Figuring out how much detail you should provide in your reports and presentations is tricky. Ask and answer three questions to gauge at which level you should explain things.
Expertise
One thing I notice about my students’ writing, is that they include a lot of technical terms that they don’t explain. I find that one of the reasons for this is that the students assume that the reader is familiar with those technical terms, so they don’t need to explain. In part, this might be due to the students not realising how quickly they gain very specific expertise while working on a research project:
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| Source: xkcd 2501, copyright: Randall Munroe. |
It’s my job to help my students figure out who their audience is and how to adjust their communication to that audience. That’s what this post is about.
Who is my audience?
This is really the key question you should be asking whenever you are communicating. Whether it is a project report, a presentation, or even a meeting with your adviser.
Once upon a time I was an editor for Universum, an astronomy magazine for kids. My fellow editors and I were always looking for ways to improve our skills. This led to us taking a writing class with Jet Sebus, who specialises in teaching experts how to write for laypeople. Exactly what we needed.
She taught us to always ask (and answer!) the following questions:
- Who is my reader?
- What does my reader know/think/believe/want/do before reading my text?
- What should my reader know/think/believe/want/do after reading my text?
This generalises to other forms of communication (such as presentations and meetings), so I would suggest that you replace “reader” with “audience”.
Example: Robin
As an example of how to answer these questions, let’s consider Robin:
Robin is a 3rd-year Bachelor student at Delft University of Technology, majoring in Computer Science and Engineering. During their second year, Robin chose the Data track for their Variant Courses. During their third year, Robin did a minor on Offshore Wind Energy at the Faculty of Aerospace Engineering. Robin’s final project before getting their diploma is a 10-week research project. At the end of this project Robin has to present their findings in a report and a presentation.
All the students who I supervised for the Research Project (RP) struggled with deciding what to include and what to leave out in their reports and presentations. When that happens, I advise them to ask and answer the above questions. Let’s answer those questions together for Robin’s RP report.
Who is Robin’s reader?
This is a tricky one. After all: anyone might read Robin’s report and the presentations public events. Hence, Robin’s audience includes their supervisor, their external examiner, their fellow students, and maybe their friends and family. Quite a wide range. However, in academic educational settings, generally speaking, the expectation is that you write or present for your peers. That narrows it down.
In this case, Robin’s peers are fellow 3rd-year Bachelor students who did the same Computer Science program, but may not have chosen the same Variant Courses track, likely did not do the same minor, and definitely did not do the same research project as Robin.
What do Robin’s peers know/think/believe/want/do before reading Robin’s RP report?
Robin can reasonably assume that their peers have retained at least some knowledge from the courses that are in the main curriculum. Anything topic-specific that Robin had to learn during their project should be considered as unknown to their peers.
Without having specified a particular project, we cannot write specifics for the knowing/thinking/believing/wanting/doing part of the question. Furthermore, since Robin’s peers may not even have heard of the problem that Robin studied or the techniques they used, it is unlikely that Robin’s peers have any thoughts on that problem or those techniques at all. Hence, in answering this question it makes sense to stick to very high-level concepts that usually relate to the (potential) societal impact of Robin’s work. Familiarity with specific societal challenges will help motivate Robin’s work. Furthermore, we should consider which specific problems or techniques Robin’s audience should really know about and why. This helps Robin decide on what to include and exclude from their writing.
Below are some examples of statements that reflect what Robin’s peers might know/think/believe/want/do before reading Robin’s report, based on real student projects that I supervised over the last academic year. They are based on personal experience of Robin’s peers, on their general knowledge about the world, and on specific knowledge that they may have picked up in their classes:
- Probabilistic inference is computationally expensive.
- Personal privacy is important. Social science is important.
- Launching satellites is expensive.
- I want to get enough sleep, but I have way too many lectures that start at 8:45 am.
- I try to eat well, but planning a weekly menu that is nutritious and affordable takes way too long.
What should Robin’s peers know/think/believe/do after reading Robin’s RP report?
Generally speaking, we want academic texts to be standalone. Conceptually, this means that we want a member of the intended audience to be able to understand the main message of the text without having to read additional sources or appendices. Concretely, this means that a reader should be able to write a summary of the text. That summary should include answers to the “What, why, and how?” of the research.
It is Robin’s responsibility to include the information that the reader needs to be able to write that summary. Answering the question of what their reader should know after reading Robin’s report, combined with the answer to what they know before reading it, helps Robin to identify which knowledge gap they must fill.
Recall the example statements above, reflecting what Robin’s peers know/think/believe/want/do before reading their report. Below are companion statements for what they should know/think/believe/want/do after reading Robin’s report:
- Weighted model counting and knowledge compilation make probabilistic inference fast in practice.
- In order to study social phenomena, researchers need access to social network data. Sharing social network data for research can compromise the privacy of the people in those networks.
- There are several exact combinatorial solving methods that can compute the smallest number of satellites that we need for the task of monitoring the Earth for disasters.
- A clever implementation of a simulated annealing algorithm can come up with a lecture roster that better accommodates students’ preferences.
- By using integer linear programming techniques we can automate the task of coming up with varied and frugal weekly menus.
Having a list of what the audience knows and a list of what the audience should know after reading Robin’s report should help them answer the central question of this blog post: “Should I explain this?” If it is something that the audience can be expected to know: no. If it is something the audience cannot be expected to know, but is on the list of things they should know: yes. Finally, Robin may have to explain things that are not on the list of things the audience should know, but will help Robin bridge the knowledge gap for something that is on the list.
This also gives Robin a tool to test how well they did. Asking a fellow student to read a draft of their report and writing a 1/2-page summary gives Robin the opportunity to check if they filled the knowledge gap.
Knowing, thinking, believing, wanting, doing
Focus in the above was mostly on what the reader should know. However, the questions also specify “think/believe/want/do”.
As academics, we obviously don’t like being told what to think or believe or want. We do, however, write opinion pieces about where our research focus should be, what we should do to improve the quality of the research in our field, or about the ethics of (pursuing) certain research topics. Hence, you may find yourself in the position where you will need to convince others of your opinion. I believe that answering the above questions will help in that situation, also.
As for “doing”: academic writing contains implicit calls to action. When we build a new solver, we want people to see how great it is, and build on it or compare their own against it. When we curate a benchmark set, we want people to use it for their research. When we write a survey paper, we want people to read and cite it. These calls to action are often more explicit in and oral presentation. They may be spelled out on the slides, or said out loud. This is usually combined with an easy first step, like scanning a QR-code.
Hence, answers to the question of “what should my audience know/think/believe/want/do after listening to me?” may also include explicit calls to action, like:
- Use my tool to solve problem X.
- Use my benchmarks to validate your solver.
- Submit benchmarks to my competition.
- Read and cite my survey paper.
- Join the conversation on the future of research field Y.
What are your writing tips?
As I described above, I found answering these questions very helpful in streamlining my writing process. What is some good writing advice that you received and now pass on to others? Please share it with me?
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