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From the abstract: "Collective Artificial Intelligence (CAI) simulates human intelligence from data contributed by many humans, mined for inter-related patterns. This thesis applies CAI to social role-playing, introducing an end-to-end process for compositing recorded performances from thousands of humans, and simulating open-ended interaction from this data. The CAI process combines crowdsourcing, pattern discovery, and case-based planning. Content creation is crowdsourced by recording role-players online. Browser-based tools allow non-experts to annotate data, organizing content into a hierarchical narrative structure. Patterns discovered from data power a novel system combining plan recognition with case-based planning. The combination of this process and structure produces a new medium, which exploits a massive corpus to realize characters who interact and converse with humans. This medium enables new experiences in videogames, and new classes of training simulations, therapeutic applications, and social robots. .... As a proof of concept, a CAI system has been evaluated by recording over 10,000 performances in The Restaurant Game, automating an AI-controlled waitress who interacts in the world, and converses with a human via text or speech. Quantitative results demonstrate CAI supports significantly open-ended interaction with humans, while focus groups reveal factors for improving engagement."

Abstract: "This paper describes the design and evaluation of Zoo U, a novel computer game to assess children's social skills development. Zoo U is an innovative product that combines theory-driven content and customized game mechanics. The game-like play creates the opportunity for stealth assessment, in which dynamic evidence of social skills is collected in real time and players' choices during gameplay provide the needed data. To ensure the development of an engaging and valid game, we utilized an iterative datadriven validation process in which the game was created, tested, revised based on student performance and feedback, and retested until game play was statistically matched to independent ratings of social skills. We first investigated whether the data collected through extensive logging of student actions provided information that could be used to improve the assessment. We found that detailed game logs of socially relevant player behavior combined with external measures of player social skills provided an efficient vector to incrementally improve the accuracy of the embedded assessments. Next, we investigated whether the game performance correlated with teachers' assessments of students' social skills competencies. An evaluation of the final game showed (a) significant correlations between in-game social skills assessments and independently obtained standard psychological assessments of the same students and (b) high levels of engagement and likeability for students. These findings support the use of the interactive and engaging computer game format for the stealth assessment of children's social skills. The created innovative design methodologies should prove useful in the design and improvement of computer games in education."

Abstract: "The purpose of this study aimed to construct an online competitive game-based learning system by using freeware for junior high school students and to assess its effectiveness. From the learning standpoints, game mechanisms including learning points, competition mechanism, training room mechanism, questioning & answering mechanism, tips, and feedback mechanism are taken into consideration while constructing the system. The system contains screens of Log-in, Game lobby, Waiting room, Player's room, Question & Answer, and Scoring. After the system was established, it was implemented in a 10 week teaching experiment. A total of 35 junior high school students participated in this teaching experiment. Both pre-test and post-test were administered and analyzed. A 5-point Likert scale questionnaire, containing domains of system operation, learning effectiveness, competition and incentive, and training room learning was also included to assess user's satisfaction. Descriptive analysis and independent t test were used to analyze the collected data. The findings of the study show that most students are satisfied with the four domains of the freeware constructed online competitive game-based learning system. Meanwhile, the online competitive game-based learning system is effective for junior high school students' learning."

Abstract: "Player metrics are an invaluable resource for game designers and QA analysts who wish to understand players, monitor and improve game play, and test design hypotheses. Usually such metrics are collected in a straightforward manner by passively recording players; however, such an approach has several potential drawbacks. First, passive recording might fail to record metrics which correspond to an infrequent player behavior. Secondly, passive recording can be a costly, laborious, and memory intensive process, even with the aid of tools. In this paper, we explore the potential for an active approach to player metric collection which strives to collect data more efficiently, and thus with less cost. We use an online, iterative approach which models the relationship between player metrics and in-game situations probabilistically using a Markov Decision Process (MDP) and solves it for the best game configurations to run. To analyze the benefits and limitations of this approach, we implemented a system, called GAMELAB, for recording player metrics in Second Life."

Abstract: "In this paper, we describe a methodology for capturing player experience while interacting with a game and we present a data-driven approach for modeling this interaction. We believe the best way to adapt games to a specic player is to use quantitative models of player ex- perience derived from the in-game interaction. Therefore, we rely on crowd-sourced data collected about game context, players behavior and players self-reports of dierent aective states. Based on this informa- tion, we construct estimators of player experience using neuroevolution- ary preference learning. We present the experimental setup and the re- sults obtained from a recent case study where accurate estimators were constructed based on information collected from players playing a rst- person shooter game. The framework presented is part of a bigger picture where the generated models are utilized to tailor content generation to particular player's needs and playing characteristics."

Abstract: "Citizen science is a form of social computation where members of the public are recruited to contribute to scientific investigations. Citizen-science projects often use web-based systems to support collaborative scientific activities, making them a form of computer-supported cooperative work. However, finding ways to attract participants and confirm the veracity of the data they produce are key issues in making such systems successful. We describe a series of web-based tools and games currently under development to support taxonomic classification of organisms in photographs collected by citizen-science projects. In the design science tradition, the systems are purpose-built to test hypotheses about participant motivation and techniques for ensuring data quality. Findings from preliminary evaluation and the design process itself are discussed."

"The U.S. government has hired a California-based company to hack into video game consoles, such as Xbox 360 and PlayStation 3, to watch criminals, especially child predators, and learn how to collect evidence against them."

Abstract: "We present a case study in the design of an educational video game about collecting, curating, and museum operations. A five-step cyclic design thinking framework was used by the studio during the design and development of the game, and the team was simultaneously the subject of a rigorous and detailed ethnographic study. Three stages of the game's design evolution are presented through the lens of the design thinking framework. The team's practice-based research is tri- angulated with our empirical data to produce four key findings: (a) that empathy for learning context is critical in aligning designs with learning objectives; (b) that meeting with stakeholders spurs empathy-building; (c) that there is a tension between horizontal and vertical slicing that is revealed by design thinking processes; and (d) that iterative design processes challenge conventions of higher education."