The module aims to provide foundational readiness for students to further study in the area of IoT in Year 2. It follows a foundational year spine structure with the module focusing on developing IoT pathway specific student skills in the key areas of academic practice, IoT-pathway evidence collection and development, AI/digital-based inquiry and judgement within the context of IoT, IoT-related professional responsibility, and developing basic technical skills such as hardware development and integration, coding, AI integration in IoT and so on. The module fits within the wider framework of year 1 delivery as an Investigative Futures Seminars (IFS) module.
A. Investigate and explain IoT-related problems, principles, methods, and smart solutions using discipline specific academic and evidence-based communication skills. B. Demonstrate self-directed learning, problem solving and technical communication in IoT tasks, reflecting on IoT-related ethics, professional practice and personal skill development . C. Apply foundational technical and AI skills required in the context of IoT-related study, through demonstrating basic proficiency in simple AIoT device configuration, sensor use, simulation, experimentation and/or programming. D. Present and evaluate individual work, explaining decisions and recognising personal development needs.
The module will be delivered through one interactive lecture per week over 13weeks duration for pathway specific skill development and implementation. The lectures will allow students to explore and implement IoT-pathway specific knowledge and understanding. Students will learn the theoretical foundations of IoT, integration of AI into IoT, IoT solution development and hands-on knowledge of key elements and components to implement and support this development. The lectures will also cover range of methods, tools and techniques to develop AIoT + X pathway specific technical and non-technical skills such as impact/technical case studies, white papers, technical design and evaluation exercises, technical sources/evaluation, 3D models/artefact/prototype(s)/experiments, IoT-specific standards, data and models’ exploration, Generative AI tools and methods in the context of IoT, sustainability and best practices evaluation in the field of IoT engineering. The learning and teaching will directly align with IFS requirements for semester 2 around the areas such as i) pathway specific knowledge and evidence building ii) mastering the use of AI/digital practice iii) interpersonal and intrapersonal skills development iv) development of ethical consideration and practices within the field of IoT v) Year 2 readiness synthesis. Finally, the lectures will highlight future prospects of taking on IoT pathway that is integrated within the Syntegrative Education Framework. Students will be assessed through a single integrated individual CW which comprises two linked complementary elements completed individually and submitted together. These elements include i) AIoT pathway-specific technical tasks which will require students to demonstrate applied AIoT knowledge and/or lab-based practical skills through the design, setup, testing and demonstration of a simple AIoT focused technical activity (technical artefact or simulated model) ii) an integrated portfolio which is a structured collection of work throughout the module bringing together areas such as research and analysis of AIoT, log of technical work, decision making and experimentation choices, reflection on subject-specific professional responsibilities and ethics, as well as, review of own’s progress and skill development. The combined submission of the two elements will be either in the form of a single recorded video which will cover both the elements, or, a combination of recorded video focusing on technical aspect complemented by a reflective report focusing on integrated portfolio. These two elements together will evaluate and cover all the Learning Outcomes (LOs) of the module.