Digital Skills | IoT
February 4, 2020

Addressing challenges for teaching the Internet of Things

By Anna Forster

The Internet of Things (IoT) has become one of the fastest growing fields and an increasing number of jobs require expertise in this field. Yet very few academic institutions offer targeted degrees in the field of IoT.

The Internet of Things is changing how we interact with the world around us. Connected smart watches can provide real-time insights into our health and wellbeing; smart home devices such as connected refrigerators and lights can increase energy efficiency; and connected streetlights can help to manage traffic flow during peak rush-hour.

As more devices become connected, we need to ensure that today’s students have the right skills to drive this technology forward.

Challenges facing IoT educators

Designing a curriculum to teach IoT can be a challenge, in part because IoT is not a stand-alone technology, scientific discipline or paradigm. Rather, it is a combination of existing and well-established fields, including communication networks, embedded programming, artificial intelligence and computer security.

Students must be equipped with the right tools and skills to keep up-to-date with the extremely fast pace of their field.

Education professionals must find a way to combine these rather isolated fields together into a meaningful programme, and to explore and teach their interactions. Additionally, students need to obtain practical experience.

Students must be equipped with the right tools and skills to keep up-to-date with the extremely fast pace of their field. The market is nowadays exploding with new products, technologies and standards; what they learn during their studies will surely be outdated by the time of their graduation.

Therefore, a successful IoT curriculum is built on three dimensions: technical content, soft skills and teaching paradigms.

Technical content

IoT is not really a scientific area. Rather, it is a business or application domain, combining recent innovations in communication, machine learning, data analytics and embedded computing. These areas have enabled new application areas, where computation can be performed on small devices, which communicate directly to each other without the intervention of people.

Therefore, several core technical concepts need to be covered for a successful degree in IoT, including:

  • General introduction and application scenarios.
  • Computer communications and protocols.
  • Computer security and encryption. Here, three main topics need to be covered and their social, financial and political implications discussed: data privacy, encryption and IoT security.
  • Application development and programming.
  • Energy consumption and harvesting. Two main topics need to be covered here: how to save energy by hardware and software design and how to harvest energy in a sustainable way.
  • IoT deployment and maintenance. This includes how to plan, deploy and maintain an IoT system. Problems include energy availability, first-time and ongoing configurations of the components, error tracking, hardware and software updates. Cost calculation is also important, with separate estimates of investment costs and maintenance costs.
  • Data analytics and machine learning. The data analysis stages are: Gathering the data and transmitting it to a central place; analysing and representing the data; high level analysis and decision making.
  • Cloud computing.
Soft skills

Soft skills as all skills, which are not purely technical. Typical examples are presentation skills, general computer literacy or time management. Soft skills become more and more important, but are rarely targeted in academic curricula.

The most important soft skills for future IoT experts include:

  • ability to find information about new products, technologies and paradigms, without external help;
  • ability to grasp new technologies and paradigms quickly and compare them to existing ones; abstraction from details;
  • ability to see and understand interconnections between different technologies and paradigms;
  • ability to lead large development projects.
Teaching paradigms

IoT should be taught only at the graduate level, based on solid technical foundations, such as an undergraduate programme in computer science, electrical engineering, computer engineering or similar.

A successful training programme in IoT combines a technical background with practical experience and soft skills development to provide the students with the necessary skills to flourish in the IoT field.

We cannot only rely on the traditional lecturing/ tutorial/exam system for successfully teaching IoT. When observing students at the University of Bremen, for example, they could not follow theoretical explanations when experts simply share their experiences with them; once they are faced with the problem themselves, they are not able to transfer the lecturing material to their problem. Therefore. hands-on experience is crucial and should comprise at least two-thirds of an IoT curriculum.

Successful tools and paradigms for teaching IoT are ones that change the game continuously. These can include:

  • Short technical lectures. Traditional, short lectures covering complex technical matters, still represent an effective teaching method, but the students must be enabled to interact and discuss with the lecturer.
  • In-class open discussions
  • In-class assignments and tests. Longer lectures should be interrupted regularly with exercises, processed and discussed immediately to encourage a deeper understanding of the subject.
  • Peer review exercises. These are slightly different from usual exercises. Students are asked to first individually work on an exercise and submit their results. Without revealing the results, the students are then asked to work in teams on the same problem and to submit their results once more. Both results are shown and discussed.
  • Poster sessions are very useful for processing and reflecting on scientific publications or technical standards. Rather than lectures with content, the students are given reading exercises, which are summarized and presented in a poster session.
  • Lab exercises are very important for teaching IoT and go beyond normal in-class exercises. Usually, the teachers prepare a hardware/ software setup, which enables the students to quickly test and make their own small modifications. Topics include different programming environments and tools, hardware components, and communication protocols.
  • Projects are well suited for summarizing and combining all new knowledge from longer periods of time.
  • Blended learning, such as online videos and exercises.
Developing an IoT training programme

The combination of the above paradigms keeps the students agile and flexible, and teaches them to quickly adapt to new “rules” in this shifting field.

Unfortunately, teaching and training efforts have not been well organized to date. Training programmes have focused mainly on technical content to help students enter the market quickly – without much focus on supporting their continued development in the field.

Therefore, a successful training programme in IoT combines a technical background with practical experience and soft skills development to provide the students with the necessary skills to flourish in the IoT field.

*Read the full article in the Digital Skills Insights 2019 publication.


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Addressing challenges for teaching the Internet of Things

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