Offline Improvement during Motor Sequence Learning Is Not Restricted to Developing Motor Chunks

Robust offline performance gains, beyond those that would be anticipated by being exposed to additional physical practice, have been reported during procedural learning and have been attributed to enhancement consolidation, a process by which memory is transformed in such a way that it is not only more resistant to forgetting but may also involve a reorganization of information that supports superior task execution. The authors assessed the impact of increasing within-session practice extent on the emergence of offline performance gains. Practice-dependent improvements occurred across 12 and 24 30-s practice trials of a 5-element motor sequencing task. Offline improvements were observed following both 12 and 24 trials. The improvement following 12 trials was associated with the formation of motor chunks important for establishing movement sequence structure. In contrast, the offline improvement after 24 trials was not related to further changes in movement structure beyond those that had emerged during practice. These data suggest that additional memory operations, beyond those needed to amalgamate subsequences of the SRT task, are susceptible to enhancement consolidation.     

Learning With Real Machines or Diagrams: Application of Knowledge to Real-World Problems

In this study, we investigated how learning from different media, either from real pulley systems or from simple line diagrams, affected mechanical learning and problem solving. Novice subjects learned about pulley systems by comparing the efficiency of different systems and receiving feedback on their accuracy. The main outcome measures were subjects' ability to compare pulley system efficiency, their level of mechanical reasoning, and their ability to apply knowledge of system efficiency and construction details. Experiment 1 showed that (a) subjects learning with the two types of media made equal improvement on the learning task, and (b) all subjects showed an increase in quantitative understanding as they learned, but (c) subjects who learned hands-on, by manipulating real pulley systems, solved application problems more accurately than those who learned from diagrams. Experiment 2 showed that both the realism of the stimuli and the opportunity to manipulate systems contributed to the improved performance on application problems.     

宽恕治疗:基于东西方文化比较的研究

在积极心理学视野下,宽恕这一主题日益受到心理学界的关注,西方心理治疗领域发展出一项针对受冒犯者的临床技术--宽恕治疗,现有研究支持了其在西方文化中的有效性.而有研究表明,宽恕是一个受文化制约的心理现象,因此,在跨文化应用时,需要考虑其文化制约性,该文在介绍西方宽恕治疗临床应用的基础上,进行文化方面的比较与讨论,并就宽恕治疗的跨文化应用提出一些思考,据此提出在中国文化背景下的宽恕治疗构想.     

Learning by imagining

Five experiments were conducted to investigate the relative effectiveness of 2 alternative instructional strategies. Students who were engaged in studying worked examples that emphasized understanding and remembering procedures and concepts were compared with students who were engaged in imagining worked examples that emphasized imagining procedures and concepts. It was hypothesized that students who held prerequisite schemas would find imagining to have a beneficial effect on learning, compared with studying the material, whereas students who were less knowledgeable would find imagining to have a negative effect on learning, compared with studying. Experimental results were in accord with our hypotheses. It was concluded that, under specific circumstances, encouraging students to imagine procedures and concepts can substantially facilitate learning.     

Maze Learning by Honeybees

This study examines whether honeybees can learn to fly through complex mazes, in the presence or the absence of specific visual cues. The results are summarized as follows: 1. Bees can learn to fly through a complex maze by following a trail of colored marks. 2. Bees, initially trained to follow color marks through an initial part of the maze, are immediately able to use the same sign-tracking cue to find their way through the rest of the maze, which is unfamiliar to them. 3. Bees trained to follow color marks through a particular maze can use the same cue to negotiate a novel maze. 4. Bees trained to use a particular color to negotiate a maze can immediately use a novel color to negotiate the same maze or even a novel maze. 5. After learning to negotiate a maze by following colored marks, bees can find their way through the maze even when the marks are removed, albeit at reduced levels of accuracy. Thus, the trained bees do not rely solely on sign-tracking to find their way through the maze: they also acquire a spatial memory of the maze or at least a sequence of motor commands describing the correct path through it. 6. Bees can learn to use color as a signal even when it indicates the path through the maze in a symbolic way, for example, blue indicating a turn to the right and green a turn to the left. 7. Bees can learn an unmarked maze. Performance under these conditions is poorer than when marks are provided, but is still significantly better than chance level. 8. Control experiments rule out the use of external landmarks in all of these situations.     

The Machines Take Over: A Comparison of Various Supervised Learning Approaches for Automated Scoring of Divergent Thinking Tasks

Traditionally, researchers employ human raters for scoring responses to creative thinking tasks. Apart from the associated costs this approach entails two potential risks. First, human raters can be subjective in their scoring behavior (inter-rater-variance). Second, individual raters are prone to inconsistent scoring patterns (intra-rater-variance). In light of these issues, we present an approach for automated scoring of Divergent Thinking (DT) Tasks. We implemented a pipeline aiming to generate accurate rating predictions for DT responses using text mining and machine learning methods. Based on two existing data sets from two different laboratories, we constructed several prediction models incorporating features representing meta information of the response or features engineered from the response’s word embeddings that were obtained using pre-trained GloVe and Word2Vec word vector spaces. Out of these features, word embeddings and features derived from them proved to be particularly effective. Overall, longer responses tended to achieve higher ratings as well as responses that were semantically distant from the stimulus object. In our comparison of three state-of-the-art machine learning algorithms, Random Forest and XGBoost tended to slightly outperform the Support Vector Regression.     

Complex Visual Learning by Rats

Rats’ learning about visual patterns was studied in a computerized Y-maze where wide-angle stimuli were viewed from a distance. Many patterns were available; some were spatially complex and others were more homogeneous figures. Experiment 1 used a discrimination paradigm in which a single S⁺could be paired with any one of 15 different S⁻s. Hooded rats learned successively six such discrimination problems. Their learning rate improved across the series, and comparison with controls suggested that the learning-set did not merely reflect simple habituation. Experiments 2 and 3 employed Dark Agouti rats, again learning many discrimination problems. Each problem comprised a constant stimulus which was paired with stimuli which varied in trial-unique fashion. The version in which the constant stimulus was nonrewarded (S⁻) and the varying stimuli rewarded was performed better than the converse, constant S⁺and varying nonrewarded, reflecting rats’ preference for relatively unfamiliar stimuli. In the constant S⁻task, rats showed substantial within-problem learning when three novel problems were given per day for 20 trials each. Rats are capable of rapid learning about complex visual displays if we engage their natural dispositions to use vision for distal stimuli and to approach relatively unfamiliar cues.     

Restricted thresholds for interval orders: A case of nonaxiomatizability by a universal sentence

Let $\text{P}$_n be the class of all finite interval orders that can be interval-represented using no more than n interval lengths or threshold levels. Thus $\text{P}$₁ is the class of finite semiorders, and $\text{P}$, the union of the $\text{P}$_n, is the class of finite interval orders. While each of $\text{P}$₁ and $\text{P}$ is axiomatizable by a universal sentence in first-order logic, no $\text{P}$_n for $\text{n ≧ 2}$ is axiomatizable in the same sense.     

Learning phonetic categories by tracking movements

We explore in this study how infants may derive phonetic categories from adult input that are highly variable. Neural networks in the form of self-organizing maps (SOMs; ) were used to simulate unsupervised learning of Mandarin tones. In Simulation 1, we trained the SOMs with syllable-sized continuous F(0) contours, produced by multiple speakers in connected speech, and with the corresponding velocity profiles (D1). No attempt was made to reduce the large amount of variability in the input or to add to the input any abstract features such as height and slope of the F(0) contours. In the testing phase, reasonably high categorization rate was achieved with F(0) profiles, but D1 profiles yielded almost perfect categorization of the four tones. Close inspection of the learned prototypical D1 profile clusters revealed that they had effectively eliminated surface variability and directly reflected articulatory movements toward the underlying targets of the four tones as proposed by . Additional simulations indicated that a further learning step was possible through which D1 prototypes with one-to-one correspondence to the tones were derived from the prototype clusters learned in Simulation 1. Implications of these findings for theories of language acquisition, speech perception and speech production are discussed.     

企业培训中员工的学习动机与学习策略的探讨

本研究在研制学习过程问卷的基础上,探讨了航修企业员工培训中学习动机与学习策略的匹配关系。研究表明:(1)学习方式包括学习动机和学习策略两个成分;(2)实用型学习动机的员工倾向于采用实用型学习策略,而应付型学习动机的员工倾向于采用应付型学习策略。这一结果证实了Marton等人关于学生的学习动机决定其学习策略的理论。     

Learning of object-object associations by monkeys

Monkeys were trained in tasks where stimulus objects were presented in pairs, one object of a pair concealing the other, and the monkeys had to displace the top object followed by the bottom object in order to obtain a food reward. In two experiments it was demonstrated that under these conditions the animals formed object-object associations such that the top object recalled in memory the bottom object that had previously been found underneath it. The monkeys were able to discriminate in recall between bottom objects that were identical in secondary reinforcing value and differed only in colour.     

Learning by observation in rhesus monkeys

Habit memory provides us with a vast repertoire of learned rules, including stimulus-reward associations, that ensures fast and adapted decision making in daily life. Because we share this ability with monkeys, lesion and recording studies in rhesus macaques have played a key role in understanding the neural bases of individual trial-and-error habit learning. Humans, however, can learn new rules at a lower cost via observation of conspecifics. The neural properties underlying this more ecological form of habit learning remain unexplored, and it is unclear whether the rhesus macaque can be a useful model in this endeavor. We addressed this issue by testing four monkeys from the same social group in their usual semi-natural habitat using a well-established marker of habit memory, concurrent discrimination learning. Each monkey learned 24 lists of 10 object-reward associations each. For one list out of two, monkeys could observe the testing session of another member of the group prior to being tested with the same list themselves. Learning was faster for these lists than for those learned solely by trial-and-error. Errors to criterion (9/10 correct responses) were reduced by 39%, and faultless performance could be achieved for up to 5 of the 10 pairs. These data demonstrate that rhesus macaques spontaneously observe a conspecific learning new stimulus-reward associations, and substantially benefit from this observation. They ascertain that the neural underpinnings of socially-mediated forms of habit learning can be explored using the powerful tools of monkey research, including neurophysiological recordings.     

Learning is impaired by activated intentions

Two experiments examined the task interference that sometimes accrues from having an intention. In standard prospective memory tasks, latency is often slower to an ongoing task performed concurrently with having an intention than it is when no intention is given. If the locus of this slowing resulted from different attentional allocation policies in the two cases, we predicted that the process of learning a word list would be impaired if participants had an intention rather than if they did not. Four different event-based prospective memory tasks were used in Experiment 1 to demonstrate that worse free recall of a word list resulted when studied with a concurrent intention than with a control condition that had no intention. In that experiment, linking an intention to a distal context that was to occur after learning did not impair free recall. Two time-based tasks were used in Experiment 2 to demonstrate that possessing a time-based prospective memory also hinders learning, unless the intention is linked to a future context that is expected to occur after the study session. In the latter case, no impairment was obtained.     

Tutoring: Guided Learning by Doing

Individualized instruction significantly improves students' pedagogical and motivational outcomes. In this article, we seek to characterize tutorial behaviors that could lead to these benefits and to consider why these actions should be pedagogically useful. This experiment examined university students learning LISP programming with the assistance of a tutor. Tutoring sessions were audiotaped, allowing u to analyze every verbal utterance during the sessions and thereby to identify the conversational events that lead to pedagogical success. This discourse analysis suggests that tutors are successful because they take a very active role in leading the problem solving by offering confirmatory feedback and additional guidance while students are on profitable paths and error feedback after mistakes. However, tutors carefully structure their feedback to allow students to perform as much of the work as possible while the tutor ensures that problem solving stays on track. These results suggest the types of strategies tutors employ to facilitate guided learning by doing.