Seminar Recordings on Transcription, CAQDAS and more

Quick post this – just sharing and embedding two recent events I’ve hosted.

The first one form the inspiring, fantastic and highly-recommended CAQDAS Networking project Seminar Series .

North West Social Sciences Doctoral Trianing Centre Seminar Session Recoridng (Feb 2023)

Qualitative Transcription for the 21st Century: combining automated transcription with human interpretation using CAQDAS packages. 

Dr. Steven Wright, Learning and research technologist at Lancaster University, UK

17th CAQDAS webinar in which Dr Steve wright discusses automated transcription with human interpretation using CAQDAS packages.

And one for the Centre for Technology Enhanced Learning in the Dept. Educational Research at Lancaster University for their Show and TEL seminars:

Technologies for qualitative analysis, transcription and mixed methods

Discussion with Steve Wright

Updated tool availalble

UPDATE: December 2021: New tool developed from Tim’s by Charles Weir now available at https://securityessentials.github.io/Teams2NVivo/

Downloading YouTube videos, captions and comments in ATLAS.ti

The scraper also works for Facebook and other social media comment scraping !

Background

From working with a PhD student it became clear that NCapture in NVivo no longer works – and hasn’t for about a year:

So this knocked out the use of NCapture to streamline importing a YouTube video and comments (and potentially in parallel the captions) into NVivo for analysis. However, this also creates an opportunity.

I generally prefer working with video in ATLAS.ti due to its different interface and less restrictive or structured options to transcripts and coding video vs transcripts separately rather than together.


Furthermore, for the project that prompted this investigation, there are methodological considerations that soemwhat favoured ATLAS.ti over NVivo as there was a priority for making conceptual connections between data (i.e. links) rather than allocating data segments to conceptual categories (i.e. via coding).

And that is where ATLAS.ti excels in comparison to other CAQDAS programmes.

So – how to replicate the functions of NCapture without it? Time to put the call out!

What can and can’t you do with YouTube videos?

NCapture allows one-click browser-based capture of a YoutTube videos – and should enable comment download too. The video is then streamed into NVivo and can be treated as if it is in NVivo in terms of working with the video – you can select, code, add transcript rows etc. You can also import and view the comments as a dataset. However, there is no direct import of transcript/captions and for at least the last year comment scraping is broken (doesn’t work in Chrome and IE not supported).

ETHICS and LEGALITY:

So it’s not technically illegal to download a YouTube video – however there are ethical considerations over what sort of video and who published it. With this project – looking at TED videos – these are not from an individual reliant on advertising revenue and there’s no individual to ask for permission to analyse.(See more at https://www.techadvisor.com/how-to/internet/is-it-legal-download-youtube-videos-3420353/#:~:text=For%20personal%20use%2C%20no%20it,of%20our%20industry%2C%20too).

Does it violate terms of use? Maybe but by a strict reading so does NCapture with it’s offline playback outside YouTube platform or app.

So if there are no legal or ethical considerations about downloading videos and comments for analysis it becomes a question of technical implementation.

YouTube Video Downloaders and Comment Scrapers

NCapture provided video linking to YouTube (treating them like an external video file hosted on your machine) – it would be great to see that sort of internet linking supported in ATLAS.ti and MAXQDA (if you can link to a local file why not an online one?).

So to work in ATLAS.ti with the video you need to download it.

I looked at Freemake Video downloader (https://freemake.com/free_video_downloader/) but hit issues as itst adds a logo at the start, thereby breaking the timestamp link for any downloaded transcript.

Downloading Video and Captions with 4k Video Downloader

4k Video downloader is the best I found 9and highest rated/recommended in TechRadar’s great article)

You just copy and paste the YouTube URL – and then it gives you options for quality *and* caption download (where available) including second captions in auto-translated languages:

The subtitles are downloaded as an SRT file – which can be directly imported into ATLAS.ti as a linked/synchronised transcript – RESULT (and way more than NCapture did).

So that gets the video and captions in – what about the comments.

Scraping and Importing the Comments

This has proved a little trickier and still has some slight anomalies I’m trying to iron out

I started out with https://app.coberry.com/ for comments – it has some great features including output as PDF or as dataset and enables sentiment analysis. BUT I also found a load of issues from the TED trsnaxritp I started working with including strings of characters like this:

😨😨😨
Â
’
‘

These require a SnR in Excel – but it wasn’t easy to pick up all of them. What ARE they?

I then tried a few others and read this good but out-of-date article with a bunch of recommendations. However the YouTube Comments Exporter chrome plugin is broken (looks like same issue as NCapture). I also looked at SEOBOTS but it charges you and had very poor data exports and threw a bunch of errors.

The best tool I found – which also opens up Facebook scraping into ATLAS.ti – is export comments. This also identified where the issues about those strange text strings came in coberry from as it would download various emoji style characters e.g.

👍
🌴
etc

Exportcomments.com DOES charge for over 100 comments – however the rates allow you to pay a modest US$11 for 3 days and the options for TikTok, Facebook etc. plug a perceived “gap” for ATLAS.ti.

THOUGHT: Is it a gap? The issue of NCapture suggests to me that enabling import of comments from custom tools might be more important than trying to develop a new software suite based on external APIs that is subject to breakage by a third party change…

An anomaly in ATLAS.ti Windows – wherefore art though emojis?

So here’s where it’s got a bit weird – those characters that caused a mare in Coberry don’t display properly in ATLAS.ti on Windows.

So the good news – ATLAS.ti for Mac works fine with emojis:

Emojis from YouTube comments displaying in ATLAS.ti for Mac
And in the Document preview

However there is an issue in Windows – no problem in document preview:

Document Preview in document manager on ATLAS.ti 9 Windows – icon shows

But when you open the document itself it’s not shown nor codable:

So where’s the palm tree gone? ATLAS.ti 9 on windows main document view for coding.

Considerations: Onscreen style comments printed or dataset?

The challenge here comes from HOW to bring in comments – and that’s one of the current limits with ATLAS.ti, there are only “Codes” and working with code groups is limited. So you can’t have a type of code for “cases” (e.g. comment authors) and give those codes attrbutes. You sort of can – using code groups but they can’t be used in the same way as document groups to easily compare across conceptual/thematic codes in the same way so then you have to create smart codes and it all gets complex.

So you need to decide: see comments together in a similar presentation to the way the appear on screen (and don’t use document groups) OR import as a dataset and work with document groups but with less familiar and potentially decontextualised chains of replies.

If you use Coberry you can easily print as PDF to have all comments on one page and then code for author AND/OR export. However any emojis will be garbled. Exportcomments.com only offers dataset download.

Marking up the comments for import

This next bit is a bit of a work in progress as I try to figure out which bits do still work and which work well for working with the downloaded comments as a dataset. Some of the information I’d found on survey import no longer works so it’s best to refer to the online manual for ATLAS.ti mac or the online manual for ATLAS.ti Windows about which prefixes can be added to column headings. However, some do not seem to work as described (I had no joy with .

I have had some issue with time/date imports as well which I’m trying to resolve.

Export Comments raw data is like this:

  Name (click to view profile):DateLikesisHeartedisPinnedComment(view source)
Raw export comments data

I chose to work with this data as follows:

Comment Export List

 !CommentNo Name#NameDate:Date:Likes.isHearted.isPinnedCommentSource URL
1JCJC26/05/2021 21:51:532021-05-260nonoSo this is where the last line of Rhett&Link’s Geek vs Nerd Rap Battle came from.
view comment
Data prepared for ATLAS.ti Import

As you can hopefully see I duplicated the name and date columns to use them as data in the document and a way to classify details. With the date column I duplicated, formatted as yyyy-mm-dd then cut, pasted it into notepad/textedit, formatted cells as text and pasted it back via paste special, paste as text to get dates-as-text.

This created a document per comment numbered by col 1 both including author name and date and in the comment as well as groups.

This *seems* to work quite well – but I’m still working on it!

Coming soon:

Here: Final bits on the comment import process and also alternatives via coberry.

A new post: A proper focus on analysis processes and opportunities – making use of split screens/tab groups, hyperlinks, networks and some coding to stitch all of this together.

Using NVivo to Correct and Code Transcripts generated automatically by Teams, Stream or Zoom

Introduction

Prerequisites

The following are important prerequisites. You will need:

  1. A media file that is either:
    1. A recording within Microsoft Teams saved to Stream
      OR
    2. A media file you can convert and upload to Microsoft Stream*
      OR
    3. An audio or video recording through an institutionally licensed Zoom account (with subtitling enabled)
      OR
    4. A recording from another system that outputs a subtitle file (that you will then convert to VTT)
  2. Installed version of NVivo – the following is illustrated for R1.
  3. Installation of the free VLC media player

Process

  1. Create a media file with subtitle file in VTT format
  2. Download the media file and the subtitle file
  3. Clean the subtitle file ready for import.
  4. Import the media file into NVivo
  5. Importing the cleaned subtitles as a synchronised transcript into NVivo
  6. Listen to the media file and read the synchronised transcript in order to begin analysis through
    • Correcting the transcript
    • Labeling speakers
    • Making notes (annotation)
    • Initial coding the transcript

Step One – Create a media file with subtitle file in VTT format

Depending where you start there are a few ways this will work – all have the same end point: a media file and a VTT transcript. It’s all detailed over in this post.

The introductory video was created with Teams, another was created in Zoom. You can also (currently) upload videos to Stream or use a wide range of other applications and system to create an automatic transcript of a media file.

Step Two – Download the media file and the subtitle file

Exporting from Zoom

NOTE: Zoom will (attempt to) label speakers based on their name in the zoom call – consider if you need to anonymise this as it’s easily done at this stage.

Step Three – Clean the subtitle file ready for import using an online tool

This is the essential step of development work that bridged the gap from a VTT file to an NVivo-ready file.

Updated tool availalble

UPDATE: December 2021: New tool developed from Tim’s by Charles Weir now available at https://securityessentials.github.io/Teams2NVivo/

Option 1 – Clean the VTT file into NVivo-ready format online

Go to https://www.lancaster.ac.uk/staff/ellist/vtttocaqdas.html

Upload your VTT file, Click convert, download the text file.

Option 2 – create your own copy of the converter

Go to the GitHub page at https://github.com/TimEllis/vttprocessor

Step Four – Import the media file into NVivo

First there’s a STRONGLY recommended preparatory step for NVivo as well which adds a column for labelling the speaker in a synchronised transcript. It’s a bit hidden in the documentation though: under the Audio/Video section in Changing Application options.

I would recommend:

  1. Set a skip back on play in transcribe mode of 1 second (this means audio skips back when correcting so you go back to where you were) AND
  2. Add a Custom Transcript Field for speaker.

NVivo Windows

NVivo Release 1 for windows transcript import is documented at https://help-nv.qsrinternational.com/20/win/Content/files/audio-and-videos.htm

(Unchanged process but slight interface changes from v12 instructions available here )

Note that it is likely you’ll need to install a codec pack for any video files.

NVivo Mac

NVivo Release 1 for Mac audio and media importing is is documented here https://help-nv.qsrinternational.com/20/mac/Content/files/audio-and-videos.htm

(Unchanged process but slight interface changes compared with the NVivo 12 notes on audio and video files here)

It’s usually pretty straightforward – if the media will play in Quicktime it will play in NVivo.

Step Five – Import the cleaned subtitles as a synchronised transcript

NVivo Windows

NVivo Release 1 for windows transcript import is documented at https://help-nv.qsrinternational.com/20/win/Content/files/import-audio-video-transcripts.htm

(Unchanged process but slight interface changes from v12 instructions available here )

NVivo Mac

NVivo Release 1 for Mac transcript import is documented here https://help-nv.qsrinternational.com/20/mac/Content/files/import-audio-video-transcripts.htm

Step Six – Listen to the media and correct the transcript (and begin initial analysis steps)

So this is where it all pays off!

This process allows you to now use the powerful tools within NVivo to playback the audio / video (including slowing playback speed,adjusting volume and setting rewind intervals when you press play/pause + keyboard shortcuts for the play/pause functions) whilst you read the transcript and make corrections. But not only corrections! You can also annotate the transcript, label speakers and even start coding at this stage.

Resources

Example project file NVivo R1 (Windows) here

Example project NVivo R1 (Mac) here

Example media file and VTT file from the first video also available here.

The blog bit – background, next steps, context

So this has been a real focus for me recently. I’ve had a lot of help and encouragement – see acknowledgements below – but also NEED from students and groups who are wondering how to do transcription better.

I also think this really gives the lie to the idea that manual transcription is “the best way” to get in touch with audio. I’m kind of hoping that the sudden shifts the pandemic has caused in practice and process might lead to some developments and rethinking of analysis. This quote has been too true for too long:

Over the past 50 years the habitual nature of our research practice has obscured serious attention to the precise nature of the devices used by social scientists (Platt 2002, Lee 2004). For qualitative researchers the tape-recorder became the prime professional instrument intrinsically connected to capturing human voices on tape in the context of interviews. David Silverman argues that the reliance on these techniques has limited the sociological imagination: “Qualitative researchers’ almost Pavlovian tendency to identify research design with interviews has blinkered them to the possible gains of other kinds of data” (Silverman 2007: 42). The strength of this impulse is widely evident from the methodological design of undergraduate dissertations to multimillion pound research grant applications. The result is a kind of inertia, as Roger Stack argues: “It would appear that after the invention of the tape-recorder, much of sociology took a deep sigh, sank back into the chair and decided to think very little about the potential of technology for the practical work of doing sociology” (Slack 1998: 1.10).

Back L. (2010) Broken Devices and New Opportunities: Re-imagining the tools of Qualitative Research. ESRC National Centre for Research Methods

Citing:
Lee, R. M. (2004) ‘Recording Technologies and the Interview in Sociology, 1920-2000’, Sociology, 38(5): 869-899
Platt, J. (2002) ‘The History of the Interview,’ in J. F. Gubrium and J. A. Holstein (eds) Handbook of the Interview Research: Context and Method, Thousand Oaks, CA: Sage pp. 35-54.
Silverman D. (2007) A very short, fairly interesting and reasonably cheap book about qualitative research, Los Angeles, Calif.: SAGE.
Slack R. (1998) On the Potentialities and Problems of a www based naturalistic Sociology. Sociological Research Online 3. http://socresonline.org.uk/3/2/3.html

How and when Stream will be changing https://docs.microsoft.com/en-gb/stream/streamnew/new-stream

Bits about zoom needing transcripts switched on and how to do this (ie.e. send this link to your institutional zoom administrator see https://support.zoom.us/hc/en-us/articles/115004794983-Using-audio-transcription-for-cloud-recordings- )

A cool free online tool for converting other transcript formats (e.g. from EStream, Panopto or other systems) https://subtitletools.com/

And finally for more information on the VTT format see this excellent page.

Thanks and acknowledgements

This hasn’t happened alone. Many thanks to Tim Ellis especially for his work on the VTT cleaner and sharing it via GitHub.

If you’ve got suggestions, ideas, updates, developments or found this useful please post a comment, link to this or build on it.

Using MAXQDA to Correct and Code Automatically generated Transcripts from Teams or Zoom

Update – May 2021

MAXQDA now supports direct subtitle file (SRT) import

https://www.maxqda.com/help-mx20/import/subtitle-data-srt

You can easily convert VTT files to SRT using https://subtitletools.com/convert-to-srt-online

MAXDAYS presentation

Here’s my presentation and session from the (excellent) MAXDAYS conference in 2021:

Introduction:

Prerequisites

The following are important prerequisites. You will need:

  1. A media file that is either:
    1. A recording within Microsoft Teams saved to Stream
      OR
    2. A media file you can convert and upload to Microsoft Stream*
      OR
    3. An audio or video recording through an institutionally licensed Zoom account (with subtitling enabled)
      OR
    4. A recording from another system that outputs a subtitle file (that you will then convert to VTT)
  2. Installed version of MAXQDA (this is all illustrated and lined to 2020 pro edition – with a common experience and manual across windows and Mac).
  3. Installation of the free VLC media player

Process

Steps four and five are reversed below from main sequence with MaxQDA as it picks up timestamps in a file and then asks you to import media (you can do it the other way around but it’s a little more efficient this way).

  1. Create a media file with subtitle file in VTT format
  2. Download the media file and the subtitle file
  3. Clean the subtitle file ready for import.
  4. Import the subtitle file into MAXQDA
  5. Importing the associated media file
  6. Listen to the media file and read the synchronised transcript in order to begin analysis through
    • Correcting the transcript
    • Labeling speakers
    • Making notes (annotation)
    • Initial coding the transcript

Step One – Create a media file with subtitle file in VTT format

Depending where you start there are a few ways this will work – all have the same end point: a media file and a VTT transcript. It’s all detailed over in this post.

The introductory video was created with Teams, another was created in Zoom. You can also (currently) upload videos to Stream or use a wide range of other applications and system to create an automatic transcript of a media file.

Step Two – Download the media file and the subtitle file

Step Three – Clean the subtitle file ready for import using an online tool

This area is developing quite rapidly – the following steps will give you a MAXQDA ready file.

Updated tool availalble

UPDATE: December 2021: New tool developed from Tim’s by Charles Weir now available at https://securityessentials.github.io/Teams2NVivo/

Option 1 – Clean the VTT file into CAQDAS ready format online

Go to https://www.lancaster.ac.uk/staff/ellist/vtttocaqdas.html

Upload your VTT file, Click convert, download the text file.

Option 2 – create your own copy of the converter

Go to the GitHub page at https://github.com/TimEllis/vttprocessor

Step Four – Import the cleaned subtitles as a synchronised transcript

Documented at https://www.maxqda.com/help-mx20/import/transcripts-with-timestamps

Step Five – Import the media file into MAXQDA

Documented at https://www.maxqda.com/help-mx20/import/inserting-audio-and-video-files-in-a-maxqda-project

Step Six – Listen to the media and correct the transcript (and begin initial analysis steps)

So this is where it all pays off!

This process allows you to now use the powerful tools within MAXQDA to playback the audio / video (including slowing playback speed,adjusting volume and setting rewind intervals when you press play/pause + keyboard shortcuts for the play/pause functions) whilst you read the transcript and make corrections. But not only corrections! You can also annotate the transcript and even start coding at this stage.

An AMAZING tool for this process in MAXQDA is the “summarise” function to use when correcting the transcript – this allows you to annotate and make notes but also use those to create candidate codes. It’s a really really nice tool and function for this process.

Resources

The example MAXQDA 2020 Project file from the above is available here.

The additional files (recordings and VTT files) can be downloaded from here if you want to have a play at cleaning, importing and correcting them.

The blog bit – background, next steps, context

So this has been a real focus for me recently. I’ve had a lot of help and encouragement – see acknowledgements below – but also NEED from students and groups who are wondering how to do transcription better.

I also think this really gives the lie to the idea that manual transcription is “the best way” to get in touch with audio. I’m kind of hoping that the sudden shifts the pandemic has caused in practice and process might lead to some developments and rethinking of analysis. This quote has been too true for too long:

Over the past 50 years the habitual nature of our research practice has obscured serious attention to the precise nature of the devices used by social scientists (Platt 2002, Lee 2004). For qualitative researchers the tape-recorder became the prime professional instrument intrinsically connected to capturing human voices on tape in the context of interviews. David Silverman argues that the reliance on these techniques has limited the sociological imagination: “Qualitative researchers’ almost Pavlovian tendency to identify research design with interviews has blinkered them to the possible gains of other kinds of data” (Silverman 2007: 42). The strength of this impulse is widely evident from the methodological design of undergraduate dissertations to multimillion pound research grant applications. The result is a kind of inertia, as Roger Stack argues: “It would appear that after the invention of the tape-recorder, much of sociology took a deep sigh, sank back into the chair and decided to think very little about the potential of technology for the practical work of doing sociology” (Slack 1998: 1.10).

Back L. (2010) Broken Devices and New Opportunities: Re-imagining the tools of Qualitative Research. ESRC National Centre for Research Methods

Citing:
Lee, R. M. (2004) ‘Recording Technologies and the Interview in Sociology, 1920-2000’, Sociology, 38(5): 869-899
Platt, J. (2002) ‘The History of the Interview,’ in J. F. Gubrium and J. A. Holstein (eds) Handbook of the Interview Research: Context and Method, Thousand Oaks, CA: Sage pp. 35-54.
Silverman D. (2007) A very short, fairly interesting and reasonably cheap book about qualitative research, Los Angeles, Calif.: SAGE.
Slack R. (1998) On the Potentialities and Problems of a www based naturalistic Sociology. Sociological Research Online 3. http://socresonline.org.uk/3/2/3.html

How and when Stream will be changing https://docs.microsoft.com/en-gb/stream/streamnew/new-stream

Bits about zoom needing transcripts switched on and how to do this (ie.e. send this link to your institutional zoom administrator see https://support.zoom.us/hc/en-us/articles/115004794983-Using-audio-transcription-for-cloud-recordings- )

A cool free online tool for converting other transcript formats (e.g. from EStream, Panopto or other systems) https://subtitletools.com/

And finally for more information on the VTT format see this excellent page.

Thanks and acknowledgements

This hasn’t happened alone. Many thanks to Tim Ellis especially for his work on the VTT cleaner and sharing it via GitHub.

If you’ve got suggestions, ideas, updates, developments or found this useful please post a comment, link to this or build on it.

Responses to 5LQDA pt2 – Much Ado About Affordances

Ahhh affordances – something of a bête noire for me!

This term has resurfaced again for me twice in the last two days – in reading the 5LQDA textbook on NVivo and in a discussion session/seminar I was at today with Chris Jones about devices, teaching and learning analytics who argued.

Chris argued FOR affordances on two fronts:

  1. they bring a focus on BOTH the materiality AND the interaction between the perceiver and the perceived and de-centre agency so that it exists in the interaction rather than as entirely in/of an object or in/of a person’s perception of it.
  2. despite quite a lot of well argued criticism, no-one has really proposed an equivalent or better term.

I would entirely agree with both of those statements, backing down from my usual strong view of affordances as being necessarily problematic when invoked.

(I was once told that the way to “make it” in academia was to pick an adversarial position and argue from that all the time never giving compromise and affordance critique seems a good one for that – maybe that’s why I don’t/won’t succeed in acadmeia I’m to willing to change position!)

BUT BUT BUT

Then someone does something like this:

“Think of the affordances of the program as frozen – they come fully formed, designed as the software developer thought best. In contrast think of TOOLS as emergent – we create them and they only exist in the context of use.”
(Woolf and Silver, 2017, p50)

And I end up back in my sniping position of “affordances have little merit as they mean all things to all people and even their supposedly best qualities can be cast out on a whim”. Here we see affordances stripped of ALL those interactice properties. They are now “fully formed, designed” not emergent or interactive. All of that is now being places onto the idea of a “tool” as being something that only has agency in use and in action and through interaction.

So if affordances are now tools – what then of affordances? And why is TOOL a better term?

A little background and further reading on affordances

Affordances are both an easy shorthand and a contested term (see Oliver, 2005) but one that usually retains both a common-sense understanding of “what’s easy to do” combine with a more interactionist idea of “what actions are invited”. (The latter appealing to my ANT-oriented interests in, or sensibility towards considering “non-human agency”.) I’ve read quite a lot on affordances and written on this before  in Wright and Parchoma (2011) whilst my former colleague Gale Parchoma has really extended that consideration too in her 2014 paper [4], (and also in this recorded presentation). With both of us drawing on Martin Oliver’s (2005) foundational critique [5]. I also really like Tim Ingold’s (20o0)  excellent extended explorations and extensions of Gibson’s work.

Should we keep and use a term that lacks the sort of theoretical purity or precision that may be desired because it’s very fuzziness partly evokes and exemplifies its concept? Probably.

But if it is so woolly then could “the affordances of CAQDAS” be explored systematically, empirically and meaningfully?

Could we actually investigate affordances meaningfully?

Thompson and Adams (2013, 2014) propose phenomenological enquiry as providing a basis. Within this there are opportunities to record user experience at particular junctures – moments of disruption and change being obvious ones. So for me currently encountering ATLAS.ti 8 presents an opportunity to look at the interaction of the software with my expectations and ideas and desires to achieve certain outcomes. Adapting my practices to a new environment creates an encounter between the familiar and the strange – between the known and the unknown.

However, is there a way to bring alternative ideas and approaches – perhaps even those which are normally regarded as oppositional or incommensurable with such a reflexive self-as-object-and-subject mode of enquiry? Could “affordances” be (dare I say it?) quantified? Or at least some methods and measures be proposed to support assertions.

For example, if an action is ever-present in the interface or only takes one click to achieve could that be regarded as a measure of ease – an indicator of “affordance”? Or does that stray into this fixed idea of affordances as being frozen and designed in? Or does the language used affect the “affordance” so their is a greater level of complexity still. Could that be explored through disruption – can software presented with a different interface language still “afford” things? Language is rarely part of the terminology of affordance with its roots in the psychology of perception, yet language and specific terminology seems to be the overlooked element of “software affordances”.

Could counting the steps required add to an investigation of the tacit knowledge and/or prior experience and/or comparable and parallel experience that is drawn on? Or would it merely fudge it and dilute it all?

My sense is that counts such as this, supplemented by screen shots could provide a useful measure but one that would have to be embedded in a more multi-modal approach rather than narrow quantification. This could however provide a dual function – both mapping and uncover the easiest path or the fewest steps to achieving a programmed action which will not only provide a sense or indication of simplicity/affordance vs complexity/un-afforded* (Hmmm – what is the opposite of an affordance? If there isn’t one doesn’t that challenge it’s over-use?) but also help inform teaching and action based on that research – in aprticular to show and teach and support ways to harness and also avoid or rethink these easy routes written into software that act to configure the user.

A five minute exploration – coding

Cursory checks – how much to software invite the user to “code” without doing any of the work associated with “coding”

Coding is usually the job identified with qualitative data analysis and the fucntion software is positioned to primarily support. However coding in qualitative analysis terms is NOT the same as “tagging” in software. Is “tagging” or “marking up” conflated with coding and made easy? Are bad habits “afforded” by interface?

Looking at ATLAS.ti 8 – select text and right-click:

VERY easy to create one or more codes – just right-click and code is created, no option there and then to add a code comment/definition.

Could we say then that an “affordance” of ATLAS.ti 8 is therefore creating codes and not defining them?

Looking at NVivo 11

Slightly different in that adding a new node does bring up the dialogue with an area for description – however pressing enter saves it,

Form data right-click and code > new node there is no place for defining, further supporting a code-and-code approach. This does allow adding into the hierarchy by first selecting the parent node so relational meaning is easily created – affordance = hierarchy?

AFFORDANCE = very short or one-sentence code definitions?

No way of easily identifying or differentiating commented and un-commented nodes.

Can only attach one memo to a node. The place for a longer consideration but separated.

Where next?

This is the most basic of explorations but it involves a range of approaches and also suggests interventions and teaching methods.

I really see where the 5LQDA approach seeks to work with this and get you to think and plan NOT get sucked into bad and problematic use of software – however I’m unsure of their differentiation of affordances as fixed and tools as having the properties usually ascribed to affordances…. So I definitely need to think about it more – and get other views too (so please feel free to comment) but a blog is a good place to record and share ideas-in-development, could that be “the affordance” of WordPress? 😉

 

References

Adams, C., & Thompson, T. L. (2014). Interviewing the Digital Materialities of Posthuman Inquiry: Decoding the encoding of research practices. Paper presented at the 9th International Conference on Networked Learning, Edinburgh. http://www.lancaster.ac.uk/fss/organisations/netlc/past/nlc2014/abstracts/adams.htm

Ingold, T. (2000). The perception of the environment essays on livelihood, dwelling & skill. London ; New York: Routledge.

Oliver, M. (2005). The Problem with Affordance. E-Learning, 2, 402-413. doi:10.2304/elea.2005.2.4.402 http://journals.sagepub.com/doi/pdf/10.2304/elea.2005.2.4.402

Parchoma, G. (2014) The contested ontology of affordances: Implications for researching technological affordances for fostering networked collaborative learning and knowledge creation. Computers in Human Behavior, 37, 360-368. 10.1016/j.chb.2012.05.028

Thompson, T. L., & Adams, C. (2013). Speaking with things: encoded researchers, social data, and other posthuman concoctions. Distinktion: Scandinavian Journal of Social Theory, 14(3), 342-361. doi:10.1080/1600910x.2013.838182 http://www.tandfonline.com/doi/full/10.1080/1600910X.2013.838182

Woolf, N. H., & Silver, C. (2017). Qualitative analysis using NVivo : the five-level QDA method. Abingdon: Taylor and Francis.

Wright, S., & Parchoma, G. (2011). Technologies for learning? An actor-network theory critique of ‘affordances’ in research on mobile learning. Research in Learning Technology, 19(3), 247-258. doi:10.1080/21567069.2011.624168 https://doi.org/10.3402/rlt.v19i3.17113

 

In practice: Analysing large datasets and developing methods for that

A quick post here but one that seeks to place the rather polemic and borderline-ranty previous post about realising the potential of CAQDAS tools into an applied rather than abstract context.

Here’s a quote that i really like:

The signal characteristic that distinguishes online from offline data collection is the enormous amount of data available online….

Qualitative analysts have mostly reacted to their new-found wealth of data by ignoring it. They have used their new computerized analysis possibilities to do more detailed analysis of the same (small) amount of data. Qualitative analysis has not really come to terms with the fact that enormous amounts of qualitative data are now available in electronic form. Analysis techniques have not been developed that would allow researchers to take advantage of this fact.

(Blank, 2008, p258)

I’m working on a project to analyse the NSS (National Student Survey) qualitative textual for Lancaster University (around 7000 comments). Next steps include analysing the PRES and PTES survey comments. But that;s small fry – the biggie is looking at the module evaluation data for all modules for all years (~130,000 comments!)

This requires using tools to help automate the classification, sorting and sampling of that unstructured data in order to be able to engage with interpretations. This sort of work NEEDS software – there’s a prevailing view that this either can’t be done (you can only work with numbers) or that it will only quantify data and somehow corrupt it and make it non-qualitative.

I would argue that isn’t the case – tools like those I’m testing and comparing including the ProSUITE from Provalis including QDA Miner/WordSTAT, Leximancer and NVivo Plus (incorporating Lexalytics) – enable this sort of working with large datasets based on principles of content analysis and data mining.

However these only go so far – they enable the classification of data and its sorting but there is still a requirement for more traditional qualitative methods of analysis and synthesis. I’ve been using (and hacking) framework matrices in NVivo Plus in order to synthesise and summarise the comments – an application of a method that is more overtly “qualitative data analysis” in a much more traditional vein but yet applied to and mediated by tools that enable application to much MUCh larger datasets than would perhaps normally be used in qual analysis.

And this is the sort of thing I’m talking about in terms of enabling the potential of the tools to guide the strategies and tactics used. But it took an awareness of the capabilities of these tools and an extended period of playing with them to find out what they could do in order to scope the project and consider which sorts of questions could be meaningfully asked, considered and explored as well. This seems to be oppositional to some of the prescriptions in the 5LQDA views about defining strategies separate from the capabilities of the tools – and is one of the reasons for taking this stance and considering it here.

Interestingly this has also led to a rejection of some tools (e.g. MaxQDA and ATLAS.ti) precisely due to their absence of functions for this sort of automated classification – again capabilities and features are a key consideration prior to defining strategies. However I’m now reassessing this as MaxQDA can do lemmatisation which is more advanced than NVivo plus…

This is just one example but to me it seems to be an important one to consider what could be achieved if we explore features and opportunities first rather than defining strategies that don’t account for those. In other words: a symbiotic exploration of the features and potentials of tools to shape and define strategies and tactics can open up new possibilities that were previously rejected rather than those tools and features necessarily or properly being subservient to strategies that fail to account for their possibilities.

On data mining and content analysis

I would highly recommend reading Leetaru (2012)  for a good, accessible overview of data mining methods and how these are used in content analysis. These give a clear insight into the methods, assumptions, applications and limitations of the aforementioned tools helping to demystify and open what can otherwise seem to be a black-box that automagically “does stuff”.

Krippendorf’s (2013) book is also an excellent overview of content analysis with several considerations of human-centred analysis using for example ATLAS.ti or NVivo as well as automated approaches like those available in the tools above.

References:

Blank G. (2008) Online Research Methods and Social Theory. In: Fielding N, Lee RM and Blank G (eds) The SAGE handbook of online research methods. Los Angeles, Calif.: SAGE, 537-549.

Preview of Ch1 available at https://uk.sagepub.com/en-gb/eur/the-Sage-handbook-of-online-research-methods/book245027

Krippendorff, K. (2012). Content analysis: An introduction to its methodology. Sage.

Preview chapters available at https://uk.sagepub.com/en-gb/eur/content-analysis/book234903#preview

Leetaru, Kalev (2012). Data mining methods for the content analyst : an introduction to the computational analysis of content. Routledge, New York

Preview available at https://books.google.co.uk/books?id=2VJaG5cQ61kC&lpg=PA98&ots=T4gZpIk4in&dq=leetaru%20data%20mining%20methods&pg=PP1#v=onepage&q=leetaru%20data%20mining%20methods&f=false 

On agency and technology: relating to tactics, strategies and tools

This continues my response to Christina Silver’s tweet and blog post. While my initial response to one aspect of that argument was pretty simple this is the much more substantive consideration.

From my perspective qualitative research reached a crossroads a while ago, though actually I think crossroads is the wrong term here. A crossroads requires a decision, it is a place steeped in mystery and mythology (see https://en.wikipedia.org/wiki/Crossroads_(mythology) ), I sometimes feel as though qualitative research did a very british thing: turned a crossroads into a roundabout thus enabling driving round and round rather than moving forwards or making a decision.

The crossroads was the explosion in the availability of qualitative data. Previously access to accounts of experience were rather limited – you had to go into the field and write about it, find people to interview, or use the letters pages of newspapers as a site of public discourse. These paper-based records were slow and time consuming to assemble, construct and analyse. For the sake of the metaphor that follows I shall refer to these as “the cavalry era” of qualitative research. Much romanticised and with doctrines that still dominate from the (often ageing, pre-digital) professoriat.

Then the digital didn’t so much happen as explode and social life expanded or shifted online:

For researchers used to gathering data in the offline world, one of the striking characteristics of online research is the sheer volume of data. (Blank, 2008, P539)

BUT…

Qualitative analysts have mostly reacted to their new-found wealth of data by ignoring it. They have used their new computerized analysis possibilities to do more detailed analysis of the same (small) amount of data. Qualitative analysis has not really come to terms with the fact that enormous amounts of qualitative data are now available in electronic form. Analysis techniques have not been developed that would allow researchers to take advantage of this fact. (Blank, 2008, P.548)

Furthermore the same methods continue to dominate – the much vaunted reflexivity that lies at the heart of claims for authenticity and trustworthiness does not seem to have been extended to tools, methods:

Over the past 50 years the habitual nature of our research practice has obscured serious attention to the precise nature of the devices used by social scientists (Platt 2002, Lee 2004). For qualitative researchers the tape-recorder became the prime professional instrument intrinsically connected to capturing human voices on tape in the context of interviews. David Silverman argues that the reliance on these techniques has limited the sociological imagination: “Qualitative researchers’ almost Pavlovian tendency to identify research design with interviews has blinkered them to the possible gains of other kinds of data” (Silverman 2007: 42). The strength of this impulse is widely evident from the methodological design of undergraduate dissertations to multimillion pound research grant applications. The result is a kind of inertia, as Roger Stack argues: “It would appear that after the invention of the tape-recorder, much of sociology took a deep sigh, sank back into the chair and decided to think very little about the potential of technology for the practical work of doing sociology” (Slack 1998: 1.10).

My concern with the approach presented and advocated by Silver and Woolf is that it holds the potential to reinforce and prolong this inertia. There are solid arguments FOR that position – especially given the conservatism of academia, mistrust of software and the apparently un-slayable discourses (Paulus, lester & Britt, 2013), entrenched critical views and misconceptions of QDAS software that “by its very nature decontextualizes data or primarily supports coding [which] have caused concerned researchers” (Paulus, Woods, Atkins and Macklin, 2017)

BUT… BUT… BUT…

New technologies enable new things – when they first arrive they are usually perhaps inevitably and restrictively fitted in to pre-existing approaches and methods, made subservient to old ways of doing things.

A metaphor – planes, tanks and tactics

I’ve been trying to think of a metaphor for this. The one I’ve ended up with is particularly militaristic and I’m not entirely comfortable with it – especially as metaphors sometimes invite over-extension which I fear may happen here. It also feels rather jingoistically “Boys Own” and British and may be alienating to key developers and methodologists in Germany. So comments on alternative metaphors would be MOST welcome, however given the rather martial themes around strategies and tactics used in Silver and Woolf’s (2015) paper and models for 5level QDA I’ll stick with it and explore tactics, strategies and technologies and how they historically related to two new technologies: the tank and the plane.

WW1 saw the rapid development of new and terrifying technologies in collision with old tactics and strategies for their use. The overarching strategies were the same (defeat the enemy) however the tactics used failed to take account of the potential of these new tools thus restricting their potential.

Cavalry were still deployed at the start of WW1. Even with the invention of tanks the tactics used in their early deployments were for mounted cavalry to follow up the breakthroughs achieved by tanks – with predictably disastrous failure at the battle of cambrai see https://en.wikipedia.org/wiki/Tanks_in_World_War_I#Battle_of_Cambrai ).

Planes were deployed from early in WW1 but in very limited capacities – as artillery spotters and as reconnaissance. Their potential to change warfare tactics were barely recognised nor exploited.

These strategies were developed by generals from an earlier era – still wedded to the cavalry charge as the ultimate glory. (See https://en.wikipedia.org/wiki/Cavalry#First_World_War ). Which seems to be a rather appropriate metaphor for professorial supervision today with regard to junior academics and PhD students.

The point I’m seeking to make is to suggest that new technologies vary in their complexity, but they also vary in their potential. Old methods of working are used with new technologies and the transformative potential of those new technologies on methods or tactics to achieve strategic aims is often far slower, and can be slowed further when there is little immediate incentive to change (unlike say a destructive war) in the face of an established doctrine.

My view is therefore that those who do work with and seek to innovate with CAQDAS tools  need to seek to do more than just fit in with the professorial field-marshall Haig’s of our day and talk in terms of CAQDAS being “fine for breaching the front old chap you know use CAQDAS to open up the data but you send in the printouts and transcripts to really do the work of harrying the data, what what old boy”.

Meanwhile Big Data is the BIG THING – and this entire sphere of large datasets and access to public discourse and digital social life threatens to be ceded entirely to quantitative methods. Yet we have tools, methods and tactics to engage in that area meaningfully by drawing on existing approaches which have always been both qual and quant (with corpus linguistics and content analysis springing to mind).

Currently the scope of any transformation seems to be pitched to taking strategies from a “cavalry era” of qualitative research. My suggestion is that to realise the full potential of some of the tools now available in order to generate new, and extend existing, qualitative analysis practices into the diverse new areas of digital social life and digital social data we need to be bolder in proposing what these tools can achieve and what new questions and datasets can be worked with. And that means developing new strategies to enter new territories – which need to understand the potential of these tools and explore ways that they can transform and extend what is possible.

If, however, we were to place the potential of these tools as subservient to existing strategies and to attempt to locate all of the agency for their use with the user and the way that we “configure the user” (Grint and Woolgar, 1997) in relation to these tools through our pedagogies and demonstrations we could limit those potentials. Using NVivo Plus or QDA Miner/WordSTAT to reproduce what could be done with a tape recorder, paper, pen and envelopes seems akin to sending horses chasing after tanks. What I am advocating for (as well, not instead) is to also try to work out what a revolutionary engagement with the potential of the new tools we have would look like for qualitative analysis with big unstructured qualitative data and big unstructured qualitatitve data-ready tools.

To continue the parallel here – the realisation of what could be accomplish by combining the new technologies of tanks and planes together created an entirely new form of attacking warfare – named Blitzkrieg by the journalists who witnessed its lightning speed. This was developed to achieve the same overarching strategies as deployed in WW1 (conquering the enemy) but by considering the potential and integration of new tools it developed a whole new mid-level strategy and associated tactics that utilised and realised the potential of those relatively new technologies. Thus it avoided becoming bogged down in the nightmare of using the strategies and tactics from a bygone era of pre-industrial warfare with new technologies that prevented their effectiveness which dominated in WW1. My suggestion is that there is a new territory now – big data – and it is one that is being rapidly and extensively ceded to a very quantitative paradigm and methods. To make the kind of rapid advances into that territory in order to re-establish qualitative analysis as having relevance we need to be bolder in developing new strategies that utilise the tools rather than making these subservient to strategies from an earlier era in deference to a frequently luddite professoriat.

My argument thus simplifies to the idea that the potential of tools can and should productively shape not only the planning and consideration the territories now amenable to exertion and engagement but also the strategies and tactics to do that. Doing that involves engagement with the conceptualisation, design and thinking about what qualitative or mixed-methods studies are and what they can do in order that this potential is realised. From this viewpoint Blitzkrieg was performed into being by the new technologies of the tank and the plane and their combination with new strategies and tactics. These contrast with the earlier subsuming of the plane’s potential to merely being tools to achieve strategies that were conceptualised before its existence. A plane was there equivalent to a tree or a balloon for spotting cannon fire. Much of CAQDAS use today seems to be just like this – sending horses chasing after tanks – rather than seeking to achieve things that couldn’t be done without it and celebration that.

This is all rather abstract I know so I’ve tried to extend and apply this into a consideration of implementation in practice working with large unstructured datasets in a new post.

References

Back L. (2010) Broken Devices and New Opportunities: Re-imagining the tools of Qualitative Research. ESRC National Centre for Research Methods

Available from: http://eprints.ncrm.ac.uk/1579/1/0810_broken_devices_Back.pdf

Citing:

Lee, R. M. (2004) ‘Recording Technologies and the Interview in Sociology, 1920-2000’, Sociology, 38(5): 869-899

E-Print available at: https://repository.royalholloway.ac.uk/file/046b0d22-f470-9890-79ad-b9ca08241251/7/Lee_(2004).pdf

Platt, J. (2002) ‘The History of the Interview,’ in J. F. Gubrium and J. A. Holstein (eds) Handbook of the Interview Research: Context and Method, Thousand Oaks, CA: Sage pp. 35-54.

Limited Book Preview available at https://books.google.co.uk/books?id=uQMUMQJZU4gC&lpg=PA27&dq=Handbook%20of%20the%20Interview%20Research%3A%20Context%20and%20Method&pg=PA27#v=onepage&q=Handbook%20of%20the%20Interview%20Research:%20Context%20and%20Method&f=false

Silverman D. (2007) A very short, fairly interesting and reasonably cheap book about qualitative research, Los Angeles, Calif.: SAGE.

Limited Book Preview at: https://books.google.co.uk/books?id=5Nr2XKtqY8wC&lpg=PP1&pg=PP1#v=onepage&q&f=false

Slack R. (1998) On the Potentialities and Problems of a www based naturalistic Sociology. Sociological Research Online 3.

Available from: http://socresonline.org.uk/3/2/3.html

Blank G. (2008) Online Research Methods and Social Theory. In: Fielding N, Lee RM and Blank G (eds) The SAGE handbook of online research methods [electronic resource]. Los Angeles, Calif. ; London : SAGE.

Grint K and Woolgar S. (1997) Configuring the user: inventing new technologies. The machine at work: technology, work, and organization. Cambridge, Mass.: Polity Press, 65-94.

Paulus TM, Lester JN and Britt VG. (2013) Constructing Hopes and Fears Around Technology. Qualitative Inquiry 19: 639-651.

Paulus T, Woods M, Atkins DP, et al. (2017) The discourse of QDAS: reporting practices of ATLAS.ti and NVivo users with implications for best practices. International Journal of Social Research Methodology 20: 35-47.

Silver C and Woolf NH. (2015) From guided-instruction to facilitation of learning: the development of Five-level QDA as a CAQDAS pedagogy that explicates the practices of expert users. International Journal of Social Research Methodology 18: 527-543.