Learning and Adjustment Outcomes in Socialized and Unsocialized Newcomers : An Ex- Post-Facto Comparative Study

Les restructurations et les mutations de plus en plus nombreuses dans les entreprises font évoluer la trajectoire de carrière des employés vers un cheminement moins linéaire et amènent une multiplication des changements de rôle (Delobbe & Vandenberghe, 2000). Les organisations doivent de plus en plus se soucier de l’intégration de ces nouveaux employés afin de leur transmettre les éléments fondamentaux du fonctionnement et de la culture qu’elles privilégient. Par contre, la plupart des recherches sur la socialisation organisationnelle portent sur les « meilleures pratiques », et les résultats qui en découlent sont mixtes. Cette étude comparative cherche à déterminer si et sur quelles variables les nouveaux employés socialisés par leur entreprise diffèrent des nouveaux employés « non socialisés ». Premièrement, cette étude vise à comparer ces deux groupes sur 1) les résultantes proximales (la maîtrise du contenu de la socialisation organisationnelle et la clarté de rôle) et 2) les résultantes distales (l’engagement organisationnel affectif, la satisfaction au travail et l’intention de quitter) du processus de socialisation organisationnelle, ainsi que sur 3) les caractéristiques des réseaux sociaux d’information, en contrôlant pour la proactivité. Dans un second temps, cette étude a pour objectif d’explorer si le processus de socialisation organisationnelle (les relations entre les variables) diffère entre les nouveaux employés socialisés ou non. Cinquante-trois nouveaux employés (moins d’un an d’ancienneté) d’une grande entreprise québécoise ont participé à cette étude. L’entreprise a un programme de socialisation en place, mais son exécution est laissée à la discrétion de chaque département, créant deux catégories de nouveaux employés : ceux qui ont été socialisés par leur département, et ceux qui n’ont pas été socialisés (« non socialisés »). Les participants ont été sondés sur les stratégies proactives, les résultantes proximales et distales et les caractéristiques des réseaux sociaux d’information. Pour le premier objectif, les résultats indiquent que les nouveaux employés socialisés maîtrisent mieux le contenu de la socialisation organisationnelle que les nouveaux employés non socialisés. En ce qui a trait au deuxième objectif, des différences dans le processus de socialisation organisationnelle ont été trouvées. Pour les nouveaux employés « non socialisés », la recherche proactive d’informations et la recherche de rétroaction sont liées à certaines caractéristiques des réseaux sociaux, alors que le cadrage positif est lié à la satisfaction au travail et à l’intention de quitter, et que la clarté de rôle est liée uniquement à la satisfaction au travail. Les nouveaux employés socialisés, quant à eux, démontrent des liens entre la maîtrise du contenu de la socialisation organisationnelle et chacune des résultantes distales (l’engagement organisationnel affectif, la satisfaction au travail et l’intention de quitter). Globalement, l’intégration des nouveaux employés non socialisés serait plutôt influencée par leurs stratégies proactives, tandis que celle des nouveaux employés non socialisés serait facilitée par leur maîtrise du contenu de la socialisation organisationnelle. De façon générale, cette étude comparative offre un aperçu intéressant des nouveaux employés rarement trouvé dans les recherches portant sur les « meilleures pratiques » de la socialisation organisationnelle. Des recommandations pour la recherche et la pratique en suivent.

E-Learning and Continuing Education in LIS

The aim of the study was to investigate the relevance of e—learning in continuing education of library professionals in the universities in Kerala. /55 part of a survey of library professionals in the seven major Universities in Kerala to find their continuing education needs, it was found that majority of the library professionals attend continuing education programmes (CEP) to be trained in the latest technologies. Internet resources were the preferred mode of information source by 38.9 per cent of the library professionals. The importance of continuing education in developing the competencies of library professionals is also stressed

Changing Role of Academic Libraries in the E-learning Environment: Issues and Challenges

The development of computer and network technology is changing the education scenario and transforming the teaching and learning process from the traditional physical environment to the digital environment. It is now possible to access vast amount of information online and enable one to one communication without the confines of place or time. While E-learning and teaching is unlikely to replace face-to-face training and education it is becoming an additional delivery method, providing new learning opportunities to many users. It is also causing an impact on library services as the increased use of ICT and web based learning technologies have paved the way for providing new ICT based services and resources to the users. Online learning has a crucial role in user education, information literacy programmes and in training the library professionals. It can help students become active learners, and libraries will have to play a greater role in this process of transformation. The significance of libraries within an institution has improved due to the fact that academic libraries and information services are now responsible for e-learning within their organization.

Prediction of Learning Disabilities in School Age Children using SVM and Decision Tree

This paper highlights the prediction of Learning Disabilities (LD) in school-age children using two classification methods, Support Vector Machine (SVM) and Decision Tree (DT), with an emphasis on applications of data mining. About 10% of children enrolled in school have a learning disability. Learning disability prediction in school age children is a very complicated task because it tends to be identified in elementary school where there is no one sign to be identified. By using any of the two classification methods, SVM and DT, we can easily and accurately predict LD in any child. Also, we can determine the merits and demerits of these two classifiers and the best one can be selected for the use in the relevant field. In this study, Sequential Minimal Optimization (SMO) algorithm is used in performing SVM and J48 algorithm is used in constructing decision trees.

Design and use of mobile technology in distance language education : Matching learning practices with technologies-in-practice

This thesis focuses on the adaptation of formal education to people’s technology- use patterns, theirtechnology-in-practice, where the ubiquitous use of mobile technologies is central. The research question is: How can language learning practices occuring in informal learning environments be effectively integrated with formal education through the use of mobile technology? The study investigates the technical, pedagogical, social and cultural challenges involved in a design science approach. The thesis consists of four studies. The first study systematises MALL (mobile-assisted language learning) research. The second investigates Swedish and Chinese students’ attitudes towards the use of mobile technology in education. The third examines students’ use of technology in an online language course, with a specific focus on their learning practices in informal learning contexts and their understanding of how this use guides their learning. Based on the findings, a specifically designed MALL application was built and used in two courses. Study four analyses the app use in terms of students’ perceived level of self-regulation and structuration. The studies show that technology itself plays a very important role in reshaping peoples’ attitudes and that new learning methods are coconstructed in a sociotechnical system. Technology’s influence on student practices is equally strong across borders. Students’ established technologies-in-practice guide the ways they approach learning. Hence, designing effective online distance education involves three interrelated elements: technology, information, and social arrangements. This thesis contributes to mobile learning research by offering empirically and theoretically grounded insights that shift the focus from technology design to design of information systems.

Planning, delivery and evaluation of information literacy training for engineering and technology students

Information literacy has become an important skill for undergraduate students due to societal changes that have seen information become a valuable commodity, the need for graduates to become lifelong learners, and the recognition that information literacy is an underpinning generic skill for effective learning in higher education. This paper describes a sequence of activities and technologies designed to help students learn and practice information literacy skills. These activities have been purposefully designed and integrated into a first-year engineering and technology study unit as a core syllabus element. A formal evaluation of aspects of these activities was planned and undertaken in semester one 2003.

Educating for professional capability in the field of information technology: integrating industry-based learning with the academic curriculum

In response to the forces of globalisation, societies and organisations have had to adapt and even proactively transform themselves. Universities, as knowledge-based organisations, have recognised that there are now many other important sites of knowledge construction and use. The apparent monopoly over valued forms of knowledge making and knowledge certification is disappearing. Universities have had to recognise the value of practical working knowledge developed in workplace settings beyond university domains, and promote the value of academic forms of knowledge making to the practical concerns of everyday learning. It is within this broader systems view that professional curriculum development undertaken by universities needs to be examined.

University educational planning responds to these external forces in ways that are drawing together formal academic capability/competence and practice-based capability/competence. Both forms of academic and practice-based knowledge and knowing are being equally valued and related one to the other. University planning in turn gives impetus to the development of new forms of professional education curricula. This paper presents a contemporary case of a designed professional curriculum in the field of information technology that situates workplace learning as a central element in the education of Information Technology (IT)/Information Systems (IS) professionals.

The key dimensions of the learning environment of Deakin University’s BIT (Hons) program are considered with a view to identifying areas of strong integration between the worlds of academic and workplace learning from the perspectives of major stakeholders. The dynamic interplay between forms of theorising and practising is seen as critical in educating students for professional capability in their chosen field. From this analysis, an applied research agenda, relating to desired forms of professional learning in higher education, is outlined, with specific reference to the information and communication technology professions.

Developing and teaching information systems for construction management students: a perspective in Deakin University

A new unit named Information Systems in Construction was developed and taught for the first time in the School of Architecture and Building at Deakin University in Semester 1 2003 for first-year construction management students. This paper reports on key issues that arose during the unit development process and the implementation of teaching activities. Special consideration is given to the learners (first year students), the teaching environment (online teaching and learning), the unit background (information technology and information system), and the discipline (international construction). Several suggestions are outlined for improving the unit development and delivery in the next round.

Gender and equity in e-Learning

Literature to date suggests contrary indicators of acceptance of the use of technology to support learning by females. With the increasing adoption of information technology to support teaching and learning, it is imperative that factors which may impede student learning are identified. The research reported here is of a large-scale survey of the perceptions of university students about eLearning and their use of the online learning environment. The aim of the survey was to gather data to inform about online learning practices at the University. The results were explored, amongst other factors, by gender. Findings include no significant differences between the female and male students with respect to being able to use the online learning environment confidently and effectively. In general the female students were more willing to participate in online discussions. However, there was no difference between the female and male students regarding their willingness to voice their opinions online. An unexpected result was the greater value placed by female students on using the online environment for communicating and collaborating with students of diverse background.

Fostering information security culture in small and medium size enterprises: an interpretive study in Australia

By having an effective organisational information security culture where employees intuitively protect corporate information assets, small and medium size enterprises (SMEs) could improve information security. However, previous research has largely overlooked the development of such a culture for SMEs, and the national context in which SMEs operate. The paper explores this topic and provides key findings from an interpretive Australian study based on a literature review, two focus groups and three case studies. A holistic framework is provided for fostering an information security culture in SMEs in a national setting. The paper discusses key managerial challenges for SMEs attempting to develop such a culture. The main findings suggest that Australian SME owners do not provide sufficient support for information security due to insufficient awareness of its importance and may also be affected by national attitudes to risk. The paper concludes that Australian SME owners may benefit from adopting a risk-based approach to information security and should be educated about the potential strategic role of information technology and information security. The paper also identifies the value and difficulty of promoting a behavioural and learning approach to information security to complement traditional technological and managerial approaches. Implications for theory and practice are discussed.

Designing blended learning in higher education : the neomillenial learner and mediated immersion

Blended learning as a term and a learning approach is still being refined, at times debated as a legitimate area of research, at times seen as the answer to the conundrum and challenges of the digital learner. Is it the Emperor’s new clothes? As Morrison (2003) suggests, blended learning could be seen as an uncertain or unsure strategy, or alternatively a way to find a solution to promises given for e-learning. Three case studies within this paper explore the possibilities of e-learning within a work-based framework. Elements of ‘neomillenial learning styles’ (Dede in Educause Quarterly vol 28 No 1 2005) reflected by students in postgraduate coursework programs provided the challenge and stimulation of designing and facilitating e-learning components, incorporating experiential or action learning with ‘associational’ approaches rather than linear ones. The journey to virtual simulations such as the postgraduate Newlandia incorporates the learner perspective, or how to activate neomillenial learning styles; blended learning with online and face-to-face community activist groups working for solutions to a water problem; and a virtual scenario which can appeal to and engage an internationalised user group. Do Dede’s neomillenial learners synthesise and process experiences rather than (or as well as) information? Is this mediated immersion a part of Newlandia’s applicability to the modern learner? The student teams of community activists and project managers described in the case studies incorporate a potent mix of learning styles, nationalities and backgrounds, expectations, interpersonal and technical skills and indicate a trend in millennial learners towards a community of knowledge which is collaborative, mobile and group-focused.

Developing effective learning programs : what extension can learn from the fields of adult education and learning communities

Learning is an investment in capacity building that has and will continue to reap rewards for primary producers and government in terms of increased sustainable production, profitability, exports, jobs and sustainable rural communities. Primary production operates in a context of continual change and requires up to date, complex and varied skills of primary producers and land managers.

A recent national research project funded by the Department of Agriculture, Forestry and Fisheries Australia confirmed that application of best practice from the theory of adult education in designing and developing learning programs in primary industry results in learning activities that provide information that is relevant to farmers’ needs, delivered in an entertaining way, and that draws on examples directly relevant to the participants. As a result, the training often exceeds the expectations of the participants.

The project produced a self-assessment checklist to identify ways of improving the development and delivery of training for extension practitioners and training providers. The key issues include continuous monitoring of client’s needs, and actively seeking opportunities to meet and work with industry organisations, other training providers and funding bodies.

There appear to be two drivers for the development of learning programs. One is problems or opportunities identified by people and organisations that could be termed ‘scanners’ and who tend not to be potential participants, the other is learning needs expressed by individuals or enterprises who want to participate in learning activities (participants). Scanners are typically industry organisations, government agencies and researchers, but may include providers and participants. Extension practitioners are well-placed to act as scanners.

It is very important that farmers and farmer organisations contribute to the development of new learning programs. Without industry input and support, extension practitioners and training providers cannot be expected to ensure they meet client needs. In other words, to develop effective learning programs, there must an industry learning community of producers, industry organisations, extension practitioners and training providers and other stakeholders such as supply chain enterprises, government and researchers.

Learning from large data : bias, variance, sampling, and learning curves

One of the fundamental machine learning tasks is that of predictive classification. Given that organisations collect an ever increasing amount of data, predictive classification methods must be able to effectively and efficiently handle large amounts of data. However, it is understood that present requirements push existing algorithms to, and sometimes beyond, their limits since many classification prediction algorithms were designed when currently common data set sizes were beyond imagination. This has led to a significant amount of research into ways of making classification learning algorithms more effective and efficient. Although substantial progress has been made, a number of key questions have not been answered. This dissertation investigates two of these key questions. The first is whether different types of algorithms to those currently employed are required when using large data sets. This is answered by analysis of the way in which the bias plus variance decomposition of predictive classification error changes as training set size is increased. Experiments find that larger training sets require different types of algorithms to those currently used. Some insight into the characteristics of suitable algorithms is provided, and this may provide some direction for the development of future classification prediction algorithms which are specifically designed for use with large data sets. The second question investigated is that of the role of sampling in machine learning with large data sets. Sampling has long been used as a means of avoiding the need to scale up algorithms to suit the size of the data set by scaling down the size of the data sets to suit the algorithm. However, the costs of performing sampling have not been widely explored. Two popular sampling methods are compared with learning from all available data in terms of predictive accuracy, model complexity, and execution time. The comparison shows that sub-sampling generally products models with accuracy close to, and sometimes greater than, that obtainable from learning with all available data. This result suggests that it may be possible to develop algorithms that take advantage of the sub-sampling methodology to reduce the time required to infer a model while sacrificing little if any accuracy. Methods of improving effective and efficient learning via sampling are also investigated, and now sampling methodologies proposed. These methodologies include using a varying-proportion of instances to determine the next inference step and using a statistical calculation at each inference step to determine sufficient sample size. Experiments show that using a statistical calculation of sample size can not only substantially reduce execution time but can do so with only a small loss, and occasional gain, in accuracy. One of the common uses of sampling is in the construction of learning curves. Learning curves are often used to attempt to determine the optimal training size which will maximally reduce execution time while nut being detrimental to accuracy. An analysis of the performance of methods for detection of convergence of learning curves is performed, with the focus of the analysis on methods that calculate the gradient, of the tangent to the curve. Given that such methods can be susceptible to local accuracy plateaus, an investigation into the frequency of local plateaus is also performed. It is shown that local accuracy plateaus are a common occurrence, and that ensuring a small loss of accuracy often results in greater computational cost than learning from all available data. These results cast doubt over the applicability of gradient of tangent methods for detecting convergence, and of the viability of learning curves for reducing execution time in general.

Information skills and the distance education student : an exploratory study into the approaches of Southern Cross University distance educators to the information needs of external students

This study unites the concepts of self-directed learning and information literacy in the external higher education environment. It asserts that many attempts by librarians at building better working relationships with distance educators have failed because the approaches of distance educators to the information needs of students are not adequately addressed. This exploratory and qualitatively based study examines the approaches of ten distance educators at Southern Cross University (SCU) to the information needs of their external students. It then makes recommendations based on these interviews which aim to improve relationships and co-operation between libraries and distance educators and to promote self-directed learning approaches by external students.

Microarray classification using statistical learning and decision tree algorithms

This considers the challenging task of cancer prediction based on microarray data for the medical community. The research was conducted on mostly common cancers (breast, colon, long, prostate and leukemia) microarray data analysis, and suggests the use of modern machine learning techniques to predict cancer.