Forberedelse til masteroppgaven - kvantitativ metode

Master Thesis Preparation Workshop - Quantitative Methods is designed for students who want to use quantitative methods in their master thesis. The course aims at giving students hands on experiences and the opportunity to learn more about how various quantitative designs can be used in social science research. Through acquiring a deeper understanding and broader overview of common quantitative techniques, students will be able to critically evaluate social science research and analyse how individuals develop over time, how social policy relates to comparative social inequalities and study reform effects.

In an applied manner and starting from a basic competence level, students will learn about extensions and alternatives to ordinary linear regression as well as longitudinal/mixed models and counterfactual/experimental approaches. The course also teaches advanced data manipulation, variable coding and applied analysis techniques using Stata programming code. Students will receive individual guidance, appropriate to their needs, on research questions and data that they are considering for their master thesis.

The course will be given in English to help Norwegian students understand international research papers and facilitate participation from international students. Individual guidance can be given in Norwegian.

The course will be offered provided that a sufficient number of students enrol.

Students taking the Master`s Programme in Applied Social Sciences or Master i sosialfag should have completed one of the courses SFF4110 or SIW4210. Applicants from other master's degree programmes should have completed and passed quantitative methodology, worth a minimum of 5 ECTs.

After completing the course, student should have the following overall learning outcomes defined in terms of knowledge, skills, and general competence:

Knowledge

The student has

• advanced knowledge about different quantitative designs and data and variable formatting.
• advanced knowledge about the use of different regression models to analyse social science topics.
• broad knowledge about different quantitative analysis techniques and how to interpret their results.
• broad knowledge about the possibilities and limitations of various statistical procedures

Skills

The student is capable of

• understanding quantitative research articles and their methodological strengths and weaknesses.
• choosing appropriate analysis techniques given specific research questions and data.
• working independently with practical data preparation, analysis, and interpretation of quantitative data.
• using the statistical tool Stata for research purposes
• presenting statistical results in assignments and articles

General competence

The student is capable of

• applying skills in quantitative method in new areas to conduct job assignments and projects.
• critically assessing results from different research designs and from different types of statistical analyses
• Interpreting and communicating empirical results in an appropriate manner.

The course consists of lectures, seminars and group supervision on campus, and e-lectures. The main emphasis is on student active teaching in the form of workshops.

The following coursework requirement must be approved in order for the student to take the exam:

• Coursework 1: Individual project description (approx. 1-3 pages). Individual supervision (around one hour per student) is offered in connection with the prosject description.

The purpose of the compulsory activity is to develop a clear and feasible research question and to reflect on relevant theoretical and methodological choices, in order to support further work on the term paper and facilitate the process towards the master’s thesis.

The coursework must be completed and approved by the given deadline for the student to take the exam. If the coursework requirement has not been approved, the student will be given one opportunity to submit an improved version by a given deadline.

The exam in the course is an individually written term paper in article format. The article must have a scope of 10 pages (+/- 10 percent). Font and font size: Calibri 12 points. Line spacing:1,5.

Students awarded a fail grade are given one opportunity to submit an improved version of the article for assessment.

All aids are permitted, as long as the student follows the rules for examinations, source use and referencing, and OsloMet's guidelines for using artificial intelligence (AI) in student assignments.

Grade scale A - F.

At least 25% of the exam papers will be assessed by two examiners. The remaining papers are assessed by one examiner. The grades awarded for the papers assessed by two examiners form the basis for determining the level for all the exam papers.

Mats Lillehagen and Therese Saltkjel