Coventry University

About: Coventry University is a education organization based out in Coventry, United Kingdom. It is known for research contribution in the topics: Population & Higher education. The organization has 4964 authors who have published 12700 publications receiving 255898 citations. The organization is also known as: Lanchester Polytechnic & Coventry Polytechnic.

Success factors for serious games to enhance learning: a systematic review

Abstract: There is no doubt that an abundance of factors exists that makes learning with serious games successful. Research articles reporting on these factors, however, tend to focus on select serious game elements and do not combine all salient factors for successful learning with serious games. Addressing this gap is a necessity for the success of serious games and may even alleviate long-standing debates about pedagogy over enjoyment, how much realism is enough or whether artificial intelligence is worth the cost. This article examines existing academic literature from 2000 to 2015, extracting shared serious game success factors that have had an encouraging impact on gameful learning experiences. As such, we subsequently aim to withdraw the field from a perpetual spiral of does-my-game-work research toward more worthwhile why-does-my-game-not-work research. Qualitative content analysis through the constant comparison method (CCM) analyzed a total of 63 articles from a variety of recognized electronic libraries and databases. Through this analysis, we reveal five central serious game themes: backstory and production; realism; artificial intelligence and adaptivity; interaction; and feedback and debriefing, all of which require deliberate intertwining with pedagogical content to ensure successful learning. This review unravels each of the five themes into their constituent factors and consequently presents the factors as practical guidelines that serious games producers should strive to include in their game productions. Applying these recommendations whenever serious games are considered will provide a foundation for effective gameful learning experiences.

Measuring and benchmarking the innovativeness of SMEs: A three-dimensional fuzzy logic approach

Abstract: SMEs have been rather slow in adopting tools and techniques used in larger companies for improving their innovative performance, even if they are very well aware of the importance of innovation, due to difficulties in applying them in their practices. Furthermore, initiatives on improving the innovation within the SMEs in the past, have addressed ways of improving the product innovation process, through a wide spectrum of methods, techniques and tools without quantifying the degree of change of ‘innovativeness’. The approach presented in this paper, addresses both these issues. In the first part of this paper, the most commonly used measures of innovation are presented, and the difficulties in applying them to SMEs are described. In the second part a new methodology is presented, which is based on measuring and benchmarking innovation with fuzzy logic, through an innovation survey. This is achieved by addressing three inter-related, but separately measurable, aspects of a company's innovation process—the ...

Panel Data Analysis

Abstract: The regression models discussed so far primarily used either cross-sectional or time series data. Each of these types of data has its exclusive features. This chapter discusses panel data regression models using the same group of entities like individuals, firms, states, countries, and the like over time. Panel data has a lot of advantages over pure cross-sectional data or pure time series data. The advantages are as follows: 1. Since panel data deals with individuals, firms, states, countries and so on over time, there is bound to be heterogeneity in these units, which may be often unobservable. The panel data estimation techniques can take such heterogeneity into account by allowing for subject-specific variables. The term subject includes micro units such individuals, firms or states. 2. By combining time series of cross-sectional observations, panel data gives “more informative data, more variability, less collinearity among variables, more degrees of freedom and more efficiency”. 3. By studying the repeated cross-sections of observations, panel data are better suited to study the dynamics of change. For example, unemployment, job turnover, duration of unemployment, and labor mobility are better studied with panel data. 4. Panel data can better detect and measure effects that cannot be observed in pure cross-sectional or time series data. For example, the effects of minimum wage laws on employment and earnings can be better studied if we follow successive waves of increases in federal and/or state minimum wages. 5. Phenomena such as economies of scale and technological change can be better studied by panel data than by pure cross-sectional or pure time series data.

Regional Development Agencies and the 'New Regionalism' in England

Abstract: (2000). Regional Development Agencies and the 'New Regionalism' in England. Regional Studies: Vol. 34, No. 9, pp. 857-864.