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On this page, you can track the course's development over time. Once the course analysis is published, data for each course offering is displayed, including the number of registered students, course results, and planned improvements for the next session. All course syllabuses and course memos are shown on the page Archive.

The information can help prospective, current, and former students with course selection, or to follow up on their own participation. Teachers, course coordinators, examiners, program directors, and others can use the page as a resource for course development.

2025

Course analysis not published

2024

Autumn 2024-10123 ( Start date 26 Aug 2024, English )

Changes planned for the next course offering

No information inserted
Coordinator
Carlo Fischione
Examiners
Carlo Fischione
Students
9
Course syllabus
Course syllabus EP271V ( Autumn 2022 - )
Course memo
No course memo added
Compulsory within programme
No information inserted
Course analysis
Course analysis EP271V: 11 Jan 2025
Changes introduced for this course offering
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.

Course data has been registered manually

Examination grade
70%*