ACIT4090 Globalisation of Technology Course description

Information and communication technology (ICT) serves as a central enabler and driving force behind globalisation processes. As global dynamics evolve, the ICT field continuously adapts, fostering more nuanced understandings of culture and innovative methodologies for exploring, analysing, and engaging with these complexities. This course provides an in-depth exploration of cultural differences and dimensions shaped by ICTs, equipping students with essential knowledge and skills in areas such as cross-cultural collaboration, innovative thinking, knowledge-sharing, and conflict resolution. These competencies will prepare students to navigate and contribute effectively to a globalised, interconnected future.

This course provides in-depth knowledge of quantitative design and statistical analysis that can be used in the students’ master’s theses, the possibilities and limitations of different quantitative designs, knowledge of different sources of data and the social science research tradition’s quality requirements for studies based on statistical analysis.

The course includes in-depth knowledge of cross-sectional design, time design, experiments and the survey method. Students will also acquire in-depth knowledge of the factors that can affect the validity and reliability of a study, as well as skills that are necessary to assess such factors. They will also learn and, not least, practise using univariate, bivariate and multivariate analyses.

The course will pay particular attention to regression analysis, and students will acquire in-depth knowledge of and skills in the use of regression-based analysis through lectures, online resources and seminars. The course aims to enable students who choose a quantitative design to use regression analysis in their master’s theses.

Language of instruction is Norwegian.

None.

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

Knowledge

The students have

• in-depth knowledge of quantitative designs and which types of knowledge they can contribute
• advanced knowledge of different methods used to generate/obtain empirical material, such as surveys and register data
• in-depth knowledge of quality assessment in the quantitative tradition
• insight into the possibility of generalising the results of quantitative studies
• advanced knowledge of the dissemination of results
• in-depth knowledge of regression-based analysis/statistical analysis

Skills

The students can

• engage in methodological reflection on the relationship between research questions and design
• develop a research design for their master's thesis that is appropriate to their research question
• apply statistical analysis techniques and interpret the results they produce
• develop statistical analysis models based on theory and empirical data
• engage in methodological reflection on the relationship between research design and knowledge claims
• acquire in-depth knowledge of the methodological approach chosen for their master’s degree project
• engage in methodological and critical reflection on other research literature
• evaluate research ethics issues in connection with their master's degree project
• evaluate which questions can be empirically studied

General competence

The students

• are familiar with and able to reflect on different consequences of conducting research
• can apply ethical discretion in relation to their own role as researchers and how their participation in research can intervene in people's lives
• are familiar with and are able to comply with ethical guidelines such as correct and complete source information, informant anonymisation, confidentiality and researcher responsibility

Teaching takes place in the form of lectures, statistics program exercises, e-lectures and assignments that the students work on independently and receive supervision on via e-based resources.

The project report counts 100% of the final grade and must follow these word limits, including a +/- 20% margin:

• Individual submission: 6 000 words (acceptable range: 4800-7200 words)
• Two students collaborating: 9 000 words (acceptable range: 7200-10 800 words)
• Three students collaborating: 12 000 words (acceptable range: 9 600-14 400 words)

Groups larger than three students are not permitted. Detailed guidelines for the project report will be provided at the start of the course. The exams can be appealed.

New/postponed exam

In case of failed exam or legal absence, the student may apply for a new or postponed exam. New or postponed exams are offered within a reasonable time span following the regular exam. The student is responsible for registering for a new/postponed exam within the time limits set by OsloMet. The Regulations for new or postponed examinations are available in Regulations relating to studies and examinations at OsloMet.

The exam in the course is

A multiple-choice school examination. Counts 30 percent of the final grade.

A individual course paper with a scope of 10 pages (+/- 10 per cent). Font and font size: Calibri 12-point font. Line spacing: 1.5. Tables and figures are in addition. Course paper counts 70 percent of final grade.

A students who receive a fail grade of the semester assignment are given one opportunity to submit an improved version of the semester assignment for assessment.

Both exams must be passed for the overall assessment to be passed.

School examination: No aids are allowed.

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

Grade scale A-F.

The exam papers are assessed by one internal and one external examiner.

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