Talent Management in Higher Education: Developing Emerging Leaders Within the Administration at Private Colleges and Universities

This research focused on identifying a series of successful practices relating to administrative talent management within the higher education setting. The field study included a thorough examination of seven small to mid-size private colleges and universities that have incorporated employee development strategies. These strategies were aimed at growing future leaders from within the organization in order to achieve continuity and support institutional priorities. Specifically, several focus areas were investigated including presidential vision, leadership commitment, talent management’s place among institutional priorities, program characteristics, and program evaluation. Among the commonalities that were gathered included support at the senior officer level who serve as advocates, mentors, and program facilitators, a strong connection between talent management and the institutions’ strategic plans, and a holistic approach to developing talent at all levels of the organizations. In addition, both coaching and opportunities for growth in the work environment were evident within several of the institutions. Also, academic leadership development was considered to be a part of the talent management strategy within three of the colleges and universities. The key differentiators included the incorporation of organizational and leadership competencies to provide focus toward the performance development process at two institutions, the implementation of a succession planning model at another institution, and the location of human resource generalists in departments across two of the institutions to identify learning opportunities for both individuals and work teams. Based on both the findings from the field study and the literature review, a comprehensive procedural model is introduced that serves to support human resource departments and higher education professionals, in general, who are looking to either begin or broaden their own talent management approach. However, despite the progress that has been made across several institutions noted throughout the research study, much more must be learned in terms of how the time and resources invested in talent management translates to institutional success. Advisor: James O‘Hanlon

Making Learning Visible: Peer Review and the Scholarship of Teaching

This is the promotional brochure from the March 2004 national conference, Making Learning Visible: Peer Review and the Scholarship of Teaching. This conference was hosted by the UNL Peer Review of Teaching project and the University of Nebraska-Lincoln.

DIGITAL LIBRARIES AND LEARNING OBJECTS REPOSITORIES

Discusses the technological changes that affects learning organizations as well as the human, technical, legal and sustainable aspects regarding learning objects repositories creation, maintenance and use. It presents concepts of information objects and learning objects, the functional requirements needed to their storage at Learning Management Systems. The role of Metadata is reviewed concerning learning objects creation and retrieval, followed by considerations about learning object repositories models, community participation/collaborative strategies and potential derived metrics/indicators. As a result of this desktop research, it can be said that not only technical competencies are critical to any learning objects repository implementation, but it urges that an engaged community of interest be establish as a key to support a learning object repository project. On that matter, researchers are applying Activity Theory (Vygostky, Luria y Leontiev) in order to seek joint perceptions and actions involving learning objects repository users, curators and managers, perceived as critical assets to a successful proposal.

Effect of a video on developing skills in undergraduate nursing students for the management of totally implantable central venous access ports

Background: Handling Totally Implantable Access Ports (TIAP) is a nursing procedure that requires skill and knowledge to avoid adverse events. No studies addressing this procedure with undergraduate students were identified prior to this study. Communication technologies, such as videos, have been increasingly adopted in the teaching of nursing and have contributed to the acquisition of competencies for clinical performance. Objective: To evaluate the effect of a video on the puncture and heparinization of TIAP in the development of cognitive and technical competencies of undergraduate nursing students. Method: Quasi-experimental study with a pretest-posttest design. Results: 24 individuals participated in the study. Anxiety scores were kept at levels 1 and 2 in the pretest and posttest. In relation to cognitive knowledge concerning the procedure, the proportion of correct answers in the pretest was 0.14 (SD=0.12) and 0.90 in the posttest (SD=0.05). After watching the video, the average score obtained by the participants in the mock session was 27.20. Conclusion: The use of an educational video with a simulation of puncture and heparinization of TIAP proved to be a strategy that increased both cognitive and technical knowledge. This strategy is viable in the teaching-learning process and is useful as a support tool for professors and for the development of undergraduate nursing students. (C) 2011 Elsevier Ltd. All rights reserved.

Knowledge management and strategic orientation: leveraging innovativeness and performance

Purpose - The aim of this study is to investigate whether knowledge management (KM) contributes to the development of strategic orientation and to enhance innovativeness, and whether these three factors contribute to improve business performance. Design/methodology/approach - A sample of 241 Brazilian companies was surveyed, using Web-based questionnaires with 54 questions, using ten-point scales to measure the degree of agreement on each item of each construct. Structural equation modeling techniques were applied for model assessment and analysis of the relationships among constructs. Exploratory factor analysis, confirmatory factor analysis, and path analysis using the technique of structural equation modeling were applied to the data. Findings - Effective KM contributes positively to strategic orientation. Although there is no significant direct effect of KM on innovativeness, the relationship is significant when mediated by strategic orientation. Similarly effective KM has no direct effect on business performance, but this relationship becomes statistically significant when mediated by strategic orientation and innovativeness. Research limitations/implications - The findings indicate that KM permeates all relationships among the constructs, corroborating the argument that knowledge is an essential organizational resource that leverages all value-creating activities. The results indicate that both KM and innovativeness produce significant impacts on performance when they are aligned with a strategic orientation that enables the organization to anticipate and respond to changing market conditions. Originality/value - There is a substantial body of research on several types of relationships involving KM, strategic orientation, innovativeness and performance. This study offers an original contribution by analyzing all of those constructs simultaneously using established scales so that comparative studies are possible.

Fidelity and game-based technology in management education

This study explores educational technology and management education by analyzing fidelity in game-based management education interventions. A sample of 31 MBA students was selected to help answer the research question: To what extent do MBA students tend to recognize specific game-based academic experiences, in terms of fidelity, as relevant to their managerial performance? Two distinct game-based interventions (BG1 and BG2) with key differences in fidelity levels were explored: BG1 presented higher physical and functional fidelity levels and lower psychological fidelity levels. Hypotheses were tested with data from the participants, collected shortly after their experiences, related to the overall perceived quality of game-based interventions. The findings reveal a higher overall perception of quality towards BG1: (a) better for testing strategies, (b) offering better business and market models, (c) based on a pace that better stimulates learning, and (d) presenting a fidelity level that better supports real world performance. This study fosters the conclusion that MBA students tend to recognize, to a large extent, that specific game-based academic experiences are relevant and meaningful to their managerial development, mostly with heightened fidelity levels of adopted artifacts. Agents must be ready and motivated to explore the new, to try and err, and to learn collaboratively in order to perform.

Knowledge management in intelligent tutoring systems

In the last years, Intelligent Tutoring Systems have been a very successful way for improving learning experience. Many issues must be addressed until this technology can be defined mature. One of the main problems within the Intelligent Tutoring Systems is the process of contents authoring: knowledge acquisition and manipulation processes are difficult tasks because they require a specialised skills on computer programming and knowledge engineering. In this thesis we discuss a general framework for knowledge management in an Intelligent Tutoring System and propose a mechanism based on first order data mining to partially automate the process of knowledge acquisition that have to be used in the ITS during the tutoring process. Such a mechanism can be applied in Constraint Based Tutor and in the Pseudo-Cognitive Tutor. We design and implement a part of the proposed architecture, mainly the module of knowledge acquisition from examples based on first order data mining. We then show that the algorithm can be applied at least two different domains: first order algebra equation and some topics of C programming language. Finally we discuss the limitation of current approach and the possible improvements of the whole framework.

Learning with Kernels on Graphs: DAG-based kernels, data streams and RNA function prediction.

In many application domains data can be naturally represented as graphs. When the application of analytical solutions for a given problem is unfeasible, machine learning techniques could be a viable way to solve the problem. Classical machine learning techniques are defined for data represented in a vectorial form. Recently some of them have been extended to deal directly with structured data. Among those techniques, kernel methods have shown promising results both from the computational complexity and the predictive performance point of view. Kernel methods allow to avoid an explicit mapping in a vectorial form relying on kernel functions, which informally are functions calculating a similarity measure between two entities. However, the definition of good kernels for graphs is a challenging problem because of the difficulty to find a good tradeoff between computational complexity and expressiveness. Another problem we face is learning on data streams, where a potentially unbounded sequence of data is generated by some sources. There are three main contributions in this thesis. The first contribution is the definition of a new family of kernels for graphs based on Directed Acyclic Graphs (DAGs). We analyzed two kernels from this family, achieving state-of-the-art results from both the computational and the classification point of view on real-world datasets. The second contribution consists in making the application of learning algorithms for streams of graphs feasible. Moreover,we defined a principled way for the memory management. The third contribution is the application of machine learning techniques for structured data to non-coding RNA function prediction. In this setting, the secondary structure is thought to carry relevant information. However, existing methods considering the secondary structure have prohibitively high computational complexity. We propose to apply kernel methods on this domain, obtaining state-of-the-art results.

Content and English Language Integrated Learning: The use of Moodle in Aircraft Maintenance Training Programs

The aim of this work is to develop a prototype of an e-learning environment that can foster Content and Language Integrated Learning (CLIL) for students enrolled in an aircraft maintenance training program, which allows them to obtain a license valid in all EU member states. Background research is conducted to retrace the evolution of the field of educational technology, analyzing different learning theories – behaviorism, cognitivism, and (socio-)constructivism – and reflecting on how technology and its use in educational contexts has changed over time. Particular attention is given to technologies that have been used and proved effective in Computer Assisted Language Learning (CALL). Based on the background research and on students’ learning objectives, i.e. learning highly specialized contents and aeronautical technical English, a bilingual approach is chosen, three main tools are identified – a hypertextbook, an exercise creation activity, and a discussion forum – and the learning management system Moodle is chosen as delivery medium. The hypertextbook is based on the technical textbook written in English students already use. In order to foster text comprehension, the hypertextbook is enriched by hyperlinks and tooltips. Hyperlinks redirect students to webpages containing additional information both in English and in Italian, while tooltips show Italian equivalents of English technical terms. The exercise creation activity and the discussion forum foster interaction and collaboration among students, according to socio-constructivist principles. In the exercise creation activity, students collaboratively create a workbook, which allow them to deeply analyze and master the contents of the hypertextbook and at the same time create a learning tool that can help them, as well as future students, to enhance learning. In the discussion forum students can discuss their individual issues, content-related, English-related or e-learning environment-related, helping one other and offering instructors suggestions on how to improve both the hypertextbook and the workbook based on their needs.

Predicting CMS datasets popularity with machine learning

In CMS è stato lanciato un progetto di Data Analytics e, all’interno di esso, un’attività specifica pilota che mira a sfruttare tecniche di Machine Learning per predire la popolarità dei dataset di CMS. Si tratta di un’osservabile molto delicata, la cui eventuale predizione premetterebbe a CMS di costruire modelli di data placement più intelligenti, ampie ottimizzazioni nell’uso dello storage a tutti i livelli Tiers, e formerebbe la base per l’introduzione di un solito sistema di data management dinamico e adattivo. Questa tesi descrive il lavoro fatto sfruttando un nuovo prototipo pilota chiamato DCAFPilot, interamente scritto in python, per affrontare questa sfida.

Big data, nosql e machine learning: un'applicazione di prediction e recommendation basata sulle api di Amazon

In questa tesi sono stati introdotti e studiati i Big Data, dando particolare importanza al mondo NoSQL, approfondendo MongoDB, e al mondo del Machine Learning, approfondendo PredictionIO. Successivamente è stata sviluppata un'applicazione attraverso l'utilizzo di tecnologie web, nodejs, node-webkit e le tecnologie approfondite prima. L'applicazione utilizza l'interpolazione polinomiale per predirre il prezzo di un bene salvato nello storico presente su MongoDB. Attraverso PredictionIO, essa analizza il comportamento degli altri utenti consigliando dei prodotti per l'acquisto. Infine è stata effetuata un'analisi dei risultati dell'errore prodotto dall'interpolazione.

A Personalized Privacy Management Framework for Android Applications

Ogni giorno, l'utente di smartphon e tablet, spesso senza rendersene conto, condivide, tramite varie applicazioni, un'enorme quantità di informazioni. Negli attuali sistemi operativi, l'assenza di meccanismi utili a garantire adeguatamente l'utente, ha spinto questo lavoro di ricerca verso lo sviluppo di un inedito framework.È stato necessario uno studio approfondito dello stato dell'arte di soluzioni con gli stessi obiettivi. Sono stati esaminati sia modelli teorici che pratici, con l'analisi accurata del relativo codice. Il lavoro, in stretto contatto con i colleghi dell'Università Centrale della Florida e la condivisione delle conoscenze con gli stessi, ha portato ad importanti risultati. Questo lavoro ha prodotto un framework personalizzato per gestire la privacy nelle applicazioni mobili che, nello specifico, è stato sviluppato per Android OS e necessita dei permessi di root per poter realizzare il suo funzionamento. Il framework in questione sfrutta le funzionalità offerte dal Xposed Framework, con il risultato di implementare modifiche al sistema operativo, senza dover cambiare il codice di Android o delle applicazioni che eseguono su quest’ultimo. Il framework sviluppato controlla l’accesso da parte delle varie applicazioni in esecuzione verso le informazioni sensibili dell’utente e stima l’importanza che queste informazioni hanno per l’utente medesimo. Le informazioni raccolte dal framework sulle preferenze e sulle valutazioni dell’utente vengono usate per costruire un modello decisionale che viene sfruttato da un algoritmo di machine-learning per migliorare l’interazione del sistema con l’utente e prevedere quelle che possono essere le decisioni dell'utente stesso, circa la propria privacy. Questo lavoro di tesi realizza gli obbiettivi sopra citati e pone un'attenzione particolare nel limitare la pervasività del sistema per la gestione della privacy, nella quotidiana esperienza dell'utente con i dispositivi mobili.

Knowledge Management and Decision Support for Sustainable Land Management

Much research has focused on desertification and land degradation assessments without putting sufficient emphasis on prevention and mitigation, although the concept of sustainable land management (SLM) is increasingly being acknowledged. A variety of SLM measures have already been applied at the local level, but they are rarely adequately recognised, evaluated, shared or used for decision support. WOCAT (World Overview of Technologies and Approaches) has developed an internationally recognised, standardised methodology to document and evaluate SLM technologies and approaches, including spatial distribution, allowing the sharing of SLM knowledge worldwide. The recent methodological integration into a participatory process allows now analysing and using this knowledge for decision support at the local and national level. The use of the WOCAT tools stimulates evaluation (self-evaluation as well as learning from comparing experiences) within SLM initiatives where all too often there is not only insufficient monitoring but also a lack of critical analysis. The comprehensive questionnaires and database system facilitate to document, evaluate and disseminate local experiences of SLM technologies and their implementation approaches. This evaluation process - in a team of experts and together with land users - greatly enhances understanding of the reasons behind successful (or failed) local practices. It has now been integrated into a new methodology for appraising and selecting SLM options. The methodology combines a local collective learning and decision approach with the use of the evaluated global best practices from WOCAT in a concise three step process: i) identifying land degradation and locally applied solutions in a stakeholder learning workshop; ii) assessing local solutions with the standardised WOCAT tool; iii) jointly selecting promising strategies for implementation with the help of a decision support tool. The methodology has been implemented in various countries and study sites around the world mainly within the FAO LADA (Land Degradation Assessment Project) and the EU-funded DESIRE project. Investments in SLM must be carefully assessed and planned on the basis of properly documented experiences and evaluated impacts and benefits: concerted efforts are needed and sufficient resources must be mobilised to tap the wealth of knowledge and learn from SLM successes.

Exploring the effectiveness of development research with a monitoring and learning approach

There is a growing demand for better understanding of the link between research, policy and practice in development. This article provides findings from a study that aimed to gain insights into how researchers engage with their non-academic partners. It draws on experiences from the National Centre of Competence in Research North-South programme, a development research network of Swiss, African, Asian and Latin American institutions. Conceptually, this study is concerned with research effectiveness as a means to identify knowledge useful for society. Research can be improved and adapted when monitoring the effects of interactions between researchers and non-academic partners. Therefore, a monitoring and learning approach was chosen. This study reveals researchers' strategies in engaging with non-academic partners and points to framing conditions considered decisive for soccessful interactions. It concludes that reserachrs need to systematically analyse the socio-political context in which they intervene. By providing insights from the ground and reflecting on them in the light of the latest theoretical concepts, this article contributes to the emerging literature founded on practice-based experience.

Reshaping Rural Extension: Learning for Sustainability (LforS): An Integrative and Learning-Based Advisory Approach for Rural Extension with Small-Scale Farmers

This publication offers concrete suggestions for implementing an integrative and learning-oriented approach to agricultural extension with the goal of fostering sustainable development. It targets governmental and non-governmental organisations, development agencies, and extension staff working in the field of rural development. The book looks into the conditions and trends that influence extension today, and outlines new challenges and necessary adaptations. It offers a basic reflection on the goals, the criteria for success and the form of a state-of-the-art approach to extension. The core of the book consists of a presentation of Learning for Sustainability (LforS), an example of an integrative, learning-oriented approach that is based on three crucial elements: stakeholder dialogue, knowledge management, and organizational development. Awareness raising and capacity building, social mobilization, and monitoring & evaluation are additional building blocks. The structure and organisation of the LforS approach as well as a selection of appropriate methods and tools are presented. The authors also address key aspects of developing and managing a learning-oriented extension approach. The book illustrates how LforS can be implemented by presenting two case studies, one from Madagascar and one from Mongolia. It addresses conceptual questions and at the same time it is practice-oriented. In contrast to other extension approaches, LforS does not limit its focus to production-related aspects and the development of value chains: it also addresses livelihood issues in a broad sense. With its focus on learning processes LforS seeks to create a better understanding of the links between different spheres and different levels of decision-making; it also seeks to foster integration of the different actors’ perspectives.