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Related Concept Videos

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Learning disabilities are cognitive disorders caused by neurological impairments that affect cognitive functions like language and reading, without indicating overall intellectual or developmental challenges. These disabilities differ from global intellectual or developmental disabilities as they are limited to distinct cognitive functions. Common learning disabilities include dysgraphia, dyslexia, and dyscalculia, each of which impacts unique aspects of learning.
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Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships. For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and...
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Supporting Remote Survey Data Analysis by Co-researchers with Learning Disabilities through Inclusive and Creative

Dorota Chapko1, Pedro Rothstein1, Lizzie Emeh

  • 1Creative Computing Institute, University of the Arts London, London, United Kingdom.

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|September 20, 2021
PubMed
Summary
This summary is machine-generated.

Co-researchers with learning disabilities (LDs) used an accessible platform to co-analyze survey data, developing an inclusive five-step process for machine learning analysis. This collaborative approach also shifted their own perspectives on public opinion.

Keywords:
Human-centered computing → Human computer interaction (HCI)Learning disabilityco-designsurveytopic model

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Area of Science:

  • Social Sciences
  • Computer Science
  • Disability Studies

Background:

  • Accessible research methodologies are crucial for inclusive participation.
  • The COVID-19 pandemic necessitated remote collaboration in research.
  • Understanding public perceptions of learning disabilities (LDs) requires diverse input.

Purpose of the Study:

  • To describe and evaluate a co-design process for an accessible survey platform.
  • To explore the role of co-researchers with LDs in remote data analysis.
  • To develop an inclusive method for analyzing qualitative data using machine learning.

Main Methods:

  • Co-design of a bespoke accessible survey platform.
  • Remote co-analysis of survey data (>1,500 responses) via 30 meetings.
  • Application of structural topic modelling (STM) to open-ended responses, co-analyzed by diverse research team members.

Main Results:

  • Development of an efficient five-step STM co-analysis process for creative and critical data engagement.
  • Successful co-analysis of demographic and textual data using graphical, art & design, and machine learning approaches.
  • Co-researchers reported shifts in their own perspectives while analyzing data aimed at influencing public opinion.

Conclusions:

  • Accessible platforms and co-design principles enable inclusive remote research participation.
  • The developed STM co-analysis process facilitates critical and creative engagement with complex data.
  • Collaborative data analysis can lead to personal growth and perspective transformation for co-researchers.