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The theoretical framework presented in this article explains expert performance as the end result of individuals ' prolonged efforts to improve performance while negotiating motivational and external constraints. In most domains of expertise, individuals begin in their childhood a regimen of effortful activities (deliberate practice) designed to optimize improvement. Individual differences, even among elite performers, are closely related to assessed amounts of deliberate practice. Many characteristics once believed to reflect innate talent are actually the result of intense practice extended for a minimum of 10 years. Analysis of expert performance provides unique evidence on the potential and limits of extreme environmental adaptation and learning. Our civilization has always recognized exceptional individuals, whose performance in sports, the arts, and science is vastly superior to that of the rest of the population. Speculations on the causes of these individuals ' extraordinary abilities and performance are as old as the first records of their achievements. Early accounts commonly attribute these individuals' outstanding performance to divine intervention, such as the

The fundamental challenge for human-computer interaction (HCI) is to invent and design a culture in which humans can express themselves and engage in personally meaningful activities. Cultures are substantially defined by their media and tools for thinking, working, learning, and collaborating. New media change (1) the structure and contents of our interests, (2) the nature of our cognitive and physical tools, and (3) the social environment in which thoughts originate and evolve, and mindsets develop. Unfortunately, a large number of new media are designed from a perspective of seeing and treating humans primarily as consumers. The possibility for humans to be and to act as designers (in cases in which they desire to do so) should be accessible not only to a small group of high-tech scribes, but rather to all interested individuals and groups. 1. Introduction Cultures are substantially defined by their media and their tools for thinking, working, learning, and collaborating. A large...

Research into free and open source software development projects has so far largely focused on how the major tasks of software development are organized and motivated. But a complete project requires the execution of “mundane but necessary” tasks as well. In this paper, we explore how the mundane but necessary task of field support is organized in the case of Apache web server software, and why some project participants are motivated to provide this service gratis to others. We find that the Apache field support system functions effectively. We also find that, when we partition the help system into its component tasks, 98 % of the effort expended by information providers in fact returns direct learning benefits to those providers. This finding considerably reduces the puzzle of why information providers are willing to perform this task “for free. ” Implications are discussed.

In writing this chapter, we (a constructivist and a situativity theorist) struggled with the distinction between situativity and constructivism. and the implications in terms of the design of learning contexts. In clarifying (and justifying) our two sides, we created straw man and pOinted fingers with respect to the limitations of each other's perspectives. We found that although discussions of situativity and of constructivism draw on different references and clearly have specialized languages, actual interpretations of situativity and of constructivism share many underlying similarities. Further, when it came to the design of learning contexts predicated on our respective theories, we found ourselves continuously forwarding similar principles and advocating for similar learning contexts. We are dealing with evolving concepts-and people use new terms to include and extend old ones. Constructivism was the label used for the departure from objectivism; however, even among those who call themselves constructivists there are different perspectives and different sets of assumptions (see Cobb, 1994, 1995; Phillips, 1995). Now the term more commonly used is situated, reflecting the key proposal from both the constructivist and situativity perspective that knowledge is situated through experience. In the context of this chapter, we found it trivial to distinguish among those learning theories and principles related to constructivism and those related to situativity theory. Rather, we discuss the various learning theories that have informed our understanding all unde ~ the heading of situativity learning theories. This term, and its associated assumptions and current interpretations, seemed to better capture the essence of the learning contexts we are forwarding as useful. However, even within the context of situativity theories we found it necessary to make distinctions, and it was these distinctions (not the distinction between constructivist and situativity views) that best captured the essence of this chapter.

There is an interplay between emotions and learning, but this interaction is far more complex than previous theories have articulated. This article proffers a novel model by which to: 1). regard the interplay of emotions upon learning for, 2). the larger practical aim of crafting computer-based models that will recognize a learner's affective state and respond appropriately to it so that learning will proceed at an optimal pace. 1. Looking around then moving forward The extent to which emotional upsets can interfere with mental life is no news to teachers. Students who are anxious, angry, or depressed don't learn; people who are caught in these states do not take in information efficiently or deal with it well . - Daniel Goleman, Emotional Intelligence Educators have emphasized conveying information and facts; rarely have they modeled the learning process. When teachers present material to the class, it is usually in a polished form that omits the natural steps of making m...

Although player enjoyment is central to computer games, there is currently no accepted model of player enjoyment in games. There are many heuristics presented in the literature, based on elements such as the game interface, mechanics, gameplay and narrative. However, there is a need to integrate these heuristics into a validated model that can be used to design, evaluate and understand enjoyment in games. We have drawn together the various heuristics into a concise model of enjoyment in games that is structured by flow. Flow, a widely accepted model of enjoyment, includes eight elements that we found to encompass the various heuristics from the literature. Our new model, GameFlow, consists of eight elements – concentration, challenge, skills, control, clear goals, feedback, immersion and social interaction. Each element includes a set of criteria for achieving enjoyment in games. An initial investigation and validation of the GameFlow model was carried out by conducting expert reviews of two real-time strategy games, one high-rating and one low-rating, using the GameFlow criteria. The result was a deeper understanding of enjoyment in real-time strategy games and the identification of the strengths and weaknesses of the GameFlow model for evaluating enjoyment in games. The GameFlow criteria were successfully able to distinguish between the high-rated and low-rated game and identify why one succeeded and the other failed. We concluded that the GameFlow model can be used in its current form to review games and further work will provide tools for designing and evaluating enjoyment in games.

The role that affective states play in learning was investigated from the perspective of a constructivist learning framework. We observed six different affect states (frustration, boredom, flow, confusion, eureka and neutral) that potentially occur during the process of learning introductory computer literacy with AutoTutor, an intelligent tutoring system with tutorial dialogue in natural language. Observational analyses revealed significant relationships between learning and the affective states of boredom, flow and confusion. The positive correlation between confusion and learning is consistent with a model that assumes that cognitive disequilibrium is one precursor to deep learning. The findings that learning correlates negatively with boredom and positively with flow are consistent with predictions from Csikszentmihalyi’s analysis of flow experiences.

For good reasons, economists have had a long-standing preference for studying peoples ’ revealed preferences; that is, looking at individuals ’ actual choices and decisions rather than their stated intentions or subjective reports of likes and dislikes. Yet people often make choices that bear a mixed relationship to their own happiness. A large literature from behavioral economics and psychology finds that people often make inconsistent choices, fail to learn from experience, exhibit reluctance to trade, base their own satisfaction on how their situation compares with the satisfaction of others and depart from the standard model of the rational economic agent in other ways. If people display bounded rationality when it comes to maximizing utility, then their choices do not necessarily reflect their “true ” preferences, and an exclusive reliance on choices to infer what people desire loses some of its appeal. Direct reports of subjective well-being may have a useful role in the measurement of consumer preferences and social welfare, if they can be done in a credible way. Indeed, economists have already made much use of subjective well-being data. From 2001 to 2005, more than 100 papers were written analyzing data on selfreported life satisfaction or happiness, according to a tabulation of EconLit, up from just four in 1991–1995. Data on subjective well-being have been used by economists to examine both macro- and micro-oriented questions. In a classic paper, Easterlin (1974) examined the relationship between economic growth and happiness. More recently, Di Tella, MacCulloch and Oswald (2001) use data on life satisfaction from the Eurobarometer to infer how people trade off inflation for unemployment, and Alesina, Glaeser and Sacerdote (2005) use the same data to study whether labor

This paper presents a gameplay experience model, assesses its potential as a tool for research and presents some directions for future work. The presented model was born from observations among game-playing children and their non-player parents, which directed us to have a closer look at the complex nature of gameplay experience. Our research led into a heuristic gameplay experience model that identifies some of the key components and processes that are relevant in the experience of gameplay, with a particular focus on immersion. The model includes three components: sensory, challenge-based and imaginative immersion (SCI-model). The classification was assessed with self-evaluation questionnaires filled in by informants who played different popular games. It was found that the gameplay experiences related to these games did indeed differ as expected in terms of the identified three immersion components.