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Human computation can be described as outsourcing part of a computational process to humans. This technique might be used when a problem can be solved better by humans than computers or it may require a level of adaptation that computers are not yet capable of handling. This can be particularly important in changeable settings which require a greater level of adaptation to the surrounding environment. In most cases, human computation has been used to gather data that computers struggle to create. Games with by-products can provide an incentive for people to carry out such tasks by rewarding them with entertainment. These are games which are designed to create a by-product during the course of regular play. However, such games have traditionally been unable to deal with requests for specific data, relying instead on a broad capture of data in the hope that it will cover specific needs. A new method is needed to focus the efforts of human computation and produce specifically requested results. This would make human computation a more valuable and versatile technique. Mutually reinforcing systems are a new approach to human computation that tries to attain this focus. Ordinary human computation systems tend to work in isolation and do not work directly with each other. Mutually reinforcing systems are an attempt to allow multiple human computation systems to work together so that each can benefit from the other's strengths. For example, a non-game system can request specific data from a game. The game can then tailor its game-play to deliver the required by-products from the players. This is also beneficial to the game because the requests become game content, creating variety in the game-play which helps to prevent players getting bored of the game. Mobile systems provide a particularly good test of human computation because they allow users to react to their environment. Real world environments are changeable and require higher levels of adaptation from the users. This means that, in addition to the human computation required by other systems, mobile systems can also take advantage of a user's ability to apply environmental context to the computational task. This research explores the effects of mutually reinforcing systems on mobile games with by-products. These effects will be explored by building and testing mutually reinforcing systems, including mobile games. A review of existing literature, human computation systems and games with by-products will set out problems which exist in outsourcing parts of a computational process to humans. Mutually reinforcing systems are presented as one approach of addressing some of these problems. Example systems have been created to demonstrate the successes and failures of this approach and their evolving designs have been documented. The evaluation of these systems will be presented along with a discussion of the outcomes and possible future work. A conclusion will summarize the findings of the work carried out. This dissertation shows that extending human computation techniques to allow the collection and classification of useful contextual information in mobile environments is possible and can be extended to allow the by-products to match the specific needs of another system.