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Interactions between conspecifics are central to the acquisition of useful memories in the real world. Observational learning, i.e., learning a task by observing the success or failure of others, has been reported in many species, including rodents. However, previous work in rats with NMDA-receptor blockade has shown that even extensive observation of an unexplored space through a clear barrier is not sufficient to generate a stable hippocampal representation of that space. This raises the question of whether rats can learn a spatial task in a purely observed space from watching a conspecific, and if so, does this somehow stabilize their hippocampal representation? To address these questions, we designed an observational spatial task in a two-part environment that is nearly identical to that of the aforementioned electrophysiological study, in which an observer rat watches a demonstrator animal to learn the location of a hidden reward. Our results demonstrate that rats do not need to physically explore an environment to learn a reward location, provided a conspecific demonstrates where it is. We also show that the behavioral memory is not affected by NMDA receptor blockade, suggesting that the spatial representation underlying the behavior has been consolidated by observation alone.

Background/Objectives: Observational learning enables children to acquire new skills by observing others’ actions. Attention is widely recognized as a key supporting process and consists of multiple components that develop substantially during the early school years. Empirical evidence on the association between specific components of attention and observational learning remains limited. Therefore, this study examined the relationship between the main components of attention and observational learning among early primary school children. Methods: Sixty-eight children, aged 6–8, completed a computerized battery assessing the main components of attention (reaction times, simple and related to a choice; focused attention; short-term span of attention; divided and alternating attention) and an observational learning task where children observed an actor detecting a hidden spatial sequence and then reproduced it across detection phase (DP), exercise phase (EP), and automatization phase (AP). Correlational and regression analyses were conducted, controlling for age and gender. Results: Visual and visual–spatial focused attention emerged as significant predictors of performance during DP and EP, with higher levels of focused attention associated with fewer errors and repetitions. Choice reaction time showed phase-specific associations with error rates during early learning phases, whereas age was primarily related to performance during the AP. Conclusions: Observational learning in early primary school relies on specific components of attention rather than on attention as a unitary construct. Visual and visual–spatial focused attention plays a central role during the acquisition and consolidation of observed sequences, with implications for understanding learning from models and for educational practices based on demonstration.

Background/Objectives: Observational learning allows people to acquire new skills by observing the actions of others embedded in their social environment. From childhood, observational learning is a central process in human cognitive development, playing a crucial role in the acquisition of complex skills. Children and adults with autism spectrum disorder (ASD) often exhibit deficits in what are considered prerequisites for observational learning to occur (i.e., attending, imitation, delayed imitation, consequence discrimination). Considering this, the present review examined the literature on the complex and timely question of whether individuals with ASD can learn by observation, while accounting for the social versus non-social nature/content of the tasks. Methods: This work was a narrative review aimed at providing an overview of published studies in which observational learning was analyzed in individuals with ASD. Twenty-two studies met the inclusion criteria and were eligible for this review. Results: The core findings indicate that individuals with ASD may be able to learn by observing others, especially when taught the prerequisites for observational learning. Furthermore, the findings indicate that observation may be an effective way to expand the typically restricted and circumscribed interests of children with ASD and to increase emotion recognition skills. Conclusions: Overall, these findings have significant educational, clinical, social, and economic implications, supporting the use of observational learning strategies for both social and non-social skills to reduce reliance on expensive one-on-one teaching and to address some of the core deficits of ASD.

Learning by observation agents learn to perform a behaviour by watching an expert perform that behaviour. The ability of the agents to learn correctly is therefore related to the quality and coverage of the observations. This article presents two novel approaches for observation acquisition, mixed-initiative observation acquisition and delayed observation acquisition, that allow learning agents to identify problems they are having difficulty solving and ask the expert for assistance solving them. The observation approaches are presented in the context of a case-based learning by observation agent and empirically compared to traditional passive observation in the domain of Tetris. Our results show that not only do the mixed-initiative and delayed observation acquisition approaches result in observations that cannot be obtained in a passive manner, but they also improve the learning performance of an agent.

In accordance with the principles of the interbehavioral model of didactic performance and the researches carried out in the area of learning by observation, the objective of the following study was to evaluate the effects of the observation of didactic interactions of illustration and feedback on effective performance in a second-order matching-to-sample task with methodological terms of research in psychology as instances. Twenty university students participated, they were assigned randomly in a trial in three experimental groups and a control group. The experimental design was of A-B-A type, with an initial test, training and a final test. The experimental groups were distinguished by the type of observational training which received: illustration, feedback and illustration-feedback. The results indicate that this latter was the most effective according to the average of attempts made to respond to the reagent of the training, as well, as of the increase in the performance of the participants between both tests. These results are discussed in terms of: a) characteristics of the didactic interactions of illustration and feedback, and b) the importance of the linguistic regulation in learning by observation in real educational situations.

The rapid development of complex virtual worlds (most notably, in 3D computer and video games) introduces new challenges for the creation of virtual agents, controlled by artificial intelligence (AI) systems. Two important subproblems in this topic area which need to be addressed are (a) believability and (b) effectiveness of agents’ behavior, i.e., human-likeness of the characters and high ability to achieving their own goals. In this paper, the authors study current approaches to believability and effectiveness of AI behavior in virtual worlds. They examine the concepts of believability and effectiveness, and analyze several successful attempts to address these challenges.

Issue Title: Special ILP Mega-Issue: ILP-2003 and ILP-2004; ILP-2003 Guest Editors: Tamás Horváth and Akihiro Yamamoto; ILP-2004 Guest Editors: Rui Camacho, Ross King and Ashwin Srinivasan We describe a relational learning by observation framework that automatically creates cognitive agent programs that model expert task performance in complex dynamic domains. Our framework uses observed behavior and goal annotations of an expert as the primary input, interprets them in the context of background knowledge, and returns an agent program that behaves similar to the expert. We map the problem of creating an agent program on to multiple learning problems that can be represented in a \"supervised concept learning'' setting. The acquired procedural knowledge is partitioned into a hierarchy of goals and represented with first order rules. Using an inductive logic programming (ILP) learning component allows our framework to naturally combine structured behavior observations, parametric and hierarchical goal annotations, and complex background knowledge. To deal with the large domains we consider, we have developed an efficient mechanism for storing and retrieving structured behavior data. We have tested our approach using artificially created examples and behavior observation traces generated by AI agents. We evaluate the learned rules by comparing them to hand-coded rules.[PUBLICATION ABSTRACT]

In two experiments, rats observed expert foragers in a laboratory foraging task. In both experiments, 12 towers with a food cup on top of each tower were placed in a circle. Six towers, marked with black and white stripes, had cups baited with cheese, and were located in randomly selected positions on successive trials. The other six towers were white with food cups that were sham baited with inaccessible food. In both experiments, during Phase 1, demonstrator rats eventually learned to find the baited towers, making approximately 90% correct choices in their first six choices. In Phase 2, observer rats each had an opportunity to observe, from a cage located inside the circle of towers, a now-expert demonstrator forage. Half of the observers were able to observe a cage mate, whereas the other half of the observers were able to observe a non-cage mate. After a delay of about 2 min (Experiment 1 ) or about 24 h (Experiment 2 ), the observers were allowed to forage among the rebaited towers. In both experiments, the observers performed better during their 20 Phase 2 trials than the demonstrators had performed during their first 20 Phase 1 trials. But, in both experiments, there was no clearly significant difference between the performance of observers able to watch cage mates as opposed to non-cage mates. Because the observational effect seen in both experiments survived a 24-h delay between observation and performance, it was deemed to have been based on learning.

We report six experiments that examine how two essential components of a category-learning paradigm, training and feedback, can be manipulated to maximize learning and transfer of real-world, complex concepts. Some subjects learned through classification and were asked to classify hypothetical experiment scenarios as either true or non-true experiments; others learned through observation, wherein these same scenarios were presented along with the corresponding category label. Additionally, some subjects were presented correct-answer feedback (the category label), whereas others were presented explanation feedback (the correct answer and a detailed explanation). For classification training, this feedback was presented after each classification judgment; for observation training this feedback was presented simultaneously with the hypothetical experiment. After the learning phase, subjects completed a posttest that included one task that involved classifying novel hypothetical scenarios and another task comprising multiple-choice questions about novel scenarios, in which subjects had to specify the issue with the scenario or indicate how it could be fixed. The posttest either occurred immediately after the learning phase (Experiments 1–2), 10 min later (Experiments 3–4), two days later (Experiment 5), or one week later (Experiment 6). Explanation feedback generally led to better learning and transfer than correct-answer feedback. However, although subjects showed clear evidence of learning and transfer, posttest performance did not differ between classification and observation training. Critically, various learning theories and principles (e.g., retrieval practice, generation, active learning) predict a classification advantage. Our results thus call into question the extent to which such theories and principles extend to the transfer of learning.

Background Clinical skill training (CST) is indispensable for first-year surgical residents. It can usually be carried out through video-based flipped learning (FL) within a web-based learning environment. However, we found that residents lack the process of reflection, blindly imitating results in losing interest and passion for learning in the traditional teaching pattern. The teaching method of \"spot the difference\" (SDTM), which is based on the fundamentals of the popular game of \"spot the difference,\" is designed to improve students' participation and reflective learning during skill training. This study aimed to evaluate this novel educational model's short-term and long-term effectiveness for surgical residents in China. Methods First-year residents who required a three-month rotation in the head and neck surgery department were recruited to participate in a series of CSTs. They were randomized into SDTM and traditional FL (control) groups. Clinical skill performance was assessed with validated clinical skill scoring criteria. Evaluations were conducted by comparing the scores that contain departmental rotation skill examinations and the first China medical licensing examination (CMLE) performance on practical skills. In addition, two-way subjective evaluations were also implemented as a reference for the training results. Training effects were assessed using t tests, Mann–Whitney–Wilcoxon tests, chi-square tests, and Cohen’ s effect size (d). The Cohen’ s d value was considered to be small (<0.2), medium (0.2-0.8), or large (>0.8). Results The SDTM group was significantly superior to the control group in terms of after-department skill examination (t=2.179, p <0.05, d=0.5), taking medical history (t=2.665, p <0.05, d=0.59), and CMLE performance on practical skill (t=2.103, p <0.05, d=0.47). The SDTM members rated the curriculum more highly than the control on the items relating to interestingness and participation ( p < 0.05) with large effect sizes (d >0.8). There were no significant differences between the two groups on clinical competence (t=0.819, p =0.415, d=0.18), the first-time pass rate for CMLE (χ2 =1.663, p =0.197, d=0.29), and short-term operational skills improvement (t=1.747, p =0.084, d=0.39). Conclusions SDTM may be an effective method for enhancing residents' clinical skills, and the effect is significant both short- and long-term. The improvement effect seemed to be more significant in the peer-involved SDTM than training alone. However, despite positive objective results, SDTM still risks student learning burnout. Trial registration ISRCTN registry, ISRCTN10598469 , 02/04/2022，retrospectively registered.