Enterprise systems (ES) are important business software which can be difficult to implement, while the failure to account for organisational culture can lead to projects that are expensive and late. However most of the existing research has focused on national level culture. As such little is known of how organisational culture influences the implementation of enterprise systems. This ongoing r...

Student modelling systems must operate in an environment in which a student’s mastery of a subject matter is likely to change as a lesson progresses. A student model is formed from evaluation of evidence about the student’s mastery of the domain. However, given that such mastery will change, older evidence is likely to be less valuable than recent evidence. Data ageing addresses this issue by d...

Virtual or Managed Learning Environments (VMLEs) cannot be fully effective unless well-integrated with existing campus information systems. Institutional planning for the UK Research Assessment Exercise (RAE) has provided an unexpected impetus at the University of Bristol. The DataHub, a reporting database created initially to back-end a locally developed Web application (IRIS) to support the R...

BACKGROUND AND OBJECTIVES Encouraging student engagement in the large-classroom setting can be difficult. Challenges include the depersonalized nature of the environment and the fact that students frequently find asking questions and participating in class discussion intimidating. Social media has the potential to address these barriers, but this has not yet been formally evaluated. Our study a...

The concept of the multirelation coe cient is de ned to describe the closeness of a set of variables to a linear relation This concept extends the linear correlation between two variables to two or more variables Parameters of a beta distribution are determined that are utilized to approximate signi cance levels of the multirelation coe cient for any given number of observations and variables A...

This article examines the ability of time-varying Gaussian and Student t copulas to accurately predict the probability of joint extreme co-movements in stock index returns. Using a sample of more than 20 years of daily return observations of the Eurostoxx 50 and Dow Jones Industrial 30 stock indices, Gaussian and Student t copulas are calibrated daily on a rolling window of the 250 most recent ...

In signed social networks, link sign prediction refers to using the observed link signs to infer the signs of the remaining links, which is important for mining and analyzing the evolution of social networks. The widely used matrix factorization-based approach – Bayesian Probabilistic Matrix Factorization (BMF), assumes that the noise between the real and predicted entry is Gaussian noise, and ...

A new variational Bayesian learning algorithm for Student-t mixture models is introduced. This algorithm leads to (i) robust density estimation, (ii) robust clustering and (iii) robust automatic model selection. Gaussian mixture models are learning machines which are based on a divide-and-conquer approach. They are commonly used for density estimation and clustering tasks, but are sensitive to ...

Increasingly, higher education institutions are exploring the potential of learning analytics to predict student retention, understand learning behaviors, and improve student learning through providing personalized feedback and support. The technical development of learning analytics has outpaced consideration of ethical issues surrounding their use. Of particular concern is the absence of the ...

We examine whether stringent formal sector borrowing requirements in developing countries restrict credit access and the potential of asset-collateralized loans. When a Kenyan dairy cooperative exogenously replaced high down payments with loans collateralized by the asset itself a large water tank loan take-up increased from 2.4% to 41.9%. In contrast, substituting joint liability requirements ...