Do infants have a sense of numerosity? A p‐curve analysis of infant numerosity discrimination studies

Research demonstrating that infants discriminate between small (e.g., 1 vs. 3 dots) and large numerosities (e.g., 8 vs. 16 dots) is central to theories concerning the origins of human numerical abilities. To date, there has been no quantitative meta‐analysis of the infant numerical competency data. Here, we quantitatively synthesize the evidential value of the available literature on infant numerosity discrimination using a meta‐analytic tool called p‐curve. In p‐curve the distribution of available p‐values is analyzed to determine whether the published literature examining particular hypotheses contains evidential value. p‐curves demonstrated evidential value for the hypotheses that infants can discriminate between both small and large unimodal and cross‐modal numerosities. However, the analyses also revealed that the published data on infants’ ability to discriminate between large numerosities is less robust and statistically powered than the data on their ability to discriminate small numerosities. We argue there is a need for adequately powered replication studies to enable stronger inferences in order to use infant data to ground theories concerning the ontogenesis of numerical cognition.     

Complementary teaching practices: Ignatian pedagogy and Buddhist‐inspired compassion meditation

While scholarly discussions on Jesuit education are plentiful, inquiries related to Ignatian pedagogy are rare. This article examines the applications of Ignatian pedagogy by juxtaposing it with the analysis of a Buddhist‐inspired and interdisciplinary contemplation program, Cognitively‐Based Compassion Training® (CBCT®). Drawing from the author's experience in teaching CBCT® at a Jesuit University, this article explores how CBCT® aligns with the Ignatian Pedagogical Paradigm's five elements: context, experience, reflection, action, and evaluation. This study uses psychometrical measurements, such as the Compassionate Love for Humanity Scale, to document how my interdisciplinary approach may enhance participants' emotional well‐being and widen their ethical concerns. As these outcomes are inherently cross‐disciplinary and include intellectual and affective dimensions, they cannot be achieved through a single field. Building a bridge between the Ignatian Pedagogical Paradigm and CBCT® provides a successful strategy for the educational objectives of developing the whole person and forming a compassionate character.     

ELM-HTM guided bio-inspired unsupervised learning for anomalous trajectory classification

Artificial intelligent systems often model the solutions of typical machine learning problems, inspired by biological processes, because of the biological system is faster and much adaptive than deep learning. The utility of bio-inspired learning methods lie in its ability to discover unknown patterns, and its less dependence on mathematical modeling or exhaustive training. In this paper, we propose a new bio-inspired learning model for a single-class classifier to detect abnormality in video object trajectories. The method uses a simple but dynamic extreme learning machine (ELM) and hierarchical temporal memory (HTM) together referred to as ELM-HTM in an unsupervised way to learn and classify time series patterns. The method has been tested on trajectory sequences in traffic surveillance to find abnormal behaviors such as high-speed, unusual stops, driving in wrong directions, loitering, etc. Experiments have also been performed with 3D air signatures captured using sensors and used for biometric authentication(forged/genuine). The results indicate a significant gain over training time and classification accuracy. The proposed method outperforms in predicting long-time patterns by observing small steps with an average accuracy gain of 15% as compared to the state-of-the-art HTM. The method has applications in detecting abnormal activities in videos by learning the movement patterns as well as in biometric authentication.     

Socially emotional brain-inspired cognitive architecture framework for artificial intelligence

Artificial Intelligence of the next generation needs to interact with users socially, convincing them in its ability to understand human minds, including emotions. For this to happen, an artificial emotional intelligence is needed, capable of adequate, believable behavior in social emotional interactions. Building on previous developments, the present work extends the general framework of emotional Biologically Inspired Cognitive Architecture (eBICA: Samsonovich, 2013, 2018), endowing it with fluents describing, in addition to appraisals, somatic markers, feelings, emotions, moods, emotional reactions and biases. Key building blocks that integrate them are moral schemas and semantic maps. The model describes interaction of three factors: plans and commitments, moral and ethical values, and somatic comfort. Learning in this framework includes self-organization of semantic maps that in turn may provide guidance for active humanlike learning. Implications for empirical studies and practical applications are discussed together with the expected impact.     

The role of instruction preference in analogy learning: Brain activity and motor performance

This study examined the role of verbal instruction preference when learning motor skills by analogy. During skill learning, analogies are a useful tool for providing knowledge about how to move. It has been argued that analogy instructions reduce reliance on verbal information processes during motor planning, compared to traditional forms of instruction (i.e., explicit rules about how to move). This may be reflected by reduced verbal activity in the brain, measured by EEG alpha power at the temporal region, as well as reduced verbal-motor cross-communication (EEG T7-Fz coherence) during the preparation phase of a movement. Preference for using verbal or visual instructions is likely to influence the efficacy of analogy instructions. This study investigated whether preference for verbal instructions was related to a) changes in performance and b) changes in verbal-cognitive information processing during performance of an adapted basketball task after instruction by analogy. Basketball novices with a high preference for verbal instructions (n = 15) showed significantly decreased activation of verbal brain regions when they used the analogy (high-alpha power), but their performance remained stable. Novices with a low preference for verbal instructions (n = 13) did not show a significant decrease in activation of verbal regions, and their performance deteriorated significantly after introduction of the analogy instruction. It is likely that both cognitive and performance changes after analogy instruction depend on personal aspects of information processing, such as verbal preference.     

Motivational climate,psychological needs,and personal and social responsibility in youth soccer: Comparisons by age group and competitive level

ObjectivesWe used a developmental lens to examine age group and competitive level differences on motivational climate dimensions, psychological needs satisfaction, and personal and social responsibility as well as relationships among variables, in line with basic psychological needs theory.DesignWe used a cross-sectional, correlational design.MethodGirls and boys age 8–13 on recreational and select soccer teams completed a survey.ResultsA 2 × 2 MANOVA showed main effects for age group and competitive level: early adolescents reported greater punishment for mistakes and autonomy compared to children; select players reported greater mastery climate dimensions and personal responsibility compared to recreational players. For all groups, path analyses revealed perceptions of cooperative learning were indirectly associated with personal and social responsibility, through coach and/or teammate relatedness.ConclusionsPatterns of relationships by age group and competitive level are discussed in reference to developmental literature. Results highlight the value of using a developmental approach to understand how coaches can promote youth soccer players’ psychological and social well-being.     

Relationship between environmental factors and burnout of psychotherapists: Meta‐analytic approach

The present study aims to extend the scope of understanding on the relationships between environmental factors and burnout symptoms by targeting and including more extensive occupational demanding variables related to therapist burnout. The present study includes not only common occupational stressors (e.g., working hours, role overload and role conflict) but also variables reflecting the quality of relationship with clients (e.g., case load and negative clientele) that have not been dealt with before in meta‐analytic studies. A meta‐analysis was conducted on 27 original studies published from the year 2006 to 2018. The findings showed that, among environmental factors, role overload had the most significant positive correlations with exhaustion. In addition, negative clientele had the most significant positive correlations with depersonalisation and reduced accomplishment. Furthermore, caseload and low income had relatively weak relations with therapist burnout. Based on these results, implications and limitations of the study are discussed.