Search (6 results, page 1 of 1)

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Abstract

Drawing from social cognitive theory, the purpose of this study is to examine how personal, environmental and behavioral factors can interplay to influence people's use of YouTube as a learning resource. Design/methodology/approach This study proposed a conceptual model, which was then tested with data collected from a survey with 150 participants who had the experience of using YouTube for learning. The bootstrap method was employed to test the direct and mediation hypotheses in the model. Findings The results revealed that personal factors, i.e. learning outcome expectations and attitude, had direct effects on using YouTube as a learning resource (person ? behavior). The environmental factor, i.e. the sociability of YouTube, influenced the attitude (environment ? person), while the behavioral factor, i.e. prior experience of learning on YouTube, affected learning outcome expectations (behavior ? person). Moreover, the two personal factors fully mediated the influences of sociability and prior experience on YouTube usage for learning. Practical implications The factors and their relationships identified in this study provide important implications for individual learners, platform designers, educators and other stakeholders who encourage the use of YouTube as a learning resource. Originality/value This study draws on a comprehensive theoretical perspective (i.e. social cognitive theory) to investigate the interplay of critical components (i.e. individual, environment and behavior) in YouTube's learning ecosystem. Personal factors not only directly influenced the extent to which people use YouTube as a learning resource but also mediated the effects of environmental and behavioral factors on the usage behavior.

Date

20. 1.2015 18:30:22

Type

a

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Abstract

In social Q&A, user-generated questions can be viewed as goal expressions shaping the responses. Several studies have identified askers' goals from questions. However, it remains unclear how questions set goals for responders. To fill this gap, this research applies goal-framing theory. Goal-frames influence responses by attracting responders' attention to different goals. Eight question cues are used to identify gain, hedonic and normative goal-frames. A total of 14,599 posts are collected. To investigate the influence of goal-frames, response networks are constructed. Results reveal that gain goal-frames attract interactions with questions, while hedonic, and normative goal-frames promote interactions among responses. Further, topic types influence the effects of goal-frames. Gain goal-frames increase interactions with questions in Science, Technology, Engineering, and Mathematics (STEM) topics while hedonic and normative goal-frames attract interactions in non-STEM topics. This research leverages responders' perspectives to explain responses to questions, which are influenced by the goals set up by question cues. Beyond that, our findings enrich the empirical knowledge of social Q&A topics, revealing that the influence of questions varies across STEM and non-STEM topics because the question cues for specifying goals are different in the two topics. Our research opens new directions to investigate questions from responders' perspectives.

Type

a

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Abstract

Applications that use games to harness human intelligence to perform various computational tasks are increasing in popularity and may be termed human computation games (HCGs). Most HCGs are collaborative in nature, requiring players to cooperate within a game to score points. Competitive versions, where players work against each other, are a more recent entrant, and have been claimed to address shortcomings of collaborative HCGs such as quality of computation. To date, however, little work has been conducted in understanding how different HCG genres influence computational performance and players' perceptions of such. In this paper we study these issues using image tagging HCGs in which users play games to generate keywords for images. Three versions were created: collaborative HCG, competitive HCG, and a control application for manual tagging. The applications were evaluated to uncover the quality of the image tags generated as well as users' perceptions. Results suggest that there is a tension between entertainment and tag quality. While participants reported liking the collaborative and competitive image tagging HCGs over the control application, those using the latter seemed to generate better quality tags. Implications of the work are discussed.

Type

a

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Abstract

The confluence of mobile content sharing and pervasive gaming yields new opportunities for developing novel applications on mobile devices. Yet, studies on users' attitudes and behaviors related to mobile gaming, content-sharing, and retrieval activities (referred to simply as content sharing and gaming) have been lacking. For this reason, the objectives of this article are three-fold. One, it introduces Indagator, an application that incorporates multiplayer, pervasive gaming elements into mobile content-sharing activities. Two, it seeks to uncover the motivations for content sharing within a game-based environment. Three, it aims to identify types of users who are motivated to use Indagator for content sharing. Informed by the uses and gratifications paradigm, a survey was designed and administered to 203 undergraduate and graduate students from two large universities. The findings revealed that perceived gratification factors, such as information discovery, entertainment, information quality, socialization, and relationship maintenance, demographic variables, such as basic familiarity with features of mobile communication devices, and IT-related backgrounds were significant in predicting intention to use mobile sharing and gaming applications such as Indagator. However, age, gender, and the personal status gratification factor were nonsignificant predictors. This article concludes by presenting the implications, limitations, and future research directions.

Type

a

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Abstract

Location-based information can now be easily accessed anytime and anywhere using mobile devices. Common ways of presenting such information include lists, maps, and augmented reality (AR). Each of these interface types has its strengths and weaknesses, but few empirical evaluations have been conducted to compare them in terms of performance and perceptions of usability. In this paper, we investigate these issues using three interface types for searching and browsing location-based information across two task types: open and closed ended. The experimental study involved 180 participants who were issued an Android mobile phone preloaded with a specific interface and asked to perform a set of open- and closed-ended tasks using both searching and browsing approaches. The results suggest that the list interface performed best across all tasks in terms of completion times, whereas the AR interface ranked second and the map interface performed worst. Participants rated the list as best across most usability constructs but the map was rated better than the AR interface, even though the latter performed better. Implications of the work are discussed.

Type

a

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Abstract

Analyzing and documenting human information behaviors in the context of global public health crises such as the COVID-19 pandemic are critical to informing crisis management. Drawing on the Elaboration Likelihood Model, this study investigates how three types of peripheral cues-content richness, emotional valence, and communication topic-are associated with COVID-19 information sharing on Twitter. We used computational methods, combining Latent Dirichlet Allocation topic modeling with psycholinguistic indicators obtained from the Linguistic Inquiry and Word Count dictionary to measure these concepts and built a research model to assess their effects on information sharing. Results showed that content richness was negatively associated with information sharing. Tweets with negative emotions received more user engagement, whereas tweets with positive emotions were less likely to be disseminated. Further, tweets mentioning advisories tended to receive more retweets than those mentioning support and news updates. More importantly, emotional valence moderated the relationship between communication topics and information sharing-tweets discussing news updates and support conveying positive sentiments led to more information sharing; tweets mentioning the impact of COVID-19 with negative emotions triggered more sharing. Finally, theoretical and practical implications of this study are discussed in the context of global public health communication.

Type

a