When half a word is enough: infants can recognize spoken words using partial phonetic information

Adults process speech incrementally, rapidly identifying spoken words on the basis of initial phonetic information sufficient to distinguish them from alternatives. In this study, infants in the second year also made use of word-initial information to understand fluent speech. The time course of comprehension was examined by tracking infants' eye movements as they looked at pictures in response to familiar spoken words, presented both as whole words in intact form and as partial words in which only the first 300 ms of the word was heard. In Experiment 1, 21-month-old infants (N = 32) recognized partial words as quickly and reliably as they recognized whole words; in Experiment 2, these findings were replicated with 18-month-old infants (N = 32). Combining the data from both experiments, efficiency in spoken word recognition was examined in relation to level of lexical development. Infants with more than 100 words in their productive vocabulary were more accurate in identifying familiar words than were infants with less than 60 words. Grouped by response speed, infants with faster mean reaction times were more accurate in word recognition and also had larger productive vocabularies than infants with slower response latencies. These results show that infants in the second year are capable of incremental speech processing even before entering the vocabulary spurt, and that lexical growth is associated with increased speed and efficiency in understanding spoken language.     

Designing for impact: a conceptual framework for learning analytics as self-assessment tools

Abstract

Although it is frequently claimed that learning analytics can improve self-evaluation and self-regulated learning by students, most learning analytics tools appear to have been developed as a response to existing data rather than with a clear pedagogical model. As a result there is little evidence of impact on learning. Even fewer learning analytics tools seem to be informed by an understanding of the social context and social practices within which they would be used. As a result, there is very little evidence that learning analytics tools are actually impacting on practice. This paper draws on research in self-regulated learning and in the social practices of learning and assessment to clarify a series of design issues which should be considered by those seeking to develop learning analytics tools which are intended to improve student self-evaluation and self-regulation. It presents a case study of how these design issues influenced the development of a particular tool: the Learning Companion.     

Pushing the entrepreneurial prodigy: Canadian Aboriginal entrepreneurship education initiatives

Globally, neoliberal education policy touts youth entrepreneurship education as a solution for staggering youth unemployment, a means to bolster economically depressed regions, and solution to the ill-defined changing marketplace. Many jurisdictions have emphasized a need for K-12 entrepreneurial education for the general population, and targeted to youth labeled ‘at risk’. The Martin Aboriginal Education Initiative’s Aboriginal Youth Entrepreneurship Program (AYEP) has been enacted across Canada. This paper applies critical discourse analysis to a corpus of texts, exposing how colonial practices, deficit discourse, and discursive neoliberalism are embedded and perpetuated though entrepreneurial education targeted at Aboriginal students via AYEP.     

An Activist Approach to Sport Meets Youth From Socially Vulnerable Backgrounds: Possible Learning Aspirations

Purpose: This study was a 2-phase activist research project aimed at co-creating a prototype pedagogical model for working with youth from socially vulnerable backgrounds in a sport context. This article addresses the learning aspirations (learning outcomes) that emerged when we created spaces for youth to develop strategies to manage the risks they face in their community. Method: This study took place in a socially and economically disadvantaged neighborhood in a Brazilian city where we worked with a group of 17 boys aged 13 to 15 years old, 4 coaches, a pedagogic coordinator, and a social worker. During a 6-month period, we collected multiple sources of data including field journal entries/observations (38) and audio records of youth work sessions (18), coaches' work sessions (16), combined coaches and youth work sessions (3), and meetings between the lead and the 2nd author for debriefing and planning sessions (36). Results: By using an activist approach, 4 learning aspirations emerged: becoming responsible/committed, learning from mistakes, valuing each other's knowledge, and communicating with others. Conclusion: Findings suggest there is a need for more sports programs that start from young people's concrete needs and life situations and look to create places for youth to see alternative possibilities and take action.     

Predicting centre of mass horizontal speed in low to severe swimming intensities with linear and non-linear models

We aimed to compare multilayer perceptron (MLP) neural networks, radial basis function neural networks (RBF) and linear models (LM) accuracy to predict the centre of mass (CM) horizontal speed at low-moderate, heavy and severe swimming intensities using physiological and biomechanical dataset. Ten trained male swimmers completed a 7 × 200 m front crawl protocol (0.05 m.s^?1 increments and 30 s intervals) to assess expiratory gases and blood lactate concentrations. Two surface and four underwater cameras recorded independent images subsequently processed focusing a three-dimensional reconstruction of two upper limb cycles at 25 and 175 m laps. Eight physiological and 13 biomechanical variables were inputted to predict CM horizontal speed. MLP, RBF and LM were implemented with the Levenberg-Marquardt algorithm (feed forward with a six-neuron hidden layer), orthogonal least squares algorithm and decomposition of matrices. MLP revealed higher prediction error than LM at low-moderate intensity (2.43 ± 1.44 and 1.67 ± 0.60%), MLP and RBF depicted lower mean absolute percentage errors than LM at heavy intensity (2.45 ± 1.61, 1.82 ± 0.92 and 3.72 ± 1.67%) and RBF neural networks registered lower errors than MLP and LM at severe intensity (2.78 ± 0.96, 3.89 ± 1.78 and 4.47 ± 2.36%). Artificial neural networks are suitable for speed model-fit at heavy and severe swimming intensities when considering physiological and biomechanical background.     

Do students notice stress in teachers? Associations between classroom teacher burnout and students' perceptions of teacher social–emotional competence

The goal of the present study was to investigate the link between elementary school teacher burnout and students' perceptions of teacher social–emotional competence (SEC). A total of 676 Grades 4–7 students in 35 classrooms rated their classroom teachers' SEC. In addition, teachers self-reported their current level of experienced burnout at work (i.e., depersonalization and emotional exhaustion). Multilevel analyses revealed significant classroom-level variability (i.e., 34%) in student-ratings of teacher SEC. Teacher burnout significantly predicted student-rated teacher SEC, over and above significant student-level variables (school self-concept, sense of autonomy in the classroom) and contextual variables (teacher age, school neighborhood income). Specifically, higher levels of teacher burnout were related to receiving lower SEC ratings by students. Teacher burnout explained a significant portion of the classroom-level variability in student-rated teacher SEC. The present study emphasizes the link between teacher burnout and the SEC. Furthermore, given that teacher reports (burnout) were linked to student reports (teacher SEC), these findings also suggest that students notice stress in their classroom teacher.     

Collaborative information seeking: A field study of a multidisciplinary patient care team

Multidisciplinary teams are an essential aspect of modern organizational work. These teams often work in information-rich environments but little is known about their collaborative information seeking (CIS) behavior. We have been studying the CIS behavior of teams in the context of medical care. We conducted an ethnographic field study of a multidisciplinary patient care team in an emergency department to identify (a) team information needs and (b) situations that trigger collaborative information seeking activities. We identified seven categories of information needs as expressed by questions asked by team members. The majority of questions focused on medical information, but there were a larger than expected percentage of questions focusing on organizational information. We also identified three triggers for CIS activities. These triggers are: (1) lack of expertise, (2) lack of immediately accessible information, and (3) complex information needs. The questions and triggers highlight the importance of face-to-face communication during CIS activities and how CIS activities could lead to interruptive workplaces. We also discuss organizational and technical implications for supporting CIS behavior of teams.     

A model for understanding collaborative information behavior in context: A study of two healthcare teams

Collaborative information behavior is an essential aspect of organizational work; however, we have very limited understanding of this behavior. Most models of information behavior focus on the individual seeker of information. In this paper, we report the results from two empirical studies that investigate aspects of collaborative information behavior in organizational settings. From these studies, we found that collaborative information behavior differs from individual information behavior with respect to how individuals interact with each other, the complexity of the information need, and the role of information technology. There are specific triggers for transitioning from individual to collaborative information behavior, including lack of domain expertise. The information retrieval technologies used affect collaborative information behavior by acting as important supporting mechanisms. From these results and prior work, we develop a model of collaborative information behavior along the axes of participant behavior, situational elements, and contextual triggers. We also present characteristics of collaborative information system including search, chat, and sharing. We discuss implications for the design of collaborative information retrieval systems and directions for future work.     

Effects of weightlifting exercise,traditional resistance and plyometric training on countermovement jump performance: a meta-analysis

Jump performance is considered an important factor in many sports. Thus, strategies such as weightlifting (WL) exercises, traditional resistance training (TRT) and plyometric training (PT) are effective at improving jump performance. However, it is not entirely clear which of these strategies can enable greater improvements on jump height. Thus, the purpose of the meta-analysis was to compare the improvements on countermovement jump (CMJ) performance between training methods which focus on WL exercises, TRT, and PT. Seven studies were included, of which one study performed both comparison. Therefore, four studies comparing WL exercises vs. TRT (total n = 78) and four studies comparing WL exercises vs. PT (total n = 76). The results showed greater improvements on CMJ performance for WL exercises compared to TRT (ES_diff: 0.72 ± 0.23; _95%CI: 0.26, 1.19; P = 0.002; Δ % = 7.5 and 2.1, respectively). The comparison between WL exercises vs. PT revealed no significant difference between protocols (ES_diff: 0.15 ± 0.23; _95%CI: ?0.30, 0.60; P = 0.518; Δ % = 8.8 and 8.1, respectively). In conclusion, WL exercises are superior to promote positive changes on CMJ performance compared to TRT; however, WL exercises and PT are equally effective at improving CMJ performance.