General Course on Research Design and Excellence

Starting Date
September 9, 2022
Ending Date
January 13, 2023
Maximum group size


This doctoral training course aims to strengthen the methodological and analytical competencies that enable to design and plan creative, critical, and autonomous academic research, capable of pushing the boundaries of scientific knowledge. This is a general course on research design and excellence, providing a holistic view of the research methodologies and process by addressing the following topics: scientific research, epistemology and methodology of science, research problems and questions, methods of data collection and analysis, validity and reliability. The course is divided into five modules: Module 1 addresses philosophical, ontological and epistemological frameworks and current trends of scientific research; Module 2 addresses systematic literature review, development of research problems and questions; Module 3 includes comprehensive overview of advanced technological tools for research (includes cases on applications of AI and machine learning to research, e.g. surveys, sentiment analysis, consumer behaviour, etc.); Module 4 addresses advanced methods, instruments and research quality criteria relevant for working with qualitative data; Module 5 addresses advanced methods, instruments, typical errors, validity and reliability of quantitative research. PhD students will use their research as case example to apply the concepts and skills learned during the course.


Audronė Telešienė (Kaunas University of Technology)

Learning outcomes    

At the end of the course, participants should be able to:

  • Critically discuss the philosophical, ontological and epistemological frameworks and current trends of scientific research
  • Formulate theory and practice informed research problems and develop research questions
  • Design and plan a scientific research project, well aligned with appropriate methodology, and methods and tools for data collection and analysis.
  • Critically appraise the relevance, novelty, validity, reliability and feasibility of a research.


Distance learning, using a flipped classroom approach. Teaching methods include lectures and seminars on the following dates (TBC):

  • Intro and Module 1: September 9
  • Module 2: September 16, 23 and 30;
  • Module 3: October 14
  • Module 4: October 21 and 28, November 4
  • Module 5: November 18 and 25, December 9.
  • Deliverables submitted: report by December 30th 2022; peer review by January 6th 2023.


The successfully completion of the course requires at least 70% attendance during required attendance dates and deliverables that meet minimum quality requirements.


6 June – 24 June (only applications received within the above dates will be considered)


Download the Registration form