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Independent Critical Analysis 30

Independent Critical Analysis 30 is an individual assessment that develops students' ability to critically analyse ethical, social, legal and professional issues arising from a computing-related scenario. The assessment is worth 30% of the overall module assessment and requires students to respond to three questions relating to the ethical and professional issues presented in the scenario. Students are expected to apply the specific analytical techniques or approaches identified in the assessment instructions when developing their responses. The assessment focuses on the critical examination of ethical issues and professional responsibilities within contemporary computing contexts. Students are expected to identify relevant ethical concerns and provide a reasoned justification for their analysis. The marking criteria emphasise the identification of a single ethical issue or ethical risk, followed by a structured analysis using the EHAZOP Framework. Higher-level responses are expected to provide clear justification for the ethical issue selected, examine the associated consequences, and demonstrate a systematic and critical approach to the scenario. A second component focuses on ethical risk analysis using the Ethical OS Toolkit. Students are expected to identify an ethical risk associated with the scenario and justify their selection through a structured analysis. The assessment therefore requires students to consider the potential consequences of computing-related decisions and to demonstrate an understanding of how ethical risks can be identified and evaluated. The final component addresses professional issues. Students are expected to identify relevant professional principles and apply an appropriate professional code of conduct, such as the ACM or BCS Code of Conduct, to the scenario. The analysis should explain which professional principles are relevant and provide a reasoned justification for their application. The marking criteria place emphasis on systematic analysis, appropriate justification and understanding of responsible computing practice. The assessment therefore connects ethical decision-making with professional responsibilities and standards. The assignment also assesses broader module learning outcomes relating to ethical standards, contemporary computing contexts, legal and professional issues, and the ability to critically analyse high-profile cases or case studies. Students are required to submit the provided answer sheet containing the scenario and three questions. The assessment brief states that submissions are subject to Turnitin and that students must follow the specified submission requirements.

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Computing and Digital Technologies 3,000 words

Contemporary Computing and Digital Technologies: AI Agents Hackathon Reflective Report

This postgraduate reflective assessment forms part of the Contemporary Computing and Digital Technologies module and is based on experiential learning undertaken through an AI-focused hackathon. The hackathon theme, “AI Agents Unleashed – Building the Future of Automation,” requires MSc students from computing-related disciplines to collaborate on intelligent agent-based solutions capable of automating complex tasks, solving real-world problems and supporting human decision-making. The hackathon encourages students to investigate agent-based system design, intelligent automation and responsible AI development. Potential applications include autonomous cybersecurity monitoring, multi-agent systems for information gathering and decision support, automated data pipelines, intelligent software-development assistants, and conversational systems such as virtual tutors or career coaches. Students may use code-based approaches or platforms such as Flowise, Microsoft Power Automate and Make.com, while more advanced implementations can use technologies including LangChain, AutoGen, Python-based agent SDKs, APIs and large language models. The 3,000-word Individual Reflective Report, worth 70% of the module assessment, evaluates the student's learning and professional development arising from these experiential activities. The first component is a 2,000-word Portfolio of Evidence, requiring evidence-based reflection on participation in the hackathon. Students should evaluate their leadership and teamwork competencies using concrete evidence such as screenshots, code commits and feedback while identifying key lessons for personal and professional development. They must also consider how the experience applies to future research, career development or professional practice. The remaining 1,000 words comprise a Critical Self-Reflection examining the student's personal contribution and achievement of learning-contract goals. Students are expected to critically consider challenges encountered, how those challenges were addressed, lessons learned and their development as effective collaborative team members. Overall, the assessment integrates technical experimentation, reflective practice, teamwork, leadership, professional development and responsible use of emerging AI technologies, supported by a structured portfolio of evidence

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