IT to Support Doctoral Writing 

Dr Jennifer Boyle, Deputy Head of Student Learning Development, University of Glasgow

The use of IT to support learning, research and writing is currently a topic of debate in HE, most specifically in the context of generative AI and its uses. Beyond the discussion in HE, though, there is an array of tools available to support the writing process for doctoral researchers, ranging from note-taking tools to those which pitch themselves as ‘solutions’ for stress points in the research process. There’s also an increasing number of researchers (PGR-level and beyond) on YouTube and Twitter offering advice on how to ‘hack’ and ‘streamline’ and ‘power-up’ the research process – often by making use of these tools. Knowing what kinds of tools are out there and how they can be used responsibly can help not only in making recommendations to PGRs, but also offer insights into which parts of the writing process might be especially challenging. 

Literature Visualisation Tools 

Literature visualisation tools can be useful to help PGRs think about the ‘bigger picture’, particularly helpful if early drafts are taking more of a ‘patchwork quilt’ approach – stitching together paraphrases and quotations in a descriptive overview, but with no real sense of how ideas/researchers are related. There are many of these tools available, the best known possibly being Research Rabbit, Connected Papers and Lit Maps.  

These tools will essentially generate a ‘map’ consisting of nodes and connections, with papers cited more frequently appearing most prominent. The user can then choose to investigate these papers and connections, and perhaps add new/unfamiliar papers generated by the tool. This makes it relatively easy to amass a collection of papers for further reading. 

While they have similar aims, literature visualisation tools work in slightly different ways, and discuss the mechanisms behind their products with varying degrees of transparency. They’re also of varying degrees of usefulness for different subject areas: more useful for scientists, less so researchers in Arts – as they often don’t trace citations in books. 

Note-taking tools 

Obsidian and Notion can both be described as note-taking tools but, in reality, these tools can do much more than this, with various plug-ins and templates available to users. Notion offers a customisable workspace where users can additionally embed external sources. Users can take notes, categorise them, organise them, create tags, connect them to specific projects (or chapters or sections). They can also create timelines, to-do lists, create their own wiki pages and more: the space can essentially be as simple or as complex as they choose to make it. 

Obsidian is another note-taking tool with various plug-ins to enhance its functionality. Notes can also be connected, as they are in Notion, with the additional feature of the graph view, which allows user to look at the connections between their notes, discovering patterns and relationships between ideas.  

AI Research Assistants 

AI Research Assistants are tools like Elicit and Semantic Scholar. They usually market themselves as tools which will ‘speed up’ or ‘streamline’ the research process, automating time-consuming tasks for busy researchers. These tools will search academic databases, but then go beyond the work of a search engine, using specific tools and processes that allow them to identify the papers most relevant to the question asked, and then to summarise that information. They have additional functionality which allows users to create a research matrix, selecting the columns they decide are most relevant. 

These tools tend to be most relevant to researchers in the sciences. Elicit, in particular, works best for empirical research, and is probably most useful for researchers who are carrying out systematic reviews and/or meta-analyses.  

As an important note, the use of tools such as these should be distinguished from more troubling uses of AI technologies as part of the writing process. The University of Glasgow has recently published guidance for researchers on the responsible use of AI to support writing: Generative AI Guidance for Researchers. Other Universities may have similar policies in place, which you might wish to use to support important conversations on this emerging area of practice with your PGRs. 

Tools for specific situations 

As well as the tools described above, which are aimed explicitly at researchers, there are also those which are more general, but can still be very useful. 

The Pomodoro Method is a popular time blocking technique that many PGRs find useful as a way to break large complex tasks down and make them more manageable, as well as structuring their writing time to help create a regular practice. There are several pomodoro apps and sites – some simple, just to allow users to try the technique and track their progress, and other more complex – which can link up with other tools like Trello and Todoist. 

Time-tracking tools like RescueTime (which is downloaded and tracks what a user does on their computer over the course of a week) and Cold Turkey (which allows users to block specific websites at specific times of day) can be used to offer more insight into working patterns, and address issues like procrastination, or simply to manage distractions. 

There’s also the use of technology to facilitate connection between PGRs who have, or are trying to create, a regular writing practice. Many Universities facilitate virtual writing retreats to foster a sense of community and solidarity around writing, and to create settings in which peer-to-peer writing support can grow. For example, the University of Glasgow is part of an inter-university group who offer shared writing retreats over Zoom. Your institution may be involved, or offer something similar; if not, writing retreats are both really rewarding, and easy to set up. These sessions offer PGRs a regular online space to work alongside other researchers, setting goals and reflecting on progress. 

When to recommend tools? 

These tools can be incredibly useful, but they also need to be considered in the more specific context of individual PGR needs. Can these tools be universally recommended, or should they be discussed on a case-by-case basis with an understanding of a PGR’s needs and situation? For example, would a PGR who is struggling with critical reading and feeling overburdened with deadlines feel drawn to those tools which make promises about speeding up the process, simplifying tasks and reducing workload? A PGR who is already struggling might particularly need our guidance to help them assess which tools are and aren’t appropriate, and how they can best use them to support their own criticality, rather than supplant it. 

In the University of Glasgow’s Guidance on the use of Generative AI for researchers mentioned above, there are several key recommendations, including advice to researchers that they remember that when they use such tools, they are the experts, not the tech, and that they should be the ones to oversee, interrogate, and assess the output of any tools that they use.  But would a PGR struggling with workload and productivity, or a PGR who has had negative feedback on their work feel like an ‘expert’? The appeal and advantages of the tools described above are obvious, but their very appeal offers important insight into the most stressful aspects of writing for PGRs and allows for a wider conversation about how to manage these in a supportive and developmental way.