exercise

Exercise: Critique the model response

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Critique the AI response

Read each claim and mark it as Verified, Unverified or Rejected. For each rejected claim, write a short justification.

○ 0 of 6 claims marked

Source: Claude Sonnet 4.6 · a prepared sample the whole class analyses.
Claim 1

Client-side prediction is a technique where the player's game client calculates in advance where their character will be, so that movements appear smooth even when latency is in the range of 80 to 150 milliseconds. When the server corrects the prediction, it is called server reconciliation.

Claim 2

SBMM, or skill-based matchmaking, attempts to pair players together based on their measured skill level. In many games, this is based on Elo-like systems or internal ratings that are not published publicly. This means a player can never see exactly why they are placed in certain matches.

Claim 3

Studies show that video games, especially shooter and fighting games, cause violent behavior in youth. This is one of the best-documented effects in the field of psychological research.

Claim 4

EOMM, or engagement-optimized matchmaking, is designed to maximize the time a player spends in the game rather than ensure fair matches. Former EA employees have confirmed in interviews that this approach has been introduced in some games, but Respawn, which EA owns, has denied that EOMM is used in Apex Legends.

Claim 5

Tick rate measures how many times per second the server updates the state of the game. Games like Counter-Strike 2 use 64 or 128 ticks per second on different servers, and players with a faster connection experience much less latency than those with a slow connection regardless of tick rate.

Claim 6

Loot box systems and reward loops in video games use variable ratio rewards similarly to how slot machines work, and Belgium has classified such systems as gambling when real money is put into them. This has led to several game companies modifying these systems in the Belgian market.

○ Mark 5 more claims (minimum 5 in total). Reject at least 2 claims (currently: 0)

Requirements: 5 claims marked · 2 rejected · 25 words of justification

Compare answers

Here you see two different ways to ask the AI for the same thing. Choose the answer you trust more and write a short justification, and the explanation will open.

Comparison 1 of 2

Prompt

Compare two ways of asking an AI to explain what SBMM does in a competitive game, one that is too open-ended and the other that is precise and demands verifiable output.

Answer A

What does SBMM actually do in competitive games, and is it good or bad?

Answer B

Describe the SBMM system in Valorant from Riot Games: how is the skill rating calculated, what is the name of the internal rating that Riot uses (MMR), and in what cases might a system like EOMM come in instead of pure SBMM? Give me one example of a difference a player would notice if EOMM were optimizing for Engagement rather than fairness, and mention what data Riot has published about this.

- 0 / 5 words

- Choose an answer to continue

Comparison 2 of 2

Prompt

Compare two ways of asking an AI to analyze whether a specific aspect of your gaming experience is due to netcode or design choices.

Answer A

Why does my game go through sometimes? Is this netcode or just design?

Answer B

I play Fortnite on my 60 Mbit/s connection and notice that when I shoot at other players, the damage registration is delayed, i.e., I see myself shooting before the shot registers. Help me analyze whether this is likely due to client-side prediction correcting late, or because the game is designed to give the shooter the advantage, and how I can test this with network measurement tools like PingPlotter or game hardware diagnostics?

- 0 / 5 words

- Choose an answer to continue

Self-check rubric, accountability document

Mark each criterion once you have met it. When you mark it, a three-level descriptor opens, compare your own work against each level.

- 0 of 5 criteria confirmable

Final decision

No claims found. Finish the critique exercise first, that is where the accountability document draws your data from.