Learning with other health professions in the United Kingdom MPharm degree:Multidisciplinary and placement education

This paper reviews the approach to multidisciplinary and placement education in UK schools of pharmacy. The methodology involved triangulation of course documentation, staff interviews and a final year student survey. Staff members were supportive of multidisciplinary learning. The advantages were development of a wider appreciation of the students? future professional role and better understanding of the roles of other professional groups. The barriers were logistics (student numbers; multiple sites; different timetables), the achievement of balanced numbers between disciplines and engagement of students from all participating disciplines. Placement education was offered by all schools, predominantly in hospital settings. Key problems were funding and the lack of staff resources. Currently, multidisciplinary learning within the UK for pharmacy students is inadequate and is coupled with relatively low levels of placement education. In order for things to change, there should be a review of funding and support from government and the private sector employers.

Protein-protein interactions classification from text via local learning with class priors

Text classification is essential for narrowing down the number of documents relevant to a particular topic for further pursual, especially when searching through large biomedical databases. Protein-protein interactions are an example of such a topic with databases being devoted specifically to them. This paper proposed a semi-supervised learning algorithm via local learning with class priors (LL-CP) for biomedical text classification where unlabeled data points are classified in a vector space based on their proximity to labeled nodes. The algorithm has been evaluated on a corpus of biomedical documents to identify abstracts containing information about protein-protein interactions with promising results. Experimental results show that LL-CP outperforms the traditional semisupervised learning algorithms such as SVMand it also performs better than local learning without incorporating class priors.

Learning with a strategic management simulation game:a case study

The use of simulation games as a pedagogic method is well established though its effective use is context-driven. This study adds to the increasing growing body of empirical evidence of the effectiveness of simulation games but more importantly emphasises why by explaining the instructional design implemented reflecting best practices. This multi-method study finds evidence that student learning was enhanced through the use of simulation games, reflected in the two key themes; simulation games as a catalyst for learning and simulation games as a vehicle for learning. In so doing the research provides one of the few empirically based studies that support simulation games in enhancing learning and, more importantly, contextualizes the enhancement in terms of the instructional design of the curriculum. This research should prove valuable for those with an academic interest in the use of simulation games and management educators who use, or are considering its use. Further, the findings contribute to the academic debate concerning the effective implementation of simulation game-based training in business and management education.

Bayesian Learning with Dependency Structures via Latent Factors, Mixtures, and Copulas

Bayesian methods offer a flexible and convenient probabilistic learning framework to extract interpretable knowledge from complex and structured data. Such methods can characterize dependencies among multiple levels of hidden variables and share statistical strength across heterogeneous sources. In the first part of this dissertation, we develop two dependent variational inference methods for full posterior approximation in non-conjugate Bayesian models through hierarchical mixture- and copula-based variational proposals, respectively. The proposed methods move beyond the widely used factorized approximation to the posterior and provide generic applicability to a broad class of probabilistic models with minimal model-specific derivations. In the second part of this dissertation, we design probabilistic graphical models to accommodate multimodal data, describe dynamical behaviors and account for task heterogeneity. In particular, the sparse latent factor model is able to reveal common low-dimensional structures from high-dimensional data. We demonstrate the effectiveness of the proposed statistical learning methods on both synthetic and real-world data.

Reprint: Learning With a Strategic Management Simulation Q2 Game: A Case Study

The use of simulation games as a pedagogic method is well established though its effective use is context-driven. This study adds to the increasing growing body of empirical evidence of the effectiveness of simulation games but more importantly emphasises why by explaining the instructional design implemented reflecting best practices. This multimethod study finds evidence that student learning was enhanced through the use of simulation games, reflected in the two key themes; simulation games as a catalyst for learning and simulation games as a vehicle for learning. In so doing the research provides one of the few empirically based studies that support simulation games in enhancing learning and, more importantly, contextualizes the enhancement in terms of the instructional design of the curriculum. This research should prove valuable for those with an academic interest in the use of simulation games and management educators who use, or are considering its use. Further, the findings contribute to the academic debate concerning the effective implementation of simulation game-based training in business and management education.

Intergenerational learning with ICT: a case study

In a context of rapid demographic and technological changes, digital skills are essential in order for citizens to actively participate in society. However, digital literacy for all citizens, especially for the older population, is not yet a reality. It is increasingly crucial for active ageing, lifelong learning, and life-wide learning that the elderly learn digital skills. Intergenerational learning can play a key role in achieving a wide range of goals. This paper focuses on the contribution of intergenerational learning to digital and social inclusion. We promoted ICT intergenerational workshops and chose the case study methodolog y to study three distinct cases of intergenerational learning with ICT. The results show that intergenerational learning with ICT contributes to the digital literacy of adults and seniors and fosters lifelong learning, active ageing, and understanding and solidarity among generations. We reveal the benefits of the intergenerational learning process for all participants and suggest some ways to achieve intergenerational learning through ICT in order to build more socially and digitally cohesive societies.

Learning with MOOCs: promises and problems

Massive Open Online Courses (MOOCs) may be considered to be a new form of virtual technology enhanced learning environments. Since their first appearance in 2008, the increase in the number of MOOCs has been dramatic. The hype about MOOCs was accompanied by great expectations: 2012 was named the Year of the MOOCs and it was expected that MOOCs would revolutionise higher education. Two types of MOOCs may be distinguished: cMOOCs as proposed by Siemens, based on his ideas of connectivism, and xMOOCs developed in institutions such as Stanford and MIT. Although MOOCs have received a great deal of attention, they have also met with criticism. The time has therefore come to critically reflect upon this phenomenon.

How textbook design may influence learning with geography textbooks

This paper investigates how textbook design may influence students’ visual attention to graphics, photos and text in current geography textbooks. Eye tracking, a visual method of data collection and analysis, was utilised to precisely monitor students’ eye movements while observing geography textbook spreads. In an exploratory study utilising random sampling, the eye movements of 20 students (secondary school students 15–17 years of age and university students 20–24 years of age) were recorded. The research entities were double-page spreads of current German geography textbooks covering an identical topic, taken from five separate textbooks. A two-stage test was developed. Each participant was given the task of first looking at the entire textbook spread to determine what was being explained on the pages. In the second stage, participants solved one of the tasks from the exercise section. Overall, each participant studied five different textbook spreads and completed five set tasks. After the eye tracking study, each participant completed a questionnaire. The results may verify textbook design as one crucial factor for successful knowledge acquisition from textbooks. Based on the eye tracking documentation, learning-related challenges posed by images and complex image-text structures in textbooks are elucidated and related to educational psychology insights and findings from visual communication and textbook analysis.

Enhancing student learning with case-based teaching and audience response systems in an interdisciplinary Food Science course

A growing body of research in higher education suggests that teachers should move away from traditional lecturing towards more active and student-focus education approaches. Several classroom techniques are available to engage students and achieve more effective teaching and better learning experiences. The purpose of this paper is to share an example of how two of them – case-based teaching, and the use of response technologies – were implemented into a graduate-level food science course. The paper focuses in particular on teaching sensory science and sensometrics, including several concrete examples used during the course, and discussing in each case some of the observed outcomes. Overall, it was observed that the particular initiatives were effective in engaging student participation and promoting a more active way of learning. Case-base teaching provided students with the opportunity to apply their knowledge and their analytical skills to complex, real-life scenarios relevant to the subject matter. The use of audience response systems further facilitated class discussion, and was extremely well received by the students, providing a more enjoyable classroom experience.

Scaling up: Achieving a breakthrough in adult learning with technology

The first report commissioned by Ufi Charitable Trust. It investigates opportunities for and barriers to the application of digital technology to adult learning. It focuses on possible ways to transform the UK’s vocational education and training system, identifying three main priorities for funding by the Ufi Charitable Trust: * increasing the capability of those involved in running the vocational learning system * exploiting networks to bring together learners, learning content and learning professionals * harnessing computers to support individualised and differentiated learning.

The influence of emotions, attitudes and perceptions on learning with technology

Welcome to this very international issue of Research in Learning Technology in which we present research that has been undertaken in UK, Chile, Finland, Germany, Portugal and USA. The articles on the use of technology span a range of effective teaching practices, showcase strategies for successful learning and propose ideas for future mechanisms to better engage students in their educational experiences. For me, one question running through this issue is: how is technology helping us to deliver more student-centred education?

Removing noisy mentions for distant supervision

Los métodos para Extracción de Información basados en la Supervisión a Distancia se basan en usar tuplas correctas para adquirir menciones de esas tuplas, y así entrenar un sistema tradicional de extracción de información supervisado. En este artículo analizamos las fuentes de ruido en las menciones, y exploramos métodos sencillos para filtrar menciones ruidosas. Los resultados demuestran que combinando el filtrado de tuplas por frecuencia, la información mutua y la eliminación de menciones lejos de los centroides de sus respectivas etiquetas mejora los resultados de dos modelos de extracción de información significativamente.

Pre-processing for noise detection in gene expression classification data

Due to the imprecise nature of biological experiments, biological data is often characterized by the presence of redundant and noisy data. This may be due to errors that occurred during data collection, such as contaminations in laboratorial samples. It is the case of gene expression data, where the equipments and tools currently used frequently produce noisy biological data. Machine Learning algorithms have been successfully used in gene expression data analysis. Although many Machine Learning algorithms can deal with noise, detecting and removing noisy instances from the training data set can help the induction of the target hypothesis. This paper evaluates the use of distance-based pre-processing techniques for noise detection in gene expression data classification problems. This evaluation analyzes the effectiveness of the techniques investigated in removing noisy data, measured by the accuracy obtained by different Machine Learning classifiers over the pre-processed data.

A 1.2 V low noise amplifier with double feedback for high gain and low noise figure

Dissertação para obtenção do Grau de Mestre em Engenharia Eletrotécnica e de Computadores