Ireland

This report will focuses on the current innovations and the future development of the practices and approaches to the assessment of learning in the area of work-based Vocational Education & Training in Ireland. The report is written from the perspective of the Irish Partner (Dublin City University) of the Leonardo da Vinci QualPraxis Research Project. In Ireland Vocational Education and Training (VET) exists mainly in the further education sector and this report will focus on this area

Learning Latent Characteristics of Data and Models using Item Response Theory

A supervised machine learning model is trained with a large set of labeled training data, and evaluated on a smaller but still large set of test data. Especially with deep neural networks (DNNs), the complexity of the model requires that an extremely large data set is collected to prevent overfitting. It is often the case that these models do not take into account specific attributes of the training set examples, but instead treat each equally in the process of model training. This is due to the fact that it is difficult to model latent traits of individual examples at the scale of hundreds of thousands or millions of data points. However, there exist a set of psychometric methods that can model attributes of specific examples and can greatly improve model training and evaluation in the supervised learning process. Item Response Theory (IRT) is a well-studied psychometric methodology for scale construction and evaluation. IRT jointly models human ability and example characteristics such as difficulty based on human response data. We introduce new evaluation metrics for both humans and machine learning models build using IRT, and propose new methods for applying IRT to machine learning-scale data. We use IRT to make contributions to the machine learning community in the following areas: (i) new test sets for evaluating machine learning models with respect to a human population, (ii) new insights about how deep-learning models learn by tracking example difficulty and training conditions, and (iii) new methods for data selection and curriculum building to improve model training efficiency, (iv) a new test of electronic health literacy built with questions extracted from de-identified patient Electronic Health Records (EHRs). We first introduce two new evaluation sets built and validated using IRT. These tests are the first IRT test sets to be applied to natural language processing tasks. Using IRT test sets allows for more comprehensive comparison of NLP models. Second, by modeling the difficulty of test set examples, we identify patterns that emerge when training deep neural network models that are consistent with human learning patterns. Specifically, as models are trained with larger training sets, they learn easy test set examples more quickly than hard examples. Third, we present a method for using soft labels on a subset of training data to improve deep learning model generalization. We show that fine-tuning a trained deep neural network with as little as 0.1% of the training data can improve model generalization in terms of test set accuracy. Fourth, we propose a new method for estimating IRT example and model parameters that allows for learning parameters at a much larger scale than previously available to accommodate the large data sets required for deep learning. This allows for learning IRT models at machine learning scale, with hundreds of thousands of examples and large ensembles of machine learning models. The response patterns of machine learning models can be used to learn IRT example characteristics instead of human response patterns. Fifth, we introduce a dynamic curriculum learning process that estimates model competency during training to adaptively select training data that is appropriate for learning at the given epoch. Finally, we introduce the ComprehENotes test, the first test of EHR comprehension for humans. The test is an accurate measure for identifying individuals with low EHR note comprehension ability, and validates the effectiveness of previously self-reported patient comprehension evaluations

THE COMMERCIAL POTENTIAL OF NEW DAIRY PRODUCTS FROM MEMBRANE TECHNOLOGY

Membrane filtration technologies are capable of creating entirely new, more functional food products. In this regard, potential new dairy products include high-protein, low-lactose fluid milk, high-protein, low-lactose ice cream, and non-far yogurt made with fewer stabilizers. An initial survey of membrane manufacturing companies determined the added cost to produce such functional food products to be two to six percent of the existing retail price for similar standard dairy products. A subsequent survey of milk processors found that the most likely adopters of such membrane technologies were yogurt manufacturers.Agribusiness,

Innovative instruments for the accreditation of vocational learning outcomes: recognition and validation of prior learning in vocationally related education in Ireland

This paper seeks to outline the key aspects of the validation and recognition of prior learning in the vocational education sector in Ireland In line with the current EU CREDIVOC project special attention will be paid to the common sector area, in this case engineering. McCarthy et al (2001) suggest that ‘VET systems can only be adequately understood with reference to the dynamic set of interrelationships between the education and training systems, the industrial relations system, the organizational structure of industry, and the class and status relations of the wider society as reflected in its political system’ (p. 425). It is important to observe that the context of any situation is relevant, not more so than in Ireland due to the rapid economic growth the country has experienced in the last ten to fifteen years. With Europe’s drive to consolidate its policies within the economic sectors through its members towards a knowledge economy (Brinkley & Lee 2006) the streamlining and harmonization of qualifications systems is key to this success. To help with this success it is firstly important to map current trends throughout Europe in vocational sectors

Diagnostic and clinical considerations in prolonged grief disorder Consideraciones diagnósticas y clínicas del trastorno por duelo prolongado Considérations et diagnostiques cliniques dans le deuil prolongé pathologique

This review focuses on the similarities and differences between prolonged grief disorder (PGD) and post-traumatic stress disorder (PTSD). It highlights how a PTSD-related understanding aids the investigation and clinical management of PGD. Grief has long been understood as a natural response to bereavement, as serious psychological and physiological stress has been regarded as a potential outcome of extreme or traumatic stress. PTSD was first included in DSM-III in 1980. In the mid-1980s, the first systematic investigation began into whether there is an extreme or pathological form of mourning. Meanwhile, there is much research literature on complicated, traumatic, or prolonged grief This literature is reviewed in this article, with the following questions: Is it possible to distinguish normal from non-normal grief? Which clinical presentation does PGD have—and how does this compare with PTSD? Finally, diagnostic, preventive, and therapeutic approaches and existing tools are presented. Esta revisión se centra en las semejanzas y diferencias entre el trastorno por duelo prolongado (TDP) y el trastorno por estrés postraumático (TEPT). Se destaca cómo una interpretación relacionada con el TEPT ayuda a la investigación y al manejo clínico del TDP. Desde hace mucho tiempo se ha supuesto que el duelo es una respuesta natural a la pérdida, y como un estrés psicológico y fisiológico grave se lo ha considerado el resultado potencial de un estrés extremo o traumático. El TEPT se incluyó ini-cialmente en el DSM-lll en 1980. A mediados de los años 1380 la primera investigación sistemática se orientó a definir si existe una forma extrema o patológica del duelo. Entretanto se ha acumulado bastante literatura relacionada con la investigación sobre duelo complicado, traumático o prolongado. En este artículo se revisa esta literatura con las siguientes preguntas: ¿Es posible distinguir el duelo normal del anormal? ¿ Cuáles son las presentaciones clínicas del TDP y cómo se diferencian del TEPT? Para finalizar se presentan las aproximaciones y herramientas disponibles para el diagnóstico, la prevención y el tratamiento. Cet article s'intéresse aux ressemblances et différences entre le deuil prolongé pathologique (DPP) et l'état de stress posi-traumatique (ESPT). La façon dont la compréhension de I'ESPT aide à la recherche et a la prise en charge clinique du DPP y est soulignée. La douleur morale a longtemps été considérée comme une réponse naturelle a la perte d'un être cher, de même qu'une réaction de stress sévère psychologique et physiologique était considérée comme une évolution potentielle d'un facteur de stress extrême ou traumatique. L'ESPT a été inclus dans le DSM-III en 1980. Au milieu des années 80 eut lieu la première recherche systématique pour savoir s'il existait une forme extrême ou pathologique de deuil. Dans I'intervalle, la littérature s'est enrichie sur le deuil prolongé, traumatique ou complique; nous I'analysons ici en posant les questions suivantes: est-il possible de distinguer la douleur morale normale de la douleur morale anormale après la perte d'un être cher? Comment se présente cliniquement le DPP et comment le comparer a I'ESPT? Et enfin, nous concluons en présentant les outils existants et les approches thérapeutiques, préventives et diagnostiques. // This review focuses on the similarities and differences between prolonged grief disorder (PGD) and post-traumatic stress disorder (PTSD). It highlights how a PTSD-related understanding aids the investigation and clinical management of PGD. Grief has long been understood as a natural response to bereavement, as serious psychological and physiological stress has been regarded as a potential outcome of extreme or traumatic stress. PTSD was first included in DSM-III in 1980. In the mid-1980s, the first systematic investigation began into whether there is an extreme or pathological form of mourning. Meanwhile, there is much research literature on complicated, traumatic, or prolonged grief This literature is reviewed in this article, with the following questions: Is it possible to distinguish normal from non-normal grief? Which clinical presentation does PGD have-and how does this compare with PTSD? Finally, diagnostic, preventive, and therapeutic approaches and existing tools are presented

Accreditation of vocational learning outcomes: perspectives for a European transfer

The fundamental principle that EQF and ECVET have in common is the description of qualifications in terms of learning outcomes. The background for implementing this outcome-based approach in the European education and training systems, however, is quite diverse. This situation is addressed by the CREDIVOC project, which involves partners from Austria, Finland, France, Germany and Ireland and focuses on the identification, testing and transfer of instruments that can be used for the recognition and accreditation of learning outcomes from initial and continuing vocational education and training for further education. The present publication is the major outcome of the first phase of the project, which aimed at the production of a general overview of the accreditation procedures and instruments in the partner countries. To this end, national case studies concerning the accreditation of vocational learning outcomes in Austria, Finland, France, Germany and Ireland have been carried out by the project partners. In order to allow for comparison between the different national approaches a common analytical framework was adopted. The criteria focus especially on the type of recognition (individual vs. blanket recognition) and the methodology of the assessment tools or instruments used. A synthesis report summarises the results of the national case studies and draws some conclusions as to what types of accreditation procedures and instruments might be appropriate for improving the transparency of qualifications and the mobility between educational programmes in Europe. (DIPF/orig.) Das gemeinsame Grundprinzip von EQR und ECVET ist die Beschreibung von Qualifikationen durch Lernergebnisse. Die Ausgangsbedingungen für eine Umsetzung dieses ergebnisorientierten Ansatzes in den europäischen Systemen der allgemeinen und beruflichen Bildung sind jedoch sehr unterschiedlich. Dieser Problematik widmet sich das Projekt CREDIVOC, das von Partnern aus Deutschland, Finnland, Frankreich, Irland und Österreich durchgeführt wird und die Identifikation, die Erprobung und den Transfer von Instrumenten zur Anrechnung beruflicher Lernergebnisse auf weiterführende Bildungsgänge zum Gegenstand hat. Die vorliegende Publikation ist das Ergebnis der ersten Projektphase, die der Herstellung einer allgemeinen Übersicht über die Anrechnungsverfahren und instrumente in den Partnerländern gewidmet war. Zu diesem Zweck haben die Partner nationale Fallstudien zur Anrechnung beruflicher Lernergebnisse in den Partnerländern durchgeführt. Um einen Vergleich der Ergebnisse zu ermöglichen, wurde ein gemeinsames Vergleichsraster erarbeitet, dessen Kriterien in der Hauptsache die Art der Anrechnung (individuelle vs. pauschale Anrechnung) sowie die Methodik der Verfahren betreffen. Ein abschließender Synthesebericht fasst die Ergebnisse der einzelnen Länderkapitel zusammen und entwickelt Schlussfolgerungen zu der Frage, welche Ansätze und Instrumente der Anrechnung beruflicher Lernergebnisse besonders geeignet sind, die Transparenz von Qualifikationen und die Bildungsmobilität in Europa zu verbessern. (DIPF/Orig.) Document type: Boo

H-COAL: Human Correction of AI-Generated Labels for Biomedical Named Entity Recognition

With the rapid advancement of machine learning models for NLP tasks, collecting high-fidelity labels from AI models is a realistic possibility. Firms now make AI available to customers via predictions as a service (PaaS). This includes PaaS products for healthcare. It is unclear whether these labels can be used for training a local model without expensive annotation checking by in-house experts. In this work, we propose a new framework for Human Correction of AI-Generated Labels (H-COAL). By ranking AI-generated outputs, one can selectively correct labels and approach gold standard performance (100% human labeling) with significantly less human effort. We show that correcting 5% of labels can close the AI-human performance gap by up to 64% relative improvement, and correcting 20% of labels can close the performance gap by up to 86% relative improvement.Comment: Presented at Conference on Information Systems and Technology (CIST) 202

Multiple approaches to reflection as a key component of assessment

This case study focuses on the learning outcomes of two separate modules within the programme: Supervised Work-Based Practice (SWBP) and Microteaching. Using ‘constructive alignment’ (Biggs, 1996), the assessors are interested in the students not only having an understanding of the skills and knowledge required as a teacher/trainer but also the ‘higher order elements’ leading to a deep understanding of themselves and the environment they are working in. The emphasis on ‘reflection’ is crucial to the assessment as the School aims to produce students who are not only knowledgeable but competent