TY - BOOK AU - Lewins,Ann TI - Using software in qualitative research :a step-by-step guide SN - 0761949224 (hbk.) U1 - 005.3 PY - 2007/// CY - Los Angeles, London PB - SAGE KW - Qualitative Research KW - Computer programs KW - Kwalitatieve Methoden KW - Sociaal-wetenschappelijk onderzoek KW - Software N1 - Includes bibliographical references (p. [281]-283) and index; Processes and Tasks in Using Qualitative Software Types of software supporting work with qualitative data What types of software do we categorize as CAQDAS? Which is the 'best' CAQDAS package? Basic functionality and aspects of work in CAQDAS: key similarities Structure of work in CAQDAS packages Data types and format 'Closeness to data' and interactivity Exploring data Code and retrieve functionality Coding schema Data organization Searching and interrogating the database Writing tools Output Making software work for your project Starting points Familiarization . , What the software project represents CAQDAS packages as project management tools The right tools for the job Flexibility in the sequencing of tasks The bits in between Teamwork 2 Data and Their Preparation for CAQDAS Packages Types of qualitative data Incorporating different types of data into the software project Incorporating different types of data into the Young People's Perceptions Project Textual data preparation considerations General guidelines for transcribing data Transcription formats Using rich text features to indicate important aspects of the data Formatting structured data Recognizable units of context: sentences, paragraphs and sections Speaker and topic identifiers What to avoid when transcribing identifiers Naming and saving data files Software-specific textual data preparations Preparing textual data for ATLAS.ti5 Preparing textual data for MAXqda2 Preparing textual data for NVivo? Summary: data preparation issues Comparative comments on data and their preparation for CAQDAS packages 3 Getting Started in Quaiitative Software: Practical Tasks Generic tasks: what can be done before primary data are ready? Task 3.1 creating and naming the project, data files and reports Task 3.2 familiarize yourself with the software Task 3.3 memoing Task 3.4 code creation Task 3.5 experimenting with importing/assigning data Task 3.6 experiment with data Task 3.7 experiment with mapping tools Task 3.8 use or throw away Software-specific variations: getting started with software Exercises in ATLAS.li5 Exercises in MAXqda2 Exercises in NVivo? Summary: reviewing the process of familiarization Comparative comments on getting started with the software 4 Exploration and Text-Level Work Early exploration of text Technological developments and methodological debates Annotation tools: their universal utility Note taking for continuity, neutrality, reflexivity and openness Text search tools: their universal utility The place of content-based searching tools Hyperlinking Generic tasks: exploring data and working at the text level in software Thsk 4.1 Using cosmetic text marking and functional text marking Task 4.2 Annotating text Thsk 4.3 Frequency counts, text searching for words or phrases Task 4.4 Hyperlinking between points in the text Software-specific variations: exploring data and working at the text level Exercises in ATLAS.tiS Exercises in MAXqda2 Exercises in N>^vo7 Summary: early exploration of data Comparative comments on exploring data 5 Qualitative Coding in Software: Principles and Processes What is qualitative coding? How coding works in qualitative software Approaches to coding Generating and using codes Inductive approaches to coding Deductive approaches to coding Combining approaches: the practice of coding using software Summary: using software to support your approach to coding 6 Coding Schemes, Coding Frames Breaking down the data, putting them back together Structures of coding schemes in software Hierarchical systems The functioning of hierarchies in software Non-hierarchical systems What arc the benefits and disadvantages of different structures? Factors which influence approaches to the development of coding schemes Is 'coding scheme' the same as 'theoretical framework*? Drilling down, or building up? Seeing beyond the coding scheme: grouping and combining codes Coding scheme predicaments Working top-down, feeling stuck between tramlines? The 'large* coding scheme: moving on, refining? Coding scheme structures in CAQDAS packages: project examples Speller (2000): 'The relocation of Arkwright* Rich et al. (2006): *Video intervention/prevention assessment (VIA)' Taggart et al. (2004): 'Curriculum progression in the arts* Silver (2002): 'Young People's Perceptions Project' Lewins (2000): 'Older people's needs assessment exercise: focus groups' Gulati (2006): 'Understanding knowledge construction in online courses' Summary: making the most of a coding scheme Comparative comments on coding schemata in CAQDAS packages 7 Coding Tasks in Software Generic tasks: generating and applying codes Task 7.1 Generating codes Task 7.2 Applying existing codes to text Task 7.3 Defining and listing codes Task 7.4 Changing your mind about how data are coded Task 7.S Reorganizing the coding schema Integrating the different aspects of your work Software-specific variations: coding processes in software Exercises in ATLAS.tiS Exercises in MAXqda2 Exercises in NVivo7 Summary: getting started with coding in software Comparative comments on coding functionality and processes 8 Basic Retrieval of Coded Data Purposes and values of basic retrieval Where did I get to last time? Reflexivity and rigour Generic tasks: retrieving coded data Task 8.1 Retrieve all data coded so far Task 8.2 View all codes appearing in one document Task 8.3 Recode data Task 8.4 Overview current coding status Software-specific variations: data retrieval Exercises in ATLAS.tiS Exercises in MAXqda2 Exercises in NVivo7 Summary: basic ways to retrieve coded data Comparative comments on retrieval functionality and processes 9 Managing Processes and Interpretations by Writing Hie importance of writing in conducting qualitative data analysis Writing as a continuous analytic process Forms and purposes of writing Field notes Research journal(s) Analytic or theoretical memos The potential value of software writing tools Generic tasks for using memos Managing your memo system Creating memos Free-standing centralized memos Naming and dating memos Grouping memos Structuring memos Integrating your writing with the rest of your project Linking memos to documents Linking memos to codes Coding your own writing Search the content of a memo Outputting memos Software-specific memo functionality Memos in ATLAS.ti5 Memos in MAXqda2 Memos in NVivo? Summary: flexible writing in software Comparative comments on memo functionality 10 Mapping Ideas and Linking Concepts Theoretical models Adaptive theory and the modelling process Grounded theory and the mapping process Mapping tools: relevant traditions Mapping software packages Mapping in CAQDAS packages: general purposes Limits of CAQDAS mapping tools Possibilities with CAQDAS mapping tools Cautions Generic tasks: mapping and linking Software-specific mapping tools The networking tool in ATLAS.ti5 The mapping tool in MAXqda2 The modeller in NVivo? Summary: mapping functionality Comparative comments on mapping functionality 11 Organizing Data to Known Characteristics The importance of organizing qualitative data Features in data which can be organized Organizing qualitative data in CAQDAS packages Document families' and ^attributes* Differentiating between organizational features and ^conceptual* codes Working incrementally Organizing whole data files Organizing parts of data files Organizing case studies Software-specific variations: data organization Exercises in ATLAS.tiS Exercises in MAXqda2 Exercises in NVivo7 Summary: data organization functionality Comparative comments on data organization 12 Interrogating the Dataset Moving on Different ways to interrogate the database Filtering and simple forms of retrieval Searching for content Code searches as iterative, incremental and repeatable Qualitative cross-tabulations in the form of tables and matrices Interrogating in maps Changing techniques of qualitative data analysis Cautions Generic tasks: searching Searching for content Code searching Generating tabular data Creating signposts from searches Software-specific searching functions Searching and interrogation tools in ATLA3-ti5 Searching and interrogation tools in MAXqda2 Searching and interrogation tools in NVivo7 Summary: reviewing searching and interrogation functionality Comparative comments on searching and interrogating the dataset 13 Convergence, Closeness, Choice Planning for the use of software Convergence of tasks and tools: software as a container for your work Closeness to data: inside software and outside it Working within your comfort zone: focused effective use of software ER -