Validation of an assessment centre process for the selection of school leaders in Chile

This study seeks to develop and validate an Assessment Centre (AC) tool for the evaluation and selection of school leaders, focusing on the identification of competencies that influence teaching and learning outcomes. International research supports the creation of Assessment Centres to select candidates for these roles, due to their superior predictive capacity over traditional methods. In this research, a model composed of four face-to-face instruments (an interview to assess competencies, a human resources exercise, a class observation exercise, and a strategic analysis exercise) was designed and validated which simulated the key tasks of a school principal. To establish the desired performance outcomes, three competencies and 15 indicators were selected, based on international and local standards. The analysis of performance results was obtained from a sample of 164 participants made up of teachers, school leaders and principals. The results suggest positive evidence for construct validity, concurrent criteria validity, and reliability between evaluators. Moreover, the data obtained from a sub-sample of principals, with three or more years of experience in their role, allowed for the association of their AC scores with the results of their school organisations, as measured by the National System for the Measurement of Educational Quality in the years 2013 and 2016.     

Can educational engagement prevent Early School Leaving? Unpacking the school’s effect on educational success

There is growing evidence that school engagement, or more specifically disengagement, is a key indicator for predicting Early School Leaving. The aim of this article is to explore the impact of secondary schools in student (dis)engagement and subsequent opportunities to succeed in school. Drawing on data from a qualitative study in five secondary schools in Barcelona, the article discusses the role of school context in inhibiting or facilitating school engagement by exploring compositional effects, organisational and pedagogical practices, and teachers’ expectations. To do so a twofold perspective is adopted: firstly, we look at the main school features and their impact on students’ educational opportunities; and secondly, a systematic analysis of the dimensions of school engagement (behavioural, emotional and cognitive) is carried out. As a result, the article contributes to the identification of the most significant variables at school level that influence student engagement and their opportunities for school success.     

The load-velocity profile differs more between men and women than between individuals with different strength levels

This study aimed to determine the suitability of the load-velocity relationship to prescribe the relative load (%1RM) in women, as well as to compare the load-velocity profile between sexes and participants with different strength levels. The load-velocity relationship of 14 men (1RM: 1.17 ± 0.19) and 14 women (1RM: 0.66 ± 0.13) were evaluated in the bench press exercise. The main findings revealed that: (I) the load-velocity relationship was always strong and linear (R² range: 0.987–0.993), (II) a steeper load-velocity profile was observed in men compared to women (Effect size [ES]: 1.09), with men showing higher velocities for light loads (ES: ? 0.81 and ? 0.40 for the y-intercept and 30%1RM, respectively), but women reporting higher velocities for the heavy loads (ES: 1.14 and 1.50 at 90%1RM and 100%1RM, respectively); and (III) while the slope of the load-velocity profile was moderately steeper for weak men compared to their strong counterpart (ES: 1.02), small differences were observed between strong and weak women (ES: ? 0.39). While these results support the use of the individual load-velocity relationship to prescribe the %1RM in the bench press exercise for women, they also highlight the large disparities in their load-velocity profile compared to men.     

Statistical biases in Information Retrieval metrics for recommender systems

There is an increasing consensus in the Recommender Systems community that the dominant error-based evaluation metrics are insufficient, and mostly inadequate, to properly assess the practical effectiveness of recommendations. Seeking to evaluate recommendation rankings—which largely determine the effective accuracy in matching user needs—rather than predicted rating values, Information Retrieval metrics have started to be applied for the evaluation of recommender systems. In this paper we analyse the main issues and potential divergences in the application of Information Retrieval methodologies to recommender system evaluation, and provide a systematic characterisation of experimental design alternatives for this adaptation. We lay out an experimental configuration framework upon which we identify and analyse specific statistical biases arising in the adaptation of Information Retrieval metrics to recommendation tasks, namely sparsity and popularity biases. These biases considerably distort the empirical measurements, hindering the interpretation and comparison of results across experiments. We develop a formal characterisation and analysis of the biases upon which we analyse their causes and main factors, as well as their impact on evaluation metrics under different experimental configurations, illustrating the theoretical findings with empirical evidence. We propose two experimental design approaches that effectively neutralise such biases to a large extent. We report experiments validating our proposed experimental variants, and comparing them to alternative approaches and metrics that have been defined in the literature with similar or related purposes.     

The strange case of reproducibility versus representativeness in contextual suggestion test collections

The most common approach to measuring the effectiveness of Information Retrieval systems is by using test collections. The Contextual Suggestion (CS) TREC track provides an evaluation framework for systems that recommend items to users given their geographical context. The specific nature of this track allows the participating teams to identify candidate documents either from the Open Web or from the ClueWeb12 collection, a static version of the web. In the judging pool, the documents from the Open Web and ClueWeb12 collection are distinguished. Hence, each system submission should be based only on one resource, either Open Web (identified by URLs) or ClueWeb12 (identified by ids). To achieve reproducibility, ranking web pages from ClueWeb12 should be the preferred method for scientific evaluation of CS systems, but it has been found that the systems that build their suggestion algorithms on top of input taken from the Open Web achieve consistently a higher effectiveness. Because most of the systems take a rather similar approach to making CSs, this raises the question whether systems built by researchers on top of ClueWeb12 are still representative of those that would work directly on industry-strength web search engines. Do we need to sacrifice reproducibility for the sake of representativeness? We study the difference in effectiveness between Open Web systems and ClueWeb12 systems through analyzing the relevance assessments of documents identified from both the Open Web and ClueWeb12. Then, we identify documents that overlap between the relevance assessments of the Open Web and ClueWeb12, observing a dependency between relevance assessments and the source of the document being taken from the Open Web or from ClueWeb12. After that, we identify documents from the relevance assessments of the Open Web which exist in the ClueWeb12 collection but do not exist in the ClueWeb12 relevance assessments. We use these documents to expand the ClueWeb12 relevance assessments. Our main findings are twofold. First, our empirical analysis of the relevance assessments of 2  years of CS track shows that Open Web documents receive better ratings than ClueWeb12 documents, especially if we look at the documents in the overlap. Second, our approach for selecting candidate documents from ClueWeb12 collection based on information obtained from the Open Web makes an improvement step towards partially bridging the gap in effectiveness between Open Web and ClueWeb12 systems, while at the same time we achieve reproducible results on well-known representative sample of the web.     

Influence of football match time–motion parameters on recovery time course of muscle damage and jump ability

ABSTRACT

We analysed the time course of recovery of creatine kinase (CK) and countermovement jump (CMJ) parameters after a football match, and correlations between changes in these variables and match time–motion parameters (GPS-accelerometry) in 15 U-19 elite male players. Plasma CK and CMJ height (CMJ_H), average concentric force (CMJ_CON) and average eccentric force (CMJ_ECC) were assessed 2 h before and 30 min, 24 h and 48 h post-match. There were substantially higher CK levels 30 min, 24 h and 48 h (ES: 0.43, 0.62, 0.40, respectively), post-match. CMJ_ECC (ES: ?0.38), CMJ_H (ES: ?0.35) decreased 30 min post, CMJ_CON (ES: ?0.35), CMJ_ECC (ES: ?0.35) and CMJ_H (ES: ?1.35) decreased 24 h post, and CMJ_CON (ES: ?0.41) and CMJ_H (ES: ?0.53) decreased 48 h post. We found correlations between distance covered at velocities ≤21 km · h^?1 and changes in CK at 24 h (r = 0.56) and at 48 h (r = 0.54) and correlations between CK and distance covered >14 km · h^?1 (r = 0.50), accelerations (r = 0.48), and decelerations (r = 0.58) at 48 h. Changes in CMJ_CON 30 min and 24 h post (both r = ?0.68) correlated with impacts >7.1·G. Decelerations >2 m · s^?2 correlated with changes CMJ_CON (r = ?0.49) at 48 h and CMJ_ECC (r = ?0.47) at 30 min. Our results suggest that match GPS-accelerometry parameters may predict muscle damage and changes in components of neuromuscular performance immediately and 24–48 h post-match.     

Impact of an incremental running test on jumping kinematics in endurance runners: can jumping kinematic explain the post-activation potentiation phenomenon?

This study aimed to determine whether kinematic data during countermovement jump (CMJ) might explain post-activation potentiation (PAP) phenomenon after an exhausting running test. Thirty-three trained endurance runners performed the Léger Test; an incremental test which consists of continuous running between two lines 20 m apart. CMJ performance was determined before (pre-test) and immediately after the protocol (post-test). Sagittal plane, video of CMJs was recorded and kinematic data were obtained throughout 2-Dimensional analysis. In addition to the duration of eccentric and concentric phases of CMJ, hip, knee and ankle angles were measured at four key points during CMJ: the lowest position of the squat, take-off, landing, and at the lowest position after landing. Additionally, heart rate was monitored, and rate of perceived exertion was recorded at post-test. Analysis of variance revealed a significant improvement in CMJ (p = 0.002) at post-test. Cluster analysis grouped according to whether PAP was experienced (responders group: RG, n = 25) or not (non-responders group: NRG, n = 8) relative to CMJ change from rest to post-test. RG significantly improved (p < 0.001) the performance in CMJ, whereas NRG remained unchanged. Kinematic data did not show significant differences between RG and NRG. Thus, the data suggest that jumping kinematic does not provide the necessary information to explain PAP phenomenon after intensive running exercises in endurance athletes.