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Kursusbeskrivelse
Kursusnavn (dansk):Project Cluster: Analysis of Qualitative Data: An Introduction to Disaster Research 
Kursusnavn (engelsk):Project Cluster: Analysis of Qualitative Data: An Introduction to Disaster Research 
Semester:Efterår 2010 
Udbydes under:cand.it., digital design og kommunikation (ddk) 
Omfang i ECTS:0,00 
Kursussprog:Engelsk 
Kursushjemmeside:https://blog.itu.dk/KF19-E2010/ 
Min. antal deltagere:
Forventet antal deltagere:12 
Maks. antal deltagere:20 
Formelle forudsætninger: At least one semester of a M.Sc.'s program completed. Students must have sufficient background in media and communication. Prior experience in qualitative data collection and analysis would be useful but not required.  
Læringsmål:After the course students should be able to:

* Conduct an appropriate background literature search to gain a deep understanding of theoretical and empirical work relevant to the data at hand
* Evaluate qualitative data
* Transcribe qualitative data
* Prepare qualitative data for analysis
* Use qualitative data analysis software
* Conduct a broad open coding of data
* Conduct a focused coding of data based on elicited themes
* Identify important outcomes and contributions
* Write up an analysis based on existing data and prepare such an analysis for an internal report or an external publication 
Fagligt indhold:The outcomes of this course will be useful to M.Sc. students who expect to use qualitative data for their masters theses.

Students will get introduced to a focused overview of the role of IT in disaster situations and a broader discussion of the role of qualitative research methods in studying such a topic. Students will learn the basic theory and practices governing qualitative research methods in data collection and data analysis. Data analysis and write up will be the focus of this course.

The course will be primarily based on an existing real data set collected by the instructor and colleagues in New Orleans after Hurricane Katrina in 2006 and 2007, focusing on how small business owners were coping with the disaster and recovery. This unique data set consists of pre-transcribed audio recordings of interviews with the same people twice in the course of a year, photographs and field notes.
 
Læringsaktiviteter:

The class will be primarily structured as a seminar with the first few meetings conducted as lectures to introduce the students to relevant material and the rest of the semester class meetings will be conducted as involved discussions around the data analysis process.

Students will learn some transcription techniques, but the main bulk of the course will be focused on preparing, organizing and analysis of the existing data set. The majority of the work will be done using qualitative coding software individually.

Class sessions will be used for working through the coding process, diagramming and sketching themes, discussing ideas and processing existing codes to develop over-arching themes. Students will learn open and focused coding, the use of inter-rater reliability assessments and data management skills. Finally, students will learn how to present qualitative data in write-ups and reports.

Class examination will be conducted in the form of a final report written on an agreed upon theme emerging from the data and using the data as supporting evidence for the argument. Each student will be free to select the theme they find most interesting and to address that theme in their report. 

Eksamensform og -beskrivelse:X. experimental examination form (7-scale; external exam), 7-trins-skala, Ekstern censur

Submission of Written Work: 08-12-2010
Oral Examination: 03-01-2011 & 04-01-2011
 

Litteratur udover forskningsartikler: The course will be based on two required books:
Emerson, R. M., Fretz, R. I., & Shaw, L. L. (1995). Writing ethnographic fieldnotes. Chicago: University of Chicago Press.
AND
Lofland, J., Snow, D., Anderson, L., & Lofland, L. H. (2005). Analyzing social settings: A guide to qualitative observation and analysis. Belmont, CA: Wadsworth Publishing. 
 
Afholdelse (tid og sted)
Kurset afholdes på følgende tid og sted:
UgedagTidspunktForelæsning/ØvelserStedLokale
Mandag 13.00-16.00 Forelæsning ITU