Fear relevancy, strategy use, and probabilistic learning of cue-outcome associations

The goal of this study was to determine how the fear relevancy of outcomes during probabilistic classification learning affects behavior and strategy use. Novel variants of the "weather prediction" task were created, in which cue cards predicted either looming fearful or neutral outcomes in a between-groups design. Strategy use was examined by goodness-of-fit estimates of response patterns across trial blocks to mathematical models of simple, complex, and nonidentifiable strategies. Participants in the emotional condition who were fearful of the outcomes had greater skin conductance responses compared with controls and performed worse, used suboptimal strategies, and had less insight into the predictive cue features during initial learning. In contrast, nonfearful participants in the emotional condition used more optimal strategies than the other groups by the end of the two training days. Results have implications for understanding how individual differences in fear relevancy alter the impact of emotion on feedback-based learning.     

Les capacités de transfert en situation d'apprentissage implicite chez des préadolescents présentant un retard mental

This study investigates the transfer issue in implicit learning in pre-adolescents with mental retardation (MR), matched with normally developing children. A simple task is used to assess the transfer of a graphic behavior learned implicitly. The results show that the behavioral modifications induced by implicit learning can be transferred to a new graphic figure, in similar proportions in same mental age (MA) participants with and without MR. This transfer effect is independent on the degree of MR. The results are discussed with respect to the robustness of implicit learning (Reber, 1989), and to the “transfer decrement” phenomena. We also discuss how this type of learning can be used for the benefit of MR persons.     

Evidence for model-based action planning in a sequential finger movement task

In this article, the authors examine whether and how humans use model-free, reflexive strategies and model-based, deliberative strategies in motor sequence learning. They asked subjects to perform the grid-sailing task, which required moving a cursor to different goal positions in a 5 × 5 grid using different key-mapping (KM) rules between 3 finger keys and 3 cursor movement directions. The task was performed under 3 conditions: Condition 1, new KM; Condition 2, new goal position with learned KM; and Condition 3, learned goal position with learned KM; with or without prestart delay time. The performance improvement with prestart delay was significantly larger under Condition 2. This result provides evidence that humans implement a model-based strategy for sequential action selection and learning by using previously learned internal model of state transition by actions.     

What is pressure? Evidence for social pressure as a type of regulatory focus

Previous research (Markman, Maddox, & Worthy, 2006) suggests that pressure leads to choking when one is learning to classify items on the basis of an explicit rule, but it leads to excelling when one is learning to classify items on the basis of an implicit strategy. In this article, we relate social pressure to regulatory focus theory. We propose that the effects of pressure on performance arise because pressure induces a prevention focus that interacts with the more local reward structure of the task. To test this hypothesis, we repeated previous research, but using a losses reward structure, so that participants under pressure were in a regulatory fit. We also successfully replicated previous results by using a gains reward structure. In contrast with participants who attempted to maximize gains on each trial, participants who attempted to minimize losses choked on the implicit-learning task but excelled on the explicit-learning task. The results suggest a three-way interaction between pressure level, task type, and reward structure.     

Comparing Multiple Paths to Mastery: What is Learned?

Contemporary theories of learning postulate one or at most a small number of different learning mechanisms. However, people are capable of mastering a given task through qualitatively different learning paths such as learning by instruction and learning by doing. We hypothesize that the knowledge acquired through such alternative paths differs with respect to the level of abstraction and the balance between declarative and procedural knowledge. In a laboratory experiment we investigated what was learned about patterned letter sequences via either direct instruction in the relevant patterns or practice in solving letter-sequence extrapolation problems. Results showed that both types of learning led to mastery of the target task as measured by accuracy performance. However, behavioral differences emerged in how participants applied their knowledge. Participants given instruction showed more variability in the types of strategies they used to articulate their knowledge as well as longer solution times for generating the action implications of that knowledge as compared to the participants given practice. Results are discussed regarding the implications for transfer, generalization, and procedural application. Learning theories that claim generality should be tested against cross-scenario phenomena, not just parametric variations of a single learning scenario.     

How do people solve the "weather prediction" task?: individual variability in strategies for probabilistic category learning

Probabilistic category learning is often assumed to be an incrementally learned cognitive skill, dependent on nondeclarative memory systems. One paradigm in particular, the weather prediction task, has been used in over half a dozen neuropsychological and neuroimaging studies to date. Because of the growing interest in using this task and others like it as behavioral tools for studying the cognitive neuroscience of cognitive skill learning, it becomes especially important to understand how subjects solve this kind of task and whether all subjects learn it in the same way. We present here new experimental and theoretical analyses of the weather prediction task that indicate that there are at least three different strategies that describe how subjects learn this task. (1) An optimal multi-cue strategy, in which they respond to each pattern on the basis of associations of all four cues with each outcome; (2) a one-cue strategy, in which they respond on the basis of presence or absence of a single cue, disregarding all other cues; or (3) a singleton strategy, in which they learn only about the four patterns that have only one cue present and all others absent. This variability in how subjects approach this task may have important implications for interpreting how different brain regions are involved in probabilistic category learning.     

The influence of information redundancy on probabilistic inferences

Information redundancy affects the accuracy of inference strategies. A simulation study illustrates that under high-information redundancy simple heuristics that rely on only the most important information are as accurate as strategies that integrate all available information, whereas under low redundancy integrating information becomes advantageous. Assuming that people exercise adaptive strategy selection, it is predicted that their inferences will more often be captured by simple heuristics that focus on part of the available information insituations ofhigh-information redundancy, especially when information search is costly. This prediction is confirmed in two experiments. The participants' task was to repeatedly infer which of two alternatives, described by several cues, had a higher criterion value. In the first experiment, simple heuristics predicted the inference process better under high-information redundancy than under low-information redundancy. In the second experiment, this result could be generalized to an inference situation in which participants had no prior opportunity to learn about the strategies' accuracies through outcome feedback. The results demonstrate that people are able to respond adaptively to different decision environments under various learning opportunities.     

两种学习模式下类别学习的结果：原型和样例

利用“学习－迁移”的任务范式和单一特征类别判断技术,探讨了分类和推理两种类别学习模式的结果,比较了两种学习模式的效果和策略。研究表明：两种学习模式产生了不同的结果,分类学习的结果是样例,推理学习的结果是原型;在学习效果方面,分类学习比推理学习在达标比例上更高,但在进度上差异不显著;在策略运用方面,分类学习比推理学习更快地使用单维度策略,而在高水平策略的运用上,两者差异不显著     

Deficit in learning of a motor skill requiring strategy, but not of perceptuomotor recalibration, with aging

We investigated the effect of aging on different aspects of motor skill learning using two computer-presented perceptuomotor tasks. The relationship between visual and proprioceptive feedback was transformed in the first task, which was open to the formation and use of strategies. This task was designed to lead to perceptuomotor adaptation that was then measured by performance on a very similar second task that was not open to the use of strategy task. Older participants showed impaired learning of the strategic task but not of the nonstrategic task. This is in line with the suggestion that the effect of aging on learning and memory may be to reduce working memory resources.     

Terminal Feedback Outperforms Concurrent Visual,Auditory, and Haptic Feedback in Learning a Complex Rowing-Type Task

Augmented feedback, provided by coaches or displays, is a well-established strategy to accelerate motor learning. Frequent terminal feedback and concurrent feedback have been shown to be detrimental for simple motor task learning but supportive for complex motor task learning. However, conclusions on optimal feedback strategies have been mainly drawn from studies on artificial laboratory tasks with visual feedback only. Therefore, the authors compared the effectiveness of learning a complex, 3-dimensional rowing-type task with either concurrent visual, auditory, or haptic feedback to self-controlled terminal visual feedback. Results revealed that terminal visual feedback was most effective because it emphasized the internalization of task-relevant aspects. In contrast, concurrent feedback fostered the correction of task-irrelevant errors, which hindered learning. The concurrent visual and haptic feedback group performed much better during training with the feedback than in nonfeedback trials. Auditory feedback based on sonification of the movement error was not practical for training the 3-dimensional movement for most participants. Concurrent multimodal feedback in combination with terminal feedback may be most effective, especially if the feedback strategy is adapted to individual preferences and skill level.     

Memory activation and the availability of explanations in sequential diagnostic reasoning

In the field of diagnostic reasoning, it has been argued that memory activation can provide the reasoner with a subset of possible explanations from memory that are highly adaptive for the task at hand. However, few studies have experimentally tested this assumption. Even less empirical and theoretical work has investigated how newly incoming observations affect the availability of explanations in memory over time. In this article we present the results of 2 experiments in which we address these questions. While participants diagnosed sequentially presented medical symptoms, the availability of potential explanations in memory was measured with an implicit probe reaction time task. The results of the experiments were used to test 4 quantitative cognitive models. The models share the general assumption that observations can activate and inhibit explanations in memory. They vary with respect to how newly incoming observations affect the availability of explanations over time. The data of both experiments were predicted best by a model in which all observations in working memory have the same potential to activate explanations from long-term memory and in which these observations do not decay. The results illustrate the power of memory activation processes and show where additional deliberate reasoning strategies might come into play.     

Stress modulates the use of spatial versus stimulus-response learning strategies in humans

Animal studies provided evidence that stress modulates multiple memory systems, favoring caudate nucleus-based "habit" memory over hippocampus-based "cognitive" memory. However, effects of stress on learning strategy and memory consolidation were not differentiated. We specifically address the effects of psychosocial stress on the applied learning strategy in humans. We designed a spatial learning task that allowed differentiating spatial from stimulus-response learning strategies during acquisition. In 13 subsequent trials, participants (88 male and female students) had to locate a "win" card out of four placed at a fixed location in a 3D model of a room. Relocating one cue in the last trial allowed inferring the applied learning strategy. Half of them participated first in the "Trier Social Stress Test." Salivary cortisol and heart rate measurements were taken. Stressed participants used a stimulus-response strategy significantly more often than controls. Subsequent verbal report revealed that spatial learners had a more complete awareness of response options than stimulus-response learners. Importantly, learning performance was not affected by stress. Taken together, stress prior to learning facilitated simple stimulus-response learning strategies in humans-at the expense of a more cognitive learning strategy. Depending on the context, we consider this as an adaptive response.     

The Impact of Goal Specificity on Strategy Use and the Acquisition of Problem Structure

Theories of skill acquisition have made radically different predictions about the role of general problem-solving methods in acquiring rules that promote effective transfer to new problems. Under one view, methods that focus on reaching specific goals, such as means-ends analysis, are assumed to provide the basis for efficient knowledge compilation (Anderson, 1987), whereas under an alternative view such methods are believed to disrupt rule induction (Sweller, 1988). We suggest that the role of general methods in learning varies with both the specificity of the problem solver's goal and the systematicity of the strategies used for testing hypotheses about rules. In the absence of a specific goal people are more likely to use a rule-induction learning strategy, whereas provision of a specific goal fosters use of difference reduction, which tends to be a non-rule-induction strategy. We performed two experiments to investigate the impact of goal specificity and systematicity of rule-induction strategies in learning and transfer within a complex dynamic system. The results of Experiment 1 indicated that during free exploration of a problem space, greater learning occurred if participants adopted more systematic strategies for rule induction, and that participants come to favor such strategies. Experiment 2 revealed that participants who were provided with a specific goal performed well on the initial problem but were impaired on a transfer test using a similar problem with a different goal. Instruction on a systematic rule-induction strategy facilitated solution for both the initial and transfer problems, but participants' use of this strategy declined if they had a specific goal. Our results support Sweller's (1988) proposal that general problemsolving methods applied to a specific goal foster acquisition of knowledge about an isolated solution path but do not provide an effective way of learning the overall structure of a problem space. We interpret these results in terms of dualspace theories of search through problem space.     

类别学习中两种学习模式的比较研究：分类学习与推理学习

采用学习迁移任务范式,使用基于单一特征的类别判断技术,比较了非线性分离结构下,分类学习和推理学习的学习效率、学习过程与策略和学习结果。结果表明：在学习效率上,分类学习比推理学习更好地习得了含有较多样例的类别知识,分类学习的速度上显著快于推理学习。在学习的过程与策略上,推理学习比分类学习更为关注类别内不同特征的相关,但在分类策略的运用上不如分类学习灵活。在学习的结果上,推理学习倾向于原型记忆,分类学习倾向于进行样例记忆,分类学习比推理学习更好地掌握了类别原型     

Optimal learning strategies and their spontaneous use: The importance of task-appropriate processing

College students were given three verbal learning tasks to perform, with some subjects instructed to use a particular verbal or imaginal encoding strategy for all three tasks and other subjects not instructed to use any particular strategy. It was found that the relative effectiveness of the assigned encoding strategies varied as a function of the learning task. In addition, “uninstructed” subjects, for the most part, spontaneously employed strategies that produced recall comparable to that observed for subjects assigned the most effective strategy for a particular learning task. In Experiment 2, subjects were instructed to perform a different encoding strategy for each learning task. Subjects who were assigned the strategies in a “task-appropriate” fashion recalled more, in general, than subjects who were assigned the same strategies paired with the learning tasks in a haphazard fashion. Subjects not instructed to use a particular strategy again demonstrated relatively high recall and were found to vary processing across learning tasks. It was concluded that optimal learning for a range of tasks can require deployment of several semantic/elaborative strategies in a task-appropriate fashion. Furthermore, mature learners seem to spontaneously utilize semantic and imaginal strategies and do so task appropriately.     

Motivated comprehension regulation: Vigilant versus eager metacognitive control

The more accurately people assess their comprehension, the more likely they are to engage in study behaviors that precisely target gaps in their learning. However, comprehension regulation involves more than knowing when to implement a new study strategy; it also involves deciding which strategy will most effectively resolve one’s confusion. In two experiments, we explored how people’s motivational orientations influence which study strategies they select to regulate their comprehension. In Experiment 1, people who were motivated to vigilantly protect against potential mistakes (i.e., prevention-focused individuals) were more likely to adopt a rereading strategy than people who were motivated to eagerly pursue new learning opportunities (i.e., promotion-focused individuals). In Experiment 2, this difference in strategy use emerged specifically in response to confusing sentences that had been inserted into the text. Furthermore, by using rereading strategies to resolve their confusion, prevention-focused individuals performed better than promotion-focused individuals on a comprehension test and a transfer task.     

Modeling how, when, and what is learned in a simple fault-finding task

We have developed a process model that learns in multiple ways while finding faults in a simple control panel device. The model predicts human participants' learning through its own learning. The model's performance was systematically compared to human learning data, including the time course and specific sequence of learned behaviors. These comparisons show that the model accounts very well for measures such as problem-solving strategy, the relative difficulty of faults, and average fault-finding time. More important, because the model learns and transfers its learning across problems, it also accounts for the faster problem-solving times due to learning when examined across participants, across faults, and across the series of 20 trials on an individual participant basis. The model shows how learning while problem solving can lead to more recognition-based performance, and helps explain how the shape of the learning curve can arise through learning and be modified by differential transfer. Overall, the quality of the correspondence appears to have arisen from procedural, declarative, and episodic learning all taking place within individual problem-solving episodes.     

Individual differences in Sternberg’s memory scanning task

This study provides a new perspective on both the cognitive processes actually implemented and the effect of a simple experimental control - the recall constraint - in Sternberg’s memory scanning task. These findings were highlighted by adopting a new approach based on the comparison of qualitative and quantitative results.The analysis of individual processing, on 72 adults, each participating in one of two experimental conditions (with or without sequence recall), highlighted a large variability in quantitative results as well as qualitative procedures. Based on the participants’ retrospective verbalisations, two categories of strategies were identified: (1) the procedures used to memorize the sequence of digits, and (2) the procedures used to compare this sequence with the test digit, which includes strategies for coding the items and processes for searching them in memory. The analysis of the strategies shows that their frequencies of use depend not only on the experimental condition, but also on the participants, the level of task difficulty and the interaction between participants and level of difficulty. This variability questions the accuracy of Sternberg’s mean model. Furthermore, this approach suggests some answers to the old debate concerning the exhaustive search pattern for the yes response. Indeed, our results show three types of strategies that can be identified according to the different models of search suggested in the literature. The “exhaustive” search, that would only be involved in the recall condition and only for some of the participants, the “self-terminating” search and the “immediate” strategy, which can be identified with a model of parallel search with limited resources. Thus our study suggests that the different search models are appropriate but depend on both the specific experimental conditions and participant’s strategy. Our results should help to improve the interpretation of data collected with this paradigm in cognitive and neuroscientific studies of memory.     

Instruction and Practice in Learning to use a Device

We explore the extent to which Anderson's (1987) theory of knowledge compilation can account for the relationship between instructions and practice in learning to use a simple device. Bibby and Payne (1993) reported experimental support for knowledge compilation in this domain. This article replicates the finding of a performance cross-over between instruction type and task type that disappears with practice on the tasks. The research is extended by using verbal protocols to model the strategies of novice and more experienced individuals. Production system models of these strategies suggest that knowledge compilation only provides an adequate account of practice for one of two Instruction groups. To model the strategy shifts for the second group, we employ a “procedure modification heuristic” (after Neches, 1987), which relies on access to a declarative model of the configuration of the device. This suggests that instructionally derived declarative knowledge may have a subtle ongoing effect on the changes in procedural knowledge with practice.