Leveling up fun: learning progress, expectations, and success influence enjoyment in video games

Area of Science:

• Cognitive Psychology
• Human-Computer Interaction
• Behavioral Economics

Background:

• Theories suggest optimal engagement and learning occur in environments of intermediate difficulty.
• Previous research often used simplified experimental paradigms, limiting real-world applicability.
• Understanding enjoyment in inherently enjoyable tasks is crucial for human learning and decision-making theories.

Purpose of the Study:

• To investigate factors influencing enjoyment in inherently enjoyable tasks within realistic settings.
• To test theories predicting intermediate difficulty leads to maximum enjoyment.
• To identify additional predictors of enjoyment beyond task difficulty.

Main Methods:

• Analysis of large-scale, real-world video game data sets (puzzle, racing, platformer) including millions of player votes.
• Controlled experimental studies to confirm findings from observational data.
• Examination of player preferences based on level difficulty, prior expectations, and success.

Main Results:

• Players consistently preferred levels of intermediate difficulty across all analyzed video games.
• Enjoyment was significantly influenced by the alignment of perceived difficulty with prior expectations.
• Player motivation was positively correlated with successful task completion.

Conclusions:

• Findings support and extend theories of human learning and decision-making in complex, realistic environments.
• Optimal enjoyment is a function of intermediate difficulty, congruent expectations, and achieved success.
• Utilizing realistic, game-like environments alongside controlled experiments provides a robust approach to studying human behavior.