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.

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.

Programming is a relatively difficult skill to acquire; the mean worldwide pass rate of CS1 courses is 68%. Programming performance is also difficult to predict. Despite plentiful studies on the topic, there is no consensus of factors predicting performance. The problem escalates from academic institutions to the whole society, as IT industry craves more IT professionals and IT faculties suffer from numerous dropouts. The aim of this study is to consider performance and attrition in higher education IT studies from the perspective of IT majors. Students are regarded as experts by experience in the study. In developing administrative and pedagogical practices, their voices should be heard. The online survey utilised a novel three-phase question methodology combining open and closed questions to elicit initial, informed and prioritised opinions of the students. The survey was replicated to consolidate the results. Students' informed and prioritised opinions on factors contributing to success in computing studies emphasised will to learn, interest in IT, problem-solving, logical reasoning, self-directed information seeking, diligence and perseverance. Main reasons to consider discontinuing IT studies were experiences of difficulty, lack of motivation and lack of time. The top factors contributing to success in computing studies can be categorised into motivational factors, cognitive skill factors and self-directional engagement factors. Scarcities in the very same factor categories were also identified as causes of attrition. Students are expected to take responsibility for their studies, but young brains may not be mature for sufficient self-direction and engagement. The developed three-phase question strategy proved to be informative.

Context: Programming is a relatively difficult skill to acquire, the mean worldwide pass rate of CS1 courses being 67.7%. Programming aptitude is also difficult to predict. Solid and justified selection criteria are still disputable, which is disconcerting for both faculties and applicants. The problem becomes even more unsettling as IT industry is craving for more IT professionals and IT faculties are suffering from numerous dropouts.Goal: Programming requires a lot of reasoning, but reasoning has seldom been examined separately from mathematics in the student selections of computing disciplines in higher education. The aim of this study is to design and initially validate a novel assessment to measure reasoning skills in the entrance examination of bachelor level degree programmes in computing. Approach: Design science addresses research through creation and evaluation of new artifacts based on scientific enquiry. The design and validation of the assessment adhere to the Standards for Educational and Psychological Testing. The evaluation of the assessment included constructs and methods from both classical test theory and item response theory.Outcomes: The novel reasoning skills assessment was designed, reviewed, piloted and evaluated. The assessment measures applicants’ reasoning skills from various angles, with questions set in real world contexts. Preliminary analyses indicate acceptable validity and reliability. Reasoning skills assessment predicted performance in programming better than mathematics or verbal skills.Conclusions: The results suggest that reasoning skills are a viable predictor of performance in programming studies. More evidence for the validation of the assessment will be gathered in subsequent runs of the national entrance examination and questions refined accordingly.

Background: Higher education student selection has significant impact both on lives of young individuals but also on national economies. Current digital era calls for digital professionals. Countless applicants apply to study Computer Science (CS) and Information Technology (IT) each year worldwide. Thousands of them are left without the university place they aspire to. At the same time, these disciplines suffer from numerous dropouts.