Interpersonal relations between school children and their peers,parents, and teachers

This article describes the nature of school children's relationships with parents, peers, and teachers, and identifies some interpersonal and academic consequences of unhealthy relationships. Also described are trends of relationship development, tools for assessing relationships, and finally, some intervention techniques available to enhance relationship building. The article points to the following conclusions: Healthy relationships are characterized by mutually reinforcing exchanges that lead to socially desirable consequences; quantification of the prevalence of unhealthy relationships is difficult; students who exhibit unhealthy relationships are at significant risk for problems later in life, such as dropping out of school, criminality, and marital maladjustment; educators have a number of assessment tools and techniques available to assess and promote social skills acquisition; and cooperative learning environments offer the greatest promise to educators for promoting healthy relationship building among students.     

Ecological influences on teachers’ well-being and “fitness”

The complex and ever-changing nature of teachers’ work challenges their well-being. Teacher well-being and “fitness” includes versatility, mental strength, and commitment to promote effective teaching and learning. In framing this notion, we seek to understand the ecological influences impacting on teacher well-being and “fitness” in the twenty-first century. Drawing on the ecological theory of Bronfenbrenner, this interpretive qualitative study explored the perceptions of pre-service teachers in relation to their teacher well-being and “fitness.” Data were collected from a teacher well-being survey completed by 120 final-year undergraduate pre-service teachers. The survey shed light on themes at four levels: the microsystem (individual and collective capacities); mesosystem (interrelationships between contexts); exosystem (organisational); and macrosystem (societal and legislative influences), compounded by the influence of time at the chronosystem level. These ecological influences were perceived to impact on teacher well-being and ability to be “fit” for sustained performance.     

恐怖峡谷(上)

你从树上摘下一只苹果时,有没有想像过苹果树会突然向你袭击?我从未有过这种念头,直到那次我和朋友杰夫·爱默生一起去怀金斯峡谷玩。在我们把车开下高速公路的时候,杰夫对我说:“你会喜欢这里的。小时候,我每一年夏天都在这里过。”我向窗外看去。大雨正扭曲地向四下里浇灌。刮雨器挣扎着,想在挡风玻璃上开辟一块视野。漆黑、阴郁的背景似乎把车灯的光亮都吸了去。我正勉强地分辨着黑暗中的景象,一道闪电突然划破了夜空。刹那间,光秃秃的树木成了明     

Book Reviews

ABSTRACT

This article focuses on primary teachers’ beliefs about teaching and learning and in particular about their preferred ways of teaching; how they integrate National Curriculum requirements into their teaching programmes and their views about stereotyped ‘models’ of pedagogy. The authors conclude that learning and teaching are understood as highly complex and cannot be subsumed under one particular model. They suggest that most primary school teachers adopt an eclectic approach, but that frequently they are confused about the content of the mix or which approach might be most appropriately used in any particular context.     

Construct validity of the K-ABC for gifted children

Fifty-four elementary-age gifted students were administered the K-ABC. To determine construct validity of the test for this population, the factor structure was obtained for mental processing and achievement subtests and then compared to the factor structure obtained for children from the standardization sample via a procedure that determines factor structure similiarity between groups. Except for minor variations, the factor structure for the gifted children was very similar to that for nongifted children in the standardization sample. However, the most parsimonious structure accounted for slightly less than 40% of the shared test variance, which leads to questions about the advisability of educational program planning based on obtained scores.     

Learning: The pupil's voice

Summaries are given of research on the learner's role in learning and pupils' attitudes to school and it is argued that few studies have collected the views of young children on learning. This provides the rationale for a pilot study which probed the perceptions of a sample of 44 Year 2 and Year 6 children in schools in and around London. The findings indicate that children as young as seven can conceptualise 'learning' and are able to articulate learning strategies and processes they use. It is suggested that the pupil's voice is an increasingly important element in furthering our understanding of teaching and learning more generally.     

Automating the Construction of Internet Portals with Machine Learning

Domain-specific internet portals are growing in popularity because they gather content from the Web and organize it for easy access, retrieval and search. For example, www.campsearch.com allows complex queries by age, location, cost and specialty over summer camps. This functionality is not possible with general, Web-wide search engines. Unfortunately these portals are difficult and time-consuming to maintain. This paper advocates the use of machine learning techniques to greatly automate the creation and maintenance of domain-specific Internet portals. We describe new research in reinforcement learning, information extraction and text classification that enables efficient spidering, the identification of informative text segments, and the population of topic hierarchies. Using these techniques, we have built a demonstration system: a portal for computer science research papers. It already contains over 50,000 papers and is publicly available at www.cora.justresearch.com. These techniques are widely applicable to portal creation in other domains.     

Table extraction for answer retrieval

The ability to find tables and extract information from them is a necessary component of many information retrieval tasks. Documents often contain tables in order to communicate densely packed, multi-dimensional information. Tables do this by employing layout patterns to efficiently indicate fields and records in two-dimensional form. Their rich combination of formatting and content presents difficulties for traditional retrieval techniques. This paper describes techniques for extracting tables from text and retrieving answers from the extracted information. We compare machine learning (especially, Conditional Random Fields) and heuristic methods for table extraction. To retrieve answers, our approach creates a cell document, which contains the cell and its metadata (headers, titles) for each table cell, and the retrieval model ranks the cells of the extracted tables using a language-modeling approach. Performance is tested using government statistical Web sites and news articles, and errors are analyzed in order to improve the system.