Education and social inequality
Course content
The purpose of the course is to familiarise students with newer sociological research in the area of education with a focus on social inequalities in education and the organisation of the education system. The course is structured in two parts. In the first part, we consider the theoretical perspectives and empirical evidence around how social background, ethnicity, and gender shape educational outcomes. In the second part, we read empirical research articles on the importance of how the education system is designed and organised. Key substantive topics, which mirror contemporary concerns found in education systems, include: school choice policy and strategies, educational decision-making at different points of the education trajectory and factors shaping this, and the role of teachers, peers and other classroom dynamics. We consider both the qualitative and quantitative research traditions and how they inform educational policies.
Please note: If you prior have signed up for the course:
* ASOB16208U Sociology of Education
You cannot follow this course as they are overlapping in topics.
The course is open to:
- Exchange and Guest students from abroad
- Credit students from Danish Universities
Full-degree students enrolled at the Faculty of Social Science, UCPH
- Master Programme in Social Data Science
- Bachelor and Master Programmes in Psychology
- Master Programmes in Anthropology
- Master programme in Global Development
-
Master Programmes in Economics
Specialisation line/course package:
Welfare, inequality, and mobility
Knowledge:
- How different education systems are organised and how changing priorities within education affect these structures;
- What different theoretical and conceptual resources sociologists who study education draw on;
- How qualitative and quantitative methods can be used to address different research questions in the field of education.
Skills:
- Review and apply different theory and empirical studies to different contemporary educational problems and questions.
Competences:
- Critically evaluate the social mobility potentiality of the education system;
- Critically evaluate educational policies based on empirical research findings;
- Articulate why a sociological lens can offer critical insights into processes, outcomes and the potentiality of education.
Key readings will be journal articles, books chapters, and short policy texts - made available on Absalon.
Have attended some research methods and sociology courses
Students will comment on each other’s informal inputs during lectures.
When registered you will be signed up for exam.
- Full-degree students – sign up at Selfservice on KUnet
- Exchange and guest students from abroad – sign up through Mobility Online and Selfservice- read more through this website.
- Credit students from Danish universities - sign up through this website.
The dates for the exams are found here Exams – Faculty of Social Sciences - University of Copenhagen (ku.dk)
Please note that it is your own responsibility to check for overlapping exam date.
- ECTS
- 7,5 ECTS
- Type of assessment
-
Home assignment
- Type of assessment details
- The students are required to formulate their own exam questions
based on pre-defined guidelines provided by the teacher. Students
will receive the exam guidelines for formulating exam questions
during the ongoing semester. The teacher is required to provide at
least two exemplary exam questions that adhere to the guidelines.
The exam can be written individually or in groups of max. 4 students.
Length of the exam is 10 pages + 5 pages pr. extra group member. - Examination prerequisites
-
To get qualified to the exam, the students must have completed a classroom presentation.
- Aid
- All aids allowed
The Department of Sociology prohibits the use of generative AI software and large language models (AI/LLMs), such as ChatGPT, for generating novel and creative content in written exams. However, students may use AI/LLMs to enhance the presentation of their own original work, such as text editing, argument validation, or improving statistical programming code. Students must disclose in an appendix if and how AI/LLMs were used; this appendix will not count toward the page limit of the exam. This policy is in place to ensure that students’ written exams accurately reflect their own knowledge and understanding of the material. All students are required to include an AI declaration in their exam submissions regardless of whether they have used generative AI software or not. This declaration should be placed as the last page of the exam submission. Please note that the AI statement is not included in the calculation of the overall length of your assignment. The template for the AI statement can be found in the Digital Exam system and on the Study Pages on KUnet under “Written exam”. Exams that do not declare if and how AI/LLMs were used will be administratively rejected and counted as one exam attempt.
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
- Exam period
-
Exam information:
The examination date can be found in the exam schedule here
The exact time and place will be available in Digital Exam from the middle of the semester.
- Re-exam
-
Reexam info:
The reexamination date/period can be found in the reexam schedule here
Same as the ordinary exam.
Note! This is an elective course. We can only guarantee that the exam can be taken during the 3 immediate exam periods after the course has ended.
Criteria for exam assessment
See learning outcome
- Category
- Hours
- Lectures
- 42
- English
- 42
Kursusinformation
- Language
- English
- Course number
- ASOA22102U
- ECTS
- 7,5 ECTS
- Programme level
- Bachelor
Full Degree Master
- Duration
-
1 semester
- Placement
- Spring
- Studyboard
- Department of Sociology, Study Council
Contracting department
- Department of Sociology
- Department of Anthropology
- Department of Psychology
- Social Data Science
- Department of Economics
Contracting faculty
- Faculty of Social Sciences
Course Coordinators
- Jesper Fels Birkelund (6-6e647836353842636e776f706b306d7730666d)
- Claire Maxwell (2-717b4e817d713c79833c7279)
Are you BA- or KA-student?
Courseinformation of students