A note on deep thinking and learning in the AI and social media era

A note on deep thinking and learning in the AI and social media era (information from perplexity.ai)

My question 1: "In the age of AI and social media browsing, suggest 4 advices on how gen y, z and alpha to enhance deep thinking and learning competence, notably in the context of Hong Kong"

The reply: "Gen Y, Z, and Alpha in Hong Kong face intense digital distractions from platforms like Instagram, Douyin, and TikTok, which shorten attention spans amid high-pressure academics and urban stress. These four practical pieces of advice can help build deep thinking and learning skills by prioritizing focus and reflection.

Schedule Deep Work Blocks

Dedicate 25-90 minute distraction-free sessions daily for intensive study, turning off notifications and using apps like Forest to block social media—essential in Hong Kong's cram-school culture where exploratory home learning boosts digital competence. Start with Pomodoro timers, gradually extending for subjects like MBA case analyses, mimicking Leonardo da Vinci's focused experimentation to counter TikTok's bite-sized habits.

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Practice Active Reading

Shift from scrolling to annotating physical books or long-form articles on topics like Western literature, summarizing in your own words to enhance retention and critical analysis—vital for countering Gen Z's preference for video content. In Hong Kong, join public library reading groups or use apps like Blinkist mindfully, applying insights to real issues like housing stress for deeper empathy and problem-solving.

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Curate Offline Communities

Build in-person study groups or mentorships via university clubs or co-working spaces in Fanling/North District, discussing ideas without screens to foster nuanced debates—addressing Gen Z's reliance on AI/social media for advice amid manager burnout. Weekly meetups for reverse mentoring on wicked problems like AI in finance can rebuild attention eroded by hybrid learning post-2019.

Use AI as a Reflection Tool

Leverage AI like ChatGPT for prompting deep questions on lecture notes (e.g., "Analyze pragmatism in Hong Kong housing policy"), then critique outputs manually to build analytical competence—flipping Gen Alpha's digital nativism into strength. Limit to 20 minutes daily, journaling insights to combat shallow processing, aligning with Hong Kong's AI literacy pushes."

My question 2: "Suggest 2 ways to study learning materials (e.g. on Business Management and Housing Studies) on YouTube that foster students' deep learning and thinking competence."

The reply: "YouTube offers accessible videos on Business Management and Housing Studies, but passive viewing risks shallow retention. These two methods transform it into deep learning by emphasizing active processing and reflection, ideal for part-time Hong Kong students balancing work.

Active Note-Taking Synthesis

Pause videos every 5-10 minutes to jot structured notes: key concepts, real-world Hong Kong examples (e.g., property policy critiques), and counterarguments—then rewrite in your own words linking to MBA cases like pragmatic urban planning. This builds analytical depth, countering Gen Z's short attention from social media, by turning lectures into personalized mind maps for dissertation synthesis.

Post-Video Application Challenges

After watching, apply concepts via self-set challenges: analyze a Housing Studies video on North District affordability against management theories, debating pros/cons in a journal or voice memo—discuss in study groups for feedback. Schedule weekly reviews of these outputs to refine thinking, fostering competence like da Vinci's iterative sketches amid Hong Kong's high-stakes exams"

A collection of blog notes on using chatgpt for research purpose.