Key Points
- 📊 Wave patterns in difficulty create flow state
- 🔬 Latest research: Optimal when skills slightly exceed challenges
- 💡 Monotonic difficulty increase diminishes fun
- 🎯 Importance of growth perception and recovery time
While not limited to Roblox, what makes games "fun"? Why do people spend hours playing games? Various research has been conducted on these questions for years. This article, the first in an 8-part series on evaluating game fun based on past research, explores "Difficulty Progression" in detail.
Introduction: Why Do People Get Absorbed in Games?
Do you think game difficulty should "gradually increase"? Actually, the answer to this simple question is surprisingly complex, derived from 50 years of psychology and game design research.
1. Difficulty Progression
📊 What We Evaluate
Whether the difficulty increase pattern throughout stages appropriately synchronizes with player growth
🔍 Specific Measurement Items
- Skill-Challenge Wave Pattern
- Whether difficulty follows a wave pattern of "easy → hard → slightly easy → harder" rather than monotonic increase
- Alignment with Learning Curve
- Whether difficulty increases align with when players acquire new skills (long-distance swings, timing jumps, etc.)
💡 Why This Leads to Fun
Constant high difficulty causes fatigue, constant ease leads to boredom. Appropriate pacing maintains flow state.
🎯 Foundation of Flow Theory Research (1975~)
Csikszentmihalyi's (1975) Flow Theory
- Initially observed rock climbers and chess players
- Started from the question "Why do they get absorbed without rewards?"
- Discovery: Optimal experience occurs when skills and challenges are "balanced"
Application to Game Research (2009-2010)
Pedersen et al.'s Groundbreaking Experiment (2009-2010)
"Modeling Player Experience in Super Mario Bros"
Experimental Method:
- 480 play sessions
- Used auto-generated Super Mario Bros levels
- Players evaluated "fun," "frustration," and "challenge"
- Built prediction model using neural networks
Key Findings:
- Challenge prediction: 77.77% accuracy
- Frustration prediction: 88.66% accuracy
- Fun prediction: 69.18% accuracy (requires more complex model)
Why Wave Patterns:
- Constantly increasing difficulty causes frustration to spike
- Same difficulty level leads to boredom (fun score decreases)
- Fun scores are highest with appropriate pacing
Latest Findings (2023-2025)
Cudo's (2025) New Discovery
"Analyzing Skill-Challenge Interaction and Flow State"
Experimental Method:
- 528 board game players
- Used new technique called Response Surface Analysis (RSA)
- 3D analysis of optimal skill-challenge combinations
Surprising Discoveries:
- Traditional "balance theory" is incomplete
- Skill = Challenge is not optimal
- Optimal when skills slightly exceed challenges
- Absolute values also matter
- Low skill × Low challenge = Boring
- High skill × High challenge = Exciting
- Same "balance" creates completely different experiences
Cutting et al.'s (2023) Counter-Evidence Research
"Difficulty-skill balance does not affect engagement and enjoyment"
Experimental Content:
- Tested traditional "inverted U-curve theory"
- Precisely controlled game difficulty in experiments
Surprising Conclusion:
- Simple "balance" doesn't predict fun
- Perception of growth is more important
- Thus, temporal change (progression) is key
Why the "Wave Pattern"?
Psychological Basis
- Habituation
- Response dulls to constant stimuli
- Contrast Effect
- Easy after hard feels "easier"
- Recovery Time
- Recovery from cognitive fatigue is necessary
Specific Wave Pattern Example
Difficulty
↑
8 | 🏔️ 🏔️🏔️
6 | 📈 📉 📈
4 | 📈 📉 📈
2 |
└─────────────────────→ Time
Flow state maximizes when slightly exceeding challengesPractical Examples: Successful Game Difficulty Design
Proven in Game Design
- Dark Souls: Safe zones after boss battles
- Super Mario: Bonus stage placement
- Celeste: Story segments after difficult sections
🎮 Implications for Roblox Game Development
In games like Obby, avoid monotonic difficulty increases. Maintain player engagement by intentionally placing "rest points" and "easy sections for achievement satisfaction."
Frequently Asked Questions (FAQ)
Q: Should game difficulty gradually increase?
Research shows that wave patterns of "easy → hard → slightly easy → harder" create more fun than monotonic difficulty increases. Pedersen et al.'s (2010) research demonstrated that fun scores are highest with appropriate pacing in difficulty design.
Q: What exactly is a flow state?
Flow state is an optimal experience where one becomes completely absorbed in an activity and loses track of time. 2025's latest research reveals that flow state is most easily achieved when skills slightly exceed challenges (not perfect balance).
Q: How can I apply this to actual game development?
Like Dark Souls' safe zones after boss battles or Mario's bonus stages, intentional "pacing" is crucial. By providing recovery time after difficult sections and creating moments for players to feel growth, you can maintain long-term engagement.
Summary
Scientific research on "fun" began with flow theory in 1975 and continues to evolve today. What's important for difficulty progression is not simple difficulty increase, but wave pattern design with appropriate pacing.
Key Takeaways:
- Wave patterns in difficulty create flow state
- Optimal when skills slightly exceed challenges (2025's latest research)
- Perception of growth is a crucial element of fun
- Incorporate recovery time from cognitive fatigue into design
References
- 📚 "Analyzing Skill-Challenge Interaction and Flow State" - Cudo (2025)
- 📚 "Modeling Player Experience for Content Creation" - Pedersen et al. (2010)