DIS. Designing Interactive Systems (Conference) · 2021
Supporting Remote Survey Data Analysis by Co-researchers with Learning Disabilities through Inclusive and Creative Practices and Data Science Approaches.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
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Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Chapko Dorota, Rothstein Pedro, Emeh Lizzie, Frumiento Pino, Kennedy Donald, Mcnicholas David, Orjiekwe Ifeoma, Overton Michaela, Snead Mark, Steward Robyn, Sutton Jenny, Bradshaw Melissa, Jeffreys Evie, Gallia Will, Ewans Sarah, Williams Mark, Grierson Mick
Аннотация
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.