EPN-V2

SP9100 Qualitative Methods and Analytical Strategies Course description

Course name in Norwegian
Kvalitativ metode og analysestrategier
Study programme
PhD Programme in Social Sciences
PhD Programme in Social Work and Social Policy
PhD Modules in Social Work and Social Policy
Elective modules from PhD Programme in Social Sciences
Weight
10.0 ECTS
Year of study
2021/2022
Curriculum
SPRING 2022
Schedule
Course history

Introduction

The course provides a sound grounding in some traditions and approaches that are categorised as qualitative research and their epistemological basis. The focus will be on different methodological approaches each time the course is taught.

Recent qualitative social science research also takes its inspiration from philosophy and the humanities, which is reflected in the course. Different ways of producing empirical material will be presented. Qualitative analysis is an important element in the course: the dialogue between theory and empirical data, the design of analytic tools and development of empirically based and theory-inspired analysis models, and theory generation based on empirical data. The course will also examine what contextualised analyses can entail in the field of social work and social policy. Different sets of quality criteria for qualitative knowledge projects are presented, and the course will also include information about the debate in the field.

The methodological approach for spring 2021

When "somethings" becomes data: From data production to analysis strategy.

Required preliminary courses

None.

Learning outcomes

After completing the course, the candidates are expected to have the following knowledge, skills and general competence:

Knowledge

Candidates

  • are capable of assessing the expediency and application of different methods' area of use, possibilities and limitations
  • have thorough and nuanced insight into one or two specific methodological approaches, and can relate them to their own research field

Skills

Candidates are capable of

  • applying qualitative research methods and conducting qualitative analyses of a high standard
  • making well-thought-through choices that fit the candidates' own projects and pertaining research questions

General competence

Candidates are capable of

  • considering ethical issues of different types with academic integrity
  • participating in relevant international debates in the subject area
  • identifying and preparing new researchable questions on the basis of complex societal conditions

Teaching and learning methods

All aids are permitted.

Course requirements

Pass or fail.

Assessment

The presentation will be assessed by the course leader, whereas the tool summary document will be assessed by the course leader together with an additional examiner. External examiner is used periodically.

Permitted exam materials and equipment

Bachelor's or master's degree in engineering science or related fields.

Grading scale

The course consists of three modules.

In the first module, the course staff and guest lecturers will provide a high-level overview of different parts of the internet's architecture.

The second part is a set of practical exercises that are designed to match the topics discussed in the first module.

The third module will consist of a set of seminars, where students elaborate on different parts of the architecture and how they can be assessed and monitored.

Examiners

The essay will be graded by the course lectures.

Admission requirements

The target group for the course are candidates from the PhD programme in Social Work and Social Policy, but it will also be open to PhD students on other programs who wish to study the field in depth.

Internal candidates register the course in their Studentweb and send a summary, maximum one page, of their project to the PhD administration.

External candidates apply through the Søknadsweb. The following documentation must be enclosed:

1. Confirmation on admission to a PhD program 2. Summary of your research proposal (approx.one page) and how this PhD course will be relevant for your research project

Maximum number of participants is 10.

Course contact person

Marit Haldar