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Genuine equity versus legitimate
 expertise: Reflections on the process
 of engaging in participatory research
 and the implications for
 researcher/participant relationships

Professor Jane Seale
The focus

• Participatory
  (inclusive
  research)
• Data Analysis
The question

Is it possible for academic
researchers to have truly
equitable research partnerships
with their co-researchers, when
they hold so much of the
legitimated research expertise?
Participatory research is.....

• Engaging marginalised people such as children or
  those with learning disabilities as equal partners in
  research,
  – facilitate political and civic engagement of excluded groups
  – responsive to concerns regarding rights and voice
• Involvement in the design, conduct and analysis of
  “research”
• Encouraging participants (co-researchers) to own the
  outcome by setting the goals and sharing in decisions
  about processes.
• Degree of participation can be mapped against a
  framework offered by Radermacher (2006) which
  identifies six categories of participant involvement
Participatory data analysis: A
battleground?
 “ I can’t see why anyone with a learning
 disability would want to analyse data”
 – Anonymous funding bid reviewer



 “ But people with learning disabilities wont be
 able to use SPSS”
 – Anonymous journal reviewer
Participatory data analysis: re-drawing the
boundaries of academic contribution
• Making data analysis expertise available versus enabling research
  participants to undertake data analysis themselves
• Jan Walmsley
  – Academic researchers have something valuable to contribute
     and they should not be ashamed of this
  – In danger of allowing themselves to become “invisible” in order
     to adhere to the spirit and politics of participatory and inclusive
     research
[1] ESRC funded research: Concepts of
access for people with learning
disabilities
                    • People with learning
                      disabilities were
                      equal partners in
                      research seminars:
                      – Presented alongside
                        researchers and
                        practitioners from
                        education, social
                        work, nursing,
                        psychology
Included in research through the use of
technology, participatory methods &
skilled, creative advocacy workers:
                      • Using mobile phones to
                        organise their travel to and from
                        the university
                      • Presenters with learning
                        disabilities able to tell their
                        powerful stories of access
                        through PowerPoint with
                        pictures and video clips
Writing partners: a voice in a
previously inaccessible research
world
                    I took a risk taking the job
                    at St George’s because I
                    knew my benefits would go
                    all over the place […] I took
                    the risk because I thought I
                    can’t live off benefits all my
                    life. I don’t want to grow old
                    and just sit there in an
                    armchair and be bored out
                    of my life. Butler, 2010
But how did we “do” participatory
 data analysis”?
• At the end of each seminar
  – Produced an accessible summary of each of the six seminars
      and distributed to all participants
• At the end of year one:
  – presented a visual representation of emergent conceptual
      framework for discussion
• At the end of year two:
  – Produced an accessible thematic analysis of themes running
      across all six seminars
  – Presented revised visual representation of conceptual
      framework which stiumulated group discussion and feedback
Example

       Figure 12.2: Characteristics of risk
        embracing approaches to access
Trusting         Co-operative
                                             Letting go


                                            Creative
Flexible              Risk Embracing
                                              Building
                                              bonds and
                                              bridges
  Happy to let luck
    play a part
                                       High expectations of
               Prepared to take              success
                a leap of faith
Was the participatory data analysis “good
enough”?

REASONS TO STAND PROUD:          REASONS TO PAUSE:
• Analysis is grounded in the    • Making data accessible is
  words and experiences of all     complex
  participants                   • Extent to which disabled
• Development of conceptual        participants led data analysis
  framework was shared and         is questionable, although it is
  negotiated                       clear they influenced it
  – Participants with learning
     disabilities were
     supported to contribute
     and advocate
[2]: disabled students at
university as equal partners
in research AND design
JISC funded Project

• LEXDIS: Learner Experience Phase II
• Team: Education, computer science, speech
  therapy/assistive technology
• Produce 30 case studies describing disabled
  learners’ different e-learning experiences
Overview of Participatory Phases
• Phase One: Consultation
  regarding proposed research
  questions and research
  methods;
• Phase Two: Opportunity to
  contribute own experiences of
  using e-learning, contributing
  artefacts of their own choosing;
• Phase Three: Opportunity to
  validate and interpret the results
  of the study and to contribute to
  the design, content and
  dissemination of project
  deliverables and outcomes.
Involving participants in the analysis of
results
• Held a focus group to share our initial interpretations of the
  data that we had collected and to invite participants to
  guide us in our analysis.
  – Why did we not train up some students to engage in the NVivo
    coding of interview data with us?
• CHALLENGE 1- How do you present a mass of data in a
  way that all participants can access and interpret?
  •   E.g. For dyslexic students need to think about structure and
      volume of information
  •   E.g. For students with manual dexterity difficulties need to think
      about handling volumes of paper
Involving participants in the analysis of
results
• Taking into account the varying abilities and needs of our participants,
  we chose to present the results in 6 summarised PowerPoint slides ( a
  real challenge!) and to give a verbal commentary. The main findings
  were summarised and presented to the participants as:

   –   As a group you appear to be resourceful and adaptable learners;
   –   As a group you appear to have a love-hate relationship with technology;
   –   As a group you appear to be making informed, yet complex decisions
       about your use of technology.

• For each of these findings, we asked the group whether they reflected
  their own personal experiences and views and whether we were
  misrepresenting the findings or missing something important from the
  results.
Involving participants in the analysis of
results
• No-one expressed concern that the suggested analysis
  would falsely represent the experience of individuals or the
  group.

  – Challenge 2: Is this just acquiescence or a consequence of
    students simply not being empowered to do anything other than
    agree with us?

• Participants felt comfortable enough to disagree with one
  another
• Participants felt comfortable enough to disagree with
  researchers
The pay-off: authenticity

• Valuable information about
  participants perceptions
  regarding whether they
  represented typical disabled
  learners
• Added authenticity to the
  students voices, which may
  enhance probability that the
  results will not be written off
  as unrepresentative
[3] PAIRS: Participatory Inclusion Related
Staff Development
1. Capture “student voices” regarding their learning experiences
   within the School of Education
   • Use these “voices” to explore whether and how our School of
      Education programmes (undergraduate and postgraduate)
      include or exclude students with a wide range of learning
      needs from experiencing positive or high quality learning
      opportunities

2. Involve students in the analysis and exploration of these “student
     voices”
     • Develop a collaborative partnership whereby students help to
        develop materials and methods that can be used to help staff
        in the work towards meeting learning needs and reducing
        barriers to inclusion.
Phase One: Tell us your “stories”

• Write or audio-record a one-two page letter to an “imaginary” friend
• Write a diary describing learning experiences on course, over the
  period of a “typical” week;
• Write a reflective journal that describes a “critical incident”
• Produce a piece of creative writing or art (e.g. poem, picture,
  sculpture, song)
• Alternatively, opt to be interviewed face-to-face, by phone or by
  webcam.

• Focus for all stories: learning experiences and whether learning
  needs have been met
Phase Two: help us understand the
stories


                 •   Formed an advisory group that
                     worked together to decide how
                     we will use the information
                     about student learning
                     experiences to design staff
                     development initiatives in the
                     School.
Phase 2: The analysis


• 5 students (also phase 1 participants) consented to being
  members of an “advisory group”
• Work and family commitments as well as distance (1 student
  had graduated) meant that all work done via email
• Sent each participant three stories and asked them to code
  stories for themes or issues that they thought were significant
  – Using highlight and comment features in Word
“Doh!”
• The nature and quality of student “coding” was variable
  – Even though the majority were PG
• I underestimated how hard participants might find this
• Why did I assume that the students would be able to code
  transcripts in the way that I can/would?
• Should have built in time to “train/induct” participants in
  analysis methods
• In the end I “analysed the analysis” and produced a core set
  of themes, that I thought most of the students had identified
  and shared this with the group for approval
The issues for reflection and discussion

• Doing participatory research takes more time and effort than
  traditional research
  – The time required to do justice to participatory data analysis is
      underestimated, particularly capacity-building element
• Is the ultimate goal of participatory research to enable co-
  researchers, particularly those who are marginalised in society, to
  take a lead in data analysis?
  – Does it matter if they don’t?
• What motivates academics to do research and do they have
  enough self-awareness to share the data analysis “limelight” and
  let go of the assumed status that “being able to analyse data” has
• Why bother?
Why bother? Impact




• Four years after the end of the project, the website is still having an
  impact on disabled students- students from all over the UK are contacting
  the team offering to add their own “case studies”.
And finally a plug

•   ESRC funded seminar series:
    “Towards equal and active
    citizenship: pushing the
    boundaries of participatory
    research with people with
    learning disabilities”

•   First seminar- Plymouth,
    January 10th

•   Email
    jane.seale@plymouth.ac.uk if
    you would like to be put on
    mailing list and sent
    programme details

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Seale methodological innovations keynote

  • 1. Genuine equity versus legitimate expertise: Reflections on the process of engaging in participatory research and the implications for researcher/participant relationships Professor Jane Seale
  • 2. The focus • Participatory (inclusive research) • Data Analysis
  • 3. The question Is it possible for academic researchers to have truly equitable research partnerships with their co-researchers, when they hold so much of the legitimated research expertise?
  • 4. Participatory research is..... • Engaging marginalised people such as children or those with learning disabilities as equal partners in research, – facilitate political and civic engagement of excluded groups – responsive to concerns regarding rights and voice • Involvement in the design, conduct and analysis of “research” • Encouraging participants (co-researchers) to own the outcome by setting the goals and sharing in decisions about processes. • Degree of participation can be mapped against a framework offered by Radermacher (2006) which identifies six categories of participant involvement
  • 5.
  • 6. Participatory data analysis: A battleground? “ I can’t see why anyone with a learning disability would want to analyse data” – Anonymous funding bid reviewer “ But people with learning disabilities wont be able to use SPSS” – Anonymous journal reviewer
  • 7. Participatory data analysis: re-drawing the boundaries of academic contribution • Making data analysis expertise available versus enabling research participants to undertake data analysis themselves • Jan Walmsley – Academic researchers have something valuable to contribute and they should not be ashamed of this – In danger of allowing themselves to become “invisible” in order to adhere to the spirit and politics of participatory and inclusive research
  • 8. [1] ESRC funded research: Concepts of access for people with learning disabilities • People with learning disabilities were equal partners in research seminars: – Presented alongside researchers and practitioners from education, social work, nursing, psychology
  • 9. Included in research through the use of technology, participatory methods & skilled, creative advocacy workers: • Using mobile phones to organise their travel to and from the university • Presenters with learning disabilities able to tell their powerful stories of access through PowerPoint with pictures and video clips
  • 10. Writing partners: a voice in a previously inaccessible research world I took a risk taking the job at St George’s because I knew my benefits would go all over the place […] I took the risk because I thought I can’t live off benefits all my life. I don’t want to grow old and just sit there in an armchair and be bored out of my life. Butler, 2010
  • 11. But how did we “do” participatory data analysis”? • At the end of each seminar – Produced an accessible summary of each of the six seminars and distributed to all participants • At the end of year one: – presented a visual representation of emergent conceptual framework for discussion • At the end of year two: – Produced an accessible thematic analysis of themes running across all six seminars – Presented revised visual representation of conceptual framework which stiumulated group discussion and feedback
  • 12. Example Figure 12.2: Characteristics of risk embracing approaches to access Trusting Co-operative Letting go Creative Flexible Risk Embracing Building bonds and bridges Happy to let luck play a part High expectations of Prepared to take success a leap of faith
  • 13. Was the participatory data analysis “good enough”? REASONS TO STAND PROUD: REASONS TO PAUSE: • Analysis is grounded in the • Making data accessible is words and experiences of all complex participants • Extent to which disabled • Development of conceptual participants led data analysis framework was shared and is questionable, although it is negotiated clear they influenced it – Participants with learning disabilities were supported to contribute and advocate
  • 14. [2]: disabled students at university as equal partners in research AND design
  • 15. JISC funded Project • LEXDIS: Learner Experience Phase II • Team: Education, computer science, speech therapy/assistive technology • Produce 30 case studies describing disabled learners’ different e-learning experiences
  • 16. Overview of Participatory Phases • Phase One: Consultation regarding proposed research questions and research methods; • Phase Two: Opportunity to contribute own experiences of using e-learning, contributing artefacts of their own choosing; • Phase Three: Opportunity to validate and interpret the results of the study and to contribute to the design, content and dissemination of project deliverables and outcomes.
  • 17. Involving participants in the analysis of results • Held a focus group to share our initial interpretations of the data that we had collected and to invite participants to guide us in our analysis. – Why did we not train up some students to engage in the NVivo coding of interview data with us? • CHALLENGE 1- How do you present a mass of data in a way that all participants can access and interpret? • E.g. For dyslexic students need to think about structure and volume of information • E.g. For students with manual dexterity difficulties need to think about handling volumes of paper
  • 18. Involving participants in the analysis of results • Taking into account the varying abilities and needs of our participants, we chose to present the results in 6 summarised PowerPoint slides ( a real challenge!) and to give a verbal commentary. The main findings were summarised and presented to the participants as: – As a group you appear to be resourceful and adaptable learners; – As a group you appear to have a love-hate relationship with technology; – As a group you appear to be making informed, yet complex decisions about your use of technology. • For each of these findings, we asked the group whether they reflected their own personal experiences and views and whether we were misrepresenting the findings or missing something important from the results.
  • 19. Involving participants in the analysis of results • No-one expressed concern that the suggested analysis would falsely represent the experience of individuals or the group. – Challenge 2: Is this just acquiescence or a consequence of students simply not being empowered to do anything other than agree with us? • Participants felt comfortable enough to disagree with one another • Participants felt comfortable enough to disagree with researchers
  • 20. The pay-off: authenticity • Valuable information about participants perceptions regarding whether they represented typical disabled learners • Added authenticity to the students voices, which may enhance probability that the results will not be written off as unrepresentative
  • 21. [3] PAIRS: Participatory Inclusion Related Staff Development 1. Capture “student voices” regarding their learning experiences within the School of Education • Use these “voices” to explore whether and how our School of Education programmes (undergraduate and postgraduate) include or exclude students with a wide range of learning needs from experiencing positive or high quality learning opportunities 2. Involve students in the analysis and exploration of these “student voices” • Develop a collaborative partnership whereby students help to develop materials and methods that can be used to help staff in the work towards meeting learning needs and reducing barriers to inclusion.
  • 22. Phase One: Tell us your “stories” • Write or audio-record a one-two page letter to an “imaginary” friend • Write a diary describing learning experiences on course, over the period of a “typical” week; • Write a reflective journal that describes a “critical incident” • Produce a piece of creative writing or art (e.g. poem, picture, sculpture, song) • Alternatively, opt to be interviewed face-to-face, by phone or by webcam. • Focus for all stories: learning experiences and whether learning needs have been met
  • 23. Phase Two: help us understand the stories • Formed an advisory group that worked together to decide how we will use the information about student learning experiences to design staff development initiatives in the School.
  • 24. Phase 2: The analysis • 5 students (also phase 1 participants) consented to being members of an “advisory group” • Work and family commitments as well as distance (1 student had graduated) meant that all work done via email • Sent each participant three stories and asked them to code stories for themes or issues that they thought were significant – Using highlight and comment features in Word
  • 25. “Doh!” • The nature and quality of student “coding” was variable – Even though the majority were PG • I underestimated how hard participants might find this • Why did I assume that the students would be able to code transcripts in the way that I can/would? • Should have built in time to “train/induct” participants in analysis methods • In the end I “analysed the analysis” and produced a core set of themes, that I thought most of the students had identified and shared this with the group for approval
  • 26. The issues for reflection and discussion • Doing participatory research takes more time and effort than traditional research – The time required to do justice to participatory data analysis is underestimated, particularly capacity-building element • Is the ultimate goal of participatory research to enable co- researchers, particularly those who are marginalised in society, to take a lead in data analysis? – Does it matter if they don’t? • What motivates academics to do research and do they have enough self-awareness to share the data analysis “limelight” and let go of the assumed status that “being able to analyse data” has • Why bother?
  • 27. Why bother? Impact • Four years after the end of the project, the website is still having an impact on disabled students- students from all over the UK are contacting the team offering to add their own “case studies”.
  • 28. And finally a plug • ESRC funded seminar series: “Towards equal and active citizenship: pushing the boundaries of participatory research with people with learning disabilities” • First seminar- Plymouth, January 10th • Email jane.seale@plymouth.ac.uk if you would like to be put on mailing list and sent programme details

Editor's Notes

  1. http://tel.ioe.ac.uk/tel-seminars/teldi2012/TEL Digital Inclusion ConferenceJanuary 17th 2012Sheffield