ASOK22210U Cancelled Visual Sociology

Volume 2024/2025
Content

This course introduces students into theories, empirical research and interdisciplinary qualitative and mixed methods approaches to the study of visual sociology. Drawing on interdisciplinary theories and methods in visual and cultural studies, media and digital communication, narrative, gender studies, and discourse analysis, this course will critically investigate how images are constructed and spread in digital publics and news media, among policy makers and in globalized arenas of affective politics, policy-making, and protest. Strategies of visual persuasion, visual storytelling, and the transformative ‘power of images’ have been studied by media theorists, art historians and by empirical analysts of gender, culture, media, political discourse and transnational social movements. Only lately have sociologists started to conduct visual analysis. We trace how journalists, bloggers, artists, indigenous and BIPoC activists or non-profit organizations as well as critical writers and gender theorists try to challenge dominant images and visual representations, and we investigate how cultural codes, familiar stories and specific stereotypes shape the boundaries of democracy and public participation. This course is fairly empirical and it requires students to hold in-class presentations and written assignments throughout the semester and conduct their own empirical Portfolio paper analysis guided by interdisciplinary theories and methods for visual analysis. Students will learn to analyse visuals using a variety of different methods including ethnography for the study of face-to-face publics, and comparative analysis to study digital media and (trans-)national public spaces.

Learning Outcome

Knowledge:

The course will provide the students with knowledge of

- the core sociological research literature within the thematic field of the course, and

- familiarity with the recent literature on visual sociology including interdisciplinary research on visuals in visual theory and art history, visual culture, gender, media studies and digital media, narrative and discourse studies. 

 

Skills:

Students will have trained their ability to

- compare and contrast key theoretical perspectives that are central to the thematic field of research within the course

- identify significant international and interdisciplinary developments in research on visual sociology.

- apply and critically discuss key theoretical concepts within the thematic field of the course

- review and reflect on the interdisciplinary scientific literature on visual sociology acquiring insights into a number of different disciplines and their conceptualization of the themes we discuss as well as their state of the art. 

 

Competences:

Further, students should also be able to

- assess and discuss practical relevance of their analysis for key actors, issues, and problems within and across the methodological and thematic fields addressed by the course.

Competencies:

In carrying out the presentations, projects, and written assignments students demonstrate that they have acquired competencies that allow them to independently

- identify and analyse empirical cases and settings for research on the themes of the course.

Readings include peer-reviewed journal articles, book chapters, NGO and civil society groups’ publications, literary narratives and digital media storytelling, newspaper articles and videos. Students are required to read approximately 1000 pages. Students are also expected to choose supplementary reading materials for their presentations, projects, and written assignments (approximately 300 pages).

Lectures, class discussions, student presentations, exercises and written assignments based on the readings. The presentations include project work (either individually or in groups). Students are expected to contribute actively to discussion of core theoretical-analytical tools as well as the more specific analytical examples and case studies. In their written assignments, including the final paper assignment, students are expected to identify their own analytical questions and demonstrate their capacity to critically assess and analyse empirical data based on the examples and case studies we discuss in class. Students should also expect to review literature and assess empirical data besides the course texts.
  • Category
  • Hours
  • Lectures
  • 48
  • Total
  • 48
Oral
Collective
Credit
7,5 ECTS
Type of assessment
Written 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.
Aid

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
Criteria for exam assesment

Please see the learning outcome