
Pokémon Card Math: One-Day Class
Laxman Shastri Joshi
Ages 6–8 · 30 min · 1 / Week
$19.00per classSee schedule

An eight-week course for ages 11-14 on adaptive game design. Learners track player data in Roblox and code games that adjust difficulty automatically based on how players perform.

Paid once.
Have you ever noticed a game getting a little easier after you fail several times? That is adaptive difficulty, a simple form of a game learning from its players. In this eight-week course learners aged 11 to 14 code games that collect player data and adjust themselves.
Learners begin by discussing why difficulty matters and what makes a game too easy or too hard. They build a simple obby or target game and code it to record useful data, such as number of attempts, time taken and success rate, storing values in tables. Next they display this data on a dashboard so they can see how players perform.
In the middle weeks learners write rules that use the data to adjust the game, such as slowing obstacles after repeated failures or adding challenges when a player succeeds easily. They experiment with averages and thresholds and discuss how small changes affect the player experience. Learners then compare their rule-based approach with how machine learning systems learn patterns from much larger data sets.
In the final weeks learners playtest with classmates, analyze the data their games collected and refine their adaptive rules. They also discuss fairness and privacy in collecting player data.
By the end learners will have an adaptive game and an understanding of data-driven design. Learners should know Lua functions and tables.
Each class introduces a data or adaptive design idea with live coding. Learners add it to their game, collect test data and adjust their rules.
Week 1: Why Difficulty Matters – Discuss too easy and too hard.
Week 2: Base Game – Build an obby or target game.
Week 3: Recording Data – Store attempts, time and success in tables.
Week 4: Data Dashboard – Display player performance.
Week 5: Adaptive Rules – Adjust obstacles based on data.
Week 6: Averages and Thresholds – Tune rules with simple statistics.
Week 7: Rules vs Machine Learning – Compare adaptive rules with ML.
Week 8: Playtest and Analyze – Analyze test data and refine rules.
Explain why difficulty balance matters
Record player performance data in tables
Code rules that adjust difficulty from data
Use averages and thresholds to tune gameplay
Discuss fairness and privacy in player data
Comfortable with Lua functions and tables.
Shreya brings seven years of experience teaching children how to apply artificial intelligence in creative, age-appropriate ways. She focuses on computer vision projects—face, hand and object detection, pose estimation, and fun game mechanics—using block-based tools like Pictoblo…

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Laxman Shastri Joshi
Beginner
Level
6–8
Ages
30 min
Duration
1 / Week
Classes
1
Weeks

Malati Devi
Beginner
Level
9–12
Ages
45 min
Duration
1 / Week
Classes
4
Weeks

Memcha Devi
Beginner
Level
8–11
Ages
45 min
Duration
1 / Week
Classes
4
Weeks

Parmeshwari Devi
Beginner
Level
9–12
Ages
55 min
Duration
4 / Week
Classes
1
Weeks

Snehalata Devi
Beginner
Level
9–12
Ages
50 min
Duration
1 / Week
Classes
4
Weeks

Dinanath Mangeshkar
Beginner
Level
7–10
Ages
45 min
Duration
1 / Week
Classes
4
Weeks

Siddharth Iyengar
Intermediate
Level
9–13
Ages
55 min
Duration
1 / Week
Classes
8
Weeks

Trisha Tiwari
Beginner
Level
9–12
Ages
55 min
Duration
1 / Week
Classes
4
Weeks