This presentation starts with brief history of CAQDAS (Computer Assisted Qualitative Data Analysis) and identifies the main features of the software. It looks at the pros and cons of the most popular programs and then examines the main activities in establishing and analyzing a project in the software

Gibbs, Graham R.

English

University of Huddersfield Repository

University of Huddersfield RepositoryGibbs, Graham R.Computer Assisted Qualitative Data Analysis: NVivo, MAXQDA, Atlas.ti, QDAMiner, HyperResearchOriginal CitationGibbs, Graham R. (2014) Computer Assisted Qualitative Data Analysis: NVivo, MAXQDA, Atlas.ti, QDAMiner, HyperResearch. In: IfM’s 21st Annual Research Methodology Workshop., 10-11th April 2014, Institute for Manufacturing, University of Cambridge, UK. This version is available at http://eprints.hud.ac.uk/22856/The University Repository is a digital collection of the research output of theUniversity, available on Open Access. Copyright and Moral Rights for the itemson this site are retained by the individual author and/or other copyright owners.Users may access full items free of charge; copies of full text items generallycan be reproduced, displayed or performed and given to third parties in anyformat or medium for personal research or study, educational or not-for-profitpurposes without prior permission or charge, provided:• The authors, title and full bibliographic details is credited in any copy;• A hyperlink and/or URL is included for the original metadata page; and• The content is not changed in any way.For more information, including our policy and submission procedure, pleasecontact the Repository Team at: E.mailbox@hud.ac.uk.http://eprints.hud.ac.uk/Computer Assisted Qualitative Data Analysis NVivo, MAXQDA, Atla s.ti, QDAMine r, Hype rRe se a rc h  Graham R Gibbs, University of Huddersfield 1 Origins  Text analysis  General Inquirer (content analysis)  Word processors and desktop computers 1984 onwards  Dedicated programs - Code-and-retrieve  The Ethnograph  Hypersoft Code-and-retrieve  Coding - mark text with code  Code list (coding frame)  Retrieve - show all text coded the same way.  Some complex retrievals - text coded with two codes. Current best selling programs  NVivo (Windows, Mac in beta)  Atlas.ti (Windows, iOS, Android, Mac in beta)  MAXQDA (Windows, Mac, iOS, Android)  HyperRESEARCH (Windows, Mac)  QDAMiner (Windows)  But still small companies cf. Microsoft.  NVivo sold 500,000, vs Millions for Office QSR NVivo  De ve lo p e d  b y Lyn a nd  To m Ric ha rd s in Austra lia .      Sta rte d  a s NUD.IST in 1980s. No w NVivo  v. 10.  Pub lishe d  b y QSR  http :/ / www.q srinte rna tio na l.c o m/ d e fa ult.a spx 5 6 NVivo vide o  http :/ / yo utu.b e / o e lXFnJ-7Ms 7 NVivo info   Mo st c o mmo n in UK  Ma ny unive rsitie s ha ve  site  lic e nc e   It’ s a ll in the re , so me whe re   But c a n ta ke  a  lo t o f c lic ks  So me  d o n’ t like  re stric te d  vie w o f c o d ing  strip e s  Ha s hie ra rc hic a l c o d ing  8 Atla s.ti  G e rma n d e ve lo p e r  Eng lish ve rsio n  Tho ma s Muhr    Sc ie ntific  So ftwa re  De ve lo pme nt G mb H  http :/ / www.a tla sti.c o m/ ind e x.html  9 Atla s.ti 10 Atla s.ti info   First to  inc lud e  d ia g ra ms/ c ha rts  We ll inte g ra te d  with d a ta  a nd  c o d ing   Co nsta nt vie w o f c o d ing  b ra c ke ts  Que ry to o l c a n b e  e xte nd e d  with G REP.  No  c o d e  hie ra rc hy 11 MAXQDA  G e rma n c o mp a ny  Eng lish ve rsio n  Ud o  Kuc ka rtz    VERBI G mb H  http :/ / www.ma xq d a .c o m/  12 MAXQDA 13 MAXQDA  Be st use r inte rfa c e   Stro ng  o n mixe d  me tho d s re se a rc h  Fo ur p a ne  d isp la y e a sy to  se e  d a ta   Alwa ys visib le  c o d ing  b ra c ke ts  Hie ra rc hic a l c o d e s  14 Ge tting  he lp  CAQDAS Ne two rking  p ro je c t, U. Surre y http :/ / www.surre y.a c .uk/ so c io lo g y/ re se a rc h/ re se a rc hc e ntre s/ c a q d a s/   Jisc Ma il d isc ussio n list (Q UAL-SOFTWARE@ JISCMAIL.AC.UK)  Instruc tio ns fo r a d va nc e d  use s  Online  QDA http :/ / o nline q d a .hud .a c .uk/ ind e x.p hp   Fo r info  o n b a sic  q ua lita tive  d a ta  a na lysis (& G ra ha m G ib b s Yo uTub e  Cha nne l http s:/ / www.yo utub e .c o m/ use r/ G ra ha mRG ib b s)  Links to  so ftwa re  we b site s a nd  tuto ria ls  So ftwa re  we b site s  Tuto ria ls (a lso  o n Yo uTub e )  He lp  syste m (a lso  fro m the  p ro g ra m)  Disc ussio n lists (a nswe re d  b y sta ff) 15 Books  Le wins, A. a nd  C . Silve r (2007). Using  So ftwa re  in Qua lita tive  Re se a rc h: A Ste p -b y-Ste p  Guide . 2ND Ed . Lo nd o n, Sa g e . (Ne w e d . Out so o n)  Ba ze le y, P. & Ja c kso n, K. (2013). Qua lita tive  Da ta  Ana lysis with NVivo . Lo nd o n, Sa g e .  Frie se , S. (2012)Qua lita tive  Da ta  Ana lysis with Atla s.ti. Lo nd o n, Sa g e .  Kuc ka rtz, U. (2014) Qua lita tive  Te xt Ana lysis. Lo nd o n, Sa g e .  G ib b s, G . R. (2007) Ana lysing  Qua lita tive  Da ta . Lo nd o n, Sa g e .   16 Ge tting  sta rte d 17 Sourc e s Doc ume nt type s Ca n a dd:  Wo rd  d o c ume nts (d o c , d o c x) a nd  e d ita b le   RTF file s (.rtf) a nd  e d ita b le   PDF file s (.p d f)  Aud io  file s (.mp 3, .wa v)  Mo vie  file s (.wmv, .mp 4)  We b  p a g e s (a s p d f via  NCa p ture  in IE o r Chro me )  Surve y d a ta  (sp re a d she e t fo rma t)  So c ia l me d ia  (Fa c e b o o k, Twitte r in NVivo ) 18 Se t up a  proje c t  Ca lle d  He rme nutic  Unit in Atla s.ti  NVivo  ke e p s so urc e s in o ne  file   MAXQDA, Atla s.ti ke e p s so urc e s e xte rna l  Vid e o  file s b e st ke p t e xte rna l 19 Wha t CAQDAS c a n do  Coding  Retrievals  Queries  Memos  Search (text and codes)  Charts  Link with quants data  Textual analysis tools  Relations  Literature review  GIS  20 Va ria ble  da ta   Also  c a lle d  a ttrib ute s  Atta c he d  to  c a se s (no rma lly = p e o p le )  E.g . o c c up a tio n, g e nd e r, a g e , b irth to wn  i.e . c a te g o ric a l d a ta  o r me a sure me nts  So rt o ut c a se s 21 Ana lysis 22 Types of Qualitative analysis  Ethnography  Analytic Induction  Content analysis.  Thematic analysis  Grounded Theory  Phenomenology  Narrative and biography  Conversation analysis  Discourse analysis  23 Induction vs. Deduction  Induction - theories and explanations derived from the data. Data led  Deduction - theories and explanations derived from theories and then tested against the data. Theory led.   Most qualitative analysis approaches are inductive (e.g. Grounded Theory, Analytic induction).   But we can also test theories against our data.  Software supports both approaches  24 Thematic Coding Grounded Theory (Glaser and Strauss + Corbin + Charmaz)  Interpretative Phenomenological Analysis (Jonathon Smith) Template analysis (Nigel King) Framework analysis (Ritchie and Lewis)  All are types of thematic analysis.  25 Coding  in NVivo, Atla s.ti, MAXQDA  Se le c t te xt, the n  Dra g  a nd  d ro p   Fa st c o d ing  b a r (NVivo  o nly, with me nu o f no d e s)  Me nu a nd  d ia lo g  b o x (c a n c o d e  a t multip le  c o d e s)  Dra g  a c ro ss time -line  to  se le c t in a ud io  & vid e o   Dra g  a n a re a  to  se le c t in ima g e s  Se le c t a  c e ll in surve y d a ta   26 Coding supports 2 forms of analysis Retrieval Using the coding frame 27 1. Retrieval Retrieve all the text coded with the same label = all passages about the same phenomenon, idea, explanation or activity - Literally cut and paste Used envelopes/files - Now done using software – retrieval very fast. Enables cross case comparison on same theme. 28 2. Using the coding frame Use the list of codes to examine further kinds of analytic questions, e.g.   relationships between the codes (and the text they code)  grouping cases Hierarchical codes in NVivo and MAXQDA, Coding families in Atlas.ti  29 Coding hierarchy  Codes can be arranged in a hierarchy e.g. with these codes from a study of friendship  Close, generalised friendships  Sporting friendships  Sports club members  Work friends  Making new friends - same sex  Making new friends - different sex  Losing touch with friends  Becoming sexual relationships  30 Example code hierarchy Friendship types  Close, generalized  Sporting  Club  Non-club Work Changes in Friendship Making new friends  New same sex friends  New different sex friends  Losing touch  Becoming sexual relationships 31 Memos  Theorizing and commenting about codes as you go along  Notes to yourself  “… the theorizing write-up of ideas about codes and their relationships as they strike the analyst while coding… it can be a sentence, a paragraph or a few pages… it exhausts the analyst’s  momentary ideation based on data with perhaps a little conceptual elaboration.”   Glaser, B.G. (1978) Theoretical Sensitivity: Advances in the methodology of grounded theory. Mill Valley CA: Sociology Press.  32 An Example Memo Word of mouth was mentioned by Harry as important for him in searching for work. Several other respondents talked about this as a method they have used. Two thoughts occur to me.  To what extent is this a separate method of looking for work, tapping into a network outside the formal one of job centres, agencies etc. or does it overlap? E.g. is some of the word of mouth information about the formal job finding agencies?  Does it refer to a specific kind of network - mates and relatives finding work for those looking for it, or is it simply a passing on of information that could have been found by those looking in newspapers ads etc? Above all it raises issues about networking as a way of finding work. Is this an important method? Is it effective? Is it more important in certain areas of work than others? (e.g. in manual work.) Do those with wider social networks have more success in finding work this way? Graham Gibbs Friday, April 28, 2000  33 Descriptive vs Analytic/theoretical  Descriptive  Just what the people said  What happened  Their terms  Analytic  Use social science theory  Groups codes together  Use terms the respondents don’t or wouldn’t 34 Example of coding 35 ‘Loss of physical co-ordination’, ‘Togetherness’, ‘Doing for’, ‘Resignation’, ‘Core activity’ ‘Dancing’,  ‘Indoor bowling’,  ‘Dances at works club’, ‘Drive together’ Descriptive codes ‘Joint activities ceased’, ‘Joint activities continuing’ Categories Analytic codes Example showing coding marks 36 

Computer Assisted Qualitative Data Analysis: NVivo, MAXQDA, Atlas.ti, QDAMiner, HyperResearch

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