23  Discussion Prompts Hub

Collaborative Learning Activities for Study Groups

23.1 Discussion Prompts Hub

TipLearn Through Discussion

Research shows that explaining concepts to peers increases retention by 70%. Use these prompts for study groups, classroom discussions, or self-reflection.


23.2 How to Use These Prompts

  1. Solo Study: Use prompts as self-reflection questions
  2. Study Groups: Take turns defending different positions
  3. Classroom: Facilitate structured debates
  4. Online: Post responses to discussion forums

23.3 Protocol Selection Debates

23.3.1 MQTT vs CoAP

NoteDiscussion Prompt

Scenario: You’re designing a smart agriculture system with 500 soil moisture sensors across a 100-hectare farm. Sensors send readings every 15 minutes. Cellular connectivity is available but expensive.

Debate: Should you use MQTT or CoAP?

Team A (MQTT): Argue for persistent connections, QoS guarantees Team B (CoAP): Argue for lower overhead, UDP efficiency

Consider: - Power consumption per message - Handling intermittent connectivity - Cost per MB of cellular data - Message delivery guarantees needed

23.3.2 LoRaWAN vs Cellular IoT

NoteDiscussion Prompt

Scenario: A city wants to deploy 10,000 smart parking sensors. Each sensor reports occupancy changes (average 20 messages/day, 10 bytes each).

Debate: LoRaWAN or NB-IoT?

Key Questions: 1. What’s the 5-year total cost of ownership? 2. How does coverage differ in urban canyons? 3. What happens when technology standards evolve? 4. Who controls the infrastructure?

23.3.3 Wi-Fi vs BLE for Indoor Positioning

NoteDiscussion Prompt

Scenario: A hospital needs to track 200 medical equipment items in a 50,000 sq ft facility with 1-meter accuracy.

Debate: Wi-Fi RSSI fingerprinting vs BLE beacons?

Defend Your Position: - Infrastructure requirements - Battery life for asset tags - Accuracy achievable - Maintenance burden


23.4 Architecture Trade-offs

23.4.1 Edge vs Cloud Processing

NoteDiscussion Prompt

Scenario: A manufacturing plant monitors 1,000 machines with vibration sensors (1kHz sampling). Goal: Predict failures before they happen.

Question: Where should the ML inference run?

Position A: Edge processing - Lower latency for real-time alerts - Bandwidth savings - Works during network outages

Position B: Cloud processing - More powerful models - Centralized model updates - Cross-plant pattern detection

Your Task: Each person picks a position and must defend it for 3 minutes. Then switch sides.

23.4.2 Monolithic vs Microservices for IoT

NoteDiscussion Prompt

Scenario: A startup is building a fleet management platform expected to scale from 100 to 100,000 vehicles over 3 years.

Debate: Start with monolith or microservices?

Consider: - Team size and expertise - Time to market pressure - Operational complexity - Scaling requirements

23.4.3 Time-Series DB vs Traditional SQL

NoteDiscussion Prompt

Scenario: An energy company needs to store and query 10 years of smart meter data (15-minute intervals, 1 million meters).

Question: InfluxDB/TimescaleDB or PostgreSQL with proper indexing?

Discussion Points: 1. Query patterns (recent vs historical) 2. Compression requirements 3. Team’s existing expertise 4. Integration with BI tools


23.5 Security Dilemmas

23.5.1 Security vs Usability

NoteDiscussion Prompt

Scenario: A smart home company wants to add two-factor authentication for remote access. User research shows 40% of users abandon complex setup flows.

Dilemma: How do you balance security with user adoption?

Options to Debate: 1. Mandatory 2FA with guided setup 2. Optional 2FA with strong defaults 3. Risk-based authentication (2FA only for sensitive actions) 4. Hardware tokens included with purchase

Each Person: Pick an option and convince the group.

23.5.2 Open Source vs Proprietary Firmware

NoteDiscussion Prompt

Scenario: You’re choosing firmware for a new IoT product line. Budget allows either: - A) Open-source RTOS with community support - B) Commercial RTOS with vendor support contract

Debate the Trade-offs: - Security vulnerability response time - Long-term maintenance costs - Regulatory compliance evidence - Talent availability


23.6 Business & Ethics

23.6.1 Data Monetization Ethics

NoteDiscussion Prompt

Scenario: A fitness wearable company has anonymized health data from 10 million users. A pharma company offers $50M for access to study medication adherence patterns.

Question: Should they sell the data?

Positions: 1. Yes, with consent: Users agreed to terms of service 2. Yes, anonymized: No individual harm possible 3. No, trust violation: Users didn’t expect this use 4. Conditional: Only for beneficial research

Facilitator Note: This has no “right” answer - explore the reasoning.

23.6.2 Planned Obsolescence in IoT

NoteDiscussion Prompt

Scenario: A smart thermostat company must decide end-of-life policy. Hardware works fine but cloud services cost money to maintain.

Options: 1. End cloud support after 5 years (device becomes “dumb”) 2. Offer paid extended support subscription 3. Open-source the cloud backend for self-hosting 4. Design for 10+ year offline operation from start

Debate: What’s the ethical and business-appropriate approach?


23.7 Design Challenges

23.7.1 Battery vs Functionality

NoteDiscussion Prompt

Scenario: You’re designing a cattle health monitor (ear tag). Requirements: - 5-year battery life - GPS location (high power) - Temperature sensing (low power) - Heart rate monitoring (medium power)

Budget: Only one CR2032 battery fits the form factor.

Challenge: Which features do you include/exclude? Justify to your team.

23.7.2 Backward Compatibility

NoteDiscussion Prompt

Scenario: Your IoT platform has 50,000 deployed devices using Protocol v1. You’ve designed v2 with major security improvements, but it’s incompatible with v1.

Options: 1. Force upgrade (break v1 devices) 2. Maintain both indefinitely 3. Gateway translation layer 4. Phase out v1 over 2 years

Debate: What’s the responsible path forward?


23.8 Quick Discussion Starters

Use these 5-minute prompts to spark quick discussions:

Topic Prompt
Protocols “If you could only use ONE IoT protocol for all projects, which would it be and why?”
Security “What’s the biggest IoT security mistake you’ve seen or read about?”
Architecture “Edge or cloud - which will dominate IoT in 10 years?”
Business “Name an IoT product that failed. What was the root cause?”
Ethics “Should IoT devices be required to work offline indefinitely?”
Design “What’s more important: battery life or features?”
Standards “Are too many IoT standards a problem or a healthy ecosystem?”

23.9 Facilitator Guide

23.9.1 Running Effective Discussions

  1. Time-box: Set 3-5 minutes per position
  2. Devil’s advocate: Assign someone to argue the unpopular view
  3. No right answers: Focus on reasoning quality, not conclusions
  4. Summarize: End with key insights from both sides
  5. Connect: Relate to real-world examples when possible

23.9.2 Assessment Rubric (for instructors)

Criteria Excellent Good Developing
Evidence Cites specific technical facts Uses general knowledge Opinion without support
Trade-offs Acknowledges counterarguments Mentions limitations One-sided argument
Clarity Structured, easy to follow Mostly clear Disorganized
Engagement Asks questions, builds on others Participates Minimal interaction