6 research outputs found
Proceedings of the 7th Python in Science conference
International audienceThe SciPy conference provides a unique opportunity to learn and affect what is happening in the realm of scientific computing with Python. Attendees have the opportunity to review the available tools and how they apply to specific problems. By providing a forum for developers to share their Python expertise with the wider commercial, academic, and research communities, this conference fosters collaboration and facilitates the sharing of software components, techniques and a vision for high level language use in scientific computing
A Method for Anticipation of Undesirable Interactions in Software for a Digital Society informed by a Thematic Analysis of Discovery Practice
This research explores current user experience design practice in the IT sector through empirical studies with practitioners. The focus is how interactions that are undesirable are identified, because they are contrary to the interests of the users. The practice area of interest is the discovery stage when designers are working to understand the user’s aims and identifying opportunities to achieve the desired outcomes.
Two research questions are explored: what methods are used in current software design practice to identify undesirable interactions during discovery activities, and how can designers be helped to structure their work in a way that assists them in identifying undesirable interactions.
Three empirical studies were conducted with user experience practitioners. The first used Ketso workshops to gather data on discovery goals, practices, and challenges. These informed the second study, which used interviews to gather data on attitudes and practices. Reflexive thematic analysis was used to analyse findings. Using findings from the first two studies and lessons from the existing literature, I developed a new method of anticipating undesirable interactions by identifying ethical properties that the design should preserve and considering how they might be lost. This Jeopardy Analysis method was evaluated in the third study through remote workshops with user experience design practitioners who were asked to apply it to an unfamiliar scenario and provide feedback on its use.
Findings about current practice from the first two studies indicate that user experience practitioners favour methods that build a shared understanding, but select them to suit the context. They tailor their approach, and actively explore and experiment with new methods. There was some recognition of the need to anticipate problems, but no methods were applied at the discovery stage, instead relying on usability testing.
The evaluation of the Jeopardy Analysis method found that it helped to challenge assumptions. Practitioners found framing the problem in ethical terms unfamiliar and difficult, but felt they could use it by themselves with more practice. The generic properties used for the evaluation were found to be too abstract, so the method step tailoring them for the domain would be an important part of its application.
The research contributes insights into the goals practitioners have for their discovery activities, and their current approaches to identifying undesirable interactions. It identifies practitioner interest in recent ‘consequence scanning’ approaches to anticipating problems that differ from current practice, and are associated with a more risk averse mindset. It contributes a novel Jeopardy Analysis method, and reports encouraging results from its initial evaluation.
Further work is needed to refine Jeopardy Analysis for use in industry, and to evaluate practitioner selection of ethical properties tailored to their domain and product. Its natural domain of use is seen as software applications supporting life in our increasingly digital society, where the general public are co-opted into our designs, and the ethical case for intervention is most compelling. Extension of Jeopardy Analysis to involve prospective users in co-analysis and design would further address the potential imbalances of power in current practices. It is suggested that teaching Jeopardy Analysis in higher education settings would contribute to learning outcomes in inclusive design, societal impact, the making of ethical choices, risk management, and the recognition of responsibilities
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Constructionism through mobile interactive knowledge elicitation (MIKE) in human-computer interaction
Mobile computing holds significant as-yet unknown applications of interest in the field of Cyberscience (e-Science) methods. This thesis provides a diverse exploration into the advancement of HC1 theory through the development and testing of mobile cyberscience tools. This is done by synthesising new metrics from learning epistemologies, with the benefits that can be provided by mobile computing solutions.
This thesis aims to explore how mobile cyberscience can improve HCI knowledge elicitation (KE) methods. A review of the current state of the art in mobile computing and mobile HCI demonstrates that there is very little reported research in the direction of applying mobile computing to HCI theory (rather than the reverse which is demonstrated to be significantly considered in academia). This motivates a review of the current methods and cyberscience-based tools in the domain of KE in HCI, with several prototype mobile tool designs discussed. A review of candidate grounding theories in pedagogical epistemologies is then covered to build a theoretical foundation for this work. This facilitates the acquisition of a mobile-applicable investigation candidate, namely Constructionism theory, for software modelling in mobile computing methods in HCI KE. A framework for investigating constructionism is designed and presented, describing three key models that extend the domain of HCI KE theory. Through the design, implementation and testing (both expert and user testing) of several mobile computing tools for HCI KE, termed MIKE (Mobile Interactive Knowledge Elicitation) tools, these three key models of constructionism are explored through empirical research and are reported in this thesis as separate case studies.
Case study 1 investigates the use of inert constructionism through the use of card sorting. Case Study 2 investigates the use of semi-dynamic constructionism through the use of affinity diagramming. Case Study 3 investigates the use of dynamic constructionism, through the use of low fidelity paper prototyping. The findings from these case studies indicate that mobile cyberscience has a significant scope for application in the practice of current-day HCI methods, and that new qualitative measures in HCI can be acquired through mobile cyberscience tools.
There are three main contributions of this thesis that provide practitioners, educators and researchers in HCI with new knowledge. Firstly, the fields of mobile computing and mobile HCI are expanded with the empirically tested simulation of the techniques of card sorting, affinity diagramming and low-fidelity paper prototyping in HCI theory through mobile software. Secondly, a developed framework of constructionism theory successfully enhances the field of HCI KE, contributing to the growth of grounding theories in the field of HCI through the findings of three separately reported case studies. Lastly, cyberscience research for HCI has been given an expansion of research in the area of augmenting HCI with mobile computing. This is achieved through the user centred design, development and user testing of several mobile tools incorporating facilities unique to HCI practitioners, educators and researchers, leading to several related peer-reviewed publications