The Need For Networks Among Public,Academic, and School Libraries in Metropolitan Sierra Leone

Metropolitan Sierra Leone is made up of Freetown, the capital city and its environs. Within its bounds are dispersed a variety of libraries, each with the mission of providing adequate, relevant and up‐to‐date materials tailored to the needs of their numerous clientele. However, because of stringent budget cuts and a lack of human and material resources, these institutions are unable to carry out their missions. One way to improve this situation is through collaboration in the provision of materials and services. This article explores the need for the establishment for networks among public, academic and school libraries in metropolitan Sierra Leone. The article begins by defining metropolis followed by a brief recounting of some features of a metropolis, the library scene in metropolitan Sierra Leone and a consideration of plausible areas for networks among these libraries. The article concludes with a discussion of some issues that have to be faced if the proposed network is to materialise.     

Public Library Services in the Knowledge Economy: The Sierra Leone Experience

Sierra Leone's knowledge economy stresses the importance of information for national development, and libraries have a crucial role to play in this development. Libraries are catalysts for human progress because they help in the development and transmission of knowledge and culture; they foster civic awareness in support of economic productivity and innovation in society. Although many economic programs have been implemented by the Sierra Leone government, a vast amount of information is unused, either because national decision-makers do not realize its importance or because people who might want it do not know how to access it. The public library has to play an increasingly significant role if rapid economic recovery is to be made. This article examines Sierra Leone's economy in postwar reconstruction, the importance of information and knowledge in a knowledge economy, and the problems affecting library services and how the public library can overcome these problems and make meaningful contributions to the knowledge economy.     

A multilevel model for effects of social capital and knowledge sharing in knowledge-intensive work teams

Although it is a widely held belief that social capital facilitates knowledge sharing among individuals, there is little research that has deeply investigated the impacts of social capital at different levels on an individual's knowledge sharing behavior. To address this research gap, this study combines a multilevel approach and an optimal network configuration view to investigate the multilevel effects of social capital on individuals’ knowledge sharing in knowledge intensive work teams. This study makes a distinction between the social capital at the team-level and that of social capital at the individual level to examine their cross-level and direct effects on an individual's sharing of explicit and tacit knowledge. A survey involving 343 participants in 47 knowledge-intensive teams was conducted for testing the multilevel model. The results reveal that social capital at both levels jointly influences an individual's explicit and tacit knowledge sharing. Further, when individuals possess a moderate betweenness centrality and the whole team holds a moderate network density, team members’ knowledge sharing can be maximized. These findings offer a more comprehensive and precise understanding of the multilevel impacts of social capital on team members’ knowledge sharing behavior, thus contributing to the social capital theory, as well as knowledge management research and practices.     

Laser cleaning of terracotta decorations of the portal of Palos of the Cathedral of Seville

Laser cleaning has been used to restore the soiled terracotta statues and decorations of the tympanum of the portal of Palos of the Cathedral of Seville in Spain. A simultaneous laboratory study performed on a representative sample helped to identify the optimum laser conditions to remove the dark soiling layer produced by air pollution. It was found that irradiation at 1064 nm with a Q-switched Nd:YAG laser was more effective than the harmonic wavelengths of 532 or 266 nm. LIBS and Raman microscopy gave information on the composition of terracotta and identified the presence of a protective layer made of gypsum and calcite. As detected by Raman spectroscopy, laser irradiation caused the elimination of the carbon component of the soiling layer and the appearance of an anhydrite component in the laser irradiated gypsum layer applied over the terracotta substrate for protective purposes. Local heating of the surface caused by laser irradiation at 1064 nm, the laser wavelength used for restoration of the portal, might be responsible for a process of partial dehydration of gypsum into anhydrite.     

Towards a personality understanding of information technology students and their IT learning in UAE university

This research investigates the personality characteristics of Information Technology students (CIT) in UAE University (UAEU) and how such features impact their IT learning. To achieve this objective, this research attempts to explain the impact of the Big-5 factors on learning using survey research. Results from 179 respondents suggested that agreeableness, extraversion, openness, and conscientiousness respectively were the most important strategies adopted by CIT students. However, neuroticism scored the lowest. Such results could be attributed to personal as well as to cultural reasons as highlighted in this research. The research highlights theoretical as well as professional contributions and implications. Some of challenges in this research could be addressed by designing programs aiming at enhancing student’s learning ability from the perspective of their personal traits.     

Learning Environment and its Association with Student Satisfaction Among Mathematics Students in Brunei Darussalam

This article reports a study of lower secondary mathematics classroom learning environment in Brunei Darussalam and its association with students' satisfaction with learning mathematics among a sample of 1565 students from 81 classes in 15 government secondary schools. Students' perceptions of the classroom learning environments were assessed with a version of the My Class Inventory (MCI) that had been modified for the Brunei context. The study revealed a satisfactory factor structure for a refined three-scale version of the MCI assessing cohesiveness, difficulty and competition. This finding is noteworthy because the factorial validity of the MCI has not previously been established in past research in other countries. Also each scale displayed satisfactory internal consistency reliability and discriminant validity and was able to differentiate between the perceptions of students in different classes. A one-way MANOVA revealed that students generally perceived a positive learning environment in mathematics classes. Also the study supported earlier research suggesting that boys and girls hold different perceptions of the same classroom learning environments. Relationships between student satisfaction and classroom environment were investigated using simple and multiple correlation analyses, using both the individual student and class mean as units of analysis. Associations between satisfaction and the learning environment were statistically significant both at student and class levels for most MCI scales. This revised version was published online in August 2006 with corrections to the Cover Date.     

Neural network approach to predict mobile learning acceptance

The proliferation of mobile computing technologies is playing major role in the growth of mobile learning (M-learning) market around the globe. The purpose of this paper is to develop a research model in the lines of commonly used models the Unified Theory of Acceptance and Use of Technology (UTAUT) and Technology Acceptance Model (TAM) by incorporating constructs namely flexibility learning, social learning, efficiency learning, enjoyment learning, suitability learning, and economic learning that can predict M-learning adoption in a developing country. The data were collected from 388 students from all major universities/colleges in the capital city (Muscat) of Oman. The neural network modeling was employed to predict M-learning adoption. The neural network modeling results showed that flexibility learning, social learning, efficiency learning, enjoyment learning, suitability learning, and economic learning variables have significant influence on the intention of students to accept mobile learning. The key outcomes of this study suggest important determinants that can assist academic administrators and telecommunication service providers to enhance the adoption of M-learning with the help of suitable strategy.