Giving voice to lifelong learning in professional nursing practice

The purpose of this phenomenological study was to uncover the meaning of lifelong learning to nurses in an Academic Health Care setting. Six female pediatric nurses were interviewed and audiotaped in response to 2 main questions of interpretation and engagement in lifelong learning with respect to their nursing practice. Four additional probing questions elicited responses of further qualities and characteristics of the meaning of lifelong learning. The emergent themes uncovered the characteristics and nature of the journey of lifelong learning. The themes evolved into parallel characteristics developing into the concepts of personal empowerment and occupational authorship. The personal empowerment concept involved processes whereby the participants overcame or removed barriers to engage in personal lifelong learning. Participants utilized personal power and internal motivators to sustain their engagement in lifelong learning. The occupational authorship concept involved participants controlling their exploration into lifelong learning through collaboration and recognition of occupational demands to be met as a professional. The remaining themes revealed a seasoning journey. This journey entailed a process of mastery through the themes of engagement discord, discovery pilgrimage, transforming, and maturation. The engagement in this journey resulted in their lifelong learning to becoming more intuitive and a part oftheir being. The overall theme uncovered from the journeys was one of a vocation described as a call to thinking critically of nursing practice. The participants responded to lifelong learning as a call to be a good nurse by using critical thinking through reflection, transformative and constructionist learning processes. This study gave voice to the meaning of lifelong learning in their nursing practice as interpreted by -ao the nurse participants.

Instructor support for self-directed learning in higher education

This study addressed the problem of instructor support for self-directed learning, specifically, learner-directed program planning, within a classroom setting in higher education. A combination of survey, interview, document analysis, and observation was used to assess and evaluate the attitudes and practices of a sample of full-time faculty at an Ontario university. Eighty-seven percent of the study sample reported instructional beliefs, values, and expectations that were not supportive of self-directed learning, especially in terms of student participation in program planning. Planning was seen as the responsibility of the instructor. Instructors were least open to student participation in the planning of the evaluation of learning. However, there was considerable stated support for other of the basic principles of adult education. The remaining 13% of the study sample reported instructional beliefs, values, and expectations that were fully supportive of self-directed learning. Instructional practices were analyzed in relation to the instructors' stated beliefs. Although practices reflected, in many instances, instructors' statements of support, there were some significant discrepancies between apparent support for the concept of self-directed learning and actual classroom practice. Both beliefs and practice were compared to a research model of self-directed learning. Most instructors did not have a concept of self-directed learning as comprehensive as that described in the research model. Instructor support for self-directed learning was profoundly influenced by the university setting. It was concluded that more strenuous attempts to research, enhance, and promote instructional and institutional support for self-directed learning in higher education are warranted.

The transformation of teachers: an adult learning approach

The study focused on the teacher as an adult learner rather than an instructor. A sample of three hundred and three elementary school teachers completed a two-part Likert survey questionnaire. The instrument was developed by the researcher in an attempt to operationalize Mezirow's Theory of Perspective Transformation. The four sub-scales collected information about teachers as they perceived themselves as adult learners and the way they conceptualize critical SelfReflection, Meaning perspectives and New Insights (Mezirow, 1978, 1981, 1989, 1990) within a framework of Mezirow's concept of Transformative Learning. Survey research methodology was used. Frequency distributions, means, and standard deviation were calculated. Reliability analysis and Pearson 'r' correlations established the internal consistency of items It Cross tabulations to describe differences in responses across demographic valuables were computed. The survey results indicated that teachers perceived themselves as self-directed learners. The findings support the need for a better understanding of the teacher as an adult learner so that teacher inservice programs and teacher supervision and evaluation can provide a viable learning alternative to the existing models used in practice.

The relationship of individual, team and organizational learning in Ontario hospital clinical labratories

I t is generally accepted among scholars that individual learning and team learning contribute to the concept we refer to as organizational learning. However, a small number of quantitative and qualitative studies that have investigated their relationship reported contradicting results. This thesis investigated the relationship between individual learning, team learning, and organizational learning. A survey instrument was used to collect information on individual learning, team learning, and organizational learning. The study sample comprised of supervisors from the clinical laboratories in teaching hospitals and community hospitals in Ontario. The analyses utilized a linear regression to investigate the relationship between individual and team learning. The relationship between individual and organizational learning, and team and organizational learning were simultaneously investigated with canonical correlation and set correlation. T-test and multivariate analysis of variance were used to compare the differences in learning scores of respondents employed by laboratories in teaching and those employed by community hospitals. The study validated its tests results with 1,000 bootstrap replications. Results from this study suggest that there are moderate correlations between individual learning and team learning. The correlation individual learning and organizational learning and team learning and organizational learning appeared to be weak. The scores of the three learning levels show statistically significant differences between respondents from laboratories in teaching hospitals and respondents from community hospitals.

The Implementations of Professional Learning Communities (PLCs) in Beijing and Ontario Schools

Since the knowledge-based economy has become a fashion over the last few decades, the concept of the professional learning community (PLC) has started being accepted by educational institutions and governments as an effective framework to improve teachers’ collective work and collaboration. The purpose of this research was to compare and contrast the implementations of PLCs between Beijing schools and Ontario schools from principals’ personal narratives. In order to discover the lessons and widen the scope to understand the PLC, this research applied qualitative design to collect the data from two principal participants in each location by semistructured interviews. Four themes emerged: (a) structure and technology, (b) identity and climate, (c) task and support, and (d) change and challenge. This research found that the root of the characteristics of the PLCs in Beijing and Ontario was the different existing teaching and learning systems as well as the test systems. Teaching Research Groups (TRGs) is one of the systems that help Chinese to organize routine time and input resources to improve teachers’ professional development. However, Canadian schools lack a similar system that guarantees the time and resources. Moreover, standardized test plays different roles in China and Canada. In China, standardized tests, such as the college entrance examination, are regarded as the important purpose of education, whereas Ontario principals saw the Education Quality and Accountability Office (EQAO) as a tool rather than a primary purpose. These two main differences influenced principals’ beliefs, attitudes, strategies, and practices. The implications based on this discovery provide new perspectives for principals, teachers, policy makers, and scholars to widen and deepen the research and practice of the PLC.

The antecedents to participation in learning activities among support staff at a college in Ontario

Les tendances de la participation à la formation des adultes au Canada n’ont pas évolué depuis des décennies, malgré les nouvelles influences économiques qui ont stimulé l’augmentation et la diversification permanente de la formation des employés et malgré les initiatives plus nombreuses en faveur de l’apprentissage des employés en milieu de travail. Il est donc nécessaire de ne plus se contenter d’étudier les prédicteurs de la formation déjà connus dans les profils des employés et des employeurs. Il est, en revanche, indispensable d’étudier les antécédents de la participation des employés à la formation, y compris les aspects et les étapes du processus qui la précède. Cette étude porte sur les antécédents de la participation des employés aux formations dans un important collège communautaire urbain en Ontario. Afin de préparer le recueil des données, un cadre théorique a été élaboré à partir du concept d’expression de la demande. Ce cadre implique l’existence d’un processus qui comporte plusieurs étapes, au cours desquelles plusieurs intervenants interagissent et dont la formation est susceptible d’être le résultat. Les résultats de l’enquête sur le profil d’apprentissage ont permis de conclure que le comportement des employés et de l’employeur est conforme aux modèles de prédicteurs existants et que les taux et les types de participation étaient similaires aux tendances nationales et internationales. L’analyse des entrevues d’un groupe d’employés atypiques, de leurs superviseurs, ainsi que de représentants du collège et du syndicat, a révélé d’importants thèmes clés : l’expression de la demande n’est pas structurée et elle est communiquée par plusieurs canaux, en excluant parfois les superviseurs. De plus, la place de l’auto évaluation est importante, ainsi que la phase de prise de décision. Ces thèmes ont souligné l’interaction de plusieurs intervenants dans le processus d’expression de la demande d’apprentissage et pendant la prise de décision. L’examen des attentes de chacun de ces intervenants au cours de ce processus nous a permis de découvrir un désir tacite chez les superviseurs et les employés, à savoir que la conversation soit à l’initiative de « l’autre ». Ces thèmes clés ont été ensuite abordés dans une discussion qui a révélé une discordance entre le profil de l’employeur et les profils des employés. Celle-ci se prête à la correction par l’employeur de son profil institutionnel pour l’harmoniser avec le profil dispositionnel des employés et optimiser ainsi vraisemblablement son offre de formation. Ils doivent, pour cela, appliquer un processus plus systématique et plus structuré, doté de meilleurs outils. La discussion a porté finalement sur les effets des motivations économiques sur la participation des employés et a permis de conclure que, bien que les employés ne semblent pas se méfier de l’offre de formation de l’employeur et que celle ci ne semble pas non plus les décourager, des questions de pouvoir sont bel et bien en jeu. Elles se sont principalement manifestées pendant le processus de prise de décision et, à cet égard, les superviseurs comme les employés reconnaissent qu’un processus plus structuré serait bénéfique, puisqu’il atténuerait les problèmes d’asymétrie et d’ambiguïté. Les constatations de cette étude sont pertinentes pour le secteur de la formation des adultes et de la formation en milieu de travail et, plus particulièrement, pour la méthodologie de recherche. Nous avons constaté l’avantage d’une méthodologie à deux volets, à l’écoute de l’employeur et des employés, afin de mieux comprendre la relation entre l’offre de formation et la participation à la formation. La définition des antécédents de la participation sous la forme d’un processus dans lequel plusieurs intervenants remplissent plusieurs rôles a permis de créer un modèle plus détaillé qui servira à la recherche future. Ce dernier a démontré qu’il est indispensable de reconnaître que la prise de décision constitue une étape à part entière, située entre l’expression de la demande et la participation à la formation. Ces constatations ont également révélé qu’il est véritablement indispensable que le secteur de la formation des adultes continue à traiter les questions reliées à la reconnaissance de la formation informelle. Ces conclusions et la discussion sur les constatations clés nous ont inspiré des recommandations à appliquer pour modifier les retombées du processus précédant la participation des employés à la formation. La majorité de ces recommandations ont trait à l’infrastructure de ce processus et ciblent donc principalement l’employeur. Certaines recommandations sont cependant destinées aux syndicats, aux superviseurs et aux employés qui peuvent aider l’employeur à remplir son rôle et favoriser la participation efficace de tous à ce processus. Les recommandations qui précédent impliquent que ce sont les antécédents de la formation qui gagneraient à être plus structurés et non la formation elle même. La structuration de l’infrastructure de l’apprentissage présente cependant des risques à elle seule. En liaison avec ce phénomène, une étude spécifique des effets de la nature, de la qualité et de l’asymétrie de la relation superviseur employé sur la participation des employés à la formation serait bénéfique. Mots clés : formation en entreprise, formation professionnelle continue, antécédents à la participation, employés de soutien

Learning analysis by reduction from positive data

Analysis by reduction is a linguistically motivated method for checking correctness of a sentence. It can be modelled by restarting automata. In this paper we propose a method for learning restarting automata which are strictly locally testable (SLT-R-automata). The method is based on the concept of identification in the limit from positive examples only. Also we characterize the class of languages accepted by SLT-R-automata with respect to the Chomsky hierarchy.

Efficient data mining based on formal concept analysis

Formal Concept Analysis is an unsupervised learning technique for conceptual clustering. We introduce the notion of iceberg concept lattices and show their use in Knowledge Discovery in Databases (KDD). Iceberg lattices are designed for analyzing very large databases. In particular they serve as a condensed representation of frequent patterns as known from association rule mining. In order to show the interplay between Formal Concept Analysis and association rule mining, we discuss the algorithm TITANIC. We show that iceberg concept lattices are a starting point for computing condensed sets of association rules without loss of information, and are a visualization method for the resulting rules.

Conceptual knowledge processing with formal concept analysis and ontologies

Among many other knowledge representations formalisms, Ontologies and Formal Concept Analysis (FCA) aim at modeling ‘concepts’. We discuss how these two formalisms may complement another from an application point of view. In particular, we will see how FCA can be used to support Ontology Engineering, and how ontologies can be exploited in FCA applications. The interplay of FCA and ontologies is studied along the life cycle of an ontology: (i) FCA can support the building of the ontology as a learning technique. (ii) The established ontology can be analyzed and navigated by using techniques of FCA. (iii) Last but not least, the ontology may be used to improve an FCA application.

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.

Learning from Ambiguity

There are many learning problems for which the examples given by the teacher are ambiguously labeled. In this thesis, we will examine one framework of learning from ambiguous examples known as Multiple-Instance learning. Each example is a bag, consisting of any number of instances. A bag is labeled negative if all instances in it are negative. A bag is labeled positive if at least one instance in it is positive. Because the instances themselves are not labeled, each positive bag is an ambiguous example. We would like to learn a concept which will correctly classify unseen bags. We have developed a measure called Diverse Density and algorithms for learning from multiple-instance examples. We have applied these techniques to problems in drug design, stock prediction, and image database retrieval. These serve as examples of how to translate the ambiguity in the application domain into bags, as well as successful examples of applying Diverse Density techniques.

Teaching an Old Robot New Tricks: Learning Novel Tasks via Interaction with People and Things

As AI has begun to reach out beyond its symbolic, objectivist roots into the embodied, experientialist realm, many projects are exploring different aspects of creating machines which interact with and respond to the world as humans do. Techniques for visual processing, object recognition, emotional response, gesture production and recognition, etc., are necessary components of a complete humanoid robot. However, most projects invariably concentrate on developing a few of these individual components, neglecting the issue of how all of these pieces would eventually fit together. The focus of the work in this dissertation is on creating a framework into which such specific competencies can be embedded, in a way that they can interact with each other and build layers of new functionality. To be of any practical value, such a framework must satisfy the real-world constraints of functioning in real-time with noisy sensors and actuators. The humanoid robot Cog provides an unapologetically adequate platform from which to take on such a challenge. This work makes three contributions to embodied AI. First, it offers a general-purpose architecture for developing behavior-based systems distributed over networks of PC's. Second, it provides a motor-control system that simulates several biological features which impact the development of motor behavior. Third, it develops a framework for a system which enables a robot to learn new behaviors via interacting with itself and the outside world. A few basic functional modules are built into this framework, enough to demonstrate the robot learning some very simple behaviors taught by a human trainer. A primary motivation for this project is the notion that it is practically impossible to build an "intelligent" machine unless it is designed partly to build itself. This work is a proof-of-concept of such an approach to integrating multiple perceptual and motor systems into a complete learning agent.

Learning and adaptation in physical heterogeneous teams of robots

In this paper we present a novel approach to assigning roles to robots in a team of physical heterogeneous robots. Its members compete for these roles and get rewards for them. The rewards are used to determine each agent’s preferences and which agents are better adapted to the environment. These aspects are included in the decision making process. Agent interactions are modelled using the concept of an ecosystem in which each robot is a species, resulting in emergent behaviour of the whole set of agents. One of the most important features of this approach is its high adaptability. Unlike some other learning techniques, this approach does not need to start a whole exploitation process when the environment changes. All this is exemplified by means of experiments run on a simulator. In addition, the algorithm developed was applied as applied to several teams of robots in order to analyse the impact of heterogeneity in these systems

Ventajas que aporta el E-Learning a los procesos de diferenciación estratégica e internacionalización en la Universidad Del Rosario

En el presente trabajo se analiza la existencia y argumenta la importancia de las ventajas que aporta el E-Learning al proceso de Internacionalización en la Universidad del Rosario, además se indaga si dichas ventajas podrían facilitar la diferenciación estratégica de la misma. Inicia con una revisión teórica sobre los conceptos de educación virtual y aprendizaje, y su estado actual en Colombia, logrando la creación de un marco teórico. En una segunda etapa se identificarán las características que comparte la institución educativa con una organización y que la hacen objeto de estudio en el campo estratégico, específicamente en cuanto a la diferenciación. Posteriormente se describirán las etapas de implementación del E-Learning en la Universidad, analizando los aspectos más importantes de este proceso. Más adelante se hace una aproximación al concepto de internacionalización y la importancia que tiene en el mundo multicultural actual. Finalmente se relacionan las ventajas de la implementación del E-Learning con las brindadas en el proceso de internacionalización y se argumenta si estas facilitan la diferenciación estratégica del Rosario.

Leadership: A complex concept awaiting a new explanation?

Leaders have the task of developing future strategy while being consciously engaged in executing current strategy and mapping landmarks, pathways and obstacles which they meet asthey endeavor to traverse challenging, rapidly evolving terrain. In an era in which there is a global leadership credibility crisis, business as usual is no longer an option in the pursuit of the longer-term survival of any organization. The leadership approach to complexity outlined here is based on learning to achieve results through experimentation, learning, and reflection. A case study is presented that illustrates the application of this approach. In this paper, the reader is first introduced to a brief overview of some key definitions and debates, shifting leadership boundaries, and emerging accountabilities and opportunities. This is followed by a summary of some of the key topics and issues that face current and future leaders.