Cultural impacts on e-learning systems' success

E-learning systems are enablers in the learning process, strengthening their importance as part of the educational strategy. Understanding the determinants of e-learning success is crucial for defining instructional strategies. Several authors have studied e-learning implementation and adoption, and various studies have addressed e-learning success from different perspectives. However, none of these studies have verified whether students' cultural characteristics, such as individualism versus collectivism (individualism/collectivism), play a determinant role in the perceived e-learning success. This study provides a deeper understanding of the impact of students' cultural characteristics, for individualism/collectivism, on the perceived outcomes of e-learning systems use. This study proposes an e-learning systems success model that includes a cultural construct, individualism/collectivism. This paper reports an empirical study developed through an electronic survey distributed to higher education students belonging to various learning levels and from various universities. The study applies quantitative methods to obtain results. Our findings demonstrate that learners' perceived individual impact is positively influenced by their satisfaction and e-learning systems' use. Results demonstrate the determinant role of individualism/collectivism on individual and organizational impacts. Students influenced by collective culture perceive more individual and organizational impacts than individualistic culture students. Individualism/collectivism also moderates the users' perceived satisfaction on individual impact, and from individual impacts to organizational impacts. The result shows that for the students with a stronger individualistic culture, satisfaction plays a central role in the way they assess the individual impacts, and individual impacts on organizational impacts. This empirical research discusses the theoretical and practical implications.info:eu-repo/semantics/acceptedVersio

Gamification: a key determinant of massive open online course (MOOC) success

Massive open online courses (MOOCs), contribute significantly to individual empowerment because they can help people learn about a wide range of topics. To realize the full potential of MOOCs, we need to understand their factors of success, here defined as the use, user satisfaction, along the individual and organizational performance resulting from the user involvement. We propose a theoretical framework to identify the determinants of successful MOOCs, and empirically measure these factors in a real MOOC context. We put forward the role of gamification and suggest that, together with information system (IS) theory, gamification proved to play a crucial role in the success of MOOCs.info:eu-repo/semantics/acceptedVersio

Business Intelligence in the Vineyard

The evolution that is nowadays taking place in the information and communication fields, namely in mobile computing and remote monitoring, constitutes a very interesting challenge to the agricultural sector. This reality places agronomic knowledge in centre stage as these technologies are dramatically improving data collection and storage capacities, challenging the farmers and the agricultural field experts to develop processes that efficiently transform data into information and knowledge and are able to support the everyday decision making at farm level. In this work we will present a demonstration project under way in a vineyard in Portugal where we are exploring the potential of the most recent technological innovations available in the market to build the i-Farm, the information and knowledge society intelligent farm. i-Farm (intelligent farm) applies at farm level the potential offered by using in an integrated way mobile solutions, sensor networks, wireless communication and digital imagery materialized in a information system that supports farmer real time decision making in the field and in the office. The i-Farm project creates a unique knowledge repository containing information from multiple sources (crop, environment, soil, operations, market, etc.) enabling accurate and timely decisions. For the project development a Business Intelligence approach is used. In the context of this paper this broad term is used to refer to the process of aggregating, processing and building rich and relevant information which is made available dynamically in real time to managers in an interactive way to support decisions and planning activitiesinfo:eu-repo/semantics/publishedVersio

Exploratory data analysis and clustering of multivariate spatial hydrogeological data by means of GEO3DSOM, a variant of Kohonen's Self-Organizing Map

International audienceThe use of unsupervised artificial neural network techniques like the self-organizing map (SOM) algorithm has proven to be a useful tool in exploratory data analysis and clustering of multivariate data sets. In this study a variant of the SOM-algorithm is proposed, the GEO3DSOM, capable of explicitly incorporating three-dimensional spatial knowledge into the algorithm. The performance of the GEO3DSOM is compared to the performance of the standard SOM in analyzing an artificial data set and a hydrochemical data set. The hydrochemical data set consists of 141 groundwater samples collected in two detritic, phreatic, Cenozoic aquifers in Central Belgium. The standard SOM proves to be more adequate in representing the structure of the data set and to explore relationships between variables. The GEO3DSOM on the other hand performs better in creating spatially coherent groups based on the data

A framework for using self-organising maps to analyse spatiotemporal patterns, exemplified by analysis of mobile phone usage

We suggest a visual analytics framework for the exploration and analysis of spatially and temporally referenced values of numeric attributes. The framework supports two complementary perspectives on spatio-temporal data: as a temporal sequence of spatial distributions of attribute values (called spatial situations) and as a set of spatially referenced time series of attribute values representing local temporal variations. To handle a large amount of data, we use the self-organising map (SOM) method, which groups objects and arranges them according to similarity of relevant data features. We apply the SOM approach to spatial situations and to local temporal variations and obtain two types of SOM outcomes, called space-in-time SOM and time-in-space SOM, respectively. The examination and interpretation of both types of SOM outcomes are supported by appropriate visualisation and interaction techniques. This article describes the use of the framework by an example scenario of data analysis. We also discuss how the framework can be extended from supporting explorative analysis to building predictive models of the spatio-temporal variation of attribute values. We apply our approach to phone call data showing its usefulness in real-world analytic scenarios

Bubbles in exchange rates and monetary policy

We evaluate the macroeconomic performance of different monetary policy rules when there are bubbles in the exchange rate. We do this in the context of a non-linear rational expectations model. The exchange rate is allowed to deviate from its fundamental value and the persistence of the deviation is modeled as a Markov switching process. Our results suggest that reacting to exchange rate movements does not significantly improve welfare. However, taking into account the switching nature of the economy may be more beneficial

Volatility in asset prices and long-run wealth effect estimates

We argue that the equation commonly used in the estimation of the wealth effect on consumption might be unsuitable for that purpose. In particular, if the usual assumptions are employed, the derivation of the equation implies that the wealth effect is indeterminate. Furthermore, it implies that the estimate of the wealth effect should decrease when asset wealth volatility increases. Estimation of a Markov-switching model of the usual long-run aggregate consumption equation provides evidence favourable to the indeterminacy hypothesis. © 2007 Elsevier B.V. All rights reserved