St Andrews HCI Research Group

 

Welcome to the website for SACHI which aims to act a focal point for human computer interaction research across the University of St Andrews and beyond.
SACHI is the St Andrews Computer Human Interaction research group (a HCI Group) based in the School of Computer Science. Members of SACHI co-supervise research students, collaborate on various projects and activities, share access to research equipment and our HCI laboratory. Established in 2011, we now have a regular seminar series, social activities, summer schools and organise workshops and conferences together. Along with the above links, you can find more news about us here.

News and Events

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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HCI meets Constraint Programming


Understanding How People Approach Constraint Modelling and Solving – University of St Andrews and University of Victoria

Ruth Hoffmann will be presenting the paper on “Understanding How People Approach Constraint Modelling and Solving” at the 28th International Conference on Principles and Practice of Constraint Programming (CP 2022) taking place between July 31 to August 5, 2022 in Haifa, Israel.

This paper is a joint collaboration between SACHI (Human Computer Interaction) and Constraint Programming groups, in both the University of St Andrews, Scotland and the University of Victoria, BC.

Abstract

Research in constraint programming typically focuses on problem solving efficiency. However, the way users conceptualise problems and communicate with constraint programming tools is often sidelined. How humans think about constraint problems can be important for the development of efficient tools that are useful to a broader audience. For example, a system incorporating knowledge on how people think about constraint problems can provide explanations to users and improve the communication between the human and the solver.
We present an initial step towards a better understanding of the human side of the constraint solving process. To our knowledge, this is the first human-centred study addressing how people approach constraint modelling and solving. We observed three sets of ten users each (constraint programmers, computer scientists and non-computer scientists) and analysed how they find solutions for well-known constraint problems. We found regularities offering clues about how to design systems that are more intelligible to humans.

Researchers

The paper can be found at: https://doi.org/10.4230/LIPIcs.CP.2022.28

Conference

Ruth will be presenting the paper in the main conference and giving an invited talk at ModRef 2022 to raise awareness of the benefits of understanding how people represent, model and solve constraint problems.

CP 2022 Conference link: https://easychair.org/smart-program/FLoC2022/CP-2022-08-03.html#talk:197219

ModRef 2022 link: https://easychair.org/smart-program/FLoC2022/ModRef-2022-07-31.html#talk:197355

More ModRef info: https://modref.github.io/ModRef2022.html#invtalks


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).