50,364 research outputs found

    Revealing the Vicious Circle of Disengaged User Acceptance: A SaaS Provider's Perspective

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    User acceptance tests (UAT) are an integral part of many different software engineering methodologies. In this paper, we examine the influence of UATs on the relationship between users and Software-as-a-Service (SaaS) applications, which are continuously delivered rather than rolled out during a one-off signoff process. Based on an exploratory qualitative field study at a multinational SaaS provider in Denmark, we show that UATs often address the wrong problem in that positive user acceptance may actually indicate a negative user experience. Hence, SaaS providers should be careful not to rest on what we term disengaged user acceptance. Instead, we outline an approach that purposefully queries users for ambivalent emotions that evoke constructive criticism, in order to facilitate a discourse that favors the continuous innovation of a SaaS system. We discuss theoretical and practical implications of our approach for the study of user engagement in testing SaaS applications

    Rationalizing Noneconomic Damages: A Health-Utilities Approach

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    Studdert et al examine why making compensation of noneconomic damages in personal-injury litigation more rational and predictable is socially valuable. Noneconomic-damages schedules as an alternative to caps are discussed, several potential approaches to construction of schedules are reviewed, and the use of a health-utilities approach as the most promising model is argued. An empirical analysis that combines health-utilities data created in a previous study with original empirical work is used to demonstrate how key steps in construction of a health-utilities-based schedule for noneconomic damages might proceed

    A study on text-score disagreement in online reviews

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    In this paper, we focus on online reviews and employ artificial intelligence tools, taken from the cognitive computing field, to help understanding the relationships between the textual part of the review and the assigned numerical score. We move from the intuitions that 1) a set of textual reviews expressing different sentiments may feature the same score (and vice-versa); and 2) detecting and analyzing the mismatches between the review content and the actual score may benefit both service providers and consumers, by highlighting specific factors of satisfaction (and dissatisfaction) in texts. To prove the intuitions, we adopt sentiment analysis techniques and we concentrate on hotel reviews, to find polarity mismatches therein. In particular, we first train a text classifier with a set of annotated hotel reviews, taken from the Booking website. Then, we analyze a large dataset, with around 160k hotel reviews collected from Tripadvisor, with the aim of detecting a polarity mismatch, indicating if the textual content of the review is in line, or not, with the associated score. Using well established artificial intelligence techniques and analyzing in depth the reviews featuring a mismatch between the text polarity and the score, we find that -on a scale of five stars- those reviews ranked with middle scores include a mixture of positive and negative aspects. The approach proposed here, beside acting as a polarity detector, provides an effective selection of reviews -on an initial very large dataset- that may allow both consumers and providers to focus directly on the review subset featuring a text/score disagreement, which conveniently convey to the user a summary of positive and negative features of the review target.Comment: This is the accepted version of the paper. The final version will be published in the Journal of Cognitive Computation, available at Springer via http://dx.doi.org/10.1007/s12559-017-9496-

    E/Valuating new media in language development

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    This paper addresses the need for a new approach to the educational evaluation of software that falls under the rubric "new media" or "multimedia" as distinct from previous generations of Computer-Assisted Language Learning (CALL) software. The authors argue that present approaches to CALL software evaluation are not appropriate for a new genre of CALL software distinguished by its shared assumptions about language learning and teaching as well as by its technical design. The paper sketches a research-based program called "E/Valuation" that aims to assist language educators to answer questions about the educational effectiveness of recent multimedia language learning software. The authors suggest that such program needs to take into account not only the nature of the new media and its potential to promote language learning in novel ways, but also current professional knowledge about language learning and teaching

    Non‐hierarchical learning: sharing knowledge, power and outcomes

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    Arguing that every student has the capacity to succeed and that every student must be provided with the opportunity to reach their full potential, this article introduces a new pedagogic approach that draws on a wide range of influences. Linking theoretical practices from sociology, pedagogy, social and educational psychology, and cultural studies, the approach posits that teaching and learning should be conducted in non‐hierarchical classrooms where all members are equal and working towards shared objectives. A theoretical frame is outlined and the factors that helped shape it are reflected on. A conceptual framework which covers the goals of instruction, instructional materials, classroom management, instructional methods, and assessment is also presented. It is hoped that educators will consider the concepts included in this article and, if possible, incorporate them into their teaching practices
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