Software Development Lifecycle

This first weekly session features a specially recorded video by the module leader for online learners, providing a comprehensive introduction to the module. The video outlines the significance of the subject and its interrelation with other modules. No preparation is required from students prior to this session.

The module leader will also provide a structured breakdown of the content to be covered in the subsequent 10 sessions. Students will access a dedicated learning portal, which will include essential reference materials and suggestions for supplementary reading. The format and criteria for the summative assessment will be clearly outlined to ensure understanding of expectations.

The video will also explain how the interactive learning platform utilises generative AI tools to enhance the learning experience, offering tailored resources and adaptive quizzes. A discussion board will promote peer interaction, allowing students to share insights and ask questions, while weekly reflection prompts will encourage critical thinking and deeper engagement with the material.

A dedicated section for submitting queries will ensure timely responses from the module leader. This structured approach promotes a high-quality academic experience, supporting student engagement and learning in an online environment.

Our institution's approach to teaching is primarily based on flipped learning. Ahead of each weekly session (Workshop/Lab), students will be required to study the essential concepts that are used in the coming session so they are familiar with the theories and ideas related to that session. The study material will be in the form of written content, illustrations, pre-recorded lectures and tutorials, and other forms of content provided through the AGS.

This content is self-navigated by the students, accommodating different learning styles and schedules, allowing students to watch or listen to them at their own pace and review them as needed.

Once each concept of the theory is studied, students will be prompted to engage in formative assessment with instant AI feedback. They include multiple-choice questions, socratic questions and answers, written questions, role-play and other AI-assisted practice scenarios.

The purpose of this automated formative assessment is to provide students with immediate feedback on their understanding of module material and highlight any areas that need support or further study. They are also used to track student progress, boost motivation and promote accountability.

In this learning activity, students explore recent real-world case studies relevant to their course topic. The case studies will have been selected and curated by the module leader to represent up-to-date examples. They guide students through key details, contextual factors, and outcomes. This approach enhances students' understanding of current industry trends, challenges, and solutions, preparing them for real-world scenarios they may encounter in their future careers.

The learning experienced will be augmented by AI (virtual private tutor) allowing the students to critically engage with the content and discuss the case studies.

For those studying in the self-paced online mode, live classes will be replaced by a set of flexible, self-directed activities designed to be completed independently. These include AI-led simulations, interactive videos, reflective prompts, and real-world case studies, all aimed at deepening understanding and fostering critical, independent thinking. AI avatars will simulate a classroom environment, allowing students to interact with virtual instructors for guidance or discussion, creating a more immersive experience. This structure promotes a high-quality, autonomous learning experience, equipping students with skills essential for both academic and professional success. Additionally, a dedicated feature for submitting questions to the module leader will provide timely responses and support.

Assignments will vary in format, including analytical essays, voice presentations, and individual projects. Instead of real-time group work, students will engage with AI avatars designed to simulate peer interactions. These avatars can provide guidance, pose questions, and simulate discussions, enhancing collaboration in a virtual setting. This approach will encourage students to work together effectively while utilising AI to generate insights and perspectives on their assignments.

Students will upload their completed assignments to the learning platform before the next weekly session. Timely feedback will be provided on each submitted task, helping students refine their understanding and enhance their skills. AI-driven feedback mechanisms will offer personalised insights, guiding students in areas for improvement.

This activity challenges students to engage with the reference material and independently explore and analyse academic literature related to the course topic. Students are expected to select relevant sources, practice critical reading skills, and where applicable technical skills, and synthesise information from multiple references. This is an opportunity to enhance research abilities, critical thinking, and self-directed learning skills while broadening and deepening subject knowledge.

Summative assessments are used to evaluate student learning at the end of a module. These assessments can take many forms, including exams, papers, or presentations. Instructors can use summative assessments to measure whether students have achieved the learning outcomes for the module and provide them with a sense of their overall progress. Summative assessments can also be used to evaluate the effectiveness of the teaching methods used in the module.