A Study of Legal Information Seeking Behaviour to Inform the Design of Electronic Legal Research Tools

Our work is motivated by the desire to support digital library users in ?getting to grips? with electronic resources. More specifically we are motivated by the desire to support users in understanding how to use, and in which situations it is appropriate to use, particular digital library or electronic resources. This work focuses on lawyers as a specific category of user; Callister [5] highlights that lawyers been traditionally regarded as having poor research skills. Electronic research skills are no exception: Howland and Lewis [8] surveyed U.S. law firm librarians to examine the quality and extent of the electronic legal research skills of summer clerks and first-year associates. They found that these graduates were unable to efficiently or effectively research issues that appear routinely in actual legal cases and concluded that they were not efficient or cost-effective users of LexisNexis and Westlaw (the two biggest digital law libraries in terms of case, legislation and journal coverage). This was despite all of the students having received some training on how to use the libraries while in law school. Digital libraries have traditionally been regarded as difficult to use [4] and based on our contextual observations with academic lawyers, digital law libraries such as LexisNexis Professional and Westlaw are no exception. We believe that this difficulty of use contributes to the problems that lawyers face with electronic legal research. Furthermore, we argue that developing better research skills goes hand-inhand with developing an understanding of the electronic environments in which these skills must be practiced. Our current work is focused on gaining a better understanding of legal academics? and professionals? information seeking behaviour when using existing electronic resources. This understanding will then be used to inform the design of user-centred support tools for digital law libraries (and potentially the design of the libraries themselves)

An original framework for understanding human actions and body language by using deep neural networks

The evolution of both fields of Computer Vision (CV) and Artificial Neural Networks (ANNs) has allowed the development of efficient automatic systems for the analysis of people's behaviour. By studying hand movements it is possible to recognize gestures, often used by people to communicate information in a non-verbal way. These gestures can also be used to control or interact with devices without physically touching them. In particular, sign language and semaphoric hand gestures are the two foremost areas of interest due to their importance in Human-Human Communication (HHC) and Human-Computer Interaction (HCI), respectively. While the processing of body movements play a key role in the action recognition and affective computing fields. The former is essential to understand how people act in an environment, while the latter tries to interpret people's emotions based on their poses and movements; both are essential tasks in many computer vision applications, including event recognition, and video surveillance. In this Ph.D. thesis, an original framework for understanding Actions and body language is presented. The framework is composed of three main modules: in the first one, a Long Short Term Memory Recurrent Neural Networks (LSTM-RNNs) based method for the Recognition of Sign Language and Semaphoric Hand Gestures is proposed; the second module presents a solution based on 2D skeleton and two-branch stacked LSTM-RNNs for action recognition in video sequences; finally, in the last module, a solution for basic non-acted emotion recognition by using 3D skeleton and Deep Neural Networks (DNNs) is provided. The performances of RNN-LSTMs are explored in depth, due to their ability to model the long term contextual information of temporal sequences, making them suitable for analysing body movements. All the modules were tested by using challenging datasets, well known in the state of the art, showing remarkable results compared to the current literature methods

In the MOOD for Citizen Psych-Science

People make funny, frustrating and fatal errors on a daily basis. People can also create and apply strategies to avoid and mitigate error – this is called cognitive resilience. Researchers at UCLIC started the Errordiary project in 2009 as a way of raising awareness of human error research. Errordiary (www.errordiary.org) is an online public repository of the errors people make and the cognitive resilience strategies that they use. People contribute to it by using the #errordiary #rsdiary hashtags through Twitter. Over 130 people have contributed so far. The project has allowed researchers to gain a better insight into the resilience strategies that people use (Furniss et al., 2012). It has also been used as a real-life data set for teaching students about the psychology of human error (Wiseman, 2012). During August 2013 we interviewed 8 Errordiary contributors (5 female, 3 male) to find out more about their motivations for taking part. Most of our participants described their contributions as “occasional”, where Errordiary contributions varied from once a week, once a month, to once every 6 months. As one participant describes, “I go through a period of not contributing for weeks and then remembering it exists.” One reason for this is that contributions are event-driven. People cannot contribute whenever they wish - it has to be once they’ve committed an error or used a resilience strategy. Some participants described forgetting to contribute. Those that were regular twitter users were more likely to remember. As one participant describes, “I was already sharing errors on Twitter, now it’s just adding a hashtag.” The content of the error also had an impact on contributions. Sometimes participants did not tweet an error because they thought others might view their contribution as “mundane” or “not funny.” Contributions are visible to a person’s Twitter network, which means they are visible to a volunteer’s followers that may not know about the project. This makes contributing to Errordiary quite different to most other citizen science projects, where people contribute within the “safety” of being among like-minded others who share their interests. A couple of participants even described how they had set up a separate Twitter account just for the purpose of contributing to Errordiary. This highlights an important issue in using Twitter for data collection, as volunteers make a trade-off between convenience and protecting their privacy. These findings also highlight some of the ways in which a citizen psych-science project differs from a typical citizen science project. In citizen science usually volunteers collect or analyse data related to their environment (Haklay, 2013). However in Errordiary, researchers are asking volunteers to contribute their experiences of error. This means that volunteers are helping to collaborate in research, but at the same time they are the participants of the research. We suggest that this makes contributing to Errordiary more personal, and perhaps more sensitive, compared to other projects. The risks associated with sharing errors (e.g. negative perceptions from others, being viewed as incompetent) may counteract a person’s general good will to help researchers. Overall our study reveals several interesting insights concerning the spectrum of citizen science, and pros and cons in using Twitter for data collection. The Errordiary project is currently changing from being an online archive of error to a hub to engage and learn about error. This includes a ‘Discovery Zone’, allowing volunteers to explore research, media and games related to errors. It is now also possible for volunteers to login and contribute via the website – so the project is no longer restricted to Twitter users only. We plan to explore how these changes impact volunteers’ experiences in future research. References: Furniss, D., Back, J. and Blandford, A. (2012). Cognitive resilience: Can we use Twitter to make strategies more tangible? Proceedings of ECCE 2012, 96-99. Haklay, M. (2013). Citizen science and volunteered geographic information: Overview and typology of participation. In D. Sui et al. (Eds.) Crowdsourcing Geographic Knowledge: VGI in Theory and Practice, pp.105-122. Springer Netherlands. Wiseman, S. (2012). Errordiary: Support for teaching human error. ‘A contextualized curriculum for HCI’ workshop at CHI 2012

Using formal game design methods to embed learning outcomes into game mechanics and avoid emergent behaviour

This paper offers an approach to designing game based learning experiences inspired by the Mechanics-Dynamics-Aesthetics (MDA) model (Hunicke et al, 2004) and the elemental tetrad (Schell, 2008) model for game design. A case for game based learning as an active and social learning experience is presented including arguments from both teachers and game designers concerning the value of games as learning tools. The MDA model is introduced with a classic game- based example and a non-game based observation of human behaviour demonstrating a negative effect of extrinsic motivators (Pink, 2011) and the need to closely align or embed learning outcomes into game mechanics in order to deliver an effective learning experience. The MDA model will then be applied to create a game based learning experience with the goal of teaching some of the aspects of using source code control to groups of Computer Science students. First, clear aims in terms of learning outcomes for the game are set out. Following the learning outcomes the iterative design process is explained with careful consideration and reflection on the impact of specific design decisions on the potential learning experience, and the reasons those decisions have been made and where there may be conflict between mechanics contributing to learning and mechanics for reasons of gameplay. The paper will conclude with an evaluation of results from a trial of computer science students and staff, and the perceived effectiveness of the game at delivering specific learning outcomes, and the approach for game design will be assessed

Patterns of interactions: user behaviour in response to search results

This paper presents patterns of users’ interaction when working with digital libraries. It focuses on strategies developed and applied by users over time to achieve their goals. Results show that users choose different patterns of interaction depending on their evaluation of results, particularly in terms of the number of results returned from a search. This study gives indications about how the user interface could better support users in developing different search strategies

The Challenges of Creating Connections and Raising Awareness: Experience from UCLIC

With current disciplinary structures and academic priorities, Human-Computer Interaction faces ongoing challenges: is it a discipline in its own right, or simply a sub-discipline of computer science, psychology or design? Is it a science or engineering discipline? Should it concern itself with developing theory or improving practice? UCLIC aims to find appropriate middle ways on such questions: it conducts scientifically-based HCI research with a view to improving practice, and thus have an impact on society. It is based in the disciplines of Psychology and Computer Science and promotes participation across the disciplines. Research and teaching cover cognitive, affective, physical, social and technical aspects of interactive system design and use. © IFIP International Federation for Information Processing 2007

Usability of Musical Digital Libraries: a Multimodal Analysis.

There has been substantial research on technical aspects of musical digital libraries, but comparatively little on usability aspects. We have evaluated four web-accessible music libraries, focusing particularly on features that are particular to music libraries, such as music retrieval mechanisms. Although the original focus of the work was on how modalities are combined within the interactions with such libraries, that was not where the main difficulties were found. Libraries were generally well designed for use of different modalities. The main challenges identified relate to the details of melody matching and to simplifying the choices of file format. These issues are discussed in detail. 1

Understanding people: A course on qualitative and quantitative HCI research methods

This course will provide an introduction to methods used in Human-Computer Interaction (HCI) research. An equal focus will be given to both the quantitative and qualitative research traditions used to understand people and interactional contexts. We shall discuss these major research traditions along with their contemporary framings (e.g., in-the-wild research and Interaction Science). By the end of the course attendees will have a detailed understanding of how to select and apply methods to address a range of problems that are of concern to contemporary HCI researchers

Research Methods for HCI: Understanding People Using Interactive Technologies

This course will provide an introduction to methods used in Human-Computer Interaction (HCI) research. An equal focus will be given to both the quantitative and qualitative research traditions used to understand people and interactional contexts. We shall discuss these major philosophical traditions along with their contemporary framings (e.g., in-the-wild research and Interaction Science). By the end of the course attendees will have a detailed understanding of how to select and apply methods to address a range of problems that are of concern to contemporary HCI researchers