Why live online training is more effective than watching videos
Lefteris Ntaflos
09 Oct, 2023
1 Comment
1 Min Read
Why live online training is more effective than watching videos
Nowadays, more and more people are turning to live online training. They use it to learn new things and get better at what they do. When compared to just watching videos, live training has a lot of benefits. In fact, it makes learning more effective. So, let’s delve into some of these advantages next:
Real-time interaction
First and foremost, a big advantage of live training is the immediate exchange between the trainer and students. Specifically, this means students can raise questions about things they’re unsure of and receive answers on the spot. Simultaneously, the trainer can provide instant feedback on their progress. However, this kind of real-time conversation doesn’t occur with videos.
More engaging and motivating
Second, live training can be more fun and motivating for students. When they’re actively involved, they pay more attention. They can put new skills to use right away, talk with the trainer and other students, and see the fruits of their work quickly. Plus, this active learning makes the sessions more enjoyable.
Sense of community and collaboration
In addition, live online training also builds community. Students can chat and team up for tasks right away. They can share ideas and cheer each other on. In a video, a student is alone. They might only talk to others in the comments.
Personalized learning experience
Finally, live online training has a big advantage: it’s personalized. The trainer can change the lesson to match what each student needs. Some can get extra help with hard topics. Others can get separate tasks. With a video, everyone sees the same thing.
A trainee engaged in a live online training session from the comfort of their home.
At Grand Slam I.T. School, live online training is a more effective way to learn new skills and improve our knowledge: it offers real-time interaction, personalized learning, community and collaboration, flexibility, and engagement. With live online training, trainees can learn from the comfort of their own home while staying connected with their trainers and fellow trainees.
Dr. Lefteris Ntaflos is the Founder & CEO of Grand Slam I.T. and a Part-Time Lecturer at The Hong Kong University of Science and Technology, where he teaches two courses in the MSc AI and Entrepreneurship programme. With a unique blend of academic expertise and entrepreneurial leadership, Dr. Ntaflos brings multiple years of industry experience spanning technical training, business development, and AI research. His professional journey includes roles as Executive Director of Global Talent, Technical Trainer, and researcher. As an active mentor in the Ilitch School of Business Corporate Mentor Program and former organizer of hackUST and Fishackathon events, Dr. Ntaflos is passionate about bridging the gap between theoretical knowledge and practical implementation. His entrepreneurial background, combined with his technical proficiency in AI systems and emerging technologies, provides students with invaluable insights into both the theoretical foundations and real-world applications of machine learning systems in today’s rapidly evolving technological landscape.
Dr. Ntaflos holds a PhD in Computer Science from HKUST and an MEng in Electrical and Computer Engineering from the University of Patras, Greece. His research has appeared in PVLDB and The VLDB Journal, focusing on influence maximization, graph partitioning, and game-theoretic methods for large-scale networks. Beyond academia, he has led multinational talent development programs, and as lead organizer of hackUST 2017/2018, helped grow it into one of Asia’s largest student-run hackathons (800+ participants, 1M+ HKD funding). He has been recognized under Hong Kong’s Innovation and Technology Fund’s Technology Talent Scheme (Postdoctoral Hub) and received HKUST’s President’s 1-HKUST Student Life Award.
As a member of HKGCC’s European Committee, Dr. Ntaflos actively contributes to discussions on innovation, tech ecosystem building, and talent pipelines across Hong Kong and the region. His current interests include AI/ML systems engineering, GenAI productization, data-driven product management, and enterprise technology education, bringing industry-grade case studies and best practices into the classroom and executive training.
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Everything is very open with a precise clarification of the challenges. It was really informative. Your website is useful. Thanks for sharing!