The paper is open access: Representational transformations: Using maps to write essays.
Summary of the paper and its findings
We built a tool to study how writers move between map and text to write essays. The main takeaway is that important cognitive work happens in the transformation process between map and text representations.
There are lots of existing tools for building representations to support complex cognitive tasks – e.g. argument maps, text, notes, slides, sketches, and so on. But tool support for the transformations *between* representations is much more neglected – and we think it’s crucial!
We built Write Reason, a tool which combines a text editor and a mapping interface. You can drag parts of the map into the text, and parts of the text into the map, and it helps you keep them in sync.
We then studied how 20 students used Write Reason to write essays. You can interactively explore the maps and essays built by participants. We identified key properties of transformations: change in representation type, cardinality, and explicitness. And we found that most used an all-at-once batch translation, while a few used bit-by-bit interleaving.
We think understanding transformations is crucial for building the next generation of multi-representational tools. How can we better support multi-transformation pipelines like these? Can automation unlock more complex + powerful workflows, which would be tedious to do manually?
Our findings revealed and falsified some of the key implicit assumptions that we baked into the design of Write Reason. We hope that these reflections will help other designers and researchers start one step ahead of us and avoid these mistakes!
