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To examine how vocabulary instruction can lead toward students connecting the known to the familiar with the unknown.

Theoretical advances in vocabulary acquisition and utility are discussed in relation to word reading and knowledge formation. Extending theory requires pedagogical planning and reinforcement to promote skill learning first toward preparing students to have the capacity to acquire vocabulary across the content areas and in turn, understand and apply that knowledge toward problem solving.

Students must be scaffolded toward connecting what they know with that which is familiar and eventually with the unknown; only then can we extend learning beyond our guidance and supervision. Students must be taught how and when to use vocabulary acquisition strategies so they are prepared to overcome difficulties associated with word meanings in independent reading.

It is timely for rich, varied, and complete vocabulary instruction to serve as the basis for learning across the curriculum. Words are the predecessors of tomorrow’s learning and we must consider how to best provide instruction for students who overuse sight words, text shorthand more than they write formally, and even substitute inappropriate language based upon a lack of vocabulary knowledge and ability to articulate their feelings.

Affiliated grocers on the whole tend to be well satisfied with group retailing, according to a study carried out by the authors. Nevertheless the loss of only a few percent of members over the year can amount to a considerable drain and could even outweigh new recruitment. The authors have carried out a study into why retailers leave voluntary groups, and this article summarises their findings.

The decline of the independent retailer as a result of the growing strength of the multiples has been a persistent factor in British retailing for decades, and the effectiveness of the affiliated retailer in fighting back in the form of voluntary groups is equally well‐known. But why do so many independent retailers still prefer to operate outside the group structure? The authors carried out a study of 100 unaffiliated retailers in the north‐west of England; this article outlines their findings.

Purpose – To provide educators with an overview of strategies that can be incorporated into clinical settings that foster vocabulary and comprehension development.

Design/methodology/approach – The chapter highlights underlying themes of reading failure, benefits of large vocabularies and comprehension skills, and components for remediation/instruction.

Findings – Content provides detailed information on designing clinics that prepare students to meet the vocabulary and comprehension demands of reading in the 21st century.

Research limitations/implications – The chapter highlights the most reliable and practical reading strategies that are fundamental to every reader's advancement.

Practical implications – This chapter serves as a resource for all clinical instructors, providing a wealth of ideas for incorporation into their clinics and classrooms.

Originality/value of paper – This compilation of vocabulary and comprehension strategies works in tandem to produce highly skilled readers who can in turn learn independently.

In this paper, we discuss the application of the constitutive relation error (CRE) to model updating and validation in the context of uncertain measurements. First, a parallel is drawn between the CRE method and a general theory for inverse problems proposed by Tarantola. Then, an extension of the classical CRE method considering uncertain measurements is proposed. It is shown that the proposed mechanics‐based approach for model validation is very effective in filtering noise in the experimental data. The method is applied to an industrial structure, the SYLDA5, which is a satellite support for Ariane5. The results demonstrate the robustness of the method in actual industrial situations.

This paper seeks to present a new solution algorithm for updating of finite element models in structural dynamics. A random search method is applied to improving the correlation between the numerical simulation and the measured experimental data.

Dynamic finite element model updating may be considered as an optimization process. It is solved using modified accelerated random search (MARS) algorithm. The effectiveness of the approach is first tested on benchmark problems. Next, several objective function formulations for dynamic model updating in modal and frequency domains are investigated for numerically simulated vibrating beam. Finally, the algorithm is applied to a real beam‐like structure using measured modal data.

The MARS algorithm is able to provide very good results in a reduced time even for hard optimization problems. It behaves very well also for the FE dynamic model updating, highly coupled problems. The efficient updating criterion has been proposed and the approach has been validated experimentally.

The method is supposed to be time consuming for large size or complicated objective function problems but the choice of optimization parameters can accelerate the convergence.

The MARS algorithm can be applied to model updating in civil and mechanical engineering.

This paper is the first to apply the MARS algorithm to the problem of FE model updating in dynamics and enables one to obtain very good results. Efficient criteria for model updating have been proposed.

Despite, or perhaps even because of, the economic uncertainties of the period, the 1970s witnessed a radical transformation of the British distributive system. Most of the changes which occurred were similar to those experienced elsewhere in the Western world, and in a review of developments in EEC countries, Dawson has suggested that the impact of these changes on society could be similar to that produced by the Industrial Revolution. In Britain at least, the changes in distribution were, and remain, a result of very marked changes in society: most notably the change in consumption patterns brought about by endemic inflation, increasing unemployment and periodic world energy crises. The result has been increased competition, a search for greater efficiency and diversification of traditional product lines. Thus the British distribution system throughout the 1970s was dominated by the trend to mass merchandising, by the emergence of large firms and a consequent increase of corporate power and by the appearance of new distribution forms. While many of the conditions and developments experienced in the 1970s are expected to continue into the 1980s, it has been predicted (Distributive Industry Training Board 1980) that by the 1990s further revolutionary changes are likely to have occurred, particularly as a result of widespread automation involving new technology. The industry is, therefore, in the middle of a period of very rapid change.

This research delves into the transformative potential of Generative Artificial Intelligence (AI), particularly ChatGPT, in enhancing higher education. It aims to explore how these advanced AI tools can be integrated into different educational settings to improve interactive learning experiences and student engagement, addressing the current challenges and opportunities in academic and administrative applications. Adopting a qualitative approach, the research utilizes the case vignette method to simulate realistic scenarios in various academic disciplines. It examines the potential applications and outcomes of AI in higher education, structured around key areas like intelligent tutoring systems, assessment, personalization and student profiling. This study employs the 4Cs framework (Critical Thinking, Creativity, Collaboration and Communication) to evaluate the effectiveness of AI integration in improving educational outcomes. The study reveals that ChatGPT can significantly enhance learning experiences by providing personalized tutoring, efficient assessment, tailored content and predictive insights into student performance. However, challenges such as ensuring content accuracy, ethical concerns and balancing AI with human interaction are also identified. Best practices for effectively integrating ChatGPT in higher education are proposed, emphasizing the complementarity of AI and human elements in education. This research contributes to the growing body of knowledge on AI in education by providing a nuanced understanding of generative AI's potential and challenges in higher education. It offers valuable insights and practical recommendations for educators and institutions, guiding the effective integration of AI technologies to enhance teaching and learning.

Purpose – To provide educators with an overview of both generalized and specific comprehension strategies applicable to the content areas.Design/methodology/approach – The chapter is organized by (a) providing a rationale for incorporating reading strategy instruction, especially at the adolescent grade range and above; (b) discussing reading strategies that are appropriate for all content areas; and (c) describing reading strategies that can be used in specific content area subjects.Findings – Research-based strategies for scaffolding comprehension in content area subjects are presented in varying levels of detail.Research limitations/implications – The strategies discussed in this chapter do not constitute an exhaustive list of strategies or approaches to content area literacy instruction.Practical implications – This is a valuable resource for educators to obtain practical guidance in providing content area reading instruction for a wide range of student ages and abilities.Originality/value of chapter – This chapter provides significant research-based information for designing and implementing content area strategy instruction.