How Personalization Algorithms Drive Mobile Game Recommendations
Jacob Murphy February 23, 2025

How Personalization Algorithms Drive Mobile Game Recommendations

Thanks to Sergy Campbell for contributing the article "How Personalization Algorithms Drive Mobile Game Recommendations".

How Personalization Algorithms Drive Mobile Game Recommendations

This research examines the application of Cognitive Load Theory (CLT) in mobile game design, particularly in optimizing the balance between game complexity and player capacity for information processing. The study investigates how mobile game developers can use CLT principles to design games that maximize player learning and engagement by minimizing cognitive overload. Drawing on cognitive psychology and game design theory, the paper explores how different types of cognitive load—intrinsic, extraneous, and germane—affect player performance, frustration, and enjoyment. The research also proposes strategies for using game mechanics, tutorials, and difficulty progression to ensure an optimal balance of cognitive load throughout the gameplay experience.

This paper explores the use of artificial intelligence (AI) in predicting player behavior in mobile games. It focuses on how AI algorithms can analyze player data to forecast actions such as in-game purchases, playtime, and engagement. The research examines the potential of AI to enhance personalized gaming experiences, improve game design, and increase player retention rates.

This paper explores the potential of mobile games to serve as therapeutic tools in the treatment of mental health conditions, such as anxiety, depression, and PTSD. It examines how game mechanics and immersive environments can be used to provide psychological relief, improve emotional regulation, and facilitate cognitive-behavioral therapy. The study discusses challenges in integrating therapeutic design with traditional game elements and offers recommendations for the development of clinically effective mobile health games.

This research explores the intersection of mobile gaming and behavioral economics, focusing on how in-game purchases influence player decision-making. The study analyzes common behavioral biases, such as the “anchoring effect” and “loss aversion,” that developers exploit to encourage spending. It provides insights into how these economic principles affect the design of monetization strategies and the ethical considerations involved in manipulating player behavior.

This paper explores the use of data analytics in mobile game design, focusing on how player behavior data can be leveraged to optimize gameplay, enhance personalization, and drive game development decisions. The research investigates the various methods of collecting and analyzing player data, such as clickstreams, session data, and social interactions, and how this data informs design choices regarding difficulty balancing, content delivery, and monetization strategies. The study also examines the ethical considerations of player data collection, particularly regarding informed consent, data privacy, and algorithmic transparency. The paper proposes a framework for integrating data-driven design with ethical considerations to create better player experiences without compromising privacy.

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