3.4 Use Your Own Work To Scaffold

If it ain’t broke, then don’t fix it.

Someone just starting in a research field might find the previous two sections’ methods for scaffolding topics very useful. A new researcher benefits from paying attention to a discipline’s conventions, or to a model manuscript. However, a more established researcher can rely on their own work to create a customized scaffold; one scaffold to use to launch several different writing projects. Established researchers often work on several related projects at the same time. By exploiting project similarity, you can develop a topics scaffold for repeated use.

A customized, reusable topics scaffold works well in a lab which explores one broad research topic, attempting to answer various questions related to the broad topic. Researchers in one lab might use different methods to explore different facets of the broader topic. They might also use similar methods to answer different questions inspired by the broad topic. Project similarities permit one topic scaffold to apply to several different projects carried out in one lab.

How might you create a tailored, reusable topics scaffold for yourself or for your lab members? You can use one or more successful writing projects of your own to provide questions for scaffolding topics.

I will use my own lab’s work to illustrate. My lab uses specific computer simulations, artificial neural networks, to provide a bridge between formal music theory and musical cognition. My lab members train networks to solve musical problems (e.g., to classify musical chords into particular chord types). They then examine the trained networks to determine how the networks solve musical problems, discovering new ideas for music theory, for musical cognition, or for finding relationships between these two research areas. When we write our research up, we try to describe the structure we discover in our networks, and to the importance of our discovery for music theory or musical cognition.

My lab has several publications related to our ‘musical networks’ project (Dawson, 2018; Dawson et al., 2020; Perez et al., 2023). Looking over the published papers, I see an emerging pattern. Our papers start by noting that many researchers use musical networks, but do not interpret network structure. The papers then argue many researchers mistakenly ignore network structure, because only by understanding network structure can a network contribute to theory. We then state our goal: to provide a case study to illustrate our approach, and to show the importance of understanding network structure. The papers then detail the case study, as well as the structure discovered in our trained networks. The papers end by noting the importance of the discovered structure.

I can convert the formula I see emerging from my lab’s publications about musical networks into a series of questions; each question provides a prompt for one or more topics to launch a paper’s outline. Table 3-2 (presented below) provides the questions. Table 3-2 provides a topics scaffold which my lab members can repeatedly use to begin outlining different papers related to our broader goals.

Table 3-2 represents a highly tailored version of the Table 3-1 IMRaD topics scaffold. The tailoring reflects the unique properties of the musical networks project. Table 3-2 eliminates many prompts from Table 3-1 because my lab’s research uses computer simulations (not human participants), and because we rarely train networks in different experimental conditions. Table 3-2’s early questions introduce my lab’s general goal, using artificial neural networks to inform how we can study music. The later questions generate topics required to describe a particular project.

Of course, Table 3-2 provides a scaffold uniquely suited to my lab’s goals. You will require a different scaffold, one customized to your own research goals. Fortunately, you can use the same approach to create your own custom topics scaffold: take one or more of your successful projects which relate to future work, reverse engineer the structure of your projects, and convert the structure into your own topic-generating questions to be used for your future projects.