Social Loafing in a Co-operative Classroom Task

Social loafing refers to the tendency for individuals to reduce their own personal input when performing as part of group. This phenomenon may be problematic if it exists in educational contexts, given a current emphasis on group collaborative classroom activities. The present study investigated whether social loafing existed in a collaborative educational task, employing groups of three and eight participants. The results indicated that individuals working within the smaller groups were more productive than those working in larger groups, consistent with the social loafing hypothesis. Future research should determine whether the detrimental effects on students' collaborative performance attributable to social loafing are justifiable in terms of gains accrued in other (e.g. interpersonal) domains.     

差异的世界:大学排名的全球调查

本文研究了全球19个大学排行榜,描述了排行榜作为质量评价手段是如何运作的,详细讨论了现有排名系统使用的质量指标并归纳出在排名上存在的不同地域模式。本文发现,世界上的主要排行榜之间没有多少联系,它们采用差别很大的指标和权重来评估大学。但是,有一些大学,无论是用何种的指标和权重,都会居于排行榜的前列。本文还探讨了与目前流行的严格按分数高低排名的“排行榜”不同的做法,并得出了结论。     

Changes in mechanical properties of sprinting during repeated sprint in elite rugby sevens athletes

This study aimed to analyse fatigue-induced changes in mechanical sprinting properties during a specific repeated-sprint test in elite rugby sevens athletes. Twenty elite rugby sevens players performed ten 40?m sprints on a 30?s cycle with participant’s running back and forth in a marked lane. Radar was used to assess maximal overground sprint performance over each 40?m. Macroscopic mechanical properties (maximal horizontal force (F₀), maximal horizontal power (P_max), maximal ratio of horizontal force (RF_peak), decrease in the ratio of horizontal-to-total force (D_RF), total force and maximal sprinting velocity (v₀)) were drawn from horizontal force velocity relationships, using a validated method applied to the speed–time data. Fatigue-induced changes were analysed comparing the first sprint to an average of 2^nd-4^th, 5^th-7^th and 8^th-10^th. Repeated-sprint ability (RSA) testing induced substantial changes in the maximal velocity component, with a decrease (–15%) in v₀ (effect size (ES)?=?–2.46 to –4.98), and to a lower extent (–5.9%) in the maximal force component F₀ (ES?=?–0.59). D_RF moderately decreased (14%; ES=–0.76–1.11), and RF_peak largely decreased in the later sprints (ES?=?–0.32 to –1.27). Fatigue observed in this RSA test appeared to have a greater effect on the technical ability to produce horizontal force at high velocities, likely due to an alteration in the ability to maintain horizontally oriented force application when velocity increases rather than during the initial acceleration phase, but also the overall force production capacity. The ability to maintain forward-oriented force at high velocities is of central importance for identifying fatigue and monitoring load.     

Neural information retrieval: at the end of the early years

A recent “third wave” of neural network (NN) approaches now delivers state-of-the-art performance in many machine learning tasks, spanning speech recognition, computer vision, and natural language processing. Because these modern NNs often comprise multiple interconnected layers, work in this area is often referred to as deep learning. Recent years have witnessed an explosive growth of research into NN-based approaches to information retrieval (IR). A significant body of work has now been created. In this paper, we survey the current landscape of Neural IR research, paying special attention to the use of learned distributed representations of textual units. We highlight the successes of neural IR thus far, catalog obstacles to its wider adoption, and suggest potentially promising directions for future research.     

The rise of the machines: Artificial intelligence meets scholarly content

Key points

• New forms of human/machine dialogue are emerging as robots understand vast amounts of content rather than simply indexing content as strings of characters.
• Recognizing strings of characters as entities (e.g. = names = authors) allows for meaningful associations between entities and reasoning over these relationships.
• Web‐scale adoption of the Semantic Web approach has been slow because it is too complex to implement and does not scale.
• User intent, discovered through conversational models of human–computer interaction, allows for a deeper understanding of exactly what researchers are looking for.
• Personal agents hold the promise of finding information that we will find useful before we have started to look for it.
• Publishers can use Academic Knowledge APIs to interpret academic user queries and find rich information from the Microsoft Academic Graph.

     

Look who’s talking: Emergent evidence for discriminating between differences in listserv participation

This paper reports findings from a study of LookJed, the oldest and largest on-line forum for Computer Mediated Discussion among individuals interested in Jewish education. The study adopted a “cyber-ethnographic” approach, with postings to the forum seen as “acts of communication” that reveal what is important to their authors. An interest in exploring similarities between forum conversations and those in teachers’ lounges led to an investigation of Herring’s claim that most listservs do not include discussion at all, only the trading of information. This investigation found that active forum participants generally use the forum for discrete purposes, most commonly to exchange information about “subject matter” or “teaching material”, less commonly to exchange opinions and ideas, and rarely to do both. Integrating an analysis of patterns of contribution with an examination of their discursive content reveals six preeminent “types” among the population of contributors, each of whom participates in the forum in different ways and acts with different purposes. Although this typology is at best suggestive and needs to be tested against other listserv cases, its easy identification suggests that in order to better understand the cultures of virtual forums, it is important to pursue a more variegated characterization of listserv participants and their motivations than has typically been the case in CMD research where users are most frequently identified as either lurkers or fanatics, or as active or passive participants.