: Data management plan + peer assessment, 30% of the total course assessment, grade 1-5
Assignment 9: Presentation of the selected study and its methodology + peer assessment, 70% of the total course grade, grade 1-5

Overall assessment of the course according to the weighting of the averages of Assignments 8 and 9, with a grade of 1-5.

Further information

RPL (Recognition of Prior Learning)
The course can be accredited with advanced studies completed earlier for a Master’s degree or in a university (60 ECTS), provided that the contents of the completed courses correspond to the contents of these courses.