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Using Atlas-ti to explore qualitative data Libby Bishop and Louise Corti, UK Data Archive, ESDS, University of Essex IASSIST 2004 workshop.

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Presentation on theme: "Using Atlas-ti to explore qualitative data Libby Bishop and Louise Corti, UK Data Archive, ESDS, University of Essex IASSIST 2004 workshop."— Presentation transcript:

1 Using Atlas-ti to explore qualitative data Libby Bishop and Louise Corti, UK Data Archive, ESDS, University of Essex IASSIST 2004 workshop

2 Workshop aims In this workshop we will present an overview of the uses and range of computer assisted qualitative data analysis software (CAQDAS) packages. Focusing on the software Atlas-ti, through hands-on sessions and exercises, participants will be introduced to the particular applications and key functions of the software. The session is intended to be practical, intensive and aims to get participants started with the software by familiarizing them with the initial usage tools, data preparation considerations, importing data into software, 'coding' data (attaching thematic labels to segments of data), searching and retrieval of coded data, use of annotation and memoing tools, and exporting quantitative data. Archived qualitative data from ESDS Qualidata will be used as the data sources

3 largely unstructured mostly text-based: –transcribed interviews –transcribed discussions –field notes –other written documents (e.g. observations and records of meetings etc.) Typical features of data: accounts of experiences, emotions descriptions of changes observations of interactions Nature of qualitative data

4 Interpreting qualitative data Interpretation is involved in both: –data collection –data analysis –so the process is iterative For collected data aim to: –provide coherence and structure to the data –retain original accounts and observations Typical analytic tasks –Defining concepts –Mapping the range, nature and dynamics of phenomena –Creating typologies –Finding associations –Seeking explanations –Developing new ideas, theories or strategies

5 Steps in data analysis efficient management of data! Getting to know your to data - detailed knowledge and sensitive exploration Identifying a thematic framework Coding: Recording your judgement about how chunks of your document are related to an idea, theme, or category –descriptive: storing and sorting data (including classifying variables) –creative: tentative ideas or thinking aloud Categorising Interpreting ability to think abstractly, see patterns and interrogate emerging patterns

6 How can CAQDAS help? Computer-Assisted Qualitative Data Analysis Examples of software: –Atlas-ti –Winmax –NVivo and NUDIST –Qualrus –Decision Explorer Helps you to: –manage data –classify your data –stay close to your data –ask questions of the data

7 " Archiv fuer Technik, Lebenswelt und Alltagssprache translated: archive for "technology, the life world and everyday language". The extension "ti" (pronounced TEE EYE) stands for text interpretation. Project ATLAS (1989-1992) of Technical University of Berlin is the "birthplace" of a first prototype of the software. What does the acronym ATLAS.ti stand for?

8 Why Atlas-ti? market leader alongside QSR products (Nvivo etc) powerful workbench for the qualitative analysis of large bodies of textual, graphical, audio and video data offers a variety of tools for accomplishing the tasks associated with any systematic approach to "soft" data- -i.e., material which cannot be analyzed by formal, statistical approaches in meaningful ways helps to uncover the complex phenomena hidden in your data in an exploratory way offers a powerful and intuitive work environment that is designed to keep you focused on the material itself – to cope with the inherent complexity of the tasks and the data can become expert quite quickly (honest!)

9 Stages Atlas.ti's four predominant strategic modes of operation are encapsulated in the acronym "VISE": –Visualization –Integration –Serendipity –Exploration


11 Some data preparation issues for Atlas-ti what can I import? –Txt; xml; html; pdf; images what about text formatting? –text must be saved as plain text (ascii) with line breaks –this enables the autocoding features –once imported text formatting (e.g bold) is NOT retained what about multi-media formats? –BMP, JPEG, TIFF, Kodak photo CD etc. –WAV

12 Systematic transcription preferable to have across all documents: –consistent layout –speaker tags –line breaks –header with identifier/ other details –checked for typos and other layout errors –ESDS Qualidata provides guidelines on transcription practice confidentiality respected –are data required to be anonymised/ pseudonymised?

13 Interfacing with SPSS Coding of: –face-sheet variables – gender, age etc –other global attributes of the text e.g. document type (eg interview, focus group, diary etc.) output of this function = a complete SPSS syntax file containing variable definitions, a data matrix and some dummy jobs statements: –"case" = usually the interview, but can also be a data segment. –variable = the code –The SPSS syntax output created with ATLAS/ti is plain ASCII which can be edited

14 Collaborative working Multi-authoring functionality Supports co-operative working User management tools –Administrator assignment – SUPER/USER –can assign accounts and relevant privileges for team/classes members –Local area network usage

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