Course development

To address the feedback and improve future iterations of the course, the following changes are proposed: 1. Incorporating Practical Elements: o Introduce optional lab sessions or tutorials focusing on simple sensor network setups. o Offer a small project or simulation-based assignment using tools like MATLAB, Python, or NS3, allowing students to apply theoretical knowledge. 2. Balancing Time: o Streamline the theoretical content to prioritize key topics, creating space for practical components. o Explore blended learning approaches, such as pre-recorded lectures for foundational material, reserving live sessions for advanced topics or practical discussions. 3. Targeted Support for Diverse Audiences: o Provide additional support materials for continuous education students, such as primers on relevant background topics. o Offer advanced challenges for program students who may seek deeper technical insights. 4. Feedback Mechanisms: o Conduct mid-course surveys to gather timely feedback for iterative improvements during the semester. 5. Resource Development: o Seek collaboration with colleagues or industry professionals to develop hands-on modules or kits for sensor network demonstrations. o Explore funding opportunities to support the inclusion of practical tools and software licenses.