Examination arrangement

Course content

This is a course in quantitative methodology designed for professional education. The course prepares for design, data collection, and analysis of quantitative data. It combines theory and practical analysis of data using SPSS. Research ethics are dealt with in different parts of the course also privacy requirements. The course covers challenges related to operationalization, population, sample and generalization and various statistical analysis methods are reviewed.

Learning outcome

Knowledge

The candidate

• can assess the strengths and weaknesses of various statistical methods
• can apply various statistical methods to empirical data
• has knowledge of statistical concepts and analysis techniques and can handle different and complex methodological questions related to validity and generalization

Skills

The candidate

• can prepare survey inquiries and conduct analyses of quantitative data sets

General competence

The candidate

• has the competence to carry out smaller research projects, which involve using quantitative methods, write scientifically about the project and the results and be able to use their skills to tutor candidates who use quantitative methods.
• has the competence to assess the quality of research based on quantitative data

Learning methods and activities

The course is block-scheduled with lectures, discussions and work with statistical data on SPSS. Participants may use their own dataset or data provided by the course. The course will be practically oriented through analysis of own or borrowed data on SPSS. The lectures will to a large extent be based on exemplary experiences from our own analysis, combined with literature. The teaching will build up understanding and achieve knowledge goals through practical work with analysis, combined with supervision and lectures. The teaching will make little use of mathematics and practical arithmetic as basis for understanding. If the course has English-speaking students, the teaching will be in English. Assignments can be submitted in Norwegian or English.

Compulsory assignments

• Obligatory attendance 80%

Further on evaluation

Individual paper. Assessments are based on submission of a paper with 10-12 pages based on analysis of an empirical example from own or borrowed dataset.

Text submitted for assessment in the required academic coursework may be included in the thesis in revised form.

For a retake of a failed exam, the candidate can submit a revised version of a previously submitted text in the course. If the submission is a revised version of a previously submitted text, this must be clarified in the text.

Specific conditions

Recommended previous knowledge

The course is an introductory course and requires no prior knowledge of quantitative methodology.

Required previous knowledge

Master's degree or equivalent university degree, where PhD students will be given first preference for admission. Admission restrictions*: The course is limited to a of maximum 25 students, where 6 spots are reserved for applicants from other institutions affiliated with NorTED (www.nor-ted.com). If there are less than 5 applicants, the Department of Teacher Education reserves the right to cancel the course. * Applicants will be ranked based on the following criteria and deadline for applications can be found here: https://www.ntnu.edu/ilu/phd-courses

Course materials

Johannessen, A. og P. A. Tufte (2022): Introduksjon til IBM SPSS statistics. Oslo: Abstrakt forlag

Ringdal, K. (2018). Enhet og mangfold. Samfunnsvitenskapelig forskning og kvantitativ metode. Bergen: Fagbokforlaget.

The participants needs to have PC/MAC with latest version of IBM SPSS.