Introducing e-learning in a large multisite academic health sciences centre: a case study of e-curriculum planning and educator support /

This qualitative study investigated how a team of 7 hospital educators collaborated to develop e-curriculum units to pilot for a newly acquired learning -r management system at a large, multisite academic health sciences centre. A case study approach was used to examine how the e-Curriculum Team was structured, how the educators worked together to develop strategies to better utilize e-leaming in their ovwi practice, what e-curriculum they chose to develop, and how they determined their priorities for e-curriculum development. It also inquired into how they planned to involve other educators in using e-leaming. One set of semistructured interviews with the 6 hospital educators involved in the project, as well as minutes of team meetings and the researcher's journal, were analyzed (the researcher was also a hospital educator on the team). Project management structure, educator support, and organizational pressures on the implementation project feature prominently in the case study. This study suggests that implementation of e-leaming will be more successful if (a) educators involved in the development of e-leaming curriculum are supported in their role as change agents, (b) the pain of vmleaming current educational practice is considered, (c) the limitations of the software being implemented are recognized, (d) time is spent leaming about best practice, and (e) the project is protected as much as possible from organizational pressures and distractions.

Continuing education learning preferences and styles of legal clinic lawyers /

The purpose of this qualitative research was to study the learning preferences and styles of management lawyers who work in Ontario's legal aid clinics. Data were gathered from two sources and analyzed using the constant comparison method. A preand postconference survey provided the principal data on clinic lawyers' learning preferences. Follow-up interviews were then conducted with 3 purposefully selected survey participants to explore their personal learning styles. Kolb's experiential learning theory provided the theoretical framework for discussing personal learning styles. The findings showed a general consistency among the lawyers to learn by listening to lectures and experts. This preference may suggest a lingering influence from law school training. The lawyers' more informal learning associated with daily practice, however, appeared to be guided by various learning styles. The learning style discussions provided some support for Kolb's model but also confirmed some shortcomings noted by other authors. Educators who design continuing education programs for lawyers may benefit from some insights gained from this exploratory research. This study adds to a limited but growing body of work on the learning preferences and styles of lawyers and suggests new questions for future research.

The role of leaders in building organizational learning capacity

In a world in which social, economic, and environmental circumstances are continuously evolving and increasingly complex, leaders face the challenging prospect of navigating their organizations through unpredictable operating conditions. Finding a way to tap into the learning capacity of the people who comprise their organizations may be the answer to adapt and to survive. This qualitative research study explored the role of leaders in building this organizational learning capacity. The literature identified three domains of personal, interpersonal, and organizational capacity for learning in an organizational setting. Interviews with three senior leaders who had successfully built learning capacity in their respective organizations revealed four elements of leader commitment: (a) to the process of building learning capacity, (b) to organizational objectives and results, (c) to personal actions and behaviours, and (d) to the people of the organization. Each of the four elements of leader commitment spans the three domains of learning capacity that can guide leaders as they build organizational learning capacity.

The Family Game: A Parent Education Intervention to Increase Positive Parent-Child Interactions in Parents with Learning Difficulties

Children of parents with learning difficulties (LD) are at risk for a variety of developmental problems including behavioural and psychiatric disorders. However, there are no empirically supported programs to prevent behavioural and psychiatric problems in these children. The purpose of the study was to test the effectiveness of a parenting intervention designed to teach parents with learning difficulties positive child behaviour management strategies. A multiple baseline across skills design was used with two parents, who were taught three skills: 1) clear instructions, 2) recognition of compliance and 3) correction of noncompliance. Training scores improved on each skill and maintained at a 1-month follow-up. Scores on generalization cards were high and showed maintenance, but improvements in parenting skills in the naturalistic environment were low at posttest and follow-up. Increases were seen in child compliance at posttest and 1-month follow-up. Results of pre-post social validity measures were also generally positive.

Short-Term Load Forecast Of A Low Loadfactor Power System For Optimization Of Merit Order Dispatch Using Adaptive Learning Algorithm

Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year

Operational Flexibility: A Model for Effective Project Management

The aim of this study is to investigate the role of operational flexibility for effective project management in the construction industry. The specific objectives are to: a) Identify the determinants of operational flexibility potential in construction project management b) Investigate the contribution of each of the determinants to operational flexibility potential in the construction industry c) Investigate on the moderating factors of operational flexibility potential in a construction project environment d) Investigate whether moderated operational flexibility potential mediates the path between predictors and effective construction project management e) Develop and test a conceptual model of achieving operational flexibility for effective project management The purpose of this study is to findout ways to utilize flexibility inorder to manage uncertain project environment and ultimately achieve effective project management. In what configuration these operational flexibility determinants are demanded by construction project environment in order to achieve project success. This research was conducted in three phases, namely: (i) exploratory phase (ii) questionnaire development phase; and (iii) data collection and analysis phase. The study needs firm level analysis and therefore real estate developers who are members of CREDAI, Kerala Chapter were considered. This study provides a framework on the functioning of operational flexibility, offering guidance to researchers and practitioners for discovering means to gain operational flexibility in construction firms. The findings provide an empirical understanding on kinds of resources and capabilities a construction firm must accumulate to respond flexibly to the changing project environment offering practitioners insights into practices that build firms operational flexibility potential. Firms are dealing with complex, continuous changing and uncertain environments due trends of globalization, technical changes and innovations and changes in the customers’ needs and expectations. To cope with the increasingly uncertain and quickly changing environment firms strive for flexibility. To achieve the level of flexibility that adds value to the customers, firms should look to flexibility from a day to day operational perspective. Each dimension of operational flexibility is derived from competences and capabilities. In this thesis only the influence on customer satisfaction and learning exploitation of flexibility dimensions which directly add value in the customers eyes are studied to answer the followingresearch questions: “What is the impact of operational flexibility on customer satisfaction?.” What are the predictors of operational flexibility in construction industry? .These questions can only be answered after answering the questions like “Why do firms need operational flexibility?” and “how can firms achieve operational flexibility?” in the context of the construction industry. The need for construction firms to be flexible, via the effective utilization of organizational resources and capabilities for improved responsiveness, is important because of the increasing rate of changes in the business environment within which they operate. Achieving operational flexibility is also important because it has a significant correlation with a project effectiveness and hence a firm’s turnover. It is essential for academics and practitioners to recognize that the attainment of operational flexibility involves different types namely: (i) Modification (ii) new product development and (iii) demand management requires different configurations of predictors (i.e., resources, capabilities and strategies). Construction firms should consider these relationships and implement appropriate management practices for developing and configuring the right kind of resources, capabilities and strategies towards achieving different operational flexibility types.

Professionalisation of management on German universities: the research liaison officers

Occupations of higher education institutions such as public relations offices, research liaison offices etc. are increasing. A study related to research liaison officers was conducted in Germany to identify activity profiles and qualifications. Results show no standardised education or training, but only learning by doing. From the viewpoint of professionalisation theories a reasonable professionalisation can only be achieved through an organisation of the various occupations in the field of med-level university management as a whole. Proposals for professionalisation were made, such as more systematic education and improved integration into the organisation of HEIs. Staff development is needed as well as more jobs.

Learning achievements of farmers during the transition to market-oriented organic agriculture in rural Uganda

Organic agriculture requires farmers with the ability to develop profitable agro-enterprises on their own. By drawing on four years of experiences with the Enabling Rural Innovation approach in Uganda, we outline how smallholder farmers transition to organic agriculture and, at the same time, increase their entrepreneurial skills and competences through learning. In order to document this learning we operationalised the Kirkpatrick learning evaluation model, which subsequently informed the collection of qualitative data in two study sites. Our analysis suggests that the Enabling Rural Innovation approach helps farmers to develop essential capabilities for identifying organic markets and new organic commodities, for testing these organic commodities under varying organic farm management scenarios, and for negotiating contracts with organic traders. We also observed several obstacles that confront farmers’ transition to organic agriculture when using the Enabling Rural Innovation approach. These include the long duration of agronomic experimentation and seed multiplication, expensive organic certification procedures and the absence of adequate mechanism for farmers to access crop finance services. Despite prevailing obstacles we conclude that the Enabling Rural Innovation approach provides a starting point for farmers to develop entrepreneurial competences and profitable agro-enterprises on their own.

Adaptive Real-time Anomaly-based Intrusion Detection using Data Mining and Machine Learning Techniques

Die zunehmende Vernetzung der Informations- und Kommunikationssysteme führt zu einer weiteren Erhöhung der Komplexität und damit auch zu einer weiteren Zunahme von Sicherheitslücken. Klassische Schutzmechanismen wie Firewall-Systeme und Anti-Malware-Lösungen bieten schon lange keinen Schutz mehr vor Eindringversuchen in IT-Infrastrukturen. Als ein sehr wirkungsvolles Instrument zum Schutz gegenüber Cyber-Attacken haben sich hierbei die Intrusion Detection Systeme (IDS) etabliert. Solche Systeme sammeln und analysieren Informationen von Netzwerkkomponenten und Rechnern, um ungewöhnliches Verhalten und Sicherheitsverletzungen automatisiert festzustellen. Während signatur-basierte Ansätze nur bereits bekannte Angriffsmuster detektieren können, sind anomalie-basierte IDS auch in der Lage, neue bisher unbekannte Angriffe (Zero-Day-Attacks) frühzeitig zu erkennen. Das Kernproblem von Intrusion Detection Systeme besteht jedoch in der optimalen Verarbeitung der gewaltigen Netzdaten und der Entwicklung eines in Echtzeit arbeitenden adaptiven Erkennungsmodells. Um diese Herausforderungen lösen zu können, stellt diese Dissertation ein Framework bereit, das aus zwei Hauptteilen besteht. Der erste Teil, OptiFilter genannt, verwendet ein dynamisches "Queuing Concept", um die zahlreich anfallenden Netzdaten weiter zu verarbeiten, baut fortlaufend Netzverbindungen auf, und exportiert strukturierte Input-Daten für das IDS. Den zweiten Teil stellt ein adaptiver Klassifikator dar, der ein Klassifikator-Modell basierend auf "Enhanced Growing Hierarchical Self Organizing Map" (EGHSOM), ein Modell für Netzwerk Normalzustand (NNB) und ein "Update Model" umfasst. In dem OptiFilter werden Tcpdump und SNMP traps benutzt, um die Netzwerkpakete und Hostereignisse fortlaufend zu aggregieren. Diese aggregierten Netzwerkpackete und Hostereignisse werden weiter analysiert und in Verbindungsvektoren umgewandelt. Zur Verbesserung der Erkennungsrate des adaptiven Klassifikators wird das künstliche neuronale Netz GHSOM intensiv untersucht und wesentlich weiterentwickelt. In dieser Dissertation werden unterschiedliche Ansätze vorgeschlagen und diskutiert. So wird eine classification-confidence margin threshold definiert, um die unbekannten bösartigen Verbindungen aufzudecken, die Stabilität der Wachstumstopologie durch neuartige Ansätze für die Initialisierung der Gewichtvektoren und durch die Stärkung der Winner Neuronen erhöht, und ein selbst-adaptives Verfahren eingeführt, um das Modell ständig aktualisieren zu können. Darüber hinaus besteht die Hauptaufgabe des NNB-Modells in der weiteren Untersuchung der erkannten unbekannten Verbindungen von der EGHSOM und der Überprüfung, ob sie normal sind. Jedoch, ändern sich die Netzverkehrsdaten wegen des Concept drif Phänomens ständig, was in Echtzeit zur Erzeugung nicht stationärer Netzdaten führt. Dieses Phänomen wird von dem Update-Modell besser kontrolliert. Das EGHSOM-Modell kann die neuen Anomalien effektiv erkennen und das NNB-Model passt die Änderungen in Netzdaten optimal an. Bei den experimentellen Untersuchungen hat das Framework erfolgversprechende Ergebnisse gezeigt. Im ersten Experiment wurde das Framework in Offline-Betriebsmodus evaluiert. Der OptiFilter wurde mit offline-, synthetischen- und realistischen Daten ausgewertet. Der adaptive Klassifikator wurde mit dem 10-Fold Cross Validation Verfahren evaluiert, um dessen Genauigkeit abzuschätzen. Im zweiten Experiment wurde das Framework auf einer 1 bis 10 GB Netzwerkstrecke installiert und im Online-Betriebsmodus in Echtzeit ausgewertet. Der OptiFilter hat erfolgreich die gewaltige Menge von Netzdaten in die strukturierten Verbindungsvektoren umgewandelt und der adaptive Klassifikator hat sie präzise klassifiziert. Die Vergleichsstudie zwischen dem entwickelten Framework und anderen bekannten IDS-Ansätzen zeigt, dass der vorgeschlagene IDSFramework alle anderen Ansätze übertrifft. Dies lässt sich auf folgende Kernpunkte zurückführen: Bearbeitung der gesammelten Netzdaten, Erreichung der besten Performanz (wie die Gesamtgenauigkeit), Detektieren unbekannter Verbindungen und Entwicklung des in Echtzeit arbeitenden Erkennungsmodells von Eindringversuchen.

Online Learning of Non-stationary Sequences

We consider an online learning scenario in which the learner can make predictions on the basis of a fixed set of experts. The performance of each expert may change over time in a manner unknown to the learner. We formulate a class of universal learning algorithms for this problem by expressing them as simple Bayesian algorithms operating on models analogous to Hidden Markov Models (HMMs). We derive a new performance bound for such algorithms which is considerably simpler than existing bounds. The bound provides the basis for learning the rate at which the identity of the optimal expert switches over time. We find an analytic expression for the a priori resolution at which we need to learn the rate parameter. We extend our scalar switching-rate result to models of the switching-rate that are governed by a matrix of parameters, i.e. arbitrary homogeneous HMMs. We apply and examine our algorithm in the context of the problem of energy management in wireless networks. We analyze the new results in the framework of Information Theory.

Supporting graduate development through work based learning

The genesis of this innovation lies in the commitment of a national Irish business enterprise to the professional development of its staff in general, and to the enhancement of its Information Technologies (IT) staff specifically, in collaboration with a national Higher Education (HE) provider. A postgraduate degree, awarded by the HE provider, seeks to bring coherence and cohesion to the education and training provision for newly recruited IT graduate staff of the business enterprise, simultaneously acting both as an induction process for new staff and as a professional capacity building exercise, thereby enhancing the enterprise’s organisational learning and collective competence in the areas of information technologies, IT security and technical service management. The curriculum was designed by the HE provider in collaboration with the business enterprise to offer it to circa sixteen IT staff per cycle of delivery through a model known generally as the new apprenticeship for professional practice which uses a combination of college-based, block release taught elements, regular day release seminars and substantial work-based learning, supported by the academic staff of the HE provider and work-based support staff/mentors of the business enterprise. Academic quality assurance, pedagogical, assessment and accreditation responsibilities remain with the HE provider. (...)

Designing context-aware adaptive units of learning based on IMS-LD standard

Learning contents adaptation has been a subject of interest in the research area of the adaptive hypermedia systems. Defining which variables and which standards can be considered to model adaptive content delivery processes is one of the main challenges in pedagogical design over e-learning environments. In this paper some specifications, architectures and technologies that can be used in contents adaptation processes considering characteristics of the context are described and a proposal to integrate some of these characteristics in the design of units of learning using adaptation conditions in a structure of IMS-Learning Design (IMS-LD) is presented. The key contribution of this work is the generation of instructional designs considering the context, which can be used in Learning Management Systems (LMSs) and diverse mobile devices

Proyecto PupitreNet. La especificación del proyecto IMS : Instructional Management System.

Resumen tomado del autor

A User-Centric Approach to eCertificate for Electronic Identities (eIDs) Management in Mobile Environment

The use of electronic documents is constantly growing and the necessity to implement an ad-hoc eCertificate which manages access to private information is not only required but also necessary. This paper presents a protocol for the management of electronic identities (eIDs), meant as a substitute for the paper-based IDs, in a mobile environment with a user-centric approach. Mobile devices have been chosen because they provide mobility, personal use and high computational complexity. The inherent user-centricity also allows the user to personally manage the ID information and to display only what is required. The chosen path to develop the protocol is to migrate the existing eCert technologies implemented by the Learning Societies Laboratory in Southampton. By comparing this protocol with the analysis of the eID problem domain, a new solution has been derived which is compatible with both systems without loss of features.