Apprenticeship training in England: a cost-effective model for firms?

In England, the government plans to incentivise spending of billions of pounds over the next few years promoting apprenticeships, with most of the finance raised from the apprenticeship levy on employers. Promoting more apprenticeships is designed to improve England’s skill base – a government policy priority given the relatively low level of skills and educational qualifications amongst a large part of the country’s workforce. But does such a policy make sense in an English context, with a historically limited participation of many employers in work related formal training? Is additional spending on apprenticeships likely to lead to positive economic returns for employers, workers and for England itself? And how varied are the net economic returns by employer and by sector? What works for one category of employment may not bring positive gains where returns to training are much lower. To answer these questions the JPMorgan Chase Foundation, the Education Policy Institute and the Bertelsmann Stiftung have come together and partnered with the internationally acknowledged economist Prof. Dr. Stefan C. Wolter to explore the costs and benefits of apprenticeship training for companies in England. This report by Prof. Dr. Stefan C. Wolter and Eva Joho brings a much needed degree of rigour and quantification to a policy area which is too often characterised by assumption, hunch, and international experience which may not apply in a very different country context. The authors have used evidence from Germany, Switzerland and Austria to simulate the costs and benefits of an apprenticeship policy applied in an English context. They are aware of the limitations of this approach - not least given the different tradition of employer engagement in England - but the analysis in this report is important and could help guide employer and government policies in directions that maximise economic returns and limit low return scenarios. In particular, the return by occupations is shown to be highly varied based on the return and cost characteristics of each sector. The returns by employer within each sector also vary markedly. The key conclusions the authors have derived in the report could help steer English policymakers and employers in more evidence based directions, which should help ensure that England’s large investment in this area is properly informed by evidence and more likely to yield positive returns. In addition, the present study complements studies with a similar methodology in Spain (2016) and Italy (to be published 2018), which will enable learnings for successful implementation of apprenticeship models across countries

Slicing and dicing the information space using local contexts

In recent years there has been growing interest in faceted grouping of documents for Interactive Information Retrieval (IIR). It is suggested that faceted grouping can offer a flexible way of browsing a collection compared to clustering. However, the success of faceted grouping seems to rely on sufficient knowledge of collection structure. In this paper we propose an approach based on the local contexts of query terms, which is inspired by the interaction of faceted search and browsing. The use of local contexts is appealing since it requires less knowledge of the collection than existing approaches. A task-based user study was carried out to investigate the effectiveness of our interface in varied complexity. The results suggest that the local contexts can be exploited as the source of search result browsing in IIR, and that our interface appears to facilitate different aspects of search process over the task complexity. The implication of the evaluation methodology using high complexity tasks is also discussed

Retrieving descriptive phrases from large amounts of free text

This paper presents a system that retrieves descriptive phrases of proper nouns from free text. Sentences holding the specified noun are ranked using a technique based on pattern matching, word counting, and sentence location. No domain specific knowledge is used. Experiments show the system able to rank highly those sentences that contain phrases describing or defining the query noun. In contrast to existing methods, this system does not use parsing techniques but still achieves high levels of accuracy. From the results of a large-scale experiment, it is speculated that the success of this simpler method is due to the high quantities of free text being searched. Parallels between this work and recent findings in the very large corpus track of TREC are drawn

Concept-based Interactive Query Expansion Support Tool (CIQUEST)

This report describes a three-year project (2000-03) undertaken in the Information Studies Department at The University of Sheffield and funded by Resource, The Council for Museums, Archives and Libraries. The overall aim of the research was to provide user support for query formulation and reformulation in searching large-scale textual resources including those of the World Wide Web. More specifically the objectives were: to investigate and evaluate methods for the automatic generation and organisation of concepts derived from retrieved document sets, based on statistical methods for term weighting; and to conduct user-based evaluations on the understanding, presentation and retrieval effectiveness of concept structures in selecting candidate terms for interactive query expansion. The TREC test collection formed the basis for the seven evaluative experiments conducted in the course of the project. These formed four distinct phases in the project plan. In the first phase, a series of experiments was conducted to investigate further techniques for concept derivation and hierarchical organisation and structure. The second phase was concerned with user-based validation of the concept structures. Results of phases 1 and 2 informed on the design of the test system and the user interface was developed in phase 3. The final phase entailed a user-based summative evaluation of the CiQuest system. The main findings demonstrate that concept hierarchies can effectively be generated from sets of retrieved documents and displayed to searchers in a meaningful way. The approach provides the searcher with an overview of the contents of the retrieved documents, which in turn facilitates the viewing of documents and selection of the most relevant ones. Concept hierarchies are a good source of terms for query expansion and can improve precision. The extraction of descriptive phrases as an alternative source of terms was also effective. With respect to presentation, cascading menus were easy to browse for selecting terms and for viewing documents. In conclusion the project dissemination programme and future work are outlined

The SPIRIT collection: an overview of a large web collection

A large scale collection of web pages has been essential for research in information retrieval and related areas. This paper provides an overview of a large web collection used in the SPIRIT project for the design and testing of spatially-aware retrieval systems. Several statistics are derived and presented to show the characteristics of the collection

Apprenticeship training in Italy: a cost-effective model for firms?

In times of rapid technological progress and increasing digitalisation in many areas of work and life, it is more important than ever to provide young people with the best possible skills for their entry into the world of work. It is certainly important to provide them with a solid theoretical knowledge base. However, it is also important to impart practical skills to ensure that they are able to adapt to the needs of the labour market. Post-school education in Italy, while providing good formal skills in this respect, is not sufficiently responsive to the needs of the labour market. With this in mind, dual training models have become politically more attractive in Italy and are already being implemented. But despite political support and the reforms in recent years, the popularity of dual training models has hardly increased. From an international point of view, this development is hardly surprising. On the one hand, interest in dual vocational training is increasing: learning a trade at two locations – in a company and at a part-time vocational school – means that apprentices gain valuable professional experience while they are still training, which enables a smoother transition to the labour market. As a result, there is less youth unemployment and a better supply of skilled labour for industry. On the other hand, reforms of this kind often encounter a major obstacle when it comes to practical implementation: a lack of commitment by the companies, especially in countries where an in-company apprenticeship tradition is absent. First and foremost, companies see training as an operational loss: why pay to train an apprentice when qualified employees can be recruited directly on the labour market? What businesses often fail to see is that in-house training does not merely incur costs, but that it also results in monetary benefits, and sometimes in net profits before training has even been completed. However, the question is: under which conditions? The costs and benefits of training are not invariables, they depend on a wide of variety of parameters such as the level of apprentices’ pay, the industry in question, the duration of training, recruiting costs for qualified skilled workers on the labour market – not to mention the quality of the training course. To examine the situation, this study uses simulations to investigate how these parameters would have to be designed in Italy in order to make dual training more attractive for Italian businesses. The conclusions derived in this report are intended to assist Italian policymakers and employers to make more evidence-based decisions, to ensure that Italy’s labour force investments are more likely to yield positive returns

Automatically organising images using concept hierarchies

In this paper we discuss the use of concept hierarchies, an approach to automatically organize a set of documents based upon a set of concepts derived from the documents themselves for image retrieval. Co-occurrence between terms associated with image captions and a statistical relation called subsumption are used to generate term clusters which are organized hierarchically. Previously, the approach has been studied for document retrieval and results have shown that automatically generating hierarchies can help users with their search task. In this paper we present an implementation of concept hierarchies for image retrieval, together with preliminary ad-hoc evaluation. Although our approach requires more investigation, initial results from a prototype system are promising and would appear to provide a useful summary of the search results

The Curving House

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