Collective efficacy belief, within-group agreement, and performance quality among instrumental chamber ensembles

We examined collective efficacy beliefs, including levels of within - group agreement and correlation with performance quality, of instrumental chamber ensembles (70 musicians, representing 18 ensembles). Participants were drawn from collegiate programs and intensive summer music festivals located in the No rthwestern and Western regions of the United States. Individuals completed a 5 - item survey gauging confidence in their group’s performance abilities; each ensemble’s aggregated results represented its collective efficacy score. Ensembles provided a video - r ecorded performance excerpt that was rated by a panel of four string specialists. Analyses revealed moderately strong levels of collective efficacy belief and uniformly high within - group agreement. There was a significant, moderately strong correlation bet ween collective efficacy belief and within - group agreement ( r S = .67, p < .01). We found no relationship between collective efficacy belief and performance quality across the total sample, but those factors correlated significantly for festival - based ensem bles ( r S = .82, p < .05). Reliability estimates suggest that our collective efficacy survey may be suitable for use with string chamber ensembles. Correlational findings provide partial support for the theorized link between efficacy belief and performance quality in chamber music settings, suggesting the importance for music educators to ensure that positive efficacy beliefs become well founded through quality instruction

Applied Research Automatic Self-Talk Questionnaire for Sports (ASTQS): Development and Preliminary Validation of a Measure Identifying the Structure of Athletes’ Self-Talk

The aim of the present investigation was to develop an instrument assessing the con­tent and the structure of athletes’ self-talk. The study was conducted in three stages. In the first stage, a large pool of items was generated and content analysis was used to organize the items into categories. Furthermore, item-content relevance analysis was conducted to help identifying the most appropriate items. In Stage 2, the factor struc­ture of the instrument was examined by a series of exploratory factor analyses (Sample A: N = 507), whereas in Stage 3 the results of the exploratory factor analysis were retested through confirmatory factor analyses (Sample B: N = 766) and at the same time concurrent validity were assessed. The analyses revealed eight factors, four pos­itive (psych up, confidence, anxiety control and instruction), three negative (worry, disengagement and somatic fatigue) and one neutral (irrelevant thoughts). The find­ings of the study provide evidence regarding the multidimensionality of self-talk, suggesting that ASTQS seems a psychometrically sound instrument that could help us developing cognitive-behavioral theories and interventions to examine and modify athletes’ self-talk

The analysis of facial beauty: an emerging area of research in pattern analysis

Much research presented recently supports the idea that the human perception of attractiveness is data-driven and largely irrespective of the perceiver. This suggests using pattern analysis techniques for beauty analysis. Several scientific papers on this subject are appearing in image processing, computer vision and pattern analysis contexts, or use techniques of these areas. In this paper, we will survey the recent studies on automatic analysis of facial beauty, and discuss research lines and practical application

Employee Line of Sight to the Organization’s Strategic Objectives – What it is, How it can be Enhanced, and What it Makes Happen

Employee_Line_of_SightWP01_06.pdf: 13661 downloads, before Oct. 1, 2020

Getting to know you: Accuracy and error in judgments of character

Character judgments play an important role in our everyday lives. However, decades of empirical research on trait attribution suggest that the cognitive processes that generate these judgments are prone to a number of biases and cognitive distortions. This gives rise to a skeptical worry about the epistemic foundations of everyday characterological beliefs that has deeply disturbing and alienating consequences. In this paper, I argue that this skeptical worry is misplaced: under the appropriate informational conditions, our everyday character-trait judgments are in fact quite trustworthy. I then propose a mindreading-based model of the socio-cognitive processes underlying trait attribution that explains both why these judgments are initially unreliable, and how they eventually become more accurate

PACRR: A Position-Aware Neural IR Model for Relevance Matching

In order to adopt deep learning for information retrieval, models are needed that can capture all relevant information required to assess the relevance of a document to a given user query. While previous works have successfully captured unigram term matches, how to fully employ position-dependent information such as proximity and term dependencies has been insufficiently explored. In this work, we propose a novel neural IR model named PACRR aiming at better modeling position-dependent interactions between a query and a document. Extensive experiments on six years' TREC Web Track data confirm that the proposed model yields better results under multiple benchmarks.Comment: To appear in EMNLP201

Survey on Evaluation Methods for Dialogue Systems

In this paper we survey the methods and concepts developed for the evaluation of dialogue systems. Evaluation is a crucial part during the development process. Often, dialogue systems are evaluated by means of human evaluations and questionnaires. However, this tends to be very cost and time intensive. Thus, much work has been put into finding methods, which allow to reduce the involvement of human labour. In this survey, we present the main concepts and methods. For this, we differentiate between the various classes of dialogue systems (task-oriented dialogue systems, conversational dialogue systems, and question-answering dialogue systems). We cover each class by introducing the main technologies developed for the dialogue systems and then by presenting the evaluation methods regarding this class