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Abstract Background Adults with schizophrenia experience a range of neurocognitive problems that affect their daily functioning. Evidence for the efficacy of cognitive remediation in schizophrenia has been established, but its implementation in under-resourced community-based settings is less well-studied. In recent years, interventions have also focused on the strategy-learning approach in favor of drill-and-practice. Moreover, there is an increasing recognition to address social cognition and negative symptoms alongside neurocognition. This study attempts to carry out cognitive remediation in a community mental health setting. The Neuropsychological and Educational Approach to Remediation (NEAR) is used as the cognitive remediation intervention. Neurocognitive and social cognitive games will be introduced during the computer-assisted cognitive exercises sessions. In addition, the instructional technique will foster the use of metacognition and cognitive strategies. Moreover, metamotivation training will be the focus of some bridging sessions to enhance motivation to engage in goal-directed learning behaviors. The aims of the study are to 1) investigate the effects of cognitive remediation on neurocognition, social cognition and functional outcomes of participants with schizophrenia/schizoaffective disorders in community mental health settings; and 2) explore the mediators for change (eg: metamotivation, metacognition and negative symptoms) in cognitive performance and functional outcomes. Methods This randomized controlled trial will be conducted in three Singapore Anglican Community Services (SACS) centers, where standard psychiatric rehabilitation is delivered. Participants who are randomized to the experimental arm will receive cognitive remediation and psychiatric rehabilitation, while those randomized to the control arm will receive standard psychiatric rehabilitation only. Cognitive remediation is carried out three times a week for 12 weeks. It consists of computer-assisted cognitive exercises, as well as bridging groups to aid transfer of learning to daily living. Baseline, post-intervention and eight-week follow-up measurements will be collected. Group by time differences in cognitive performance, negative symptoms, metamotivation, metacognition, functioning and recovery will be analyzed across the three time points. Mediators for improvement in cognitive performance and functioning will also be explored. Discussion Findings of this research will add to the body of knowledge about the key therapeutic ingredients within a strategy-based cognitive remediation program and improve its implementation within under-resourced community settings. Trial registration This study has been registered with ClinicalTrials.gov (ID: NCT06286202). Date of registration: 29 February 2024. Date of last update: 21 May 2024.

Background: Adults with schizophrenia experience a range of neurocognitive problems that affect their daily functioning. Evidence for the efficacy of cognitive remediation in schizophrenia has been established, but its implementation in under-resourced community-based settings is less well-studied. In recent years, interventions have also focused on the strategy-learning approach in favor of drill-and-practice. Moreover, there is an increasing recognition to address social cognition and negative symptoms alongside neurocognition. This study attempts to carry out cognitive remediation in a community mental health setting. The Neuropsychological and Educational Approach to Remediation (NEAR) is used as the cognitive remediation intervention. Neurocognitive and social cognitive games will be introduced during the computer-assisted cognitive exercises sessions. In addition, the instructional technique will foster the use of metacognition and cognitive strategies. Moreover, metamotivation training will be the focus of some bridging sessions to enhance motivation to engage in goal-directed learning behaviors. The aims of the study are to 1) investigate the effects of cognitive remediation on neurocognition, social cognition and functional outcomes of participants with schizophrenia/schizoaffective disorders in community mental health settings; and 2) explore the mediators for change (eg: metamotivation, metacognition and negative symptoms) in cognitive performance and functional outcomes. Methods: This randomized controlled trial will be conducted in three Singapore Anglican Community Services (SACS) centers, where standard psychiatric rehabilitation is delivered. Participants who are randomized to the experimental arm will receive cognitive remediation and psychiatric rehabilitation, while those randomized to the control arm will receive standard psychiatric rehabilitation only. Cognitive remediation is carried out three times a week for 12 weeks. It consists of computer-assisted cognitive exercises, as well as bridging groups to aid transfer of learning to daily living. Baseline, post-intervention and eight-week follow-up measurements will be collected. Group by time differences in cognitive performance, negative symptoms, metamotivation, metacognition, functioning and recovery will be analyzed across the three time points. Mediators for improvement in cognitive performance and functioning will also be explored. Discussion: Findings of this research will add to the body of knowledge about the key therapeutic ingredients within a strategy-based cognitive remediation program and improve its implementation within under-resourced community settings. Trial registration: This study has been registered with ClinicalTrials.gov (ID: NCT06286202). Date of registration: 29 February 2024. Date of last update: 21 May 2024. [ABSTRACT FROM AUTHOR]

Reading comprehension is one of the challenges in education, because it involves, rather than repeating orally, what is written. It is an essential factor for achieving personal growth and proper incorporation into society. It is therefore considered important for teachers to adapt to new changes in the teaching and learning process. Therefore, it is necessary to investigate whether collaborative learning as a pedagogical resource can significantly improve students' reading understanding. The objective of this research is to analyze collaborative learning as a didactic strategy, for the strengthening of reading comprehension in the students of the "Siete de Noviembre" School of Santa Elena canton. Descriptive research was developed, with a nonexperimental design, cross-sectional and mixed approach. Two surveys, one aimed at students and the other at teachers were applied to assess their perception of collaborative learning and its current use for improving understanding. Survey results show that, although teachers mention that the collaborative learning environment contributes to the development of student learning, they lack information on strategies that encourage the application of collaborative learning. To this end, a group of pedagogical strategies is proposed that consider the application of collaborative learning in the development of reading comprehension for the support of teachers. [ABSTRACT FROM AUTHOR]

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Many instructors have struggled for a long time with the issue of how to teach language effectively. These techniques include generating student curiosity and interest, employing part-of-speech conversion, using syntactic analysis, formative assessment, and using the game method after briefly reviewing the history of the evolution of English teaching methods. Using this method, students' vocabulary mastery has increased dramatically, an essential and fundamental component of teaching English. Thus, teaching vocabulary efficiently and adequately will significantly help improve general English education. The result of this research is that the implementation of this strategy is efficient in terms of student learning. vocabulary accumulation. Like the bricks that make up a house, vocabulary is the foundation and most important element of teaching English. If students have extensive vocabulary storage, it will be very helpful for English education in general. As a result, the authors of this paper believe that this essay will offer useful answers to the longstanding problem of teaching language effectively and efficiently. Since teaching vocabulary is a creative endeavor, educators can design their unique methods or techniques for teaching vocabulary based on their current situation and abilities. [ABSTRACT FROM AUTHOR]

In this paper we propose a strategy learning model for autonomous agents based on classification. In the literature, the most commonly used learning method in agent-based systems is reinforcement learning. In our opinion, classification can be considered a good alternative. This type of supervised learning can be used to generate a classifier that allows the agent to choose an appropriate action for execution. Experimental results show that this model can be successfully applied for strategy generation even if rewards are delayed. We compare the efficiency of the proposed model and reinforcement learning using the farmer-pest domain and configurations of various complexity. In complex environments, supervised learning can improve the performance of agents much faster that reinforcement learning. If an appropriate knowledge representation is used, the learned knowledge may be analyzed by humans, which allows tracking the learning process

Mobile edge computing (MEC) is expected to provide cloud-like capacities for mobile users (MUs) at the edge of wireless networks. However, deploying MEC systems faces many challenges, one of which is to achieve an efficient distributed offloading mechanism for multiple users in time-varying wireless environments. In this paper, we study a multi-user multi-edge-node computation offloading problem. Since edge nodes’ communication and computing capacities are limited which leads resource contention when many MUs offload to the same edge node at the same time, we formulate this problem as a non-cooperative exact potential game (EPG), where each MU, in each time slot, selfishly maximizes its number of processed central processor unit (CPU) cycles and reduces its energy consumption. Assuming that channel information is static and available to MUs, we show that MUs could achieve a Nash equilibrium via a best response-based offloading mechanism. Next, we extend the problem to a practical scenario, where the number of processed CPU cycles is time-varying and unknown to MUs because of the uncertain channel information. In this case, we adopt an unknown payoff game framework and prove that the EPG properties still hold. Then, we propose a model-free reinforcement learning offloading mechanism which helps MUs learn their long-term offloading strategies to maximize their long-term utilities. Numerical results illustrate that our proposed algorithm for unknown CSI outperforms other schemes, such as local processing and random assignment, and achieves up to 87.87% average long-term payoffs compared to the perfect CSI case. [ABSTRACT FROM AUTHOR]

Elke Van Steendam, Anne Toorenaar,Journal of Writing Research 1(1), 53-83In this paper we discuss the role of observation in learning to write. We argue that the acquisition of skill in such a complex domain as writing relies on observation, the classical imitatio. An important phase in learning to write, at all ages, is learning to write by observing and evaluating relevant processes: writing processes, reading processes or communication processes between writers and readers.First, we present two practical cases: writing lessons in which observation and inquiry are amongst other key elements and where students participate in a community of learners. Then, we review research that may inspire and substantiate proposals for implementing observation as a learning activity in writing education. Two types of studies are discussed: studies in which learners acquire strategies by observing and evaluating writing and reading processes of peers, as a prewriting instructional activity, and studies in which learners are stimulated to 'pre-test' and then revise their first draft, as a post writing instructional activity. The paper closes with some recommendations for further research.

The Tower of Hanoi (TOH) is a classic problem that can be solved via multiple strategies. This study used TOH to examine how mode of presentation of a problem influences strategy use and transfer. Undergraduate students (Experiment 1) or Prolific workers (Experiment 2) completed two TOH problems of varying difficulty (4-disk/5-disk). They were randomly assigned to different conditions in which problems were either high in internal representation (mental) or high in external representation (computer). Participants were better able to complete problems successfully when external representations were available but completed problems in fewer moves when relying on internal representations. In addition, participants spent more time between moves when solving problems mentally, suggesting that external representations encourage speed while internal representations promote accuracy when solving recursion problems. Lastly, both experiments provide evidence that first solving a problem mentally encouraged participants to use strategies similar to goal recursion on a second problem. [ABSTRACT FROM AUTHOR]

A question answering (QA) system can be built using multiple QA modules that can individually serve as a QA system in and of themselves. This paper proposes a learnable, strategy-driven QA model that aims at enhancing both efficiency and effectiveness. A strategy is learned using a learning-based classification algorithm that determines the sequence of QA modules to be invoked and decides when to stop invoking additional modules. The learned strategy invokes the most suitable QA module for a given question and attempts to verify the answer by consulting other modules until the level of confidence reaches a threshold. In our experiments, our strategy learning approach obtained improvement over a simple routing approach by 10.5% in effectiveness and 27.2% in efficiency. [ABSTRACT FROM AUTHOR]

The paper presents an algorithm for multi-agent strategic modeling (MASM). The method applies domain knowledge and transforms sequences of basic multi-agent actions into a set of strategic action descriptions in the form of graph paths, agent actions, roles and corresponding rules. The rules, constructed by machine learning, enrich the graphical strategic patterns, which are presented in the form of graph paths. The method was evaluated on the RoboCup Soccer Server Internet League data. Tests showed that the constructed rules successfully captured some decisive offensive moves and some major defense flaws, although the description itself was a bit awkward and needed interpretation by a human expert. [ABSTRACT FROM AUTHOR]

The purpose of this study was to compare the effectiveness of two training approaches, Spaced Retrieval (SR) and a modified Cueing Hierarchy (CH), for teaching persons with dementia a strategy goal involving an external memory aid. Twenty-five persons with dementia living in either community or nursing home settings received training on two individual-specific strategy goals, one with each training approach. Results revealed that significantly more goals were attained using SR procedures than CH, but that a majority of participants learned to use external aids using both strategies. There were no significant differences in the number of sessions required to master goals in either condition; however, significantly more SR goals were maintained at both 1-week and 4-months post-training compared to CH goals. Mental status was not significantly correlated with goal mastery, suggesting the potential benefits of strategy training beyond the early stages of dementia.: Learning outcomesAs a result of this activity, the reader will be able to (1) identify ways to enable persons with dementia to make effective use of external memory aids; (2) describe a method, Spaced Retrieval, by which persons with dementia can learn and retain information; and (3) describe two approaches to working with persons with dementia to train a strategy learning goal. [Copyright &y& Elsevier]

Extortion strategy can play the role of a Trojan horse for cooperators and act as a catalyst for the evolution of cooperation in social dilemma games. Based on the prisoner's dilemma game model with extortion, an emotion-imitating rule for strategy updating is proposed in this study, which takes into account the diverse attitudes of a player towards a strong or weak opponent. Furthermore, by employing evidential reasoning, we establish an improved rule for strategy updating, which integrates the emotion-imitating rule into strategy learning as well as the original myopic best response rule, and via a fusion weight, the role of emotion-imitating can be subtly adjusted in the process of strategy learning. The effect of emotion-imitating on cooperation is investigated in the presence of extortioners. Through Monte Carlo simulations, it is shown that the new rule can significantly boost cooperation when the fusion weight is close to 0.5. In strategy learning, the emotion-imitating rule relieves the direct exploitation from defectors for cooperators and also facilitates cooperators to cluster and spread in the population. The extortion strategy provides shelter for cooperators to survive even at the extremely high temptation to defect. In addition, the myopic best response rule can also improve the performance of the emotion-imitating rule, especially in the region of high temptation to defect. Based on evidential reasoning, the new rule integrates sophisticatedly the advantage of the two single rules, enhancing the emergence of cooperation as well as the average payoffs of the whole system. The robustness of the shelter effects of extortioners under the new learning rule model is also studied by considering action errors and the cognition cost of extortioners respectively. The results further support the catalyst roles of extortioners, provided that the dilemma strength is not too strong. We also demonstrate the enhancement of cooperation when the model is extended to four competing strategies where the tit for tat (TFT) strategy is also included. The coexistence of extortioners and TFT players restricts the expansion of defectors, and the extortioners' catalyst role still works prominently in the interval of low tempt values. [ABSTRACT FROM AUTHOR]