Explanation and prior knowledge interact to guide learning

How do explaining and prior knowledge contribute to learning? Four experiments explored the relationship between explanation and prior knowledge in category learning. The experiments independently manipulated whether participants were prompted to explain the category membership of study observations and whether category labels were informative in allowing participants to relate prior knowledge to patterns underlying category membership. The experiments revealed a superadditive interaction between explanation and informative labels, with explainers who received informative labels most likely to discover (Experiments 1 and 2) and generalize (Experiments 3 and 4) a pattern consistent with prior knowledge. However, explainers were no more likely than controls to discover multiple patterns (Experiments 1 and 2), indicating that effects of explanation are relatively targeted. We suggest that explanation recruits prior knowledge to assess whether candidate patterns are likely to have broad scope (i.e., to generalize within and beyond study observations). This interpretation is supported by the finding that effects of explanation on prior knowledge were attenuated when learners believed prior knowledge was irrelevant to generalizing category membership (Experiment 4). This research provides evidence that explanation can serve as a mechanism for deploying prior knowledge to assess the scope of observed patterns.     

Considering prior knowledge when using elaborative interrogation

Previous studies have promoted the use of elaborative interrogation (a “why”-questioning strategy) for the acquisition of factual information. One assumption in these studies is that prior knowledge influences when students will be able to use the strategy, with greater prior knowledge leading to higher recall performance. In the studies reviewed here, the effect of prior knowledge on strategy effectiveness was investigated. Specifically, students' performances were compared for materials about which they possessed substantial prior knowledge, little prior knowledge, inconsistent prior knowledge, or shared prior knowledge. In general, the data support the use of elaborative interrogation when studying alone or in dyads especially when learners possess some relevant prior knowledge about the new information.     

Category learning with minimal prior knowledge

In 6 experiments, the authors examined the use of prior knowledge in category learning. Previous studies of the effects of knowledge on category learning have used categories in which knowledge was related to all of the category's features. However, people's knowledge of real-world categories often consists of many "rote" features that are not related to their prior knowledge. Five experiments found that even minimal prior knowledge (1 knowledge-relevant feature and 5 rote features per exemplar) can facilitate category learning. Posttests revealed that although the knowledge aided learning, subjects also acquired the rote features that were not related to knowledge, contradicting predictions of an attentional explanation of the knowledge effect. The results of Experiment 6 suggested that subjects attempt to link even rote features to their knowledge.     

Using segmentation to support the learning from animated soccer scenes: An effect of prior knowledge

ObjectivesWe used a cognitive load perspective to investigate the effects of levels of learner expertise and different forms of segmentation in learning from animated soccer scenes.MethodExpert and novice players (N = 48) completed a recall reconstruction-test and rated their invested mental effort after studying a continuous animation, a macro-step and a micro-step segmented animation.ResultsFindings demonstrated an expertise reversal effect for segmentation. It positively affected learning outcomes of novices but not experts (even though they still invested less mental effort and repeated the animation less often in the two segmented conditions). Additionally, novices benefited more from micro-step segmentation than from macro-step segmentation, while experts performed at the same level with both forms of segmentation.ConclusionsStudy results suggested that adapting instructional animation formats to players with different levels of expertise should be a crucial part of successful training.     

The role of prior knowledge and curiosity in learning

Psychonomic Bulletin & Review - Recent work has argued that curiosity can improve learning. However, these studies also leave open the possibility that being on the verge of...     

Effects of prior knowledge on memory for new information

Three experiments examined the effects of prior knowledge on the learning and retention of new information. Subjects learned varying amounts of prior knowledge about individuals referred to by first name/last name combinations. In the first two experiments, subjects more rapidly learned new information about individuals for whom they were given prior knowledge, retrieved this information more slowly, and showed smaller interference (fan) effects. This complex of results is predicted by a spreading activation model in which we assume subjects try to integrate the prior knowledge with the new information in a network fashion. The third experiment, in addition to including conditions of prior vs. no prior experimental knowledge, included well-known names like Ted Kennedy, about which subjects have a great deal of preexperimental prior knowledge. The relationships between conditions of experimental prior knowledge and no prior knowledge obtained in Experiments 1 and 2 were replicated, but the well-known names did not behave simply like the extreme of experimental prior knowledge. In particular, subjects showed the fastest verification of new facts learned about the well-known names, rather than the slowest, as predicted from the spreading activation network model.     

Reading strategies and prior knowledge in learning from hypertext

In two experiments, we identified two main strategies followed by hypertext readers in selecting their reading orders. The first consisted in selecting the text semantically related to the previously read section (coherence strategy), and the second in choosing the most interesting text, delaying reading of less interesting sections (interest strategy). Comprehension data revealed that these strategies affected learning differently as a function of the reader's prior knowledge. For low-knowledge readers, the coherence strategy supported better learning of the content. This effect seems to rely on the improvement of reading order coherence induced by this strategy. By contrast, for intermediate-knowledge readers the coherence and the interest strategies benefited comprehension equally. In both cases, learning was supported through the active processing induced by these strategies. Discussion focuses on resolving inconsistencies in the literature concerning whether or not hypertext supports better comprehension than does traditional linear texts.     

The influence of prior knowledge in intentional versus incidental concept learning

Previous research has demonstrated that background knowledge has a clear influence on concept learning. This influence, however, has been observed with a narrow range of intentional learning tasks. In the present experiments, the role of background knowledge was examined as a function of a variety of incidental learning tasks as well as with intentional learning tasks. The influence of prior knowledge was investigated by comparing the encoding of conceptually related co-occurrences with the encoding of conceptually unrelated co-occurrences. A clear influence of prior knowledge was observed with incidental encoding, and conceptual relatedness was found to have at least as powerful an influence with incidental as with intentional learning tasks. The results indicate that many types of knowledge-based influences will not vary as a function of encoding strategy. The pervasiveness and strength of the influence of background knowledge on concept learning are discussed.     

Influencing prior knowledge through a short reading impacts curiosity and learning

Curiosity predicts memory performance and it is influenced by prior knowledge. Reading a well-organized text can increase curiosity in a classroom setting, however it is not clear if reading a short text written in an encyclopedic style can increase curiosity and learning without explicit educational goals. We presented participants with a short text and examined if questions related to this reading could elicit higher curiosity ratings and better recall in a thematized version of the trivia task. In the first experiment, participants subjectively judged their prior knowledge of trivia questions. The curiosity of the participants was not influenced by the reading, but the memory effect of curiosity was amplified for the questions related to it. In the second experiment, we objectively verified whether the participants knew the answers. The curiosity ratings were higher for the questions related to the reading, but only the curiosity ratings influenced recall performance. These results show that prior knowledge induced by reading can have an effect on curiosity and learning, but it depends on how this knowledge is assessed by the learner.     

Role of prior knowledge in implicit and explicit learning of artificial grammars

Artificial grammar learning (AGL) performance reflects both implicit and explicit processes and has typically been modeled without incorporating any influence from general world knowledge. Our research provides a systematic investigation of the implicit vs. explicit nature of general knowledge and its interaction with knowledge types investigated by past AGL research (i.e., rule- and similarity-based knowledge). In an AGL experiment, a general knowledge manipulation involved expectations being either congruent or incongruent with training stimulus structure. Inconsistent observations paradoxically led to an advantage in structural knowledge and in the use of general world knowledge in both explicit (conscious) and implicit (unconscious) cases (as assessed by subjective measures). The above findings were obtained under conditions of reduced processing time and impaired executive resources. Key findings from our work are that implicit AGL can clearly be affected by general knowledge, and implicit learning can be enhanced by the violation of expectations.     

Drift in children's categories: when experienced distributions conflict with prior learning

Psychological intuitions about natural category structure do not always correspond to the true structure of the world. The current study explores young children's responses to conflict between intuitive structure and authoritative feedback using a semi‐supervised learning (Zhu et al., 2007) paradigm. In three experiments, 160 children between the ages of 4 and 8 learned a one‐dimensional decision criterion for distinguishing yummy and yucky ‘alien fruits’. They then categorized a large number of new fruits without corrective feedback. The distribution of the new fruits was manipulated such that the natural boundary in the stimuli did not always correspond to the learned boundary. Children changed their decision criteria to reflect the structure of the new stimuli, effectively unlearning the original boundary. Younger children were especially swayed by the distributional information, being relatively insensitive to feedback that the original non‐natural boundary was, in fact, still correct. Results are discussed in terms of children's ability to selectively attend to specific information (i.e. feedback vs. distribution), and their interests in forming generally useful representations of experience.     

Modeling the effects of prior knowledge on learning incongruent features of category members

The authors conducted 3 experiments addressing the issue of how observations and multiple sources of prior knowledge are put together in category learning. In Experiments 1 and 2, learning was faster for critical features, which were predictable on the basis of prior knowledge, than for filler features, and this advantage increased as more observations were made. In addition, learning was fastest for incongruent features that could only be predicted using knowledge from other domains. In Experiment 3, presenting contradictory features that violated prior knowledge led to rote learning rather than use of prior knowledge. The results were simulated with the Baywatch model, which addresses how observations of category members lead to recruitment and selection of sources of prior knowledge.     

Putting together prior knowledge, verbal arguments, and observations in category learning

Two experiments addressed the novel issue of how people incorporate verbal arguments into category learning. In Experiment 1, at the start of learning, subjects were given verbal arguments, which had an influence equivalent to a fixed number of category members. In Experiment 2, subjects learned under slower paced conditions, and it was found that both prior knowledge and arguments had multiple effects on categorization: a fixed initial influence plus selective weighting of new observations. The results supported the idea that verbally presented arguments can be treated in a similar manner as other forms of prior knowledge, from the perspective of applying models of categorization.     

How prior knowledge affects selective attention during category learning: An eyetracking study

Research has shown that category learning is affected by (a) attention, which selects which aspects of stimuli are available for further processing, and (b) the existing semantic knowledge that learners bring to the task. However, little is known about how knowledge affects what is attended. Using eyetracking, we found that (a) knowledge indeed changes what features are attended, with knowledge-relevant features being fixated more often than irrelevant ones, (b) this effect was not due to an initial attentional bias toward relevant dimensions but rather emerged gradually as a result of observing category members, and (c) this effect grew even after a learning criterion was reached, that is, despite the absence of negative feedback. We argue that models of knowledge-based learning will remain incomplete until they specify mechanisms that dynamically select prior knowledge in response to observed category members and which then directs attention to knowledge-relevant dimensions and away from irrelevant ones.     

Eye movements reveal solution knowledge prior to insight

In two experiments, participants solved anagram problems while their eye movements were monitored. Each problem consisted of a circular array of five letters: a scrambled four-letter solution word containing three consonants and one vowel, and an additional randomly-placed distractor consonant. Viewing times on the distractor consonant compared to the solution consonants provided an online measure of knowledge of the solution. Viewing times on the distractor consonant and the solution consonants were indistinguishable early in the trial. In contrast, several seconds prior to the response, viewing times on the distractor consonant decreased in a gradual manner compared to viewing times on the solution consonants. Importantly, this pattern was obtained across both trials in which participants reported the subjective experience of insight and trials in which they did not. These findings are consistent with the availability of partial knowledge of the solution prior to such information being accessible to subjective phenomenal awareness.     

Spatial interference and response control in sequence learning: the role of explicit knowledge

In several sequence learning studies it has been suggested that response control shifts from the stimuli to some internal representation (i.e., motor program) through the learning process. The main questions addressed in this paper are whether this control shift is related to explicit knowledge and whether the formation of these internal representations depends on the stimulus attributes. In one experiment we compared the learning of a response sequence triggered by either spatial location or location symbol (left-right) by using a serial response task (SRT). Symbols were presented at either a centered or random location. The results showed that in the symbolic conditions the shift of response control correlated with the emergence of explicit knowledge. Only participants with complete explicit knowledge seemed to learn the sequence structure beyond probabilistic information (response time "RT" did not depend on the frequency of the response). Moreover, these participants were able to overcome, when needed, spatial interference (RT was the same for both spatially corresponding and non-corresponding trials). However, when spatial location was relevant, RT was always faster, especially for more frequent responses. These results suggest that the relevant stimulus dimension (location or symbol) seems to engage different sequence learning mechanisms.     

Algorithms for detecting concealed knowledge among groups when the critical information is unavailable

We examined whether the Concealed Information Test (CIT) may be used when the critical details are unavailable to investigators (the Searching CIT [SCIT]). This use may have important applications in criminal investigations (e.g., finding the location of a murder weapon) and in security-related threats (e.g., detecting individuals and groups suspected in planning a terror attack). Two classes of algorithms designed to detect the critical items and classify individuals in the SCIT were examined. The 1st class was based on averaging responses across subjects to identify critical items and on averaging responses across the identified critical items to identify knowledgeable subjects. The 2nd class used clustering methods based on the correlations between the response profiles of all subject pairs. We applied a principal component analysis to decompose the correlation matrix into its principal components and defined the detection score as the coefficient of each subject on the component that explained the largest portion of the variance. Reanalysis of 3 data sets from previous CIT studies demonstrated that in most cases the efficiency of differentiation between knowledgeable and unknowledgeable subjects in the SCIT (indexed by the area under the receiver operating characteristic curve) approached that of the standard CIT for both algorithms. We also examined the robustness of our results to variations in the number of knowledgeable and unknowledgeable subjects in the sample. This analysis demonstrated that the performance of our algorithms is relatively robust to changes in the number of individuals examined in each group, provided that at least 2 (but desirably 5 or more) knowledgeable examinees are included. (PsycINFO Database Record (c) 2012 APA, all rights reserved).     

Knowing in advance: the impact of prior event information on memory and event knowledge

We examined the influence of newly acquired information on children's memory and general representation of a personally experienced event. Thirty-five children between the ages of 5 and 7 years participated in the novel event (Visiting the Pirate). The day before participating, children were: (1) provided with new information specific to the up-coming event; (2) engaged in a discussion generally related to the event topic based on existing knowledge; or (3) discussed an unrelated topic. Advance information specific to the event led to better recall and, in particular, to better integration of the experience into a general event representation both soon after the event and at a follow-up interview 4 months later, whereas general discussion of the topic without the event specific information neither enhanced memory reports nor facilitated the integration of event information. Providing information in advance can have significant effects on memory and knowledge acquisition although many variables, including those relating to the specific content of the information, will affect this relation.