The Impact of External Audience on Second Graders\u27 Writing Quality

The overarching purpose of writing is to communicate; as such, the intended audience is a critical consideration for writers. However, elementary school writing instruction commonly neglects the role of the audience. Typically, children are asked to compose a piece of text without a specific audience that is usually evaluated by the classroom teacher. Previous studies have found a relationship between audience specification and higher quality writing among older children; this study examines the impact of audience specification on young children’s writing. Using a within-subjects design, the study compared writing quality when second-grade students wrote for internal versus external audiences and found that children are more likely to produce higher quality writing when writing for an external audience than when writing for their teacher

Skeleton-Based Human Action Recognition with Global Context-Aware Attention LSTM Networks

Human action recognition in 3D skeleton sequences has attracted a lot of research attention. Recently, Long Short-Term Memory (LSTM) networks have shown promising performance in this task due to their strengths in modeling the dependencies and dynamics in sequential data. As not all skeletal joints are informative for action recognition, and the irrelevant joints often bring noise which can degrade the performance, we need to pay more attention to the informative ones. However, the original LSTM network does not have explicit attention ability. In this paper, we propose a new class of LSTM network, Global Context-Aware Attention LSTM (GCA-LSTM), for skeleton based action recognition. This network is capable of selectively focusing on the informative joints in each frame of each skeleton sequence by using a global context memory cell. To further improve the attention capability of our network, we also introduce a recurrent attention mechanism, with which the attention performance of the network can be enhanced progressively. Moreover, we propose a stepwise training scheme in order to train our network effectively. Our approach achieves state-of-the-art performance on five challenging benchmark datasets for skeleton based action recognition

Attentive monitoring of multiple video streams driven by a Bayesian foraging strategy

In this paper we shall consider the problem of deploying attention to subsets of the video streams for collating the most relevant data and information of interest related to a given task. We formalize this monitoring problem as a foraging problem. We propose a probabilistic framework to model observer's attentive behavior as the behavior of a forager. The forager, moment to moment, focuses its attention on the most informative stream/camera, detects interesting objects or activities, or switches to a more profitable stream. The approach proposed here is suitable to be exploited for multi-stream video summarization. Meanwhile, it can serve as a preliminary step for more sophisticated video surveillance, e.g. activity and behavior analysis. Experimental results achieved on the UCR Videoweb Activities Dataset, a publicly available dataset, are presented to illustrate the utility of the proposed technique.Comment: Accepted to IEEE Transactions on Image Processin

The Hardcore Scorecard: Defining, Quantifying and Understanding “Hardcore” Video Game Culture

ABSTRACT The goal of the current study is to further conceptualize and define the term “hardcore” as it relates to video game culture. Past research indicates that members of cultural subdivisions favor their own group versus others due to perceived commonalities (Durkheim, 1915; Tajfel, 1970). In gaming culture, the subdivisions of “hardcore” and “casual” games/gamers have become especially salient in recent years. However, the definition of what constitutes “hardcore” and “casual” is inconsistent (Adams, 2000; Alexandre, 2012; Jacobs & Ip, 2003; Juul, 2010; Kim, 2001; Kuittinen, Kultima, Niemelä & Paavilainen, 2007; Wallace & Robbins, 2006). Therefore, it is beneficial to better understand these terms considering the implications: less audience infighting, more accurately tailored game design/marketing, and less ambiguous/sensationalist gaming journalism/media. A sample of 109 undergraduate students from a large university (19,000 undergraduates) in an upstate New York city (metropolitan population of 1.1 million) completed an online survey, reporting their perceptions of hardcore gaming. Values were then attributed to certain video game criteria based on the survey results and applied to popular games. The sum of these values produced a hardcore index for the “scorecard.” To assess the scorecard’s validity, correlations were run between our final values and an independently collected hardcore percentage publicly available on the Wii’s Nintendo Channel (327,818.45 average respondents per game). Results suggest hardcore gaming is perceived as a harsh subculture consisting of long play times, challenging play, anti-social behavior, and content not suitable for children. The index produced by the resulting “hardcore scorecard” was significantly correlated (r = .765, p \u3c .01) with the independently collected data on the Nintendo Channel. Thus, the current research provides tools the gaming industry (users, developers, journalists) can use to their advantage by better understanding and defining the term “hardcore,” as well as a valuable blueprint for future research to continue refining and improving