“Showing off” your mobile device:adult literacy learning in the classroom and beyond

For a very large number of adults, tasks such as reading. understanding, and using everyday items are a challenge. Although many community-based organizations offer resources and support for adults with limited literacy skills. current programs have difficulty reaching and retaining those that would benefit most. In this paper we present the findings of an exploratory study aimed at investigating how a technological solution that addresses these challenges is received and adopted by adult learners. For this, we have developed a mobile application to support literacy programs and to assist low-literacy adults in today's information-centric society. ALEX© (Adult Literacy support application for Experiential learning) is a mobile language assistant that is designed to be used both in the classroom and in daily life in order to help low-literacy adults become increasingly literate and independent. Through a long-term study with adult learners we show that such a solution complements literacy programs by increasing users' motivation and interest in learning, and raising their confidence levels both in their education pursuits and in facing the challenges of their daily lives.

Putting supply chain learning theory into practice:lessons from an Irish case

The logistics service market is currently going through a fundamental transition. The development of closer relationships with customers and the continuous adaptation of products and services, represent potentially successful approaches to the development of improved competitive capability. To this end knowledge resources and learning processes increasingly represent key elements within the evolving framework of the 3PL business. This paper describes the case of NITL’s Foundation Certificate Programme (FCP) learning programme with specific reference to its use in addressing some of current shortcomings related to supply chain knowledge and skills in the Irish third party logistics (3PL) industry. The FCP rationale is based on the need to move from traditional approaches of supply chain organisation where the various links in the chain were measured and managed in isolation from each other and thus tended to operate at cross purposes, towards more integrated approaches.

ICT adoption by logistics service providers:developing a learning agenda

Recent years have seen innovations in the logistics and freight transport industry in relation to Information and communication technologies (ICT) diffusion. The implementation of such technologies by third party logistics providers (3PLs) allows the real-time exchange of information between supply chain partners, thereby improving planning capability and customer service. However, the logistics and freight transport industry is lagging somewhat behind other sectors in ICT diffusion. In relation to the latter point, it is important to note that the dissemination of ICT in logistics and supply chain management (SCM) is shifting the 3PL industry to an increasingly knowledge-intensive approach. In this process, the role of learning becomes more central and an assessment of the impact of future ICT learning needs for the logistics providers is a strategic imperative. The aim of this paper is to assess the impact of ICT on logistics and freight transport industry in Italy and Ireland, and to identify learning needs for more effective ICT adoption in 3PLs.

Using observation ageing to improve Markovian model learning in QoS engineering

Markovian models are widely used to analyse quality-of-service properties of both system designs and deployed systems. Thanks to the emergence of probabilistic model checkers, this analysis can be performed with high accuracy. However, its usefulness is heavily dependent on how well the model captures the actual behaviour of the analysed system. Our work addresses this problem for a class of Markovian models termed discrete-time Markov chains (DTMCs). We propose a new Bayesian technique for learning the state transition probabilities of DTMCs based on observations of the modelled system. Unlike existing approaches, our technique weighs observations based on their age, to account for the fact that older observations are less relevant than more recent ones. A case study from the area of bioinformatics workflows demonstrates the effectiveness of the technique in scenarios where the model parameters change over time.