Active learning for the identification of nonliteral language

Active avoidance learning is a complex form of aversive feedback learning that in humans and other animals is essential for actively coping with unpleasant, aversive, or dangerous situations. Since the functional circuits involved in two-way avoidance (TWA) learning have not yet been entirely identified, the aim of this study was to obtain an overall picture of the brain circuits that are involved in active avoidance learning. In order to obtain a longitudinal assessment of activation patterns in the brain of freely behaving rats during different stages of learning, we applied single-photon emission computed tomography (SPECT). We were able to identify distinct prefrontal cortical, sensory, and limbic circuits that were specifically recruited during the acquisition and retrieval phases of the two-way avoidance learning task.

Different memory types for generating saccades at different stages of learning

Hippocampal strata theta oscillations change their frequency and coupling during spatial learning

This paper presents Koob, an eBook Reader app that coalesces three key ideas to enhance students’ language learning, specifically for ambiguous words. The first idea is to improve the effectiveness of word lookup functionality through contextualization – by incorporating word sense disambiguation (WSD) techniques to show the contextually relevant definition at the top. The second idea is to augment WSD results with crowd-sourcing solutions. The last idea seeks to reinforce students’ learning by augmenting textual information with a visual aid, pictures related to the word, as part of the word lookup functionality. An empirical evaluation demonstrates that existing WSD techniques can successfully employed to dynamically reorder definitions such that the most relevant definition is at the top of the list for more than 80% of the instances.

Active learning has recently attracted increasing attention in the task of person re-identification, due to its unique scalability that not only maximally reduces the annotation cost but also retains the satisfying performance. Although some preliminary active learning methods have been explored in scalable person re-identification task, they have the following two problems: 1) the inefficiency in the selection process of image pairs due to the huge search space, and 2) the ineffectiveness caused by ignoring the impact of unlabeled data in model training. Considering that, we propose a Multi-grained Active Semi-Supervised learning framework, named MASS, to address the scalable person re-identification problem existing in the practical scenarios. Specifically, we firstly design a cluster-scatter procedure to alleviate the inefficiency problem, which consists of two components: cluster step and scatter step. The cluster step shrinks the search space into individual small clusters by a coarse-grained clustering method, and the subsequent scatter step further mines the hard distinguished image pairs from unlabelled set to purify the learned clusters by a novel centrality-based adaptive purification strategy. Afterward, we introduce a customized purification loss for the purified clustering, which utilizes the complementary information in both labeled and unlabeled data to optimize the model for solving the ineffectiveness problem. The cluster-scatter procedure and the model optimization are performed in an iterative fashion to achieve the promising performance while greatly reducing the annotation cost. Extensive experimental results have demonstrated that MASS can even achieve a competitive performance with fully supervised methods in the case of extremely less annotation requirements.

Mandatory information-based policy tools facilitate California farmers’ learning about nitrogen management

Mapping the neural patterns that drive human behavior is a key challenge in neuroscience. Even the simplest of our everyday actions stem from the dynamic and complex interplay of multiple neural structures across the central nervous system (CNS). Yet, most neuroimaging research has focused on investigating cerebral mechanisms, while the way the spinal cord accompanies the brain in shaping human behavior has been largely overlooked. Although the recent advent of functional magnetic resonance imaging (fMRI) sequences that can simultaneously target the brain and spinal cord has opened up new avenues for studying these mechanisms at multiple levels of the CNS, research to date has been limited to inferential univariate techniques that cannot fully unveil the intricacies of the underlying neural states. To address this, we propose to go beyond traditional analyses and instead use a data-driven multivariate approach leveraging the dynamic content of cerebro-spinal signals using innovation-driven coactivation patterns (iCAPs). We demonstrate the relevance of this approach in a simultaneous brain-spinal cord fMRI dataset acquired during motor sequence learning (MSL), to highlight how large-scale CNS plasticity underpins rapid improvements in early skill acquisition and slower consolidation after extended practice. Specifically, we uncovered cortical, subcortical and spinal functional networks, which were used to decode the different stages of learning with a high accuracy and, thus, delineate meaningful cerebro-spinal signatures of learning progression. Our results provide compelling evidence that the dynamics of neural signals, paired with a data-driven approach, can be used to disentangle the modular organization of the CNS. While we outline the potential of this framework to probe the neural correlates of motor learning, its versatility makes it broadly applicable to explore the functioning of cerebro-spinal networks in other experimental or pathological conditions.

PurposeThe paper explores several key issues in organizational learning and their contributions to practice and policy. It determines the different stages of learning, crucial factors and performance outcomes associated with organizational learning.Design/methodology/approachFour Singapore organizations were studied, from which a total of 24 organizational learning practitioners representing both the private and public sectors were interviewed.FindingsQualitative data were presented in the form of excerpts from the respondents in support of the key research objectives as well as quantitatively through the number of mentions, a technique which is uncommon yet useful for an exploratory study.Research limitations/implicationsThe research was limited by the single geographical context, which might not adequately represent the Asian perspective. However, the paper provides room for continuation as the author introduces two other parts (for subsequent issues) that further detail implications for practice and policy based on the same study.Practical implicationsData revealed that: the complexity between the different levels of learning can be simplified by understanding the goals set at each level; and the relationship between learning and performance goes beyond tangible expectations.Originality/valueOf considerable value to practitioners is the discovery of several crucial factors influencing organizational learning and a list of possible learning outcomes ranked in order of importance; the ranking system being a unique technique helping practitioners in their decision‐making more effectively.

The issues of creating intelligent automated learning systems with a reflection function are considered. Using the theory of reflexive games by V.A. Lefebvre, an intelligent reflexive agent (IRA) is introduced into the structure of the learning system planner, providing a search for compromise solutions in the interaction of the models of the student, teacher, subject tutor and methodologist. The basic components of the model of reflexive perception of the IRA of the student and the learning situation are given, taking into account the specifics of decision-making for different stages of learning.

A QUIZ-EXPERIMENT USING DATA-SHOW AND ION EXCHANGE RESINS.A demonstractive experiment was proposed in order to verify students' habilities in recognizing the presence and nature of ions in solutions, before and after their passage through ion-exchange columns.The students have no previous contact with ion-exchange resins, so they must deduce how they work and explain the experimental facts.The performance of classes, at different stages of learning, is compared and discussed.

The authors’ interest is connected with the application of new technologies in physics education as a means of improving the learning achievement of Physics students at different stages of learning The New Kind of Visual Model instructional strategy introduced in this research is a computer intelligent-based PowerPoint visual simulation used to investigate learning achievement in physics. The research study adopted the Quasi-Experimental Research design. The population comprised of a sample of 168 Secondary School Class-two Physics students purposively selected and treated to 40 minutes tutorials class on the concept of motion. The instrument used consisted in two parts: PowerPoint Computer-simulated visual models which constituted the treatment; and printed materials used to elicit responses to the treatment. There were two activity groups: Experimental group; and Control group. The research study revealed that New Kind of Visual Model instructional strategy contributed positively to learning achievement in physics; result also show that there is significant effect of treatment on students’ retention of learned materials; and has positive significant effect on students’ learning attitude. New Kind of Visual Model instructional strategy will reduce the effects of novelty in method of instruction in all areas of teaching-learning, and may constitute a basis for the use of conceptualism in Computer-aided physics education.

Supporting learners at different stages of learning is essential to achieve positive learning, critical thinking, technical and problem solving skills, and gainful employment upon graduation. Collaboration is critical to providing strong foundational educational support to all learners as they advance to higher level of learning. More important is the need to promote collaboration among educators and other professionals across the Science, Technology, Engineering, and Mathematics (STEM) fields who educate the learners throughout their academic pursuit in their respective institutions of learning. To reap the value in diverse teams, the promotion of emergent interdependence fosters seamless collaborative activities across STEM disciplines. For industrial technology programs to prepare students with skills necessary to supervise and manage the future workforce of any organization successfully, necessary tools must be utilized for the success of the collaborative effort. This paper addresses leadership and knowledge sharing among collaborators, the educational aspects of research facilities and research clusters as some of the tools necessary to develop program through collaboration in STEM fields.

Blocking the ghrelin receptor type 1a in the rat brain impairs memory encoding

Place cells in the hippocampus can maintain multiple representations of a single environment and respond to physical and/or trajectory changes by remapping. Within the hippocampus there are anatomical, electrophysiological, and behavioral dissociations between the dorsal and ventral hippocampus and within dorsal CA1. Arc expression was used to measure the recruitment of ensembles across different hippocampal subregions in rats trained to utilize two different cognitive strategies while traversing an identical trajectory. This behavioral paradigm allowed for the measurement of remapping in the absence of changes in external cues, trajectory traversed (future/past), running speed, motivation, or different stages of learning. Changes in task demands induced remapping in only some hippocampal regions: reorganization of cell ensembles was observed in dorsal CA1 but not in dorsal CA3. Moreover, a gradient was found in the degree of remapping within dorsal CA1 that corresponds to entorhinal connectivity to this region. Remapping was not seen in the ventral hippocampus: neither ventral CA1 nor CA3 exhibited ensemble changes with different cognitive demands. This contrasts with findings of remapping in both the dorsal and ventral dentate gyrus using this task. The results suggest that the dorsal pole of the hippocampus is more sensitive to changes in task demands.

This study examines the relationship between anxiety and learning outcomes in English language acquisition among Arab Palestinian students attending Israeli colleges. Anxiety, widely acknowledged as a significant barrier in educational settings—particularly in foreign language learning—often contributes to negative attitudes toward the learning process. Adopting a qualitative, inductive methodology, this research investigates the multifaceted aspects of anxiety affecting the targeted demographic. A sample of 67 participants completed a modified version of the Foreign Language Classroom Anxiety Scale (FLCAS) questionnaire, providing comprehensive data for analysis. The study begins by assessing the prevalence of anxiety among Arab Palestinian students, uncovering varying levels of anxiety across different stages of learning. Through extensive analysis, the research explores the sources and impacts of anxiety, as well as strategies for its management, offering detailed insights into its dynamics. Key findings highlight the critical roles of personal resources, teaching methods, and the classroom environment in shaping anxiety levels. Moreover, the study identifies distinct effects of anxiety on junior, intermediate, and senior students, emphasizing the unique challenges faced by learners at each level. These insights enhance understanding of the interplay between anxiety and English language acquisition, offering practical recommendations for educational interventions to foster supportive, anxiety-reducing learning environments. The findings of this research align with the results of a study conducted by Hyderpour et al., which demonstrated a correlation between test anxiety and performance in reading compre-hension tests within the context of English for General Purposes (EGP).