SN5900 The Master's Thesis Emneplan

The student submits a thesis that investigates a research question using one or several relevant research methodologies.

All other courses within the master's degree must be passed before submitting the master's thesis.

A student who has completed his or her qualification has the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

The student has advanced knowledge of

• research designs relevant to the investigation of a particular research question
• a particular area of social or health policy of relevance to their degree
• relevant research literature on the subject matter of the master-s thesis
• theories and methodological approaches relevant for the chosen subject matter
• basic conceptual tools needed to understand an critically examine relevant social research

Skills

The student can

• conduct a review of the state of scientific knowledge related to a research question in social policy
• conduct a limited, independent research project under supervision
• choose a methodology that is relevant for a specific welfare research question
• apply research methods in a reflective manner
• critically evaluate relevant quantitative or qualitative methods used in reports, books or articles investigating a particular welfare policy problem

General Competence

The student can

• read and critically assess academic literature
• present specialised knowledge and research findings in the form of academic writing
• apply advanced skills and knowledge in the field of social welfare policy
• evaluate issues related to the academic, professional and research ethics

At the end of the second semester, a two page project description must be submitted and approved before the student gets a supervisor. A master's thesis preparation seminar will help the student to produce the two page project description.

A supervisor will be appointed by the programme director. Supervision is a crucial component in the preparation of the thesis. The supervisor is to assist the student when he or she is acquiring the necessary and relevant knowledge, as well as, when collecting and analysing data. The supervisor must ensure that the student-s research activity comply with accepted ethical standards within social research, including standards defined by the Norwegian Data Protection Official and the National Committees for Research Ethics in the Social Sciences and the Humanities

Every student is entitled to approximately 10 hours of face-to-face consultation, individually or in groups, or the equivalent if part of the supervision is conducted via email. Two students co-writing will together receive 15 hours of face-to-face consulation.

An agreement between the student and the supervisor must be signed by both parties to ensure that rights and obligations are understood. The student and the supervisor may request a substitute if either party fails to meet the obligations outlined in the agreement.

The research work (analysis of qualitative and/or quantitative data or a literature review) is conducted during the fourth semester. Students are encouraged to carry out their data collection abroad.

Compulsory activities must be completed and approved by the given deadline in order for the student to take the exam:

• A two page project description must be submitted and approved.
• A signed agreement between the student and the supervisor must be submitted by a set date.

The exam consists of two parts: the Master's thesis itself and an oral examination. The Master's thesis must receive a passing grade before the student can sit for the oral examination. The oral examination begins with the student presenting their Master's thesis in lecture format (30 minutes, 45 minutes if co-authored with another student). Following this, the student will participate in an individual, oral discussion and assessment (of approx. 45 minutes).

The student can choose to receive the grade on the written master's thesis before the oral presentation of the thesis (the lecture) commences.

The oral presentation (the lecture) and the subsequent individual, oral discussion and assessment can change the grade that is given for the Master's thesis. After the oral examination, the final grade is set. The final grade is entered into the diploma.

When two students co-author a Master's thesis, both will receive the same grade for the written thesis. Each individual student will, however, individually present their part of the thesis in lecture form and subsequently participate in an individual, oral discussion and assessment. The presentation and oral discussion and assessment will be evaluated as the individual student’s contribution and will be used for possible adjustment of the final grade.

A student can deliver a new or revised Master's thesis one time if the Master thesis does not receive a passing grade. The student in this case will receive an offer of three-hours further supervision before submitting. Students receiving a passing grade on their Master's thesis do not have the right to have their thesis re-evaluated within the same study program.

All aids are permitted, as long as the rules for source referencing are complied with.

The students will gain knowledge of and insight into how to use data visualisation to present information, for example statistics, in a more understandable way. The students will learn to use different methods of processing data, so that they are easier to work with.

No requirements over and above the admission requirements.

After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and competence:

Knowledge

The student:

• is familiar with terminology and concepts used in the field of visualisation
• is familiar with the history of the field
• is familiar with fundamental perception theory
• is capable of explaining different types of information and what kind of visualisation techniques are expedient
• is capable of explaining how visualisation can make it easier to understand large amounts of data
• is capable of explaining typical limitations in the visualisation of complex data sets
• is capable of explaining what methods can be used to visualise different types of data

Skills

The student is capable of:

• identifying the properties of a data set and deciding what visualisation method is most expedient
• evaluating whether visualisation will make it easier to understand a data set, and what method(s) will give the best result
• using specific tools to create visualisations
• using visualisation as a tool

General competence

The student is capable of:

• using visualisation as a tool for understanding and communicating complex contexts