The Future of Online Learning in Wireless Networks (2034)
Thoughts on the future of Learning Wireless Networks
Things I see we need to prepare for:
Highly-interactive simulations: Advanced troubleshooting on real complex wireless networks with AI-powered "virtual clients" using real behaviors and real issues. Provide an immersive environment to apply theoretical knowledge and develop real-life troubleshooting skills.
Gamified learning: Gamification elements like points, badges, and leader-boards will immerse Gen Z students into known competition elements. They will be challenged to identifying and resolving network issues within the real-world simulations. Difficulty levels will increase just like a game as the learner progresses through the course.
Real-time data analysis and visualization: Students will analyze real-time data from existing operational wireless networks. This will allow them to observe and understand complex network behavior firsthand in real-time. Coupled with advanced visualization tools for identifying patterns and anomalies.
Collaborative troubleshooting and case studies: Learners will work together in virtual environments to solve wireless network problems presented as case studies. Their peers will be worldwide much like the games they are playing today. This will foster teamwork and competition in problem-solving skills, in a global context.
Industry-specific focus: Courses will cater to specific needs of different industries, healthcare, manufacturing, or transportation. This enables the course to incorporate industry-specific scenarios and vendor equipment. The instructor could say "Run this simulation with a Cisco Meraki Model 36" Which although is current Top of the Line today, it will be EOL (End of Life) in 10 years. How does an End of Life Access Point impact this industrial scenario?
AR/VR-assisted learning: Artificial Reality glasses and Virtual Reality will overlay network information on the real-world. Allowing students to visualize signal strength, coverage zones, and interference sources all in simulations. Virtual Reality will create simulations of complex network deployments, like stadium Wi-Fi, Prisons WiFi, or smart city networks.
AI-powered personalized learning paths: Because all students learn differently, AI will suggest personalized learning paths, recommending specific modules, simulations, or resources catered to the students needs. Optimizing the students experience and progress.
Challenges and considerations:
With all good things come risk and challenges. Some of the things I see in the future that provide me pause involve both student issues and faculty issues. I also see issues for companies looking at these types of training.
Security and privacy:
For a student several issues surround Security and privacy, involved with Online training in 2034. In order for a student to participate in real world scenarios the Generative AI will learn fundamental behavior and knowledge levels of that student. Imagine being passed over for a position because a computer predicted that it was too advanced or too complex for that student? How much of a students behavior will be analyzed? Would AI be able to predict how a student would behave in a certain scenario? It will be recorded and it will be analyzed, the data is all there.
From a company standpoint. In order for a real world scenario to exist it has to be based on a real world network. That means a company will have put their entire network into a simulation. So now instead of black-hats stealing Personal Identification information, they will be able to steal a company's Network. Quite Literally. As a security professional this scares me. having an online existing simulation of my network out there that a nefarious individual could test against until they found a weakness? Very Scary.
Cost and access:
For a company standpoint, cost to play in this new world of 2034? With AI Nvidia cards going in the thousands and the shear number of processors required to run some of these complex scenarios, it's not going to be a poor man's game. Cost of entry for a company will involve dedicated resources and training that is going to be price prohibitive. Sure the entry price will come down as all things do, however that won't happen in the next 10 years. In fact prices will go up as more enhanced versions become available. Cheaper versions will exist but not to the current level of 2034. If you want a 2030 version we can let you have that for half price. If they are even available. 2024s backlog on processors is insane, as demand increase I don't expect that to change by 2034. Companies will be pre-ordering cards for 2038 in 2034.
It's going to be just as bad for a new student. When I started working on a CCIE in 1998 it cost $2500 to take a test. That's just the test. I was funded by a company so it wouldn't have impacted me, but for a student without backing or prior knowledge it just isn't going to be feasible. Today that same CCIE test is $1600 so it has come down some in price. But that price is every time you take the test. Nobody passes on the first try. A Generative AI test on a Wireless network utilizing resources in the Millions is not going to have an entry point at $2500. It'll be 10x that price, if the student can even gain access to proprietary information. How many companies are going to trust a student with the keys to the kingdom?
Faculty training: The other major issue I see is training for the new crop of instructors.
- Designing simulations utilizing AI, Fostering active participation and providing in a virtual space requires different skills than in-person. Understanding the vast amount of data generated by AI simulations and using it to will be crucial.
- Comfort with advanced technologies like AI and immersive simulations. Training should address navigation of the simulation platforms, utilize AI tools, and troubleshoot technical issues, as well as ethical considerations. Understanding biases of AI and helping make sure its fair for all students.
- Flexible training options: Online modules and self-paced learning opportunities can cater to diverse needs and schedules.
- Incentives and support: Providing financial assistance, course release time, and ongoing support can encourage participation, wireless simulation is not going to be cheap.
Conclusion:
Overall, the future of online learning in wireless network assessment holds huge potential for a more effective learning experience. By embracing innovative technologies and addressing the challenges, we can equip future network professionals with the skills and knowledge to navigate the increasingly complex world of wireless networks. Generative AI is coming, and students today need to know more about it. I’m not alone in positing that “The development of AI is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone. It will change the way people work, learn, travel, get health care, and communicate with each other.” (Gates 2023). How quickly can we embrace the change and empower the next generation of network professionals?
References
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Performing Network Wireless Assessments: A Field Guide for the Network Assurance Team," Oracle, Retrieved from “https://oracle.com/sharepoint___.html” Accessed February 18, 2024
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