GRA 6141 Methodology for Communication and Digitalization Research
GRA 6141 Methodology for Communication and Digitalization Research
Solid methods are the foundation for solid science. In this course we focus not only on how to conduct research, but also increase your awareness of why certain methods and tests are relevant, and how they relate to your research question. The course will help you reflect on the different qualitative and quantitative methods that are most commonly used in digital communication research. You will learn how to choose the method best fitting to your research question and design. We will develop a portfolio that you can use as a resource when conducting research projects in other courses, or in your thesis.
The course will cover most of the basic statistical analyses, starting with data handling and recoding, and covering experimental statistics (ANOVA, ANCOVA) and statistics fitting survey research (regression). In addition to the quantitative approach, this course will also cover qualitative research methods such as interview and coding, and analysis of digital and social network data. Upon completion of this course, students will be able to conduct quantitative and qualitative research independently.
At completion of this course, students should have knowledge of various research methods in the domain of communication and digitalization such as
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Experimental research design
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Single- and multi- source regression designs
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Diary studies
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Qualitative analysis – interviews and case studies
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Ethnography methods
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Network designs
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Online platform research
After this course, students should be able to
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Prepare datasets for statistical analysis
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Apply basic statistical techniques, specifically;
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Basic regression analysis
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ANOVA, ANCOVA
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Moderation and mediation analysis
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Multilevel analysis
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Understand core considerations for qualitative analysis
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Interview
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Making code books
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Ethnographies
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Social Network Analysis
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Be able to read and modify r scripts
After the course students should be able to
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Critically assess and reflect on various research methods
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Compare research methods and choose the method best fitting to answer the research question
- Introduction to the course: Different methods in the field and how to critically assess them
- Data preparation and critical design decisions: Data quality, Variable type, Experimental vs. non-experimental designs, Power and reliability, Replications, Code books, Response rates
- Experimental statistics: T-tests (comparisons of two groups), Anova, Ancova, Effect sizes
- Regression analysis: Basic: Regression analysis 3, Moderation analysis, Mediation analysis, Use of control variables
- Diary studies and interventions: Diary study methods, Multilevel designs
- Consolidation session 1: What test in what situation? Recap
- Library session on paper writing: Systematic literature review
- Qualitative analysis: Interviews and coding, Coding at different levels, case study methods
- Digital ethnographies and case study methods:
- Scraping and analyzing social media/platform data: Platform choice and data selection, Scraping and analysis
- Social Network Analysis: Social media, bibliometric representation
- Consolidation session 2. Recap
The course will consist of
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Lectures including interactive exercises
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Participation in a discussion board that helps to critically reflect on design questions
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Weekly excercises with video support that will build up to the portfolio (see examination)
The students will also obtain an understanding of information search strategies. Including:
- Acquaintance with methods for information, harvesting and search techniques
- Know what a critical literature review is and how this type of articles may be searched for and used
- Critical evaluation of sources
Please note that while attendance is not compulsory in all courses, it is the student’s own responsibility to obtain any information provided in class.
This is a course with a portfolio assessment. The portfolio consists of a selection of weekly assignments, and will be graded in its totality at the end of the course.
At re-sit all exam components must, as a main rule, be retaken during next scheduled course.
All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have specific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.
Disclaimer
Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.
| Assessments |
|---|
Exam category: Submission Form of assessment: Written submission Weight: 90 Grouping: Individual Duration: 1 Semester(s) Comment: A paper consisting of excercises that are completed throughout the semester. Exam code: GRA 61411 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
Exam category: Submission Form of assessment: Written submission Weight: 10 Grouping: Group/Individual (1 - 3) Duration: 1 Week(s) Comment: Library assignment Exam code: GRA 61411 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
| Activity | Duration | Comment |
|---|---|---|
Teaching | 24 Hour(s) | Lectures |
Student's own work with learning resources | 48 Hour(s) | Readings and instructional videos |
Examination | 82 Hour(s) | Writing a portfolio consisting of exercises and reflections corresponding to the weekly class topics, as well as improving the writing based on lecturer feedback |
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.