Preferences for Various Learning Environments: Teachers' and Parents' Perceptions

In the last ten years, a number of innovations, mainly inspired by constructivist notions of learning, have been introduced at various levels of the Dutch educational system. However, constructivist learning environments are rarely implemented. Teachers tend to stick to expository and structured learning environments. This consistent finding requires research in order to gain insight into teachers' preferences for learning environments and to determine the factors that support and impede the realization of these learning environments. Regarding the influence of social backgrounds on student learning, is it also important to take stock of parental views on learning environments.This study is focused on teachers' preferences for learning environments, their reported teaching behavior, and how these match with parents' preferences. Three parallel questionnaires were developed for teachers (n = 285), students (n = 951), and parents (n = 636) to measure preferences and behavior at different levels of education, for three types of learning environments: direct instruction; discovery learning; and authentic pedagogy. The results show that teachers often prefer direct instruction, and seldom promote discovery learning. While teachers sometimes realize authentic pedagogy, constructive learning tasks are seldom used. Teachers' reported practice and parents' preferences for their children appear to correspond reasonably.Results of multiple regression analyses show that the use of the three types of learning environments yield different predictors. For the use of discovery learning and authentic pedagogy, confidence in students' regulative skills is an important predictor. In predicting the use of direct instruction, the teacher's own conception of learning turns out to be an important predictor.     

Desperately seeking data: methodological complications in researching 'hard to find' young people

This paper explores challenges arising from research (Daniels & Macnab, 2004), which sought to identify young people aged 14–16 years who were emotionally vulnerable and not in receipt of educational provision within two local UK authorities. Two particular challenges are identified in this research. The first was the challenge of defining the term used to identify the young people. Second, the research faced an almost insurmountable challenge in finding and obtaining data on a sample for which the outcomes of the research may pose a threat to those holding the data. Discussion focuses upon possible ways in which research can address these issues.     

The David Wills Lecture 2001

Abstract

In this, the Annual David Wills Lecture, Dr. John Visser explores common, recurrent themes in the development of our understanding of approaches to EBD. He describes these themes as eternal verities!     

Essential Characteristics for a Professional Development Program for Promoting the Implementation of a Multidisciplinary Science Module

Teachers involved in the implementation of a curriculum innovation can be prepared for this task through a professional development program. In this paper, we describe essential characteristics (identified empirically and theoretically) for such a professional development program that promotes the acquisition of competences by these teachers. The innovation deals with the introduction of modules from a new multidisciplinary subject, in which elements from physics, chemistry, biology, mathematics, and physical geography are integrated. A 3-step approach was used to identify the essential characteristics: (a) evidence from classroom practice, (b) characteristics of the new subject, and (c) theoretical and empirical evidence from curriculum implementation studies. Analysis of the data showed that 5 characteristics need particular attention in a professional development program.     

Some modifications to the SNIP journal impact indicator

The SNIP (source normalized impact per paper) indicator is an indicator of the citation impact of scientific journals. The indicator, introduced by Henk Moed in 2010, is included in Elsevier's Scopus database. The SNIP indicator uses a source normalized approach to correct for differences in citation practices between scientific fields. The strength of this approach is that it does not require a field classification system in which the boundaries of fields are explicitly defined.In this paper, a number of modifications that were recently made to the SNIP indicator are explained, and the advantages of the resulting revised SNIP indicator are pointed out. It is argued that the original SNIP indicator has some counterintuitive properties, and it is shown mathematically that the revised SNIP indicator does not have these properties. Empirically, the differences between the original SNIP indicator and the revised one turn out to be relatively small, although some systematic differences can be observed. Relations with other source normalized indicators proposed in the literature are discussed as well.     

The Attentional Blink in Developing Readers

The attentional blink refers to a reduction in accuracy that occurs when identifying the second of two targets presented within approximately 500 msec of each other. This research explored individual differences in the attentional blink in a sample of 86 children (aged 8–10) with normally developing reading skills. The attentional blink was examined in relation to general reading performance as well as specific orthographic and phonological reading subprocesses. No associations were evident between attentional blink duration and reading ability. However significant correlations did exist between each of the three reading measures and mean second target correct given first target correct (T2|T1) performance across all lags, with less skilled readers exhibiting inferior performance regardless of the temporal lag between first and second targets. Performance on a rapid naming task mediated some of the relationship between mean T2|T1 performance and reading, yet the association remained significant when this factor was accounted for.     

On the interplay between normalisation,bias, and performance of paper impact metrics

We evaluate article-level metrics along two dimensions. Firstly, we analyse metrics’ ranking bias in terms of fields and time. Secondly, we evaluate their performance based on test data that consists of (1) papers that have won high-impact awards and (2) papers that have won prizes for outstanding quality. We consider different citation impact indicators and indirect ranking algorithms in combination with various normalisation approaches (mean-based, percentile-based, co-citation-based, and post hoc rescaling). We execute all experiments on two publication databases which use different field categorisation schemes (author-chosen concept categories and categories based on papers’ semantic information).In terms of bias, we find that citation counts are always less time biased but always more field biased compared to PageRank. Furthermore, rescaling paper scores by a constant number of similarly aged papers reduces time bias more effectively compared to normalising by calendar years. We also find that percentile citation scores are less field and time biased than mean-normalised citation counts.In terms of performance, we find that time-normalised metrics identify high-impact papers better shortly after their publication compared to their non-normalised variants. However, after 7 to 10 years, the non-normalised metrics perform better. A similar trend exists for the set of high-quality papers where these performance cross-over points occur after 5 to 10 years.Lastly, we also find that personalising PageRank with papers’ citation counts reduces time bias but increases field bias. Similarly, using papers’ associated journal impact factors to personalise PageRank increases its field bias. In terms of performance, PageRank should always be personalised with papers’ citation counts and time-rescaled for citation windows smaller than 7 to 10 years.     

The Impact of Context on the Development of Aggressive Behavior in Special Elementary School Children

The role of context in the development of child aggression was studied. The effects of peer aggregation and group composition on aggression development in intervention contexts and classroom contexts were compared using 71 elementary school children. We hypothesized that, due to peer group effects, group-trained children would benefit less from a social skills intervention program than individually trained children. We further hypothesized that children who transferred from special to regular education would show a change toward less aggression. This was hypothesized because of the relatively fewer accounts of negative peer-group effects in regular education. The results show that the social skills intervention program did not have differential effects for group-trained versus individually trained children. However, a change toward less aggression was found in children who transferred from special to regular education. We suggest that interventions toward decreasing child aggression might be more fruitful if the social context in which the children operate daily is considered.     

Globalised vs averaged: Bias and ranking performance on the author level

We analyse the difference between the averaged (average of ratios) and globalised (ratio of averages) author-level aggregation approaches based on various paper-level metrics. We evaluate the aggregation variants in terms of (1) their field bias on the author-level and (2) their ranking performance based on test data that comprises researchers that have received fellowship status or won prestigious awards for their long-lasting and high-impact research contributions to their fields. We consider various direct and indirect paper-level metrics with different normalisation approaches (mean-based, percentile-based, co-citation-based) and focus on the bias and performance differences between the two aggregation variants of each metric. We execute all experiments on two publication databases which use different field categorisation schemes. The first uses author-chosen concept categories and covers the computer science literature. The second covers all disciplines and categorises papers by keywords based on their contents. In terms of bias, we find relatively little difference between the averaged and globalised variants. For mean-normalised citation counts we find no significant difference between the two approaches. However, the percentile-based metric shows less bias with the globalised approach, except for citation windows smaller than four years. On the multi-disciplinary database, PageRank has the overall least bias but shows no significant difference between the two aggregation variants. The averaged variants of most metrics have less bias for small citation windows. For larger citation windows the differences are smaller and are mostly insignificant.In terms of ranking the well-established researchers who have received accolades for their high-impact contributions, we find that the globalised variant of the percentile-based metric performs better. Again we find no significant differences between the globalised and averaged variants based on citation counts and PageRank scores.