St Andrews HCI Research Group

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HCI Staff Position at SACHI


Come and join our group! We are currently advertising for a new staff member to join our HCI group at the School of Computer Science.


Supporting the expansion and development of the SAHCI group, topics of interest include but are not limited to: tangible computing, digital fabrication, ubiquitous computing, information visualization, human-centered artificial intelligence, augmented reality, novel software and hardware interactions, and critical HCI. Expertise in the field of HCI and technical expertise in the creation of hardware and or software interactions is of particular interest.


For more details: https://www.jobs.ac.uk/job/CRS296/lecturer-senior-lecturer-reader-in-human-computer-interaction-ac7180gb


Closing Date: 17th August 2022


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Congratulations to Adam Binks, Alice Toniolo and Miguel Nacenta on publishing their paper ‘Representational transformations: Using maps to write essays’


The paper is open access: Representational transformations: Using maps to write essays.

Summary of the paper and its findings

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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. 

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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?

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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!

Project page. Paper (open access).

Congratulations Dr. Carneiro & Dr. Carson


Thrilled to see Iain and Guilherme graduating this week. Congratulations on your well-deserved success Dr. Carneiro & Dr. Carson!