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Social Software Engineering (Social SE), that is SE aiming to promote positive social change, is a rapidly emerging area. Here, software and digital artefacts are seen as tools for social change, rather than end products or 'solutions'. Moreover, Social SE requires a sustained buy-in from a range of stakeholders and end-users working in partnership with multidisciplinary software development teams often at a distance. This context poses new challenges to software engineering: it requires both an agile approach for handling uncertainties in the software development process, and the application of participatory, creative design processes to bridge the knowledge asymmetries and the geographical distances in the partnership. This paper argues for the role of design thinking in Social SE and highlights its implications for software engineering in general. It does so by reporting on the contributions that design thinkingand in particular physical design-has brought to (1) the problem space definition, (2) user requirements capture and (3) system feature design of a renewable energy forecasting system developed in partnership with a remote Scottish Island community.

This paper makes the case for the study of human values in Software Engineering (SE) as a highly important emerging area of research with significant societal implications. We offer two key principles in order to advance this research agenda: firstly, the significance of values as distinguished from, though connected to, ethics; and secondly, the need for clear theoretical frameworks for values study. We provide the emerging findings from an initial study (N=12 participants) using a Values Q-Sort tool that was designed in accordance with these two principles. We conclude with discussion around lessons learnt, ongoing challenges, and future directions. CCS CONCEPTS• Social and professional topics → Computing profession; • Software and its engineering;KEYWORDS human values, mixed methods, qualitative study, software industry ACM Reference Format:

This paper reports on the development of ongoing research into the systematic study of human values in software engineering (SE). Firstly, we outline the rationale for this work, highlighting the significance of human values in SE and the need for both a more structured approach to their study and tools to support their articulation in the SE domain. We then explain our theoretical framework, which draws on social psychology research on values. Secondly, we introduce tools designed in line with this framework and the context of their use so far. Our tools adopt a variety of research methods, including structured mixed-method techniques, such as the 'Values Q-Sort' (V-QS), and more open design-based methods, such as the 'Values Probes'. Given the multi-faceted nature of the topic, we argue that a combination of qualitative, quantitative and design thinking techniques is a necessary step for the study of human values in SE; and that these methods should be both a) robust and replicable, and b) creative and provocative. Finally, we highlight the potential applications of our tools in SE industry and education.

In many parts of the world, the electricity supply industry makes the task of dealing with unpredictable spikes and dips in production and demand invisible to consumers, maintaining a seemingly unlimited supply. A future increase in reliance on time-variable renewable sources of electricity may lead to greater fluctuations in supply. We engaged remote islanders as equal partners in a research project that investigated through technology-mediated enquiry the topic of synchronising energy consumption with supply, and together built a prototype renewable energy forecast display. A number of participants described a change in their practices, saving high energy tasks for times when local renewable energy was expected to be available, despite having no financial incentive to do so. The main contributions of this paper are in: 1) the results of co-development sessions exploring systems supporting synchronising consumption with supply and 2) the findings arising from the deployment of the prototype.