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This Register of Current Research in Britain in the field of marketing has been compiled from the response to a request for such information made to educational institutes. It is intended to publish amendments and additions at regular intervals in this journal. Each issue will contain up‐dating material, and the complete register will be published each year. The present issue contains the first such up‐dating.

Purpose – This chapter explores the work of one expert seventh-grade science teacher, Ann, as she used the gradual release of responsibility (GRR) to develop students’ knowledge and use of science language and conceptual knowledge. Ann’s use of scaffolds such as thoughtful definition, classroom discussion, and writing frameworks is explored, as well as her methods of incorporating language into science inquiry, and the evidence she gathered as proof of learning. Her instructional decision-making and specific instructional actions are analyzed to describe the ways she gradually guided students from heavily scaffolded learning opportunities, through guided practice with extensive modeling, and ultimately to independent and accurate use of science language and conceptual knowledge in spoken and written discourse.

Design/methodology/approach – In a researcher/teacher partnership modeled on the practice embedded educational research (PEER) framework (Snow, 2015) the author worked with Ann over four school years, collecting data that included interviews, Ann’s teaching journal, student artifacts, and vocabulary pre/post-assessments. The initial task of the partnership was review of science standards and curricular documents and analysis of disciplinary language in seventh-grade science in order to construct a classroom science vocabulary assessment that incorporated a scaffolded format to build incremental knowledge of science words. Results of 126 students’ pre/post scores on the vocabulary assessment were analyzed using quantitative methods, and interviews and the teaching journal were analyzed using qualitative techniques. Student artifacts support and triangulate the quantitative and qualitative analyses.

Findings – Analysis of students’ pre/post-scores on the vocabulary assessment supported the incremental nature of vocabulary learning and the value of a scaffolded assessment. Improvement in ability to choose a one-word definition and choose a sentence-length definition had significant and positive effect on students’ ability to write a sentence using a focus science word correctly to demonstrate science conceptual knowledge. Female students performed just as well as male students: a finding that differs from other vocabulary intervention research. Additionally, Ann’s use of scaffolded, collaborative methods during classroom discussion and writing led to improved student knowledge of science language and the concepts it labels, as evident in students’ responses during discussion and their writing in science inquiry reports and science journals.

Research limitations – These data were collected from students in one science teacher’s classroom, limiting generalization. However, the expertise of this teacher renders her judgments useful to other teachers and teacher trainers, despite the limited context of this research.

Practical implications – Science knowledge is enhanced when language and science inquiry coexist, but the language of science often presents a barrier to learning science, and there are significant student achievement gaps in science learning across race, ethnicity, and gender. Researchers have described ways to make explicit connections between science language, concepts, and knowledge, transcending the gaps and leveling the playing field for all students. Analysis of Ann’s teaching practice, drawn from four years of teacher and student data, provides specific and practical ways of doing this in a real science classroom. Scaffolding, modeling, and co-construction of learning are key.

Originality/value of paper – This chapter details the methods one expert teacher used to make her own learning the object of inquiry, simultaneously developing the insights and the strategies she needed to mentor students. It describes how Ann infused the GRR into planning and instruction to create learning experiences that insured student success, even if only at incremental levels. Ann’s methods can thus become a model for other teachers who wish to enhance their students’ learning of science language and concepts through infusion of literacy activity.

This chapter reflectively explores the idea of doing art-based research (ABR) through poetic methods for studying the experience of learning in higher education. Taking some literature on faculty development to exemplify different ways of experiencing learning, this chapter serves as a counterpoint to researching experiences of learning from a phenomenological approach. The fundamental reasoning for this is that the basic epistemological assumptions in phenomenology would limit our understanding of experiences of learning and thus, other methodological options would be worth exploring. To that end, this chapter elaborates on the relationship between knowledge production, speech and experience, all circling around the notions of research method and construction. Here, the aim is to reflect upon an understanding of research that is aligned with a dialogical and relational conceptualization of the experience of learning. Finally, an argument will be outlined that suggests conducting research as an experience. Taking from Dewey, Kvale, Law, Scheurich, Talmy and others, this exploration will present the idea of studying the experiences of learning by way of producing/devising experiences through arts. With the notion of art as experience from Dewey, the argument goes to ABR in a general sense, and poetry in particular, as a sound and coherent alternative way of researching learning as an experience. Thus, this chapter explores the possible theoretical-methodological contributions of thinking about and doing research understood as an experience through art.

The United States has been at the forefront of a global shift away from direct state funding of higher education and toward student loans, and student debt has become an issue of growing social concern. Why did student loans expand so much in the United States in the 1990s and 2000s? And how does organization theory suggest their expansion, and the growth of federal student aid more generally, might affect higher education as a field? In the 1960s and 1970s, policy actors worked to solve what was then a central problem around student loans: banks’ disinterest in lending to students. They did this so well that by 1990, a new field of financial aid policy emerged, in which all major actors had an interest in expanding loans. This, along with a favorable environment outside the field, set the stage for two decades of rapid growth. Organization theory suggests two likely consequences of this expansion of federal student loans and financial aid more generally. First, while (public) colleges have become less dependent on state governments and more dependent on tuition, the expansion of aid means colleges are simultaneously becoming more dependent on the federal government, which should make them more susceptible to federal demands for accountability. Second, the expansion of federal student aid should encourage the spread of forms and practices grounded in a logic focused on students’ financial value to the organization, such as publicly traded for-profit colleges and enrollment management practices.

This chapter reports from a qualitative study on how identity categories, including gender and ethnicity, are experienced and constructed through video gaming among immigrant youth in Norway. The aim here is to explore the manifestations and contestations of gendered power and hegemonic practices among the young immigrant girls and boys. This chapter builds on research about everyday media use especially video games, and our analysis is based on theories of hegemony, power, gender, and ethnicity. Three key findings are observed from the study: (a) video games acting as a bridge between ethnic minority boys (not so much with the girls) and ethnic Norwegians, (b) hegemonic gendered practices, emphasizing the “otherness,” in particular for girls adhering to the category of gamer, and finally, to a lesser degree, (c) marginalization within video games on the basis of being a non-Western youth in a Western context. As such the study simultaneously not only confirms but also challenges dominant discourses on video games by suggesting that, although some positive strides have been made, the claims of a post-gender neutral online world, or celebrations of an inclusive and democratic online media culture, especially video gaming, are still premature.

Describes an elastic visco‐plastic finite element formulation that is applied to the modelling of pastes. Comparisons are made with experimental results obtained for a particular paste, plasticine. Special attention is applied to the frictional boundary conditions, for which the usual Coulombic procedure is augmented by a “cohesive” wall friction component. Viscous effects also are considered.

Sets out to provide a selected bibliography or recent resources on library instruction and information literacy.

Introduces and annotates periodical articles, monographs, and exhibition catalogues examining library instruction and information literacy.

Provides information about each source, discusses the characteristics of current scholarship, and describes sources that contain unique scholarly contributions and quality reproductions.

The information may be used by librarians and interested parties as a quick reference to literature on library instruction and information literacy.

To discuss a new parallel algorithmic platform (minlp_machine) for complex mixed‐integer non‐linear programming (MINLP) problems.

The platform combines features from classical non‐linear optimization methodology with novel innovations in computational techniques. The system constructs discrete search zones around noninteger discrete‐valued variables at local solutions, which simplifies the local optimization problems and reduces the search process significantly. In complicated problems fast feasibility restoration may be achieved through concentrated Hessians. The system is programmed in strict ANSI C and can be run either stand alone or as a support library for other programs. File I/O is designed to recognize possible usage in both single and parallel processor environments. The system has been tested on Alpha, Sun and Linux mainframes and parallel IBM and Cray XT4 supercomputer environments. The constrained problem can, for example, be solved through a sequence of first order Taylor approximations of the non‐linear constraints and feasibility restoration utilizing Hessian information of the Lagrangian of the MINLP problem, or by invoking a nonlinear solver like SQP directly in the branch and bound tree. minlp_machine( ) has been tested as a support library to genetic hybrid algorithm (GHA). The GHA(minlp_machine) platform can be used to accelerate the performance of any linear or non‐linear node solver. The paper introduces a novel multicomputer partitioning of the discrete search space of genuine MINLP‐problems.

The system is successfully tested on a small sample of representative MINLP problems. The paper demonstrates that – through concurrent nonlinear branch and bound search – minlp_machine( ) outperforms some recent competing approaches with respect to the number of nodes in the branch and bound tree. Through parallel processing, the computational complexity of the local optimization problems is reduced considerably, an important aspect for practical applications.

This paper shows that binary‐valued MINLP‐problems will reduce to a vector of ordinary non‐linear programming on a suitably sized mesh. Correspondingly, INLP‐ and ILP‐problems will require no quasi‐Newton steps or simplex iterations on a compatible mesh.

Behavioral pattern mining for intelligent system such as SmEs sensor data are vitally important in many applications and performance optimizations. Sensor pattern mining (SPM) is also dynamic and a hot research issue to pervasive and ubiquitous of smart technologies toward improving human life. However, in large-scale sensor data, exploring and mining pattern, which leads to detect the abnormal behavior is challenging. The paper aims to discuss these issues.

Sensor data are complex and multivariate, for example, which data captured by the sensors, how it is precise, what properties are recorded or measured, are important research issues. Therefore, the method, the authors proposed Sequential Data Mining (SDM) approach to explore pattern behaviors toward detecting abnormal patterns for smart space fault diagnosis and performance optimization in the intelligent world. Sensor data types, modeling, descriptions and SPM techniques are discussed in depth using real sensor data sets.

The outcome of the paper is measured as introducing a novel idea how SDM technique’s scale-up to sensor data pattern mining. In the paper, the approach and technicality of the sensor data pattern analyzed, and finally the pattern behaviors detected or segmented as normal and abnormal patterns.

The paper is focussed on sensor data behavioral patterns for fault diagnosis and performance optimizations. It is other ways of knowledge extraction from the anomaly of sensor data (observation records), which is pertinent to adopt in many intelligent systems applications, including safety and security, efficiency, and other advantages as the consideration of the real-world problems.