Software development has evolved significantly. In the past, developers were required to have comprehensive understanding of programming languages, algorithms, and computer architecture. However, with the emergence of the Internet, software libraries, frameworks, and forums became widely available, which utilize reusable software components that can reduce development time and costs. The advent of Generative Artificial Intelligence (AI) tools, such as ChatGPT, GitHub Copilot, and Amazon CodeWhisperer, has further enhanced the developer's toolkit, as these tools can be used for a wide variety of tasks such as code generation, documentation, commenting and reviewing. As programming is often slow and requires trial and error, novice programmers can be tempted to apply the first solution found on the Internet or proposed by an AI tool without much critical reflection or notion of responsibility. Hence, the advances of AI have raised both excitement and concerns among Information Technology (IT)/Computer Science (CS) students and educators. Yet, AI tools are here to stay, and students must learn to use them responsibly. The aim of this paper is to investigate how to design learning activities that introduce Generative AI tools (GitHub Copilot and ChatGPT) for programming while promoting critical thinking practices among students in an introductory programming course in the first semester. Students' opinions and customs were surveyed before and after the AI-based programming assignment. The results indicate that students' awareness of the possibilities and limitations of AI, as well as practices of critical thinking in programming increased. This is encouraging as critical thinking is an integral part of best programming practices.

Teaching programming efficiently to students in the first year of computer science education is challenging. It is especially cumbersome to retain the interest of both groups, when the student group consists of novice (i.e., those who have never programmed before) and expert programmers in the same crowd. Thus, individualized teaching cannot be achieved in a traditional lecture hall for a larger student population setting and poses a pedagogical challenge. This article presents various pedagogical approaches and explores different assessment forms to foster student active learning (SAL), drawing from years of experience teaching a programming course. A detailed analysis has been conducted to understand the effect on the students’ learning and perception of a course given different pedagogical approaches and varied assessment forms. The analysis is based on a course offered across three different campuses with the same course description. The key difference between the campuses however is the choice of pedagogical approach, where one of the campuses uses a bottom-up pedagogy. In contrast, the other two campuses use the top-down pedagogy to teach programming concepts to the students. Across the three campuses, the assessment form in the course has varied from regular practical school exams together with a theoretical multiple choice format, a practical home exam during the pandemic and most recently a portfolio. The findings show no significant differences in the learning outcomes based on an analysis of the grades across campuses and extensive student surveys.

Web frameworks have significantly changed how developers create web applications for the Internet. Thanks to pre-defined libraries, these frameworks not only accelerate development time but also reduce the amount of code developers need to write. However, to get the most out of the frameworks and libraries, developers need to have a deep understanding of core web programming languages. This allows them to write efficient code, troubleshoot effectively, and push the boundaries of what the frameworks can achieve. The same principle applies to Generative Artificial Intelligence (AI) tools, as they have the potential to enhance a developer's toolkit. However, they will only be useful if the developer has sound fundamental knowledge to verify the output from these tools. Educators in higher education face a similar predicament with the widespread use of Generative AI tools by learners. Many learners rely on these tools as a go-to solution without being able to verify or fully comprehend the output, leading to shallow understanding. The work in this paper outlines an approach used in a first-year web programming module within the School of Electronic Engineering and Computer Science at Queen Mary University of London, where learners were encouraged to use Generative AI tools to stimulate critical thinking when conducting assessments. Specifically, GitHub CoPilot was used as a pair programmer, and ChatGPT served as a peer reviewer. In this context, the peer reviewer's role was to help the learner reflect on the tool's output. The aim of this study was to explore the design of active learning activities that incorporate Generative AI tools for web programming to foster critical thinking practices among learners. To evaluate our approach, we employed a critical thinking self-evaluation questionnaire instrument, where learners' opinions and customs were surveyed before and after both of the assignments.

Reducing light pollution and promoting sustainable lighting practices require new tools that integrate environmental, social, and technical considerations in design processes. Urban Digital Twins are emerging as powerful instruments for this purpose, enabling integrated evaluation of lighting impacts on both people and ecosystems. This paper presents an exploratory evaluation of NorDark-DT, a recently developed urban digital twin designed to support the sustainable planning of lighting infrastructure in green urban areas. This exploratory assessment was conducted with master’s students engaged in lighting design practices. Participants performed two task-oriented exercises of planning and comparing lighting configurations after-dark for a site in Uppsala, Sweden. Results show that NorDark-DT effectively facilitates the exploration of alternative lighting solutions within realistic green urban area contexts and encourages reflection on issues such as light pollution, biodiversity, and ecological preservation. Nevertheless, further improvements are required to enhance the user interface, expand analytical capabilities, strengthen integration with professional lighting software, and optimize performance for varying hardware setups. Beyond professional practice, the tool also proved valuable for educational purposes by promoting interdisciplinary collaboration and broadening students’ understanding of sustainability in lighting design. Overall, this study provides an initial step in a usability assessment of NorDark-DT, confirming its potential to support environmentally responsible, socially aware, and well-informed lighting interventions.