Supporting Remote Survey Data Analysis by Co-researchers with Learning Disabilities through Inclusive and Creative Practices and Data Science Approaches.

Universal & Inclusive DesignCollaborative Learning & Peer TeachingTelemedicine & Remote Patient MonitoringUniversity Professors & ResearchersSpecial Education TeachersHCI Researchers

Through a process of robust co-design, we created a bespoke accessible survey platform to explore the role of co-researchers with learning disabilities (LDs) in research design and analysis. A team of co-researchers used this system to create an online survey to challenge public understanding of LDs [3]. Here, we describe and evaluate the process of remotely co-analyzing the survey data across 30 meetings in a research team consisting of academics and non-academics with diverse abilities amid new COVID-19 lockdown challenges. Based on survey data with >1,500 responses, we first co-analyzed demographics using graphs and art & design approaches. Next, co-researchers co-analyzed the output of machine learning-based structural topic modelling (STM) applied to open-ended text responses. We derived an efficient five-steps STM co-analysis process for creative, inclusive, and critical engagement of data by co-researchers. Co-researchers observed that by trying to understand and impact public opinion, their own perspectives also changed.

Quick Actions

Share

Share this page

ios_share

https://hci.top/en/papers/dis/60136/2021

AdRecommended

Learn AI Coding at CodeNow

open_in_newOpen DOI Link
DOI: https://dl.acm.org/doi/10.1145/3461778.3462010
At a Glance

Paper Snapshot

fact_check
dataset
Source
DIS
calendar_month
Year
2021
emoji_events
Award
No award tagged
group
Authors
17 authors
sell
Subtopics
Universal & Inclusive Design, Collaborative Learning & Peer Teaching, Telemedicine & Remote Patient Monitoring
work
Professions
University Professors & Researchers, Special Education Teachers, HCI Researchers
article
Content Status
Abstract only
hub
Related Papers
0 related papers