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Flow The Psychology Of Optimal Experience

QUITE apart from the academic consideration that vital and medical statistics now form an obligatory part of the education of students seeking the University of London's diploma in public health, the demand for information about the methods of vital and medical statistics is increasing. The most casual reader of the newspapers is now aware that population problems are of serious practical importance and that the publications of the General Register Office cannot be ignored. It is scarcely an exaggeration to say that the recently issued preliminary report on the census of 1931 is one of the most sensational documents which has appeared for years, and that he who reads it intelligently will understand what is meant by saying that civilisation is in the melting pot. An Introduction to Medical Statistics. By Hilda M. Woods William T. Russell. Pp. x + 125. (London: P. S. King and Son, Ltd., 1931.) 7s. 6d.

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An Introduction to Medical Statistics

We must all accept that science is data and that data are science, and thus provide for, and justify the need for the support of, much-improved data curation. (Hanson, Sugden, & Alberts) 
 
Researchers are producing an unprecedented deluge of data by using new methods and instrumentation. Others may wish to mine these data for new discoveries and innovations. However, research data are not readily available as sharing is common in only a few fields such as astronomy and genomics. Data sharing practices in other fields vary widely. Moreover, research data take many forms, are handled in many ways, using many approaches, and often are difficult to interpret once removed from their initial context. Data sharing is thus a conundrum. Four rationales for sharing data are examined, drawing examples from the sciences, social sciences, and humanities: (1) to reproduce or to verify research, (2) to make results of publicly funded research available to the public, (3) to enable others to ask new questions of extant data, and (4) to advance the state of research and innovation. These rationales differ by the arguments for sharing, by beneficiaries, and by the motivations and incentives of the many stakeholders involved. The challenges are to understand which data might be shared, by whom, with whom, under what conditions, why, and to what effects. Answers will inform data policy and practice. © 2012 Wiley Periodicals, Inc.

科研数据共享的挑战 (The Conundrum of Sharing Research Data)

Identifying causal relationships is an important aspect of scientific inquiry. Causal relationships help us to infer, predict, and plan. This research investigates the causal relationships between two constructs, perceived enjoyment (PE) and perceived ease of use (PEOU), within the nomological net of user technology acceptance. PE has been theorized and empirically validated as either an antecedent or a consequence of PEOU. We believe that there are two reasons that account for this ambiguity the conceptual coupling of PE and PEOU and the limitations of covariance-based statistical methods. Accordingly, we approach this inconsistency by providing more theoretical reasoning and employing an alternative statistical method, namely Cohen’s path analysis. Specifically, as suggested by previous research on the difference between utilitarian and hedonic systems, we propose the conditional dominance of causal directions. Empirical results from two studies using different technologies and user samples support the theoretical claim that the PE∆PEOU causal direction outweighs the PEOU∆PE direction for utilitarian systems. There are both theoretical and the methodical contributions of this research. The approach applied in this research can be generalized to study causal relationships between conceptually coupled variables, which otherwise may be overlooked by confirmatory methods. We encourage researchers to pay attention to causal directions in addition to causal connectedness.

Causal Relationships Between Perceived Enjoyment and Perceived Ease of Use: An Alternative Approach

textEstablishing predictive validity of measures is a major concern in marketing research. This paper investigates the conditions favoring the use of single items versus multi-item scales in terms of predictive validity. A series of complementary studies reveals that the predictive validity of single items varies considerably across different (concrete) constructs and stimuli objects. In an attempt to explain the observed instability, a comprehensive simulation study is conducted aimed at identifying the influence of different factors on the predictive validity of single versus multi-item measures. These include the average inter-item correlations in the predictor and criterion constructs, the number of items measuring these constructs, as well as the correlation patterns of multiple and single items between the predictor and criterion constructs. The simulation results show that, under most conditions typically encountered in practical applications, multi-item scales clearly outperform single items in terms of predictive validity. Only under very specific conditions do single items perform equally well as multi-item scales. Therefore, the use of single-item measures in empirical research should be approached with caution, and the use of such measures should be limited to special circumstances.

Guidelines for choosing between multi-item and single-item scales for construct measurement: A predictive validity perspective

Despite the fact that enterprise social software solutions such as IBM Connections and Microsoft Sharepoint are able to increase the communication as well as the collaboration among employees, companies are constantly confronted with the necessity to improve their employees’ motivation to interact with the system. Since gamification has been identified as an effective tool to enhance user acceptance, software developers adopt an increasing number of gamification elements to take advantage of it. Based on an in-depth analysis of the international market leaders in enterprise social software solutions, this chapter examines the implementation of gamification elements and critically reflects on how well they fit with the current insights of flow research in motivational psychology. We argue that current gamification elements predominately aim at the augmentation of the users’ extrinsic motivation whereas intrinsic motivation has mostly been ignored. Furthermore, we identify a trend in which gamification solutions primarily focus on rewarding quantitative improvement of work activities, neglecting qualitative performance. Subsequently, current solutions do not match recent findings in research and ignore risks that can lower the employees’ motivation and work performance in the long run.

Social Collaboration and Gamification

Background E-science technologies have significantly increased the availability of data. Research grant providers such as the European Union increasingly require open access publishing of research results and data. However, despite its significance to research, the adoption rate of open data technology remains low across all disciplines, especially in Europe where research has primarily focused on technical solutions (such as Zenodo or the Open Science Framework) or considered only parts of the issue. Methods and findings In this study, we emphasized the non-technical factors perceived value and uncertainty factors in the context of academia, which impact researchers' acceptance of open data-the idea that researchers should not only publish their findings in the form of articles or reports, but also share the corresponding raw data sets. We present the results of a broad quantitative analysis including N = 995 researchers from 13 large to medium-sized universities in Germany. In order to test 11 hypotheses regarding researchers' intentions to share their data, as well as detect any hierarchical or disciplinary differences, we employed a structured equation model (SEM) following the partial least squares (PLS) modeling approach. Conclusions Grounded in the value-based theory, this article proclaims that most individuals in academia embrace open data when the perceived advantages outweigh the disadvantages. Furthermore, uncertainty factors impact the perceived value (consisting of the perceived advantages and disadvantages) of sharing research data. We found that researchers' assumptions about effort required during the data preparation process were diminished by awareness of e-science technologies (such as Zenodo or the Open Science Framework), which also increased their tendency to perceive personal benefits via data exchange. Uncertainty factors seem to influence the intention to share data. Effects differ between disciplines and hierarchical levels.

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When are researchers willing to share their data? - Impacts of values and uncertainty on open data in academia.

In this study, we first show that while both the perceived usefulness and perceived enjoyment of enterprise social networks impact employees' intentions for continuous participation, the utilitarian value significantly outpaces its hedonic value. Second, we prove that the network's utilitarian value is constituted by its digital infrastructure characteristics: versatility, adaptability, interconnectedness and invisibility-in-use. The study is set within a software engineering company and bases on quantitative survey research, applying partial least squares structural equation modeling.

Enterprise Social Networks as Digital Infrastructures -- Understanding the Utilitarian Value of Social Media at the Workplace

In this study, we first show that while both the perceived usefulness and perceived enjoyment of enterprise social networks impact employees’ intentions for continuous participation, the ut...

https://www.tandfonline.com/doi/pdf/10.1080/10580530.2019.1652448

Enterprise Social Networks as Digital Infrastructures - Understanding the Utilitarian Value of Social Media at the Workplace

Digital transformation refers to changes that digital technologies cause and that influence various aspects of human life. Previous researchers mainly focused on the impact of the digital transformation in the context of commercial organisations and business processes. In this study, we aim to examine how digital transformation affects universities and students. We examine differences and changes in the usage of collaboration and communication platforms between different groups of members at the university and within the university lifecycle. To gain new insights, a qualitative case study with semi-structured interviews was conducted. One of the main results shows that Bachelor and Master students prefer the usage of social network sites for collaboration and communication while Ph.D. students and employees do not. Even though an increasing number of modern platforms for direct communication is offered, the results show that the communication between the groups of students and employees still takes place via email.

Konstantin Wilms

Papers

Social Collaboration and Gamification

When are researchers willing to share their data? - Impacts of values and uncertainty on open data in academia.

Enterprise Social Networks as Digital Infrastructures -- Understanding the Utilitarian Value of Social Media at the Workplace

Enterprise Social Networks as Digital Infrastructures - Understanding the Utilitarian Value of Social Media at the Workplace

Digital Transformation in Higher Education – New Cohorts, New Requirements?