CS-E5011 - Research Methods: Case Studies & Design Science D, Lecture, 23.10.2024-28.11.2024

Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

After completing the course, students will be able to …

  • Plan and implement empirical studies in the industrial setting
  • Explain and compare the goals, nature, and processes of design science, case studies, and action research
  • Select appropriate research approach for a research goal in the industrial setting
  • Evaluate the validity and reliability of research results

Credits: 2

Schedule: 23.10.2024 - 28.11.2024

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Sari Kujala

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content

  • valid for whole curriculum period:

    This course represents one of the possible specialisations following the basic research methods teaching in CS-E5010 Research Methods: Foundations D. The goal of the course is to introduce the participants to scientific research approaches frequently used in technical fields and in the context of industry.

    In addition, the course provides students practice on planning empirical studies using design science, case study, and action research approaches for their doctoral or master's theses.

    The needs and interests of students from different majors and programmes (e.g. Information Networks, Software Engineering) will be met based on a diverse set of research examples and custom-tailored learning and exercise materials. 

    Alternatives to this specialisation course:

    • Research Methods: AI-based Data Synthesis & Analysis.

    One specialisation cannot necessarily substitute another as degree requirement, and students are consequently encouraged to check their desired course choice against the requirements of their respective major. The same holds if students wish to take multiple specialisation courses, and wonder whether the additional credits can be counted toward their study progress.

Workload

  • valid for whole curriculum period:

    Lectures, lab and assignments.

DETAILS

Substitutes for Courses
Prerequisites

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Language: English

    Teaching Period: 2024-2025 Autumn II
    2025-2026 Autumn II

    Registration:

    Max. 40 students will be accepted to the course. Priority is given to 1. Master's students for whom this course is mandatory; 2. Other Master's and Doctoral students 3. Exchange students.

Rules of Conduct - Students´ Rights and Responsibilities (in force from 1 August 2020)

Aalto University Code of Academic Integrity and Handling Violations Thereof