Research into the School as an Organization. II: The School as a Complex Organization

Berg, G. & Wallin, E. 1982. Research into the School as an Organization. II: The School as a Complex Organization. Scandinavian Journal of Educational Research 26, 161‐181. This article starts by examining the development of general organization theory, then proposes an overall organization model for analysing the school. A distinction is made between the school as an institution and the school as an organization, the latter defined as a function of the control emanating from the societal and the ‘actor’ level. A set of conceptual tools believed to describe and analyse the school as an organization is outlined. In the latter part of the article an illustration of how the theoretical discussion can be applied to practical situations is given, firstly by an analysis of a case study and secondly by giving examples of factors worth taking into account in concrete analyses of the organizational structures of schools.     

Red to Green or Fast to Slow? Infants' Visual Working Memory for “Just Salient Differences”

In this study, 6‐month‐old infants' visual working memory for a static feature (color) and a dynamic feature (rotational motion) was compared. Comparing infants' use of different features can only be done properly if experimental manipulations to those features are equally salient (Kaldy & Blaser, 2009; Kaldy, Blaser, & Leslie, 2006). The interdimensional salience mapping method was used to find two objects that each were one Just Salient Difference from a common baseline object (N = 16). These calibrated stimuli were then used in a subsequent two‐alternative forced‐choice preferential looking memory test (N = 28). Results showed that infants noted the color change, but not the equally salient change in rotation speed.     

Some aspects of research on learning and cognitive development in Europe 1

A model of human learning processes is presented, wherein learning is conceived as a qualitative development of the structure of the learner's actions. As an illustration of this conception a concise outline of Gal'perin's theory of learning is given. In connection with the relation between cognitive development and learning some Russian research is reviewed, which provides evidence for the standpoint that cognitive development can be strongly stimulated by appropriate learning and instruction. Finally an analysis is presented of structures of action, which represent important objectives of learning to think.     

Bayesian network based extreme learning machine for subjectivity detection

Subjectivity detection is a task of natural language processing that aims to remove ‘factual’ or ‘neutral’ content, i.e., objective text that does not contain any opinion, from online product reviews. Such a pre-processing step is crucial to increase the accuracy of sentiment analysis systems, as these are usually optimized for the binary classification task of distinguishing between positive and negative content. In this paper, we extend the extreme learning machine (ELM) paradigm to a novel framework that exploits the features of both Bayesian networks and fuzzy recurrent neural networks to perform subjectivity detection. In particular, Bayesian networks are used to build a network of connections among the hidden neurons of the conventional ELM configuration in order to capture dependencies in high-dimensional data. Next, a fuzzy recurrent neural network inherits the overall structure generated by the Bayesian networks to model temporal features in the predictor. Experimental results confirmed the ability of the proposed framework to deal with standard subjectivity detection problems and also proved its capacity to address portability across languages in translation tasks.     

Commercially available compression garments or electrical stimulation do not enhance recovery following a sprint competition in elite cross-country skiers

This study investigated whether commercially available compression garments (COMP) exerting a moderate level of pressure and/or neuromuscular electrical stimulation (NMES) accelerate recovery following a cross-country sprint skiing competition compared with a control group (CON) consisting of active recovery only. Twenty-one senior (12 males, 9 females) and 11 junior (6 males, 5 females) Swedish national team skiers performed an outdoor sprint skiing competition involving four sprints lasting ～3–4 min. Before the competition, skiers were matched by sex and skiing level (senior versus junior) and randomly assigned to COMP (n?=?11), NMES (n?=?11) or CON (n?=?10). Creatine kinase (CK), urea, countermovement jump (CMJ) height, and perceived muscle pain were measured before and 8, 20, 44 and 68?h after competition. Neither COMP nor NMES promoted the recovery of blood biomarkers, CMJ or perceived pain post-competition compared with CON (all P?>?.05). When grouping all 32 participants, urea and perceived muscle pain increased from baseline, peaking at 8?h (standardised mean difference (SMD), [95% confidence intervals (CIs)]): 2.8 [2.3, 3.2]) and 44?h (odds ratio [95% CI]: 3.3 [2.1, 5.1]) post-competition, respectively. Additionally, CMJ was lower than baseline 44 and 68?h post-competition in both males and females (P?相似文献   

A machine learning approach to sentiment analysis in multilingual Web texts

Sentiment analysis, also called opinion mining, is a form of information extraction from text of growing research and commercial interest. In this paper we present our machine learning experiments with regard to sentiment analysis in blog, review and forum texts found on the World Wide Web and written in English, Dutch and French. We train from a set of example sentences or statements that are manually annotated as positive, negative or neutral with regard to a certain entity. We are interested in the feelings that people express with regard to certain consumption products. We learn and evaluate several classification models that can be configured in a cascaded pipeline. We have to deal with several problems, being the noisy character of the input texts, the attribution of the sentiment to a particular entity and the small size of the training set. We succeed to identify positive, negative and neutral feelings to the entity under consideration with ca. 83% accuracy for English texts based on unigram features augmented with linguistic features. The accuracy results of processing the Dutch and French texts are ca. 70 and 68% respectively due to the larger variety of the linguistic expressions that more often diverge from standard language, thus demanding more training patterns. In addition, our experiments give us insights into the portability of the learned models across domains and languages. A substantial part of the article investigates the role of active learning techniques for reducing the number of examples to be manually annotated.     

Everyday personal laptop usage in secondary schools in Trinidad and Tobago

The e-Connect And Learn (eCAL) programme is a Trinidad and Tobago government-led initiative, launched in 2010, that grants personal laptop computers to students entering secondary school. The purpose of this paper is to provide a snapshot of how students are using these government-issued personal laptops 3 years after the programme’s launch. This paper explores the fissure between what the policy recommends and what is actually enacted in the context of laptop usage in the classroom. Data were drawn from 1,451 students, from 32 secondary schools across Trinidad and Tobago. Responses indicate that students are falling short of the expectations for in-class laptop usage and in schools where usage is less often but on a regular basis, laptops are mainly used for technology-related subjects. These findings not only suggest that students’ everyday personal laptop usage in the classroom is not in alignment with the eCAL programme goals, but also highlight some of the issues to be considered by other countries when implementing large-scale laptop programmes.     

Research-based knowledge: researchers’ contribution to evidence-based practice and policy making in career guidance

To present evidence for the outcomes of career guidance is increasingly seen as pivotal for a further professionalization of policy making and service provision. This paper puts an emphasis on researchers’ contribution to evidence-based practice and policy making in career guidance. We argue for a broader and more pluralistic research strategy to meet the complexity of possible questions needed to be asked to provide evidence in career guidance. The article puts a specific focus on the need for a stronger involvement of the voice of users.