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Linda Dickey Linda Jaco Margaret Williams Nancy Sager Tany Slay 《International Journal of Disability, Development & Education》1983,30(3):185-189
The Behavior Intervention Centres are part of the Houston Independent School District's (HISD) Special Education Department. Their purpose is to provide educational services to elementary and secondary students, aged 3 through 21, who exhibit either severely aggressive or severely withdrawn behaviours. This article describes a formalized follow‐up service considered by the authors to be a critical component of the BIC program. 相似文献
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We evaluate author impact indicators and ranking algorithms on two publication databases using large test data sets of well-established researchers. The test data consists of (1) ACM fellowship and (2) various life-time achievement awards. We also evaluate different approaches of dividing credit of papers among co-authors and analyse the impact of self-citations. Furthermore, we evaluate different graph normalisation approaches for when PageRank is computed on author citation graphs.We find that PageRank outperforms citation counts in identifying well-established researchers. This holds true when PageRank is computed on author citation graphs but also when PageRank is computed on paper graphs and paper scores are divided among co-authors. In general, the best results are obtained when co-authors receive an equal share of a paper's score, independent of which impact indicator is used to compute paper scores. The results also show that removing author self-citations improves the results of most ranking metrics. Lastly, we find that it is more important to personalise the PageRank algorithm appropriately on the paper level than deciding whether to include or exclude self-citations. However, on the author level, we find that author graph normalisation is more important than personalisation. 相似文献
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教师专业发展项目一直强调提升高等教育整体质量,对发展高校科研、教学以及学生的学习都有着举足轻重的作用。本文选取澳大利亚、英国和美国的四所世界一流大学的教师专业发展中心进行研究,阐释了教师专业发展在四所大学的长期实践及其对教师教学和科研水平提高的积极意义,由此总结并提出一系列提高高等教育整体质量的实践经验和关于未来研究方向的建议。 相似文献
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In the field of scientometrics, impact indicators and ranking algorithms are frequently evaluated using unlabelled test data comprising relevant entities (e.g., papers, authors, or institutions) that are considered important. The rationale is that the higher some algorithm ranks these entities, the better its performance. To compute a performance score for an algorithm, an evaluation measure is required to translate the rank distribution of the relevant entities into a single-value performance score. Until recently, it was simply assumed that taking the average rank (of the relevant entities) is an appropriate evaluation measure when comparing ranking algorithms or fine-tuning algorithm parameters.With this paper we propose a framework for evaluating the evaluation measures themselves. Using this framework the following questions can now be answered: (1) which evaluation measure should be chosen for an experiment, and (2) given an evaluation measure and corresponding performance scores for the algorithms under investigation, how significant are the observed performance differences?Using two publication databases and four test data sets we demonstrate the functionality of the framework and analyse the stability and discriminative power of the most common information retrieval evaluation measures. We find that there is no clear winner and that the performance of the evaluation measures is highly dependent on the underlying data. Our results show that the average rank is indeed an adequate and stable measure. However, we also show that relatively large performance differences are required to confidently determine if one ranking algorithm is significantly superior to another. Lastly, we list alternative measures that also yield stable results and highlight measures that should not be used in this context. 相似文献
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Liebenberg J Scharf J Forrest D Dufek JS Masumoto K Mercer JA 《Journal of sports sciences》2011,29(2):207-214
The aim of this study was to investigate how lower extremity muscles are influenced by body weight support during running at different speeds. Nine participants (age 24 ± 2 years, height 1.75 ± 0.12 m, mass 73.5 ± 15.7 kg) ran at 100%, 115%, and 125% of preferred speed at 100%, 90%, 80%, 70%, and 60% of body weight on a treadmill that provided body weight support. Preferred speed was self-selected by each participant and represented a speed that he or she could sustain if going for a 30 min run. Electromyography (EMG) data were recorded (1000 Hz, 1 min) from the bicep femoris, rectus femoris, tibialis anterior, and gastrocnemius for each condition together with knee angle (electrogoniometer). Average and root mean square EMG were calculated across 30 s. Muscle patterns were determined by smoothing (low-pass filter, 4 Hz) and extracting patterns for 49 cycles defined by consecutive maximum knee flexion angles. Repeated-measures analyses of variance were used to compare average and root mean square across body weight and speeds. Correlations were computed between the 100% speed/100% body weight condition and all other conditions per muscle. There was no interaction between body weight and speed (P > 0.05). Average and root mean square decreased as body weight decreased for all muscles (P < 0.05) and increased across speeds for all muscles (P < 0.05). Correlations for all muscles between conditions were high (range: 0.921-0.999). Although a percent reduction in body weight did not lead to the same reduction in muscle activity, it was clear that reducing body weight leads to a reduction in muscle activity with no changes in muscle activity patterns. 相似文献
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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. 相似文献
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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. 相似文献
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Bob Heere Matthew Walker Heather Gibson Brijesh Thapa Sue Geldenhuys Willie Coetzee 《Journal of Sport Tourism》2016,20(1):41-56
The purpose of this study was to examine whether a mega sport event has the potential to bring the nation together by increasing the importance of national identity and decreasing the importance of ethnic identity on the outcome of social cohesion. Instead of replicating prior work that has performed mean score comparisons of national identity, ethnic identity, and social cohesion before and after a particular event, the authors compared the variance explained (pre vs. post event) to show the aggregate influence of the two identities on social cohesion. By focusing on this reporting method, the subsequent discussion rests entirely on the practical influence of the perceptual changes that resulted from event hosting. Data for this trend analysis were collected from South African residents, pre (N?=?1749), and post (N?=?2020) the 2010 FIFA World Cup. Results indicated that while the importance of national identity on social cohesion did not increase, the importance of ethnic identity did decrease strongly, indicating that these mega sports events might cause individuals to forget about their ethnic differences as a result of these events. 相似文献
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