BET on Top Hat: challenges to improve language proficiency

Within the business context, communication and interaction tends to be considerably rooted in the use of English (as lingua franca), as well as in ICT use. Thus, professionals have to be able to speak the English language, resorting to specific, internationally recognised terminology and be proficient in the use of manifold ICT tools. In fact, the tendency is for the great majority of higher education (HE) students to own mobile devices (laptops, smartphones and/or tablets) and use them to access information and communicate/interact with content and other people. Bearing this in mind, a teaching and learning strategy was designed, in which m-learning (i.e. learning in which the delivery platform is a mobile device) was used to approach Business English Terminology (BET). The strategy was labelled as ‘BET on Top Hat’, once the selected application was Top Hat (https://tophat.com/) and the idea was for students to face it as if it were a game/challenge. In this scenario, the main goals of this exploratory study were to find evidence as to: i) the utility of m-learning activities for learning BET and ii) if and how m-learning activities can generate intrinsic motivation in students to learn BET. Participants (n=23) were enrolled in English II, a curricular unit of the 1st cycle degree in Retail Management offered at Águeda School of Technology and Management – University of Aveiro (2014/15 edition). The data gathered included the students’ results in quizzes and their answers to a short final evaluation questionnaire regarding their experience with BET on Top Hat. Consequently, data were treated and analysed resorting to descriptive statistical analysis, and, when considered pertinent, the teacher’s observation notes were also considered. The results unveil that, on the one hand, the strategy had a clear positive impact on the students’ intrinsic motivation and, on the other hand, the students’ performance as to BET use tended to improve over time.

An alternative benchmarking approach for electricity utility regulation using maximum entropy

The main purpose of this study is to present an alternative benchmarking approach that can be used by national regulators of utilities. It is widely known that the lack of sizeable data sets limits the choice of the benchmarking method and the specification of the model to set price controls within incentive-based regulation. Ill-posed frontier models are the problem that some national regulators have been facing. Maximum entropy estimators are useful in the estimation of such ill-posed models, in particular in models exhibiting small sample sizes, collinearity and non-normal errors, as well as in models where the number of parameters to be estimated exceeds the number of observations available. The empirical study involves a sample data used by the Portuguese regulator of the electricity sector to set the parameters for the electricity distribution companies in the regulatory period of 2012-2014. DEA and maximum entropy methods are applied and the efficiency results are compared.