Why students need to be prepared to cooperate: a cooperative nudge in statistics learning at university

Despite the potential benefits of cooperative learning at university, its implementation is challenging. Here, we propose a theory-based 90-min intervention with 185 first-year psychology students in the challenging domain of statistics, consisting of an exercise phase and an individual learning post-test. We compared three conditions that manipulated the exercise phase: individual work, cooperative dyadic instructions (structuring three basic components of cooperative learning: positive goal interdependence, individual responsibility and promotive interactions) and cooperative dyadic interactions (the three basic components with an additional cooperative nudge, namely explaining why and how to cooperate in this task) in order to test whether a progressive increase in benefits occurs as the cooperative structure is reinforced. Results indicated a linear trend in individual post-test learning and competence perception, from individual work to cooperative instructions to cooperative interactions. Competence perception mediated the effect of experimental conditions on learning. The results highlight the benefits of the cooperative nudge.     

The neuroscience of perceptual categorization in pigeons: A mechanistic hypothesis

We are surrounded by an endless variation of objects. The ability to categorize these objects represents a core cognitive competence of humans and possibly all vertebrates. Research on category learning in nonhuman animals started with the seminal studies of Richard Herrnstein on the category “human” in pigeons. Since then, we have learned that pigeons are able to categorize a large number of stimulus sets, ranging from Cubist paintings to English orthography. Strangely, this prolific field has largely neglected to also study the avian neurobiology of categorization. Here, we present a hypothesis that combines experimental results and theories from categorization research in pigeons with neurobiological insights on visual processing and dopamine-mediated learning in primates. We conclude that in both fields, similar conclusions on the mechanisms of perceptual categorization have been drawn, despite very little cross-reference or communication between these two areas to date. We hypothesize that perceptual categorization is a two-component process in which stimulus features are first rapidly extracted in a feed-forward process, thereby enabling a fast subdivision along multiple category borders. In primates this seems to happen in the inferotemporal cortex, while pigeons may primarily use a cluster of associative visual forebrain areas. The second process rests on dopaminergic error-prediction learning that enables prefrontal areas to connect top down the relevant visual category dimension to the appropriate action dimension.     

Consensus statement on placebo effects in sports and exercise: The need for conceptual clarity,methodological rigour,and the elucidation of neurobiological mechanisms

In June 2017 a group of experts in anthropology, biology, kinesiology, neuroscience, physiology, and psychology convened in Canterbury, UK, to address questions relating to the placebo effect in sport and exercise. The event was supported exclusively by Quality Related (QR) funding from the Higher Education Funding Council for England (HEFCE). The funder did not influence the content or conclusions of the group. No competing interests were declared by any delegate. During the meeting and in follow-up correspondence, all delegates agreed the need to communicate the outcomes of the meeting via a brief consensus statement. The two specific aims of this statement are to encourage researchers in sport and exercise science to

1. Where possible, adopt research methods that more effectively elucidate the role of the brain in mediating the effects of treatments and interventions.

2. Where possible, adopt methods that factor for and/or quantify placebo effects that could explain a percentage of inter-individual variability in response to treatments and intervention.     

Preferential text classification: learning algorithms and evaluation measures

In many applicative contexts in which textual documents are labelled with thematic categories, a distinction is made between the primary categories of a document, which represent the topics that are central to it, and its secondary categories, which represent topics that the document only touches upon. We contend that this distinction, so far neglected in text categorization research, is important and deserves to be explicitly tackled. The contribution of this paper is threefold. First, we propose an evaluation measure for this preferential text categorization task, whereby different kinds of misclassifications involving either primary or secondary categories have a different impact on effectiveness. Second, we establish several baseline results for this task on a well-known benchmark for patent classification in which the distinction between primary and secondary categories is present; these results are obtained by reformulating the preferential text categorization task in terms of well established classification problems, such as single and/or multi-label multiclass classification; state-of-the-art learning technology such as SVMs and kernel-based methods are used. Third, we improve on these results by using a recently proposed class of algorithms explicitly devised for learning from training data expressed in preferential form, i.e., in the form “for document d _i , category c′ is preferred to category c′′”; this allows us to distinguish between primary and secondary categories not only in the classification phase but also in the learning phase, thus differentiating their impact on the classifiers to be generated.     

A virtual experience to strengthen students' understanding of inference in experimental design

Although our students correctly define the terms p‐value, Type I and Type II errors, they sometimes misinterpret results from real data. In this work we present an assignment intended to clear up these misconceptions.     

Commercializing the laboratory: Faculty patenting and the open science environment

This paper investigates the relationship between patenting and publication of research results by university faculty members. Our study adds to the limited evidence on this topic with an empirical investigation based on a panel data set for a broad sample of university researchers. Results suggest that publication and patenting are complementary, not substitute, activities for faculty members. This is not consistent with recent concerns regarding deleterious effects of patenting on the research output of faculty members. Average citations to publications, however, appear to decline for repeat patenters, suggesting either a decrease in quality or restrictions on use associated in patent protection.     

Nearest neighbor search in metric spaces through Content-Addressable Networks

Most of the Peer-to-Peer search techniques proposed in the recent years have focused on the single-key retrieval. However, similarity search in metric spaces represents an important paradigm for content-based retrieval in many applications. In this paper we introduce an extension of the well-known Content-Addressable Network paradigm to support storage and retrieval of more generic metric space objects. In particular we address the problem of executing the nearest neighbors queries, and propose three different algorithms of query execution. An extensive experimental study on real-life data sets explores the performance characteristics of the proposed algorithms by showing their advantages and disadvantages.     

Effects of fast-velocity eccentric resistance training on early and late rate of force development

This study examined whether short-term maximal resistance training employing fast-velocity eccentric knee extensor actions would induce improvements in maximal isometric torque and rate of force development (RFD) at early (<100 ms) and late phases (>100 ms) of rising torque. Twenty healthy men were assigned to two experimental groups: eccentric resistance training (TG) or control (CG). Participants on the TG trained three days a week for a total of eight weeks. Training consisted of maximal unilateral eccentric knee extensors actions performed at 180°s-1. Maximal isometric knee extensor torque (MVC) and incremental RFD in successive 50 ms time-windows from the onset contraction were analysed in absolute terms (RFD_INC) or when normalised relative to MVC (RFD_REL). After eight weeks, TG demonstrated increases in MVC (28%), RFD_INC (0–50 ms: 30%; 50–100 ms: 31%) and RFD_REL (0–50 ms: 29%; 50–100 ms: 32%). Moreover, no changes in the late phase of incremental RFD were observed in TG. No changes were found in the CG. In summary, we have demonstrated, in active individuals, that a short period of resistance training performed with eccentric fast-velocity isokinetic muscle contractions is able to enhance RFD_INC and RFD_REL obtained at the early phase of rising joint torque.     

Generating suggestions for queries in the long tail with an inverted index

This paper proposes an efficient and effective solution to the problem of choosing the queries to suggest to web search engine users in order to help them in rapidly satisfying their information needs. By exploiting a weak function for assessing the similarity between the current query and the knowledge base built from historical users’ sessions, we re-conduct the suggestion generation phase to the processing of a full-text query over an inverted index. The resulting query recommendation technique is very efficient and scalable, and is less affected by the data-sparsity problem than most state-of-the-art proposals. Thus, it is particularly effective in generating suggestions for rare queries occurring in the long tail of the query popularity distribution. The quality of suggestions generated is assessed by evaluating the effectiveness in forecasting the users’ behavior recorded in historical query logs, and on the basis of the results of a reproducible user study conducted on publicly-available, human-assessed data. The experimental evaluation conducted shows that our proposal remarkably outperforms two other state-of-the-art solutions, and that it can generate useful suggestions even for rare and never seen queries.     

“Too complex for me!” Why do performance-approach and performance-avoidance goals predict exam performance?

Classroom research on achievement goals has revealed that performance-approach goals (goals to outperform others) positively predict exam performance whereas performance-avoidance goals (goals not to perform more poorly than others) negatively predict it. Because prior classroom research has primarily utilized multiple-choice exam performance, the first aim of the present study was to extend these findings to a different measure of exam performance (oral examination). The second aim of this research was to test the mediating role of perceived difficulty. Participants were 49 4th year psychology students of the University of Geneva. Participants answered a questionnaire assessing their level of performance-approach and performance-avoidance goal endorsement in one of their classes as well as the perceived difficulty of this class for themselves. Results indicated that performance-approach goals significantly and positively predicted exam grades. Performance-avoidance goals significantly and negatively predicted grades. Both of these relationships were mediated by the perceived difficulty of the class for oneself. Thus, the links previously observed between performance goals and exam performance were replicated on an oral exam. Perceived difficulty is discussed as a key dimension responsible for these findings.