The intention of this chapter is to show how autoethnographic research might promote reflexivity among career professionals. We aim to answer the question: can writing one’s own life and career story assist career practitioners and researchers in identifying patterns, idiosyncrasies, vulnerabilities that will make them more aware of the elements that are fundamental to career construction and that have been mentioned in a variety of disparate places in the existing career literature? What interested us as career researchers and co-creators of the narrative approach Career Writing in considering the innovative intention of this book, was how writing our own career story could deepen our professional reflexivity and might also help others to do so. https://doi.org/10.1007/978-3-030-22799-9_30 LinkedIn: https://www.linkedin.com/in/reinekke-lengelle-phd-767a4322/
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This article presents a novel and highly interactive process to generate natural language narratives based on our ongoing work on semiotic relations, providing four criteria for composing new narratives from existing stories. The wide applicability of this semiotic reconstruction process is suggested by a reputed literary scholar's deconstructive claim that new narratives can often be shown to be a tissue of previous narratives. Along, respectively, three semiotic axes – syntagmatic, paradigmatic, and meronymic – existing stories can yield new stories by the combination, imitation, or expansion of an iconic scene; lastly, a new story may emerge through reversal via an antithetic consideration, i.e., through the adoption of opposite values. Targeting casual users, we present a fully operational prototype with a simple and user-friendly interface that incorporates an AI agent, namely ChatGPT. The prototype, in a coauthor capacity, generates context-compatible sequences of events in storyboard format using backward-chaining abductive reasoning (employing Stable Diffusion to draw scene illustrations), conforming as much as possible to the user's authorial instructions. The extensive repertoire of book and movie summaries available to the AI agent obviates the need to manually supply laborious and error-prone context specifications. A user study was conducted to evaluate user experience and satisfaction with the generated narratives. The preliminary findings suggest that our approach has the potential to enhance story quality while offering a positive user experience.
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This book is the account of teaching practice linked to research projects, a practice that is able to create new, unexpected values in the complex patchwork of the city through experimental and strategic interventions with greenery. That the interventions involve greenery is obviously linked to the fact that the Van Hall Larenstein university of applied sciences specializes in nature and agriculture, but there is also a practical reason. Green spaces act as a cohesive force, as is shown again and again in the Netherlands and in the Lively Cities programme. Particularly in the urban context, green spaces have a distinctive and perhaps even emotional value that encourages people to pause there and makes them think about their appreciation of a place. Greenery triggers people to take part in social experiments. But that is just the beginning.
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This paper presents a method for generating player-driven narratives from visual inputs by exploring the visual analysis capabilities of multimodal large language models. By employing Bartle’s taxonomy of player types—Achievers, Explorers, Socializers, and Killers—our method creates stories that are tailored to different player characteristics. We conducted a fourfold experiment using a set of images extracted from a well-known game, generating distinct narratives for each player type that are aligned with the visual elements of the input images and specific player motivations. By adjusting narrative elements to emphasize achievement for Achievers, exploration for Explorers, social connections for Socializers, and competition for Killers, our system produced stories that adhere to established narratology principles while resonating with the characteristics of each player type. This approach can serve as a helping tool for game designers, offering new insights into how players might engage with game worlds through personalized image-driven narratives.
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In this paper we introduce a novel highly interactive process to generate natural language narratives on the basis of our ongoing work on semiotic relations. To the two basic components of interactive systems, namely, a software tool and a user interface, we add a third component - AI agents, understood as an upgraded rendition of software agents. Our semiotic relations approach considers four ways of composing new narratives from existing narratives. Along what semioticians call the horizontal syntagmatic axis, one can form the new narrative by combining two or more previous narratives. Along the vertical paradigmatic axis, the new narrative may emerge as a similar version, which imitates the previous one, possibly in a different context. Along the depth meronymic axis, the hierarchic narrative levels, such as plot, event, and scene, are explored, allowing either expansion or summarization. Lastly, the antithetic consideration, rather than adding a dimension, aims at some form of reversal, through the adoption of opposite values. A fully operational prototype is described. Its name, ChatGeppetto, conflates the skilled Geppetto, who fashioned Pinocchio, an early case of artisanship-produced human level intelligence, with ChatGPT, which operates as the main AI agent component. To run the experiments, we concentrated on book narratives.
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This paper explores how the concept of life has been used in video games through time. Life is an essential element in different types of action games and several nuances have been used to provide various types of emotions and effects during gameplay. However, the details and patterns have not been extendedly analyzed. Primarily, we survey works regarding the description and formalization of game analysis with emphasis on works in which the concepts have impact in the arguably accepted notion of life. Multiple examples are provided to show different approaches to the concept of life and the impact of such approaches in overall gameplay, namely in the game difficulty and emotions. The examples are then generalized, resulting in a proposal of framework to describe life representation in games. The proposed framework was evaluated in a user study, having participants with gaming culture (professionals, academics, and students of game development courses). Each participant was assigned with the task of fitting a preselected set of games within the framework. The results indicate good coverage of the main concepts with satisfactory consistency.
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