The use of Generative AI in software development is gaining traction. But what are the potentials and implications on software development education? We gathered insights on the use of Generative AI from professional software developers and make some pedagogical recommendations.

Learning is a lifelong process, especially in the fast-paced software industry. In addition to formal training courses, good software developers continually learn by reflecting on what they've done in the past. However, reflective practice is rarely taught explicitly in university software engineering education. One way to teach reflective techniques from the start is through studio-based learning.

Objective: To determine whether multiple computer use behaviours can distinguish between cognitively healthy older adults and those in the early stages of cognitive decline, and to investigate whether these behaviours are associated with cognitive and functional ability.Methods: Older adults with cognitive impairment (n = 20) and healthy controls (n = 24) completed assessments of cognitive and functional abilities and a series of semi‐directed computer tasks. Computer use behaviours were captured passively using bespoke software.Results: The profile of computer use behaviours was significantly different in cognitively impaired compared with cognitively healthy control participants including more frequent pauses, slower typing, and a higher proportion of mouse clicks. These behaviours were significantly associated with performance on cognitive and functional assessments, in particular, those related to memory.Conclusion: Unobtrusively capturing computer use behaviours offers the potential for early detection of neurodegeneration in non‐clinical settings, which could enable timely interventions to ultimately improve long‐term outcomes.

Background: People have various and changing needs as they age, and the number of people living with some form of dementia is steadily increasing. Smart homes have a unique potential to provide assisted living but are often designed rigidly with a specific and fixed problem in mind. Objectives: To make smart-ready homes and communities that can be adaptively and easily updated over time to support varying user needs and to deliver the needed assistance, empowerment, and living independence. Method: The design and deployment of programmable assistive environment for older adults. Results: The use of platform technology (a special form of what is known today as the Internet of Things or IoT) has enabled the decoupling of goal setting and application development from sensing and assistive technology deployment and insertion in the assistive environment. Personalising a smart home or changing its applications and its interfaces dynamically as the user needs change was possible and has been demonstrated successfully in one house – the Gator Tech Smart House. Scaling up the platform technology approach to a planned living community is underway at one of UK’s National Health Services (NHS) Healthy New Town projects. Conclusions: There is a great need to integrate technology with living spaces to provide assistance and independent living, but to smarten these spaces for lifelong living, the technology and the smart home applications must be flexible, adaptive, and changeable over time. However, people do not just live at home, they live in communities. Looking at the big picture (communities), as well as the small (homes), we consider how to progress beyond smart-ready homes towards smart-ready communities.

Studio-based teaching is a method commonly used in arts and design that emphasizes a physical "home" for students, problem-based and peer-based learning, and mentoring by academic staff rather than formal lectures. There have been some attempts to transfer studio-based teaching to software engineering education. In many ways, this is natural as software engineering has significant practical elements. However, attempts at software studios have usually ignored experiences and theory from arts and design studio teaching. There is therefore a lack of understanding of what "studio" really means, how well the concepts transfer to software engineering, and how effective studios are in practice. Without a clear definition of "studio", software studios cannot be properly evaluated for their impact on student learning nor can best and worst practices be shared between those who run studios. In this paper, we address this problem head-on by conducting a qualitative analysis of what "studio" really means in both arts and design. We carried out 15 interviews with a range of people with studio experiences and present an analysis and model for evaluation here. Our results suggest that there are many intertwined aspects that define studio education, but it is primarily the people and the culture that make a studio. Digital technology on the other hand can have an adverse effect on studios, unless properly recognised.