GAAD TAKEOVER WEEK: How Do Disabled Students Use and View Generative AI Tools at the University of Sheffield
By Xin Zhao, Andrew Cox, Bryan Coleman, Xuanning Chen
The appearance of a growing range of generative AI-based services used by students has created controversy across Higher Education. Concerns have been raised about their impact particularly regarding academic integrity, personal privacy breaches, and misinformation (Zhao, Cox, & Cai, 2024).
Despite these concerns, these new services also potentially offer significant benefits, in enhancing writing quality, work efficiency, and employability (OECD, 2023; Ding, Zhao, & Wang, 2024; Zhao, Xu, & Cox, 2024). In particular, they have the potential to level the playing field for disabled student groups (Arora, 2024). Currently, there is limited research about how students use generative AI tools in self-directed learning, especially how disabled students use them.
To inform the University of Sheffield's policies and practices in supporting disabled students, the Information School and the Disability and Dyslexia Support Service (DDSS) conducted a collaborative survey.
Informed by the results of a previous interview-based study (Zhao, Cox, & Cai, 2024), the questionnaire was organised in three main sections: Demographic data, Disability-related questions, General GenAI usage and views. This blog covers some of the key findings of the survey report and highlights our recommendations for staff who are interested in or have a responsibility for supporting disabled students at the University of Sheffield. A detailed report on the survey can be found here.
Participants
As of February 2024, the University of Sheffield has 7188 disabled students.The survey gathered 124 valid responses from disabled students. Most participants identified themselves as female (57%) or male (28%). The majority of respondents were pursuing a bachelor's degree (69%, n=85), followed by 20% (n=25) studying for a master's degree. Students came from a wide range of departments, with the largest representation from Bioscience (12%, n=15). 95% (n=118) of participants reported that English was their native language. In terms of digital competence, most participants rated themselves as having an intermediate (61%, n=75) or advanced level of skills (27%, n=33)
Disability Conditions Affecting Students' Academic Writing
The three groups of disability that were most common among questionnaire respondents were: 1) neurodiversity, including ADHD (34.7%, n=43), 2) specific learning difficulties such as dyslexia and dyspraxia (29%, n=36), or 3) and social/communication impairments such as autism spectrum conditions (21.8%, n=27). The response rate from these groups suggests that they that see value in generative AI. It is important to note that some students disclosed having more than one condition in this survey.
Main Barriers to Writing Associated With the Identified Conditions
Given that a significant portion of survey participants reported neurodiversity, with ADHD (34.7%) and specific learning difficulties like dyslexia and dyspraxia (29%), the main barriers encountered in the writing process may stem from these conditions. Open-text data on challenges in writing suggest students face the following barriers:
- Difficulty in understanding assignment briefs and rubrics, particularly in grasping expectations and interpreting hints or prompts.
- Mental blocks, characterised by difficulty in translating thoughts into written words, experiencing brain fog, and mind blanks.
- Low motivation or difficulty in maintaining concentration levels for writing, often attributed to fatigue and stress.
- The need for extra time for reading and writing tasks.
- Struggles with the reading and proofreading/editing stages.
- Challenges in word choice.
- Writing structure issues, such as organising sentences and paragraphs effectively.
- Finding an appropriate tone of voice and writing style.
- Time management challenges
Many students said they use GenAI to summarise reading materials, a preference that may stem from difficulties with word reading accuracy or fluency. Another notable finding is that students reported GenAI tools help them overcome mental blocks. This is followed in frequency of mention by the use of these tools to support the idea-generation process, structuring assignments, rewrite and paraphrase text. These usages correlate with the challenges that students reported during their writing process in the above section.
- General/introductory training on GenAI
- Training on how to use GenAI effectively
- Training on avoiding unfair means and unethical uses
- Writing prompts
- How to use GenAI to search for information
- How to fact-check or reference information from GenAI
- How to use GenAI for summarising texts effectively
- Introduction to a wider range of tools available for students
- Who needs support.
- Policy
- AI literacy
- Training.
- Signpost students to existing GenAI training provided by the university, including advice on effective prompt engineering targeting support for students in summarising reading, overcoming mental blocks, brainstorming ideas, and structuring assignments.
- Design training on university recommended GenAI tools and how to effectively use them in the context of disability, particularly focusing on Google Gemini (although ChatGPT is the favourite one), Translation tools (Google Translate, DeepL), Proofreading and Rewrite Tools (GrammarlyGO, Quillbot), addressing barriers including translating thoughts into writing and motivation.
- Design training on how to critically engage with information provided by GenAI, including fact-checking, finding and referencing original sources.
- Equity in access to GenAI tools.
- Given their popularity and usefulness, it might be appropriate to provide subscriptions for students to tools such as GrammarlyGO and possibly translation tools.