Design - Data Driven Design and Production - Collect the right data to make smarter game designs (Mike Ambinder)
Training created on 6/19/24. Last update on 11/25/24.
Programme version: 1
Training programme
As game designers, our hope is that every design decision we make is the ‘right’ one. Unfortunately, the real world is far less kind. Put another way, game designs are hypotheses about predicted player behavior. In this class, you will learn how to use data (all kinds of data) to validate these hypotheses, drive your design-making, and maximize your chances at making the best possible game – at any stage of development. The workshop will be led by Mike Ambinder who spent 15 years guiding games research efforts at Valve using these exact methods. 1) The scientific approach to game design a- Introduction to data-driven decision-making b- Data collection methodologies c- Pitfalls d- Case studies 2) Expert Practical a- Playtests b- Interviews c- Game Telemetry d- Surveys e- Design Experiments 3) Wrap-up a- Summary b- Future thoughts c- Final Q&A
Objectives of the training
- Implement the most useful ways to gather player data to inform game design (playtesting, game telemetry, surveys, interviews, design experiments)
- Work on how data-informed game design increases the likelihood of predicting player behavior
- Develop your awareness of the biases and confounds present in data (and data collection) that can lead to erroneous conclusions about player intent
- Master the techniques needed to accurately measure player sentiment and engagement at every point of your development timeline.
Profile of beneficiaries
- Game Designers
- Producers
- Game Developers
- User Experience Designers and Researchers
- Any discipline in game development looking to make more informed decisions
- Professional game design experience expected
- Master class in English
Training content
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The scientific approach to game design
- Introduction to data-driven decision-making Game design basics, data collection basics, using data to inform decision-making.
- Data collection methodologies Kinds of data – playtests, telemetry, interviews, surveys, ancillary sources.
- Pitfalls
- Case studies
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Expert Practical
- Playtest
- Interviews
- Game Telemetry
- Surveys
- Design Experiments
-
Wrap-up
- Summary
- Future thoughts
- Final Q&A
Mike Ambinder spent 15 years at Valve as an applied psychologist working at the intersections of psychology, game design, statistics and data science, machine learning, brain-computer interfaces, and user research all in service of improving the quality of game design decision-making. Regarded in the field as a pioneer in the disciplines of Games User Research, Applied Psychology and Game Design, and Brain-Computer Interface (BCI) based gaming, Mike now consults for game companies seeking to make better games through empirical research. Professional credits: Dota 2, Counter-Strike: Global Offensive, Team Fortress 2, Half-Life: Alyx, Portal 2, Alien Swarm, Counter-Strike 2, Underlords, Artifact, Left 4 Dead, Left 4 Dead 2, Steam, Valve Index, HTC Vive, Steam Controller, and Steam Deck.
- Assessment of acquired skills via a questionnaire
Quality and satisfaction
Certification procedures
- Délivrance d'un certificat de réalisation