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Sample records for abstract rule learning

  1. Sequential learning and rule abstraction in Bengalese finches.

    PubMed

    Yamazaki, Yumiko; Suzuki, Kenta; Inada, Masayuki; Iriki, Atsushi; Okanoya, Kazuo

    2012-05-01

    The Bengalese finch (Lonchura striata var. domestica) is a species of songbird. Males sing courtship songs with complex note-to-note transition rules, while females discriminate these songs when choosing their mate. The present study uses serial reaction time (RT) to examine the characteristics of the Bengalese finches' sequential behaviours beyond song production. The birds were trained to produce the sequence with an "A-B-A" structure. After the RT to each key position was determined to be stable, we tested the acquisition of the trained sequential response by presenting novel and random three-term sequences (random test). We also examined whether they could abstract the embedded rule in the trained sequence and apply it to the novel test sequence (abstract test). Additionally, we examined rule abstraction through example training by increasing the number of examples in baseline training from 1 to 5. When considered as (gender) groups, training with 5 examples resulted in no statistically significant differences in the abstract tests, while statistically significant differences were observed in the random tests, suggesting that the male birds learned the trained sequences and transferred the abstract structure they had learned during the training trials. Individual data indicated that males, as opposed to females, were likely to learn the motor pattern of the sequence. The results are consistent with observations that males learn to produce songs with complex sequential rules, whereas females do not.

  2. Neural Correlates of Abstract Rule Learning: An Event-Related Potential Study

    ERIC Educational Resources Information Center

    Sun, Fang; Hoshi-Shiba, Reiko; Abla, Dilshat; Okanoya, Kazuo

    2012-01-01

    Abstract rule learning is a fundamental aspect of human cognition, and is essential for language acquisition. However, despite its importance, the neural mechanisms underlying abstract rule learning are still largely unclear. In this study, we investigated the neural correlates of abstract rule learning by recording auditory event-related…

  3. Communicative signals support abstract rule learning by 7-month-old infants

    PubMed Central

    Ferguson, Brock; Lew-Williams, Casey

    2016-01-01

    The mechanisms underlying the discovery of abstract rules like those found in natural language may be evolutionarily tuned to speech, according to previous research. When infants hear speech sounds, they can learn rules that govern their combination, but when they hear non-speech sounds such as sine-wave tones, they fail to do so. Here we show that infants’ rule learning is not tied to speech per se, but is instead enhanced more broadly by communicative signals. In two experiments, infants succeeded in learning and generalizing rules from tones that were introduced as if they could be used to communicate. In two control experiments, infants failed to learn the very same rules when familiarized to tones outside of a communicative exchange. These results reveal that infants’ attention to social agents and communication catalyzes a fundamental achievement of human learning. PMID:27150270

  4. Abstract rule learning: the differential effects of lesions in frontal cortex.

    PubMed

    Kayser, Andrew S; D'Esposito, Mark

    2013-01-01

    Learning progressively more abstract stimulus-response mappings requires progressively more anterior regions of the lateral frontal cortex. Using an individual differences approach, we studied subjects with frontal lesions performing a hierarchical reinforcement-learning task to investigate how frontal cortex contributes to abstract rule learning. We predicted that subjects with lesions of the left pre-premotor (pre-PMd) cortex, a region implicated in abstract rule learning, would demonstrate impaired acquisition of second-order, as opposed to first-order, rules. We found that 4 subjects with such lesions did indeed demonstrate a second-order rule-learning impairment, but that these subjects nonetheless performed better than subjects with other frontal lesions in a second-order rule condition. This finding resulted from both their restricted exploration of the feature space and the task structure of this condition, for which they identified partially representative first-order rules. Significantly, across all subjects, suboptimal but above-chance performance in this condition correlated with increasing disconnection of left pre-PMd from the putative functional hierarchy, defined by reduced functional connectivity between left pre-PMd and adjacent nodes. These findings support the theory that activity within lateral frontal cortex shapes the search for relevant stimulus-response mappings, while emphasizing that the behavioral correlate of impairments depends critically on task structure.

  5. Bimodal emotion congruency is critical to preverbal infants' abstract rule learning.

    PubMed

    Tsui, Angeline Sin Mei; Ma, Yuen Ki; Ho, Anna; Chow, Hiu Mei; Tseng, Chia-huei

    2016-05-01

    Extracting general rules from specific examples is important, as we must face the same challenge displayed in various formats. Previous studies have found that bimodal presentation of grammar-like rules (e.g. ABA) enhanced 5-month-olds' capacity to acquire a rule that infants failed to learn when the rule was presented with visual presentation of the shapes alone (circle-triangle-circle) or auditory presentation of the syllables (la-ba-la) alone. However, the mechanisms and constraints for this bimodal learning facilitation are still unknown. In this study, we used audio-visual relation congruency between bimodal stimulation to disentangle possible facilitation sources. We exposed 8- to 10-month-old infants to an AAB sequence consisting of visual faces with affective expressions and/or auditory voices conveying emotions. Our results showed that infants were able to distinguish the learned AAB rule from other novel rules under bimodal stimulation when the affects in audio and visual stimuli were congruently paired (Experiments 1A and 2A). Infants failed to acquire the same rule when audio-visual stimuli were incongruently matched (Experiment 2B) and when only the visual (Experiment 1B) or the audio (Experiment 1C) stimuli were presented. Our results highlight that bimodal facilitation in infant rule learning is not only dependent on better statistical probability and redundant sensory information, but also the relational congruency of audio-visual information. A video abstract of this article can be viewed at https://m.youtube.com/watch?v=KYTyjH1k9RQ.

  6. Bimodal Emotion Congruency Is Critical to Preverbal Infants' Abstract Rule Learning

    ERIC Educational Resources Information Center

    Tsui, Angeline Sin Mei; Ma, Yuen Ki; Ho, Anna; Chow, Hiu Mei; Tseng, Chia-huei

    2016-01-01

    Extracting general rules from specific examples is important, as we must face the same challenge displayed in various formats. Previous studies have found that bimodal presentation of grammar-like rules (e.g. ABA) enhanced 5-month-olds' capacity to acquire a rule that infants failed to learn when the rule was presented with visual presentation of…

  7. Category learning strategies in younger and older adults: Rule abstraction and memorization.

    PubMed

    Wahlheim, Christopher N; McDaniel, Mark A; Little, Jeri L

    2016-06-01

    Despite the fundamental role of category learning in cognition, few studies have examined how this ability differs between younger and older adults. The present experiment examined possible age differences in category learning strategies and their effects on learning. Participants were trained on a category determined by a disjunctive rule applied to relational features. The utilization of rule- and exemplar-based strategies was indexed by self-reports and transfer performance. Based on self-reported strategies, the frequencies of rule- and exemplar-based learners were not significantly different between age groups, but there was a significantly higher frequency of intermediate learners (i.e., learners not identifying with a reliance on either rule- or exemplar-based strategies) in the older than younger adult group. Training performance was higher for younger than older adults regardless of the strategy utilized, showing that older adults were impaired in their ability to learn the correct rule or to remember exemplar-label associations. Transfer performance converged with strategy reports in showing higher fidelity category representations for younger adults. Younger adults with high working memory capacity were more likely to use an exemplar-based strategy, and older adults with high working memory capacity showed better training performance. Age groups did not differ in their self-reported memory beliefs, and these beliefs did not predict training strategies or performance. Overall, the present results contradict earlier findings that older adults prefer rule- to exemplar-based learning strategies, presumably to compensate for memory deficits. (PsycINFO Database Record

  8. Abstract Rule Learning in 11- and 14-Month-Old Infants

    ERIC Educational Resources Information Center

    Koulaguina, Elena; Shi, Rushen

    2013-01-01

    This study tests the hypothesis that distributional information can guide infants in the generalization of word order movement rules at the initial stage of language acquisition. Participants were 11- and 14-month-old infants. Stimuli were sentences in Russian, a language that was unknown to our infants. During training the word order of each…

  9. Beyond learning fixed rules and social cues: abstraction in the social arena.

    PubMed Central

    Call, Joseph

    2003-01-01

    Abstraction is a central idea in many areas of physical comparative cognition such as categorization, numerical competence or problem solving. This idea, however, has rarely been applied to comparative social cognition. In this paper, I propose that the notion of abstraction can be applied to the social arena and become an important tool to investigate the social cognition and behaviour processes in animals. To make this point, I present recent evidence showing that chimpanzees know about what others can see and about what others intend. These data do not fit either low-level mechanisms based on stimulus-response associations or high-level explanations based on metarepresentational mechanisms such as false belief attribution. Instead, I argue that social abstraction, in particular the development of concepts such as seeing in others, is key to explaining the behaviour of our closest relative in a variety of situations. PMID:12903652

  10. Learning Abstracts, 1999.

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    League for Innovation in the Community Coll.

    This document contains volume two of Learning Abstracts, a bimonthly newsletter from the League for Innovation in the Community College. Articles in these seven issues include: (1) "Get on the Fast Track to Learning: An Accelerated Associate Degree Option" (Gerardo E. de los Santos and Deborah J. Cruise); (2) "The Learning College:…

  11. Sticky Rules: Integration Between Abstract Rules and Specific Actions

    ERIC Educational Resources Information Center

    Mayr, Ulrich; Bryck, Richard L.

    2005-01-01

    The authors manipulated repetitions and/or changes of abstract response rules and the specific stimulus- response (S-R) associations used under these rules. Experiments 1 and 2, assessing trial-to-trial priming effects, showed that repetition of complete S-R couplings produced only benefits when the rule also repeated (i.e., rule-S-R conjunctions)…

  12. A Bayesian Theory of Sequential Causal Learning and Abstract Transfer.

    PubMed

    Lu, Hongjing; Rojas, Randall R; Beckers, Tom; Yuille, Alan L

    2016-03-01

    Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about abstract causal constraints? Recent empirical studies have revealed that experience with one set of causal cues can dramatically alter subsequent learning and performance with entirely different cues, suggesting that learning involves abstract transfer, and such transfer effects involve sequential presentation of distinct sets of causal cues. It has been demonstrated that pre-training (or even post-training) can modulate classic causal learning phenomena such as forward and backward blocking. To account for these effects, we propose a Bayesian theory of sequential causal learning. The theory assumes that humans are able to consider and use several alternative causal generative models, each instantiating a different causal integration rule. Model selection is used to decide which integration rule to use in a given learning environment in order to infer causal knowledge from sequential data. Detailed computer simulations demonstrate that humans rely on the abstract characteristics of outcome variables (e.g., binary vs. continuous) to select a causal integration rule, which in turn alters causal learning in a variety of blocking and overshadowing paradigms. When the nature of the outcome variable is ambiguous, humans select the model that yields the best fit with the recent environment, and then apply it to subsequent learning tasks. Based on sequential patterns of cue-outcome co-occurrence, the theory can account for a range of phenomena in sequential causal learning, including various blocking effects, primacy effects in some experimental conditions, and apparently abstract transfer of causal knowledge.

  13. Rapid transfer of abstract rules to novel contexts in human lateral prefrontal cortex.

    PubMed

    Cole, Michael W; Etzel, Joset A; Zacks, Jeffrey M; Schneider, Walter; Braver, Todd S

    2011-01-01

    Flexible, adaptive behavior is thought to rely on abstract rule representations within lateral prefrontal cortex (LPFC), yet it remains unclear how these representations provide such flexibility. We recently demonstrated that humans can learn complex novel tasks in seconds. Here we hypothesized that this impressive mental flexibility may be possible due to rapid transfer of practiced rule representations within LPFC to novel task contexts. We tested this hypothesis using functional MRI and multivariate pattern analysis, classifying LPFC activity patterns across 64 tasks. Classifiers trained to identify abstract rules based on practiced task activity patterns successfully generalized to novel tasks. This suggests humans can transfer practiced rule representations within LPFC to rapidly learn new tasks, facilitating cognitive performance in novel circumstances.

  14. Rapid Transfer of Abstract Rules to Novel Contexts in Human Lateral Prefrontal Cortex

    PubMed Central

    Cole, Michael W.; Etzel, Joset A.; Zacks, Jeffrey M.; Schneider, Walter; Braver, Todd S.

    2011-01-01

    Flexible, adaptive behavior is thought to rely on abstract rule representations within lateral prefrontal cortex (LPFC), yet it remains unclear how these representations provide such flexibility. We recently demonstrated that humans can learn complex novel tasks in seconds. Here we hypothesized that this impressive mental flexibility may be possible due to rapid transfer of practiced rule representations within LPFC to novel task contexts. We tested this hypothesis using functional MRI and multivariate pattern analysis, classifying LPFC activity patterns across 64 tasks. Classifiers trained to identify abstract rules based on practiced task activity patterns successfully generalized to novel tasks. This suggests humans can transfer practiced rule representations within LPFC to rapidly learn new tasks, facilitating cognitive performance in novel circumstances. PMID:22125519

  15. Automata Learning with Automated Alphabet Abstraction Refinement

    NASA Astrophysics Data System (ADS)

    Howar, Falk; Steffen, Bernhard; Merten, Maik

    on is the key when learning behavioral models of realistic systems, but also the cause of a major problem: the introduction of non-determinism. In this paper, we introduce a method for refining a given abstraction to automatically regain a deterministic behavior on-the-fly during the learning process. Thus the control over abstraction becomes part of the learning process, with the effect that detected non-determinism does not lead to failure, but to a dynamic alphabet abstraction refinement. Like automata learning itself, this method in general is neither sound nor complete, but it also enjoys similar convergence properties even for infinite systems as long as the concrete system itself behaves deterministically, as illustrated along a concrete example.

  16. Sleep facilitates learning a new linguistic rule

    PubMed Central

    Batterink, Laura J.; Oudiette, Delphine; Reber, Paul J.; Paller, Ken A.

    2014-01-01

    Natural languages contain countless regularities. Extraction of these patterns is an essential component of language acquisition. Here we examined the hypothesis that memory processing during sleep contributes to this learning. We exposed participants to a hidden linguistic rule by presenting a large number of two-word phrases, each including a noun preceded by one of four novel words that functioned as an article (e.g., gi rhino). These novel words (ul, gi, ro and ne) were presented as obeying an explicit rule: two words signified that the noun referent was relatively near, and two that it was relatively far. Undisclosed to participants was the fact that the novel articles also predicted noun animacy, with two of the articles preceding animate referents and the other two preceding inanimate referents. Rule acquisition was tested implicitly using a task in which participants responded to each phrase according to whether the noun was animate or inanimate. Learning of the hidden rule was evident in slower responses to phrases that violated the rule. Responses were delayed regardless of whether rule-knowledge was consciously accessible. Brain potentials provided additional confirmation of implicit and explicit rule-knowledge. An afternoon nap was interposed between two 20-min learning sessions. Participants who obtained greater amounts of both slow-wave and rapid-eye-movement sleep showed increased sensitivity to the hidden linguistic rule in the second session. We conclude that during sleep, reactivation of linguistic information linked with the rule was instrumental for stabilizing learning. The combination of slow-wave and rapid-eye-movement sleep may synergistically facilitate the abstraction of complex patterns in linguistic input. PMID:25447376

  17. Sleep facilitates learning a new linguistic rule.

    PubMed

    Batterink, Laura J; Oudiette, Delphine; Reber, Paul J; Paller, Ken A

    2014-12-01

    Natural languages contain countless regularities. Extraction of these patterns is an essential component of language acquisition. Here we examined the hypothesis that memory processing during sleep contributes to this learning. We exposed participants to a hidden linguistic rule by presenting a large number of two-word phrases, each including a noun preceded by one of four novel words that functioned as an article (e.g., gi rhino). These novel words (ul, gi, ro and ne) were presented as obeying an explicit rule: two words signified that the noun referent was relatively near, and two that it was relatively far. Undisclosed to participants was the fact that the novel articles also predicted noun animacy, with two of the articles preceding animate referents and the other two preceding inanimate referents. Rule acquisition was tested implicitly using a task in which participants responded to each phrase according to whether the noun was animate or inanimate. Learning of the hidden rule was evident in slower responses to phrases that violated the rule. Responses were delayed regardless of whether rule-knowledge was consciously accessible. Brain potentials provided additional confirmation of implicit and explicit rule-knowledge. An afternoon nap was interposed between two 20-min learning sessions. Participants who obtained greater amounts of both slow-wave and rapid-eye-movement sleep showed increased sensitivity to the hidden linguistic rule in the second session. We conclude that during sleep, reactivation of linguistic information linked with the rule was instrumental for stabilizing learning. The combination of slow-wave and rapid-eye-movement sleep may synergistically facilitate the abstraction of complex patterns in linguistic input.

  18. Rule learning by zebra finches in an artificial grammar learning task: which rule?

    PubMed

    van Heijningen, Caroline A A; Chen, Jiani; van Laatum, Irene; van der Hulst, Bonnie; ten Cate, Carel

    2013-03-01

    A hallmark of the human language faculty is the use of syntactic rules. The natural vocalizations of animals are syntactically simple, but several studies indicate that animals can detect and discriminate more complex structures in acoustic stimuli. However, how they discriminate such structures is often not clear. Using an artificial grammar learning paradigm, zebra finches were tested in a Go/No-go experiment for their ability to distinguish structurally different three-element sound sequences. In Experiment 1, zebra finches learned to discriminate ABA and BAB from ABB, AAB, BBA, and ABB sequences. Tests with probe sounds consisting of four elements suggested that the discrimination was based on attending to the presence or absence of repeated A- and B-elements. One bird generalized the discrimination to a new element type. In Experiment 2, we continued the training by adding four-element songs following a 'first and last identical versus different' rule that could not be solved by attending to repetitions. Only two out of five birds learned the overall discrimination. Testing with novel probes demonstrated that discrimination was not based on using the 'first and last identical' rule, but on attending to the presence or absence of the individual training stimuli. The two birds differed in the strategies used. Our results thus demonstrate only a limited degree of abstract rule learning but highlight the need for extensive and critical probe testing to examine the rules that animals (and humans) use to solve artificial grammar learning tasks. They also underline that rule learning strategies may differ between individuals.

  19. a Heterosynaptic Learning Rule for Neural Networks

    NASA Astrophysics Data System (ADS)

    Emmert-Streib, Frank

    In this article we introduce a novel stochastic Hebb-like learning rule for neural networks that is neurobiologically motivated. This learning rule combines features of unsupervised (Hebbian) and supervised (reinforcement) learning and is stochastic with respect to the selection of the time points when a synapse is modified. Moreover, the learning rule does not only affect the synapse between pre- and postsynaptic neuron, which is called homosynaptic plasticity, but effects also further remote synapses of the pre- and postsynaptic neuron. This more complex form of synaptic plasticity has recently come under investigations in neurobiology and is called heterosynaptic plasticity. We demonstrate that this learning rule is useful in training neural networks by learning parity functions including the exclusive-or (XOR) mapping in a multilayer feed-forward network. We find, that our stochastic learning rule works well, even in the presence of noise. Importantly, the mean learning time increases with the number of patterns to be learned polynomially, indicating efficient learning.

  20. Myths and legends in learning classification rules

    NASA Technical Reports Server (NTRS)

    Buntine, Wray

    1990-01-01

    A discussion is presented of machine learning theory on empirically learning classification rules. Six myths are proposed in the machine learning community that address issues of bias, learning as search, computational learning theory, Occam's razor, universal learning algorithms, and interactive learning. Some of the problems raised are also addressed from a Bayesian perspective. Questions are suggested that machine learning researchers should be addressing both theoretically and experimentally.

  1. Myths and legends in learning classification rules

    NASA Technical Reports Server (NTRS)

    Buntine, Wray

    1990-01-01

    This paper is a discussion of machine learning theory on empirically learning classification rules. The paper proposes six myths in the machine learning community that address issues of bias, learning as search, computational learning theory, Occam's razor, 'universal' learning algorithms, and interactive learnings. Some of the problems raised are also addressed from a Bayesian perspective. The paper concludes by suggesting questions that machine learning researchers should be addressing both theoretically and experimentally.

  2. Different ERP profiles for learning rules over consonants and vowels.

    PubMed

    Monte-Ordoño, Júlia; Toro, Juan M

    2017-03-01

    The Consonant-Vowel hypothesis suggests that consonants and vowels tend to be used differently during language processing. In this study we explored whether these functional differences trigger different neural responses in a rule learning task. We recorded ERPs while nonsense words were presented in an Oddball paradigm. An ABB rule was implemented either over the consonants (Consonant condition) or over the vowels (Vowel condition) composing standard words. Deviant stimuli were composed by novel phonemes. Deviants could either implement the same ABB rule as standards (Phoneme deviants) or implement a different ABA rule (Rule deviants). We observed shared early components (P1 and MMN) for both types of deviants across both conditions. We also observed differences across conditions around 400ms. In the Consonant condition, Phoneme deviants triggered a posterior negativity. In the Vowel condition, Rule deviants triggered an anterior negativity. Such responses demonstrate different neural responses after the violation of abstract rules over distinct phonetic categories.

  3. Fronting, Rule Loss and Abstractness in Old English Phonology.

    ERIC Educational Resources Information Center

    Shannon, Thomas F.

    An analysis of Old English phonology examines two traditional sound changes, the First and Second Frontings, that have been analyzed by different linguists with rather abstract theories. These analyses are refuted, and a more concrete and realistic treatment is proposed for each. Examination of Anglo-Frisian Brightening, or First Fronting, raises…

  4. Representation of abstract quantitative rules applied to spatial and numerical magnitudes in primate prefrontal cortex.

    PubMed

    Eiselt, Anne-Kathrin; Nieder, Andreas

    2013-04-24

    Processing quantity information based on abstract principles is central to intelligent behavior. Neural correlates of quantitative rule selectivity have been identified previously in the prefrontal cortex (PFC). However, whether individual neurons represent rules applied to multiple magnitude types is unknown. We recorded from PFC neurons while monkeys switched between "greater than/less than" rules applied to spatial and numerical magnitudes. A majority of rule-selective neurons responded only to the quantitative rules applied to one specific magnitude type. However, another population of neurons generalized the magnitude principle and represented the quantitative rules related to both magnitudes. This indicates that the primate brain uses rule-selective neurons specialized in guiding decisions related to a specific magnitude type only, as well as generalizing neurons that respond abstractly to the overarching concept "magnitude rules."

  5. Learning rules and persistence of dendritic spines.

    PubMed

    Kasai, Haruo; Hayama, Tatsuya; Ishikawa, Motoko; Watanabe, Satoshi; Yagishita, Sho; Noguchi, Jun

    2010-07-01

    Structural plasticity of dendritic spines underlies learning, memory and cognition in the cerebral cortex. We here summarize fifteen rules of spine structural plasticity, or 'spine learning rules.' Together, they suggest how the spontaneous generation, selection and strengthening (SGSS) of spines represents the physical basis for learning and memory. This SGSS mechanism is consistent with Hebb's learning rule but suggests new relations between synaptic plasticity and memory. We describe the cellular and molecular bases of the spine learning rules, such as the persistence of spine structures and the fundamental role of actin, which polymerizes to form a 'memory gel' required for the selection and strengthening of spine synapses. We also discuss the possible link between transcriptional and translational regulation of structural plasticity. The SGSS mechanism and spine learning rules elucidate the integral nature of synaptic plasticity in neuronal network operations within the actual brain tissue.

  6. Reflective Abstraction and Mathematics Education: The Genetic Decomposition of the Chain Rule--Work in Progress

    ERIC Educational Resources Information Center

    Jojo, Zingiswa Monica Mybert; Maharaj, Aneshkumar; Brijlall, Deonarain

    2012-01-01

    Students have experienced difficulty in understanding and using the chain rule. This study aims at assisting the students to understand and apply the chain rule and thus inform the author's teaching for future learning of students. A questionnaire will be designed to explore the conceptual understanding of the concept of the chain rule by first…

  7. Implicit learning of a recursive rule in an artificial grammar.

    PubMed

    Poletiek, Fenna H

    2002-11-01

    Participants performed an artificial grammar learning task, in which the standard finite state grammar (J. Verb. Learn. Verb. Behavior 6 (1967) 855) was extended with a recursive rule generating self-embedded sequences. We studied the learnability of such a rule in two experiments. The results verify the general hypothesis that recursivity can be learned in an artificial grammar learning task. However this learning seems to be rather based on recognising chunks than on abstract rule induction. First, performance was better for strings with more than one level of self-embedding in the sequence, uncovering more clearly the self-embedding pattern. Second, the infinite repeatability of the recursive rule application was not spontaneously induced from the training, but it was when an additional cue about this possibility was given. Finally, participants were able to verbalise their knowledge of the fragments making up the sequences-especially in the crucial front and back positions-, whereas knowledge of the underlying structure, to the extent it was acquired, was not articulatable. The results are discussed in relation to previous studies on the implicit learnability of complex and abstract rules.

  8. Effects of Abstract and Concrete Simulation Elements on Science Learning

    ERIC Educational Resources Information Center

    Jaakkola, T.; Veermans, K.

    2015-01-01

    Contemporary evidence on the effectiveness of concrete and abstract representations in science education is based solely on studies conducted in college context. There it has been found that learning with abstract representations produces predominantly better outcomes than learning with concrete representations and combining the representations…

  9. Reducing Abstraction When Learning Graph Theory

    ERIC Educational Resources Information Center

    Hazzan, Orit; Hadar, Irit

    2005-01-01

    This article presents research on students' understanding of basic concepts in Graph Theory. Students' understanding is analyzed through the lens of the theoretical framework of reducing abstraction (Hazzan, 1999). As it turns out, in spite of the relative simplicity of the concepts that are introduced in the introductory part of a traditional…

  10. A Bayesian Theory of Sequential Causal Learning and Abstract Transfer

    ERIC Educational Resources Information Center

    Lu, Hongjing; Rojas, Randall R.; Beckers, Tom; Yuille, Alan L.

    2016-01-01

    Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about…

  11. Effects of Variation and Prior Knowledge on Abstract Concept Learning

    ERIC Educational Resources Information Center

    Braithwaite, David W.; Goldstone, Robert L.

    2015-01-01

    Learning abstract concepts through concrete examples may promote learning at the cost of inhibiting transfer. The present study investigated one approach to solving this problem: systematically varying superficial features of the examples. Participants learned to solve problems involving a mathematical concept by studying either superficially…

  12. Refining Linear Fuzzy Rules by Reinforcement Learning

    NASA Technical Reports Server (NTRS)

    Berenji, Hamid R.; Khedkar, Pratap S.; Malkani, Anil

    1996-01-01

    Linear fuzzy rules are increasingly being used in the development of fuzzy logic systems. Radial basis functions have also been used in the antecedents of the rules for clustering in product space which can automatically generate a set of linear fuzzy rules from an input/output data set. Manual methods are usually used in refining these rules. This paper presents a method for refining the parameters of these rules using reinforcement learning which can be applied in domains where supervised input-output data is not available and reinforcements are received only after a long sequence of actions. This is shown for a generalization of radial basis functions. The formation of fuzzy rules from data and their automatic refinement is an important step in closing the gap between the application of reinforcement learning methods in the domains where only some limited input-output data is available.

  13. Learning with LOGO: Abstracts from the LOGO '84 Conference.

    ERIC Educational Resources Information Center

    Estes, Yvonne

    1984-01-01

    Presents abstracts of three papers given at the first national LOGO conference. They are: "LOGO as an Empirical Window" (Sylvia Weir); "Quasi-Piagetian Learning in LOGO" (Uri Leron); and "Theories of LOGO" (Guy Groen). (JN)

  14. The acquisition of allophonic rules: statistical learning with linguistic constraints.

    PubMed

    Peperkamp, Sharon; Le Calvez, Rozenn; Nadal, Jean-Pierre; Dupoux, Emmanuel

    2006-10-01

    Phonological rules relate surface phonetic word forms to abstract underlying forms that are stored in the lexicon. Infants must thus acquire these rules in order to infer the abstract representation of words. We implement a statistical learning algorithm for the acquisition of one type of rule, namely allophony, which introduces context-sensitive phonetic variants of phonemes. This algorithm is based on the observation that different realizations of a single phoneme typically do not appear in the same contexts (ideally, they have complementary distributions). In particular, it measures the discrepancies in context probabilities for each pair of phonetic segments. In Experiment 1, we test the algorithm's performances on a pseudo-language and show that it is robust to statistical noise due to sampling and coding errors, and to non-systematic rule application. In Experiment 2, we show that a natural corpus of semiphonetically transcribed child-directed speech in French presents a very large number of near-complementary distributions that do not correspond to existing allophonic rules. These spurious allophonic rules can be eliminated by a linguistically motivated filtering mechanism based on a phonetic representation of segments. We discuss the role of a priori linguistic knowledge in the statistical learning of phonology.

  15. Harder Words: Learning Abstract Verbs with Opaque Syntax

    ERIC Educational Resources Information Center

    Becker, Misha; Estigarribia, Bruno

    2013-01-01

    Highly abstract predicates (e.g. "think") present a number of difficulties for language learners (Gleitman et al., 2005). A partial solution to learning these verbs is that learners exploit regularities in the syntactic frames in which these verbs occur. While agreeing with this general approach to learning verbs, we caution that this…

  16. Abstract rule neurons in the endbrain support intelligent behaviour in corvid songbirds.

    PubMed

    Veit, Lena; Nieder, Andreas

    2013-01-01

    Despite the lack of a layered neocortex and fundamental differences in endbrain organization in birds compared with mammals, intelligent species evolved from both vertebrate classes. Among birds, corvids show exceptional cognitive flexibility. Here we explore the neuronal foundation of corvid cognition by recording single-unit activity from an association area known as the nidopallium caudolaterale (NCL) while carrion crows make flexible rule-guided decisions, a hallmark of executive control functions. The most prevalent activity in NCL represents the behavioural rules, while abstracting over sample images and sensory modalities of the rule cues. Rule coding is weaker in error trials, thus predicting the crows' behavioural decisions. This suggests that the abstraction of general principles may be an important function of the NCL, mirroring the function of primate prefrontal cortex. These findings emphasize that intelligence in vertebrates does not necessarily rely on a neocortex but can be realized in endbrain circuitries that developed independently via convergent evolution.

  17. Phonological Memory and Rule Learning

    ERIC Educational Resources Information Center

    Williams, John N.; Lovatt, Peter

    2005-01-01

    Our research reflects the current trend to relate individual differences in second language learning to underlying cognitive processes e.g., Robinson, 2002. We believe that such investigations, apart from being of practical importance, can also shed light on the cognitive mechanisms underlying the language learning process. Here we focus on the…

  18. Concrete-Semiconcrete-Abstract (CSA) Instruction: A Decision Rule for Improving Instructional Efficacy

    ERIC Educational Resources Information Center

    Sealander, Karen A.; Johnson, Gae R.; Lockwood, Adam B.; Medina, Catherine M.

    2012-01-01

    A concrete-semiconcrete-abstract (CSA) instructional approach derived from discovery learning (DIS) was embedded in a direct instruction (DI) methodology to teach eight elementary students with math disabilities. One-minute abstract-level probes were the primary metric used to assess student performance on subtraction problems (minuends 0-9). A…

  19. Grounded understanding of abstract concepts: The case of STEM learning.

    PubMed

    Hayes, Justin C; Kraemer, David J M

    2017-01-01

    Characterizing the neural implementation of abstract conceptual representations has long been a contentious topic in cognitive science. At the heart of the debate is whether the "sensorimotor" machinery of the brain plays a central role in representing concepts, or whether the involvement of these perceptual and motor regions is merely peripheral or epiphenomenal. The domain of science, technology, engineering, and mathematics (STEM) learning provides an important proving ground for sensorimotor (or grounded) theories of cognition, as concepts in science and engineering courses are often taught through laboratory-based and other hands-on methodologies. In this review of the literature, we examine evidence suggesting that sensorimotor processes strengthen learning associated with the abstract concepts central to STEM pedagogy. After considering how contemporary theories have defined abstraction in the context of semantic knowledge, we propose our own explanation for how body-centered information, as computed in sensorimotor brain regions and visuomotor association cortex, can form a useful foundation upon which to build an understanding of abstract scientific concepts, such as mechanical force. Drawing from theories in cognitive neuroscience, we then explore models elucidating the neural mechanisms involved in grounding intangible concepts, including Hebbian learning, predictive coding, and neuronal recycling. Empirical data on STEM learning through hands-on instruction are considered in light of these neural models. We conclude the review by proposing three distinct ways in which the field of cognitive neuroscience can contribute to STEM learning by bolstering our understanding of how the brain instantiates abstract concepts in an embodied fashion.

  20. Episodes to Scripts to Rules: Concrete-Abstractions in Kindergarten Children's Explanations of a Robot's Behavior

    ERIC Educational Resources Information Center

    Mioduser, David; Levy, Sharona T.; Talis, Vadim

    2009-01-01

    This study explores young children's abstraction of the rules underlying a robot's emergent behavior. The study was conducted individually with six kindergarten children, along five sessions that included description and construction tasks, ordered by increasing difficulty. We developed and used a robotic control interface, structured as…

  1. Abstracts

    ERIC Educational Resources Information Center

    American Biology Teacher, 1977

    1977-01-01

    Included are over 50 abstracts of papers being presented at the 1977 National Association of Biology Teachers Convention. Included in each abstract are the title, author, and summary of the paper. Topics include photographic techniques environmental studies, and biological instruction. (MA)

  2. On learning dynamics underlying the evolution of learning rules.

    PubMed

    Dridi, Slimane; Lehmann, Laurent

    2014-02-01

    In order to understand the development of non-genetically encoded actions during an animal's lifespan, it is necessary to analyze the dynamics and evolution of learning rules producing behavior. Owing to the intrinsic stochastic and frequency-dependent nature of learning dynamics, these rules are often studied in evolutionary biology via agent-based computer simulations. In this paper, we show that stochastic approximation theory can help to qualitatively understand learning dynamics and formulate analytical models for the evolution of learning rules. We consider a population of individuals repeatedly interacting during their lifespan, and where the stage game faced by the individuals fluctuates according to an environmental stochastic process. Individuals adjust their behavioral actions according to learning rules belonging to the class of experience-weighted attraction learning mechanisms, which includes standard reinforcement and Bayesian learning as special cases. We use stochastic approximation theory in order to derive differential equations governing action play probabilities, which turn out to have qualitative features of mutator-selection equations. We then perform agent-based simulations to find the conditions where the deterministic approximation is closest to the original stochastic learning process for standard 2-action 2-player fluctuating games, where interaction between learning rules and preference reversal may occur. Finally, we analyze a simplified model for the evolution of learning in a producer-scrounger game, which shows that the exploration rate can interact in a non-intuitive way with other features of co-evolving learning rules. Overall, our analyses illustrate the usefulness of applying stochastic approximation theory in the study of animal learning.

  3. Active Learning-Based Pedagogical Rule Extraction.

    PubMed

    Junqué de Fortuny, Enric; Martens, David

    2015-11-01

    Many of the state-of-the-art data mining techniques introduce nonlinearities in their models to cope with complex data relationships effectively. Although such techniques are consistently included among the top classification techniques in terms of predictive power, their lack of transparency renders them useless in any domain where comprehensibility is of importance. Rule-extraction algorithms remedy this by distilling comprehensible rule sets from complex models that explain how the classifications are made. This paper considers a new rule extraction technique, based on active learning. The technique generates artificial data points around training data with low confidence in the output score, after which these are labeled by the black-box model. The main novelty of the proposed method is that it uses a pedagogical approach without making any architectural assumptions of the underlying model. It can therefore be applied to any black-box technique. Furthermore, it can generate any rule format, depending on the chosen underlying rule induction technique. In a large-scale empirical study, we demonstrate the validity of our technique to extract trees and rules from artificial neural networks, support vector machines, and random forests, on 25 data sets of varying size and dimensionality. Our results show that not only do the generated rules explain the black-box models well (thereby facilitating the acceptance of such models), the proposed algorithm also performs significantly better than traditional rule induction techniques in terms of accuracy as well as fidelity.

  4. Alternate Learning Center. Abstracts of Inservice Training Programs.

    ERIC Educational Resources Information Center

    Rhode Island State Dept. of Education, Providence. Div. of Development and Operations.

    This booklet is a collection of abstracts describing the 18 programs offered at the Alternate Learning Center of the Rhode Island Teacher Center which has as its Primary function school based inservice training for local teachers and administrators. Each project is described in detail, including course goals, specific objectives, training…

  5. Self-Directed Learning Dissertation Abstracts 1966-1991.

    ERIC Educational Resources Information Center

    Long, Huey B.; Redding, Terrence R.

    This index contains abstracts of 173 doctoral dissertations about the following aspects of adult self-directed learning: program areas of adult education (AE); instructional methods/techniques; institutional sponsors of AE; personnel and staffing in AE; education of particular clientele groups; processes of program planning and administration;…

  6. Neural signature of hierarchically structured expectations predicts clustering and transfer of rule sets in reinforcement learning.

    PubMed

    Collins, Anne Gabrielle Eva; Frank, Michael Joshua

    2016-07-01

    Often the world is structured such that distinct sensory contexts signify the same abstract rule set. Learning from feedback thus informs us not only about the value of stimulus-action associations but also about which rule set applies. Hierarchical clustering models suggest that learners discover structure in the environment, clustering distinct sensory events into a single latent rule set. Such structure enables a learner to transfer any newly acquired information to other contexts linked to the same rule set, and facilitates re-use of learned knowledge in novel contexts. Here, we show that humans exhibit this transfer, generalization and clustering during learning. Trial-by-trial model-based analysis of EEG signals revealed that subjects' reward expectations incorporated this hierarchical structure; these structured neural signals were predictive of behavioral transfer and clustering. These results further our understanding of how humans learn and generalize flexibly by building abstract, behaviorally relevant representations of the complex, high-dimensional sensory environment.

  7. Brains rule! fun = learning = neuroscience literacy.

    PubMed

    Zardetto-Smith, Andrea M; Mu, Keli; Phelps, Cynthia L; Houtz, Lynne E; Royeen, Charlotte B

    2002-10-01

    Brains Rule! Neuroscience Expositions is a project designed to improve neuroscience literacy among children and the general public by applying a model where neuroscience professionals transfer knowledge and enthusiasm about neuroscience through fun, engaging hands-on activities. This educational model draws strength from many national and local partnerships of neuroscience professionals to coordinate expositions across the country in a variety of local communities. Brains Rule! Neuroscience Expositions uses a flexible science fair-like format to engage children in the process of science and teach about neuroscience concepts, facts, and professions. Neuroscience literacy is important to everyday life and helps individuals better understand themselves, make informed decisions about health and drug use, participate knowledgeably in governmental and social issues, and better understand scientific advancements. In this study, children's ratings of Brains Rule! Neuroscience Expositions activities were analyzed both quantitatively and qualitatively. Analysis of the responses revealed that overall the children perceived the learning activities as fun and interesting and believed that they learned something about the brain and nervous system after engaging in the activities. The Brains Rule! Neuroscience Expositions education model can be an effective tool in improving neuroscience literacy for both children and adults.

  8. An implementation and analysis of the Abstract Syntax Notation One and the basic encoding rules

    NASA Technical Reports Server (NTRS)

    Harvey, James D.; Weaver, Alfred C.

    1990-01-01

    The details of abstract syntax notation one standard (ASN.1) and the basic encoding rules standard (BER) that collectively solve the problem of data transfer across incompatible host environments are presented, and a compiler that was built to automate their use is described. Experiences with this compiler are also discussed which provide a quantitative analysis of the performance costs associated with the application of these standards. An evaluation is offered as to how well suited ASN.1 and BER are in solving the common data representation problem.

  9. Same/Different Abstract Concept Learning by Archerfish (Toxotes chatareus)

    PubMed Central

    Newport, Cait; Wallis, Guy; Siebeck, Ulrike E.

    2015-01-01

    While several phylogenetically diverse species have proved capable of learning abstract concepts, previous attempts to teach fish have been unsuccessful. In this report, the ability of archerfish (Toxotes chatareus) to learn the concepts of sameness and difference using a simultaneous two-item discrimination task was tested. Six archerfish were trained to either select a pair of same or different stimuli which were presented simultaneously. Training consisted of a 2-phase approach. Training phase 1: the symbols in the same and different pair did not change, thereby allowing the fish to solve the test through direct association. The fish were trained consecutively with four different sets of stimuli to familiarize them with the general procedure before moving on to the next training phase. Training phase 2: six different symbols were used to form the same or different pairs. After acquisition, same/different concept learning was tested by presenting fish with six novel stimuli (transfer test). Five fish successfully completed the first training phase. Only one individual passed the second training phase, however, transfer performance was consistent with chance. This individual was given further training using 60 training exemplars but the individual was unable to reach the training criterion. We hypothesize that archerfish are able to solve a limited version of the same/different test by learning the response to each possible stimulus configuration or by developing a series of relatively simple choice contingencies. We conclude that the simultaneous two-item discrimination task we describe cannot be successfully used to test the concepts of same and different in archerfish. In addition, despite considerable effort training archerfish using several tests and training methods, there is still no evidence that fish can learn an abstract concept-based test. PMID:26599071

  10. Learning to use working memory: a reinforcement learning gating model of rule acquisition in rats

    PubMed Central

    Lloyd, Kevin; Becker, Nadine; Jones, Matthew W.; Bogacz, Rafal

    2012-01-01

    Learning to form appropriate, task-relevant working memory representations is a complex process central to cognition. Gating models frame working memory as a collection of past observations and use reinforcement learning (RL) to solve the problem of when to update these observations. Investigation of how gating models relate to brain and behavior remains, however, at an early stage. The current study sought to explore the ability of simple RL gating models to replicate rule learning behavior in rats. Rats were trained in a maze-based spatial learning task that required animals to make trial-by-trial choices contingent upon their previous experience. Using an abstract version of this task, we tested the ability of two gating algorithms, one based on the Actor-Critic and the other on the State-Action-Reward-State-Action (SARSA) algorithm, to generate behavior consistent with the rats'. Both models produced rule-acquisition behavior consistent with the experimental data, though only the SARSA gating model mirrored faster learning following rule reversal. We also found that both gating models learned multiple strategies in solving the initial task, a property which highlights the multi-agent nature of such models and which is of importance in considering the neural basis of individual differences in behavior. PMID:23115551

  11. Optimal Learning Rules for Discrete Synapses

    PubMed Central

    Barrett, Adam B.; van Rossum, M. C. W.

    2008-01-01

    There is evidence that biological synapses have a limited number of discrete weight states. Memory storage with such synapses behaves quite differently from synapses with unbounded, continuous weights, as old memories are automatically overwritten by new memories. Consequently, there has been substantial discussion about how this affects learning and storage capacity. In this paper, we calculate the storage capacity of discrete, bounded synapses in terms of Shannon information. We use this to optimize the learning rules and investigate how the maximum information capacity depends on the number of synapses, the number of synaptic states, and the coding sparseness. Below a certain critical number of synapses per neuron (comparable to numbers found in biology), we find that storage is similar to unbounded, continuous synapses. Hence, discrete synapses do not necessarily have lower storage capacity. PMID:19043540

  12. How learning to abstract shapes neural sound representations.

    PubMed

    Ley, Anke; Vroomen, Jean; Formisano, Elia

    2014-01-01

    The transformation of acoustic signals into abstract perceptual representations is the essence of the efficient and goal-directed neural processing of sounds in complex natural environments. While the human and animal auditory system is perfectly equipped to process the spectrotemporal sound features, adequate sound identification and categorization require neural sound representations that are invariant to irrelevant stimulus parameters. Crucially, what is relevant and irrelevant is not necessarily intrinsic to the physical stimulus structure but needs to be learned over time, often through integration of information from other senses. This review discusses the main principles underlying categorical sound perception with a special focus on the role of learning and neural plasticity. We examine the role of different neural structures along the auditory processing pathway in the formation of abstract sound representations with respect to hierarchical as well as dynamic and distributed processing models. Whereas most fMRI studies on categorical sound processing employed speech sounds, the emphasis of the current review lies on the contribution of empirical studies using natural or artificial sounds that enable separating acoustic and perceptual processing levels and avoid interference with existing category representations. Finally, we discuss the opportunities of modern analyses techniques such as multivariate pattern analysis (MVPA) in studying categorical sound representations. With their increased sensitivity to distributed activation changes-even in absence of changes in overall signal level-these analyses techniques provide a promising tool to reveal the neural underpinnings of perceptually invariant sound representations.

  13. A Local Learning Rule for Independent Component Analysis

    PubMed Central

    Isomura, Takuya; Toyoizumi, Taro

    2016-01-01

    Humans can separately recognize independent sources when they sense their superposition. This decomposition is mathematically formulated as independent component analysis (ICA). While a few biologically plausible learning rules, so-called local learning rules, have been proposed to achieve ICA, their performance varies depending on the parameters characterizing the mixed signals. Here, we propose a new learning rule that is both easy to implement and reliable. Both mathematical and numerical analyses confirm that the proposed rule outperforms other local learning rules over a wide range of parameters. Notably, unlike other rules, the proposed rule can separate independent sources without any preprocessing, even if the number of sources is unknown. The successful performance of the proposed rule is then demonstrated using natural images and movies. We discuss the implications of this finding for our understanding of neuronal information processing and its promising applications to neuromorphic engineering. PMID:27323661

  14. A Local Learning Rule for Independent Component Analysis

    NASA Astrophysics Data System (ADS)

    Isomura, Takuya; Toyoizumi, Taro

    2016-06-01

    Humans can separately recognize independent sources when they sense their superposition. This decomposition is mathematically formulated as independent component analysis (ICA). While a few biologically plausible learning rules, so-called local learning rules, have been proposed to achieve ICA, their performance varies depending on the parameters characterizing the mixed signals. Here, we propose a new learning rule that is both easy to implement and reliable. Both mathematical and numerical analyses confirm that the proposed rule outperforms other local learning rules over a wide range of parameters. Notably, unlike other rules, the proposed rule can separate independent sources without any preprocessing, even if the number of sources is unknown. The successful performance of the proposed rule is then demonstrated using natural images and movies. We discuss the implications of this finding for our understanding of neuronal information processing and its promising applications to neuromorphic engineering.

  15. A Flexible Mechanism of Rule Selection Enables Rapid Feature-Based Reinforcement Learning

    PubMed Central

    Balcarras, Matthew; Womelsdorf, Thilo

    2016-01-01

    Learning in a new environment is influenced by prior learning and experience. Correctly applying a rule that maps a context to stimuli, actions, and outcomes enables faster learning and better outcomes compared to relying on strategies for learning that are ignorant of task structure. However, it is often difficult to know when and how to apply learned rules in new contexts. In our study we explored how subjects employ different strategies for learning the relationship between stimulus features and positive outcomes in a probabilistic task context. We test the hypothesis that task naive subjects will show enhanced learning of feature specific reward associations by switching to the use of an abstract rule that associates stimuli by feature type and restricts selections to that dimension. To test this hypothesis we designed a decision making task where subjects receive probabilistic feedback following choices between pairs of stimuli. In the task, trials are grouped in two contexts by blocks, where in one type of block there is no unique relationship between a specific feature dimension (stimulus shape or color) and positive outcomes, and following an un-cued transition, alternating blocks have outcomes that are linked to either stimulus shape or color. Two-thirds of subjects (n = 22/32) exhibited behavior that was best fit by a hierarchical feature-rule model. Supporting the prediction of the model mechanism these subjects showed significantly enhanced performance in feature-reward blocks, and rapidly switched their choice strategy to using abstract feature rules when reward contingencies changed. Choice behavior of other subjects (n = 10/32) was fit by a range of alternative reinforcement learning models representing strategies that do not benefit from applying previously learned rules. In summary, these results show that untrained subjects are capable of flexibly shifting between behavioral rules by leveraging simple model-free reinforcement learning and context

  16. A Flexible Mechanism of Rule Selection Enables Rapid Feature-Based Reinforcement Learning.

    PubMed

    Balcarras, Matthew; Womelsdorf, Thilo

    2016-01-01

    Learning in a new environment is influenced by prior learning and experience. Correctly applying a rule that maps a context to stimuli, actions, and outcomes enables faster learning and better outcomes compared to relying on strategies for learning that are ignorant of task structure. However, it is often difficult to know when and how to apply learned rules in new contexts. In our study we explored how subjects employ different strategies for learning the relationship between stimulus features and positive outcomes in a probabilistic task context. We test the hypothesis that task naive subjects will show enhanced learning of feature specific reward associations by switching to the use of an abstract rule that associates stimuli by feature type and restricts selections to that dimension. To test this hypothesis we designed a decision making task where subjects receive probabilistic feedback following choices between pairs of stimuli. In the task, trials are grouped in two contexts by blocks, where in one type of block there is no unique relationship between a specific feature dimension (stimulus shape or color) and positive outcomes, and following an un-cued transition, alternating blocks have outcomes that are linked to either stimulus shape or color. Two-thirds of subjects (n = 22/32) exhibited behavior that was best fit by a hierarchical feature-rule model. Supporting the prediction of the model mechanism these subjects showed significantly enhanced performance in feature-reward blocks, and rapidly switched their choice strategy to using abstract feature rules when reward contingencies changed. Choice behavior of other subjects (n = 10/32) was fit by a range of alternative reinforcement learning models representing strategies that do not benefit from applying previously learned rules. In summary, these results show that untrained subjects are capable of flexibly shifting between behavioral rules by leveraging simple model-free reinforcement learning and context

  17. Preattentive Extraction of Abstract Auditory Rules in Speech Sound Stream: A Mismatch Negativity Study Using Lexical Tones

    PubMed Central

    Wang, Xiao-Dong; Gu, Feng; He, Kang; Chen, Ling-Hui; Chen, Lin

    2012-01-01

    Background Extraction of linguistically relevant auditory features is critical for speech comprehension in complex auditory environments, in which the relationships between acoustic stimuli are often abstract and constant while the stimuli per se are varying. These relationships are referred to as the abstract auditory rule in speech and have been investigated for their underlying neural mechanisms at an attentive stage. However, the issue of whether or not there is a sensory intelligence that enables one to automatically encode abstract auditory rules in speech at a preattentive stage has not yet been thoroughly addressed. Methodology/Principal Findings We chose Chinese lexical tones for the current study because they help to define word meaning and hence facilitate the fabrication of an abstract auditory rule in a speech sound stream. We continuously presented native Chinese speakers with Chinese vowels differing in formant, intensity, and level of pitch to construct a complex and varying auditory stream. In this stream, most of the sounds shared flat lexical tones to form an embedded abstract auditory rule. Occasionally the rule was randomly violated by those with a rising or falling lexical tone. The results showed that the violation of the abstract auditory rule of lexical tones evoked a robust preattentive auditory response, as revealed by whole-head electrical recordings of the mismatch negativity (MMN), though none of the subjects acquired explicit knowledge of the rule or became aware of the violation. Conclusions/Significance Our results demonstrate that there is an auditory sensory intelligence in the perception of Chinese lexical tones. The existence of this intelligence suggests that the humans can automatically extract abstract auditory rules in speech at a preattentive stage to ensure speech communication in complex and noisy auditory environments without drawing on conscious resources. PMID:22238691

  18. Many faces, one rule: the role of perceptual expertise in infants’ sequential rule learning

    PubMed Central

    Bulf, Hermann; Brenna, Viola; Valenza, Eloisa; Johnson, Scott P.; Turati, Chiara

    2015-01-01

    Rule learning is a mechanism that allows infants to recognize and generalize rule-like patterns, such as ABB or ABA. Although infants are better at learning rules from speech vs. non-speech, rule learning can be applied also to frequently experienced visual stimuli, suggesting that perceptual expertise with material to be learned is critical in enhancing rule learning abilities. Yet infants’ rule learning has never been investigated using one of the most commonly experienced visual stimulus category available in infants’ environment, i.e., faces. Here, we investigate 7-month-olds’ ability to extract rule-like patterns from sequences composed of upright faces and compared their results to those of infants who viewed inverted faces, which presumably are encountered far less frequently than upright faces. Infants were habituated with face triads in either an ABA or ABB condition followed by a test phase with ABA and ABB triads composed of faces that differed from those showed during habituation. When upright faces were used, infants generalized the pattern presented during habituation to include the new face identities showed during testing, but when inverted faces were presented, infants failed to extract the rule. This finding supports the idea that perceptual expertise can modulate 7-month-olds’ abilities to detect rule-like patterns. PMID:26539142

  19. Learning categories via rules and similarity: comparing adults and children.

    PubMed

    Rabi, Rahel; Miles, Sarah J; Minda, John Paul

    2015-03-01

    Two experiments explored the different strategies used by children and adults when learning new perceptual categories. Participants were asked to learn a set of categories for which both a single-feature rule and overall similarity would allow for perfect performance. Other rules allowed for suboptimal performance. Transfer stimuli (Experiments 1 and 2) and single features (Experiment 2) were presented after training to help determine how the categories were learned. In both experiments, we found that adults made significantly more optimal rule-based responses to the test stimuli than children. Children showed a variety of categorization styles, with a few relying on the optimal rules, many relying on suboptimal single-feature rules, and only a few relying on overall family resemblance. We interpret these results within a multiple systems framework, and we argue that children show the pattern they do because they lack the necessary cognitive resources to fully engage in hypothesis testing, rule selection, and verbally mediated category learning.

  20. Implicit Learning of Nonlocal Musical Rules: Implicitly Learning More Than Chunks

    ERIC Educational Resources Information Center

    Kuhn, Gustav; Dienes, Zoltan

    2005-01-01

    Dominant theories of implicit learning assume that implicit learning merely involves the learning of chunks of adjacent elements in a sequence. In the experiments presented here, participants implicitly learned a nonlocal rule, thus suggesting that implicit learning can go beyond the learning of chunks. Participants were exposed to a set of…

  1. Prior Knowledge of Rules in Concept Learning.

    ERIC Educational Resources Information Center

    Brainerd, Charles J.

    This paper briefly reviews the literature concerning the Paiget-Burner debate over the roles of identify and reversibility rules in conservation acquisition, and describes an experiment designed to determine whether one group of rules is more closely related to conservation than the other. A group of children, aged 4-6 years, received tests of…

  2. Simple learning rules to cope with changing environments.

    PubMed

    Gross, Roderich; Houston, Alasdair I; Collins, Edmund J; McNamara, John M; Dechaume-Moncharmont, François-Xavier; Franks, Nigel R

    2008-10-06

    We consider an agent that must choose repeatedly among several actions. Each action has a certain probability of giving the agent an energy reward, and costs may be associated with switching between actions. The agent does not know which action has the highest reward probability, and the probabilities change randomly over time. We study two learning rules that have been widely used to model decision-making processes in animals-one deterministic and the other stochastic. In particular, we examine the influence of the rules' 'learning rate' on the agent's energy gain. We compare the performance of each rule with the best performance attainable when the agent has either full knowledge or no knowledge of the environment. Over relatively short periods of time, both rules are successful in enabling agents to exploit their environment. Moreover, under a range of effective learning rates, both rules are equivalent, and can be expressed by a third rule that requires the agent to select the action for which the current run of unsuccessful trials is shortest. However, the performance of both rules is relatively poor over longer periods of time, and under most circumstances no better than the performance an agent could achieve without knowledge of the environment. We propose a simple extension to the original rules that enables agents to learn about and effectively exploit a changing environment for an unlimited period of time.

  3. Evolving fuzzy rules in a learning classifier system

    NASA Technical Reports Server (NTRS)

    Valenzuela-Rendon, Manuel

    1993-01-01

    The fuzzy classifier system (FCS) combines the ideas of fuzzy logic controllers (FLC's) and learning classifier systems (LCS's). It brings together the expressive powers of fuzzy logic as it has been applied in fuzzy controllers to express relations between continuous variables, and the ability of LCS's to evolve co-adapted sets of rules. The goal of the FCS is to develop a rule-based system capable of learning in a reinforcement regime, and that can potentially be used for process control.

  4. Bayesian Learning and the Psychology of Rule Induction

    ERIC Educational Resources Information Center

    Endress, Ansgar D.

    2013-01-01

    In recent years, Bayesian learning models have been applied to an increasing variety of domains. While such models have been criticized on theoretical grounds, the underlying assumptions and predictions are rarely made concrete and tested experimentally. Here, I use Frank and Tenenbaum's (2011) Bayesian model of rule-learning as a case study to…

  5. Rule-Based Category Learning in Down Syndrome

    ERIC Educational Resources Information Center

    Phillips, B. Allyson; Conners, Frances A.; Merrill, Edward; Klinger, Mark R.

    2014-01-01

    Rule-based category learning was examined in youths with Down syndrome (DS), youths with intellectual disability (ID), and typically developing (TD) youths. Two tasks measured category learning: the Modified Card Sort task (MCST) and the Concept Formation test of the Woodcock-Johnson-III (Woodcock, McGrew, & Mather, 2001). In regression-based…

  6. Compositional Verification with Abstraction, Learning, and SAT Solving

    DTIC Science & Technology

    2015-05-01

    of the human mind To love and music To nature iv Abstract Compositional reasoning is an approach for scaling model checking to complex com- puter...Charlotte Yano were two indispensable people who made my life at CMU so much easier! Music has been a significant part of my non-academic life at CMU. I...thank the Indian Graduate Student Association and the fellow students of the Indian music team for giving me a platform to take rebirth in music , after

  7. Abstract of Research Project Sensory Integrative Processes and Learning Disorders.

    ERIC Educational Resources Information Center

    Ayres, A. Jean

    To further clarify the nature of sensory integrative dysfunction, 148 public school children (mean age 92.6, mean IQ 96.5) with learning disorders were first given a battery of sensorimotor, psycholinguistic, and cognitive tests, and factors were extrapolated. The test scores were also employed to generate step-wise regression equations predicting…

  8. Importance of Fe and Mn Pipe Deposits to Lead and Copper Rule Compliance - abstract

    EPA Science Inventory

    When Madison, WI exceeded the lead Action Level in 1992, residential and off-line tests suggested that lead release into the water was more complex than a lead solubility mechanism. The water utility chose to address the Lead and Copper Rule (LCR) exceedance by implementing full ...

  9. Switching between Abstract Rules Reflects Disease Severity but Not Dopaminergic Status in Parkinson's Disease

    ERIC Educational Resources Information Center

    Kehagia, Angie A.; Cools, Roshan; Barker, Roger A.; Robbins, Trevor W.

    2009-01-01

    This study sought to disambiguate the impact of Parkinson's disease (PD) on cognitive control as indexed by task set switching, by addressing discrepancies in the literature pertaining to disease severity and paradigm heterogeneity. A task set is governed by a rule that determines how relevant stimuli (stimulus set) map onto specific responses…

  10. Learning a New Selection Rule in Visual and Frontal Cortex

    PubMed Central

    van der Togt, Chris; Stănişor, Liviu; Pooresmaeili, Arezoo; Albantakis, Larissa; Deco, Gustavo; Roelfsema, Pieter R.

    2016-01-01

    How do you make a decision if you do not know the rules of the game? Models of sensory decision-making suggest that choices are slow if evidence is weak, but they may only apply if the subject knows the task rules. Here, we asked how the learning of a new rule influences neuronal activity in the visual (area V1) and frontal cortex (area FEF) of monkeys. We devised a new icon-selection task. On each day, the monkeys saw 2 new icons (small pictures) and learned which one was relevant. We rewarded eye movements to a saccade target connected to the relevant icon with a curve. Neurons in visual and frontal cortex coded the monkey's choice, because the representation of the selected curve was enhanced. Learning delayed the neuronal selection signals and we uncovered the cause of this delay in V1, where learning to select the relevant icon caused an early suppression of surrounding image elements. These results demonstrate that the learning of a new rule causes a transition from fast and random decisions to a more considerate strategy that takes additional time and they reveal the contribution of visual and frontal cortex to the learning process. PMID:27269960

  11. Symbol manipulation and rule learning in spiking neuronal networks.

    PubMed

    Fernando, Chrisantha

    2011-04-21

    It has been claimed that the productivity, systematicity and compositionality of human language and thought necessitate the existence of a physical symbol system (PSS) in the brain. Recent discoveries about temporal coding suggest a novel type of neuronal implementation of a physical symbol system. Furthermore, learning classifier systems provide a plausible algorithmic basis by which symbol re-write rules could be trained to undertake behaviors exhibiting systematicity and compositionality, using a kind of natural selection of re-write rules in the brain, We show how the core operation of a learning classifier system, namely, the replication with variation of symbol re-write rules, can be implemented using spike-time dependent plasticity based supervised learning. As a whole, the aim of this paper is to integrate an algorithmic and an implementation level description of a neuronal symbol system capable of sustaining systematic and compositional behaviors. Previously proposed neuronal implementations of symbolic representations are compared with this new proposal.

  12. Prosodic cues enhance rule learning by changing speech segmentation mechanisms

    PubMed Central

    de Diego-Balaguer, Ruth; Rodríguez-Fornells, Antoni; Bachoud-Lévi, Anne-Catherine

    2015-01-01

    Prosody has been claimed to have a critical role in the acquisition of grammatical information from speech. The exact mechanisms by which prosodic cues enhance learning are fully unknown. Rules from language often require the extraction of non-adjacent dependencies (e.g., he plays, he sings, he speaks). It has been proposed that pauses enhance learning because they allow computing non-adjacent relations helping word segmentation by removing the need to compute adjacent computations. So far only indirect evidence from behavioral and electrophysiological measures comparing learning effects after exposure to speech with and without pauses support this claim. By recording event-related potentials during the acquisition process of artificial languages with and without pauses between words with embedded non-adjacent rules we provide direct evidence on how the presence of pauses modifies the way speech is processed during learning to enhance segmentation and rule generalization. The electrophysiological results indicate that pauses as short as 25 ms attenuated the N1 component irrespective of whether learning was possible or not. In addition, a P2 enhancement was present only when learning of non-adjacent dependencies was possible. The overall results support the claim that the simple presence of subtle pauses changed the segmentation mechanism used reflected in an exogenously driven N1 component attenuation and improving segmentation at the behavioral level. This effect can be dissociated from the endogenous P2 enhancement that is observed irrespective of the presence of pauses whenever non-adjacent dependencies are learned. PMID:26483731

  13. Abstraction, ethics and software: Why don`t the rules work?

    SciTech Connect

    Warwick, S.

    1994-12-31

    A theory is presented that one of the reasons why the use of unlicensed software is so widespread and unstigmatized is that legislatures, courts and other bodies which create policy operate at a higher level of abstraction than do individuals, and that abstraction is a key factor in the divergence of societal behavior from that condoned by legal statute. This theory is explored through a pilot study consisting of medium depth interviews with two volunteers who had used unlicensed software. Their attitudes, understanding of the law, and characterization of the their use of unlicensed software as based on {open_quotes}need{close_quotes} is reported. In addition, the concept of face is examined, and how it is maintained while violating law. It is suggested that further studies, using multiple methodologies, (in-depth interview, focus groups, and surveys) be conducted prior to developing further policy or legislation regarding intellectual property protection for software.

  14. Learning from Pulsating Stars: Progress over the Last Century (Abstract)

    NASA Astrophysics Data System (ADS)

    Smith, H.

    2016-12-01

    (Abstract only) Scarcely more than a century has elapsed since it began to be widely accepted that pulsation plays an important role in the variability of stars. During that century pulsating stars have been used as tools to explore a variety of astrophysical questions, including the determination of distances to other galaxies, the testing of timescales of evolution through the HR diagram, and the identification of the ages and star formation histories of stellar populations. Among the significant early milestones along this investigative path are Henrietta Leavitt's discovery of a relation between the periods and luminosities of Cepheids, Harlow Shapley's proposal that all Cepheids are pulsating stars, and Arthur Stanley Eddington's use of the observed period change of d Cephei to constrain its power source. Today our explorations of pulsating stars are bolstered by long observational histories of brighter variables, surveys involving unprecedentedly large numbers of stars, and improved theoretical analyses. This talk will review aspects of the history and our current understanding of pulsating stars, paying particular attention to RR Lyrae, d Scuti, and Cepheid variables. Observations by AAVSO members have provided insight into several questions regarding the behavior of these stars.

  15. Bayesian learning and the psychology of rule induction

    PubMed Central

    Endress, Ansgar D.

    2014-01-01

    In recent years, Bayesian learning models have been applied to an increasing variety of domains. While such models have been criticized on theoretical grounds, the underlying assumptions and predictions are rarely made concrete and tested experimentally. Here, I use Frank and Tenenbaum's (2011) Bayesian model of rule-learning as a case study to spell out the underlying assumptions, and to confront them with the empirical results Frank and Tenenbaum (2011) propose to simulate, as well as with novel experiments. While rule-learning is arguably well suited to rational Bayesian approaches, I show that their models are neither psychologically plausible nor ideal observer models. Further, I show that their central assumption is unfounded: humans do not always preferentially learn more specific rules, but, at least in some situations, those rules that happen to be more salient. Even when granting the unsupported assumptions, I show that all of the experiments modeled by Frank and Tenenbaum (2011) either contradict their models, or have a large number of more plausible interpretations. I provide an alternative account of the experimental data based on simple psychological mechanisms, and show that this account both describes the data better, and is easier to falsify. I conclude that, despite the recent surge in Bayesian models of cognitive phenomena, psychological phenomena are best understood by developing and testing psychological theories rather than models that can be fit to virtually any data. PMID:23454791

  16. Dimensional Salience and Developmental Effects Upon the Learning of Rules.

    ERIC Educational Resources Information Center

    Katsuyama, Ronald M.; Hoffarth, Gary D.

    This study had two major purposes: to examine the effects of dimensional salience upon the learning of conjunction and disjunction rules, and to investigate an alternative to the prevailing cognitive-change accounts of developmental differences in multidimensional problem solving. The relative salience of each of four stimulus dimensions (form,…

  17. Rote Learning and Rule Learning in Foreign-Language Teaching

    ERIC Educational Resources Information Center

    Engels, L. K.

    1975-01-01

    The article outlines the need to eliminate rote-learning and pure imitative strategies in second language learning, particularly in the areas of syntax and semantics. Theoretical foundations for this need are discussed, with reference to the coding hypothesis for memory functions in language learning. Results of experimental investigations are…

  18. Learning multiple rules simultaneously: Affixes are more salient than reduplications.

    PubMed

    Gervain, Judit; Endress, Ansgar D

    2016-11-21

    Language learners encounter numerous opportunities to learn regularities, but need to decide which of these regularities to learn, because some are not productive in their native language. Here, we present an account of rule learning based on perceptual and memory primitives (Endress, Dehaene-Lambertz, & Mehler, Cognition, 105(3), 577-614, 2007; Endress, Nespor, & Mehler, Trends in Cognitive Sciences, 13(8), 348-353, 2009), suggesting that learners preferentially learn regularities that are more salient to them, and that the pattern of salience reflects the frequency of language features across languages. We contrast this view with previous artificial grammar learning research, which suggests that infants "choose" the regularities they learn based on rational, Bayesian criteria (Frank & Tenenbaum, Cognition, 120(3), 360-371, 2013; Gerken, Cognition, 98(3)B67-B74, 2006, Cognition, 115(2), 362-366, 2010). In our experiments, adult participants listened to syllable strings starting with a syllable reduplication and always ending with the same "affix" syllable, or to syllable strings starting with this "affix" syllable and ending with the "reduplication". Both affixation and reduplication are frequently used for morphological marking across languages. We find three crucial results. First, participants learned both regularities simultaneously. Second, affixation regularities seemed easier to learn than reduplication regularities. Third, regularities in sequence offsets were easier to learn than regularities at sequence onsets. We show that these results are inconsistent with previous Bayesian rule learning models, but mesh well with the perceptual or memory primitives view. Further, we show that the pattern of salience revealed in our experiments reflects the distribution of regularities across languages. Ease of acquisition might thus be one determinant of the frequency of regularities across languages.

  19. Proof Rules for Automated Compositional Verification through Learning

    NASA Technical Reports Server (NTRS)

    Barringer, Howard; Giannakopoulou, Dimitra; Pasareanu, Corina S.

    2003-01-01

    Compositional proof systems not only enable the stepwise development of concurrent processes but also provide a basis to alleviate the state explosion problem associated with model checking. An assume-guarantee style of specification and reasoning has long been advocated to achieve compositionality. However, this style of reasoning is often non-trivial, typically requiring human input to determine appropriate assumptions. In this paper, we present novel assume- guarantee rules in the setting of finite labelled transition systems with blocking communication. We show how these rules can be applied in an iterative and fully automated fashion within a framework based on learning.

  20. Within-Category Discontinuity Interacts with Verbal Rule Complexity in Perceptual Category Learning

    ERIC Educational Resources Information Center

    Maddox, W. Todd; Filoteo, J. Vincent; Lauritzen, J. Scott

    2007-01-01

    A test of the predicted interaction between within-category discontinuity and verbal rule complexity on information-integration and rule-based category learning was conducted. Within-category discontinuity adversely affected information-integration category learning but not rule-based category learning. Model-based analyses suggested that some…

  1. Ego depletion interferes with rule-defined category learning but not non-rule-defined category learning

    PubMed Central

    Minda, John P.; Rabi, Rahel

    2015-01-01

    Considerable research on category learning has suggested that many cognitive and environmental factors can have a differential effect on the learning of rule-defined (RD) categories as opposed to the learning of non-rule-defined (NRD) categories. Prior research has also suggested that ego depletion can temporarily reduce the capacity for executive functioning and cognitive flexibility. The present study examined whether temporarily reducing participants’ executive functioning via a resource depletion manipulation would differentially impact RD and NRD category learning. Participants were either asked to write a story with no restrictions (the control condition), or without using two common letters (the ego depletion condition). Participants were then asked to learn either a set of RD categories or a set of NRD categories. Resource depleted participants performed more poorly than controls on the RD task, but did not differ from controls on the NRD task, suggesting that self regulatory resources are required for successful RD category learning. These results lend support to multiple systems theories and clarify the role of self-regulatory resources within this theory. PMID:25688220

  2. The Convallis Rule for Unsupervised Learning in Cortical Networks

    PubMed Central

    Yger, Pierre; Harris, Kenneth D.

    2013-01-01

    The phenomenology and cellular mechanisms of cortical synaptic plasticity are becoming known in increasing detail, but the computational principles by which cortical plasticity enables the development of sensory representations are unclear. Here we describe a framework for cortical synaptic plasticity termed the “Convallis rule”, mathematically derived from a principle of unsupervised learning via constrained optimization. Implementation of the rule caused a recurrent cortex-like network of simulated spiking neurons to develop rate representations of real-world speech stimuli, enabling classification by a downstream linear decoder. Applied to spike patterns used in in vitro plasticity experiments, the rule reproduced multiple results including and beyond STDP. However STDP alone produced poorer learning performance. The mathematical form of the rule is consistent with a dual coincidence detector mechanism that has been suggested by experiments in several synaptic classes of juvenile neocortex. Based on this confluence of normative, phenomenological, and mechanistic evidence, we suggest that the rule may approximate a fundamental computational principle of the neocortex. PMID:24204224

  3. Statistical learning is constrained to less abstract patterns in complex sensory input (but not the least).

    PubMed

    Emberson, Lauren L; Rubinstein, Dani Y

    2016-08-01

    The influence of statistical information on behavior (either through learning or adaptation) is quickly becoming foundational to many domains of cognitive psychology and cognitive neuroscience, from language comprehension to visual development. We investigate a central problem impacting these diverse fields: when encountering input with rich statistical information, are there any constraints on learning? This paper examines learning outcomes when adult learners are given statistical information across multiple levels of abstraction simultaneously: from abstract, semantic categories of everyday objects to individual viewpoints on these objects. After revealing statistical learning of abstract, semantic categories with scrambled individual exemplars (Exp. 1), participants viewed pictures where the categories as well as the individual objects predicted picture order (e.g., bird1-dog1, bird2-dog2). Our findings suggest that participants preferentially encode the relationships between the individual objects, even in the presence of statistical regularities linking semantic categories (Exps. 2 and 3). In a final experiment we investigate whether learners are biased towards learning object-level regularities or simply construct the most detailed model given the data (and therefore best able to predict the specifics of the upcoming stimulus) by investigating whether participants preferentially learn from the statistical regularities linking individual snapshots of objects or the relationship between the objects themselves (e.g., bird_picture1-dog_picture1, bird_picture2-dog_picture2). We find that participants fail to learn the relationships between individual snapshots, suggesting a bias towards object-level statistical regularities as opposed to merely constructing the most complete model of the input. This work moves beyond the previous existence proofs that statistical learning is possible at both very high and very low levels of abstraction (categories vs. individual

  4. Differences between Neural Activity in Prefrontal Cortex and Striatum during Learning of Novel, Abstract Categories

    PubMed Central

    Antzoulatos, Evan G.; Miller, Earl K.

    2011-01-01

    Summary Learning to classify diverse experiences into meaningful groups, like categories, is fundamental to normal cognition. To understand its neural basis, we simultaneously recorded from multiple electrodes in the lateral prefrontal cortex and dorsal striatum, two interconnected brain structures critical for learning. Each day, monkeys learned to associate novel, abstract dot-based categories with a right vs. left saccade. Early on, when they could acquire specific stimulus-response associations, striatum activity was an earlier predictor of the corresponding saccade. However, as the number of exemplars was increasing, and monkeys had to learn to classify them, PFC began predicting the saccade associated with each category before the striatum. While monkeys were categorizing novel exemplars at a high rate, PFC activity was a strong predictor of their corresponding saccade early in the trial, before the striatal neurons. These results suggest that striatum plays a greater role in stimulus-response association and PFC in abstraction of categories. PMID:21791284

  5. Chunking, Rule Learning, and Multiple Item Memory in Rat Interleaved Serial Pattern Learning

    ERIC Educational Resources Information Center

    Fountain, Stephen B.; Benson, Don M., Jr.

    2006-01-01

    Nonhuman animals, like humans, appear sensitive to the structure of the elements of sequences, perhaps even when the structure relates nonadjacent elements. In the present study, we examined the contribution of chunking, rule learning, and item memory when rats learned serial patterns composed of two interleaved subpatterns. In one group, the…

  6. Learning about Regiochemistry from a Hydrogen-Atom Abstraction Reaction in Water

    ERIC Educational Resources Information Center

    Sears-Dundes, Christopher; Huon, Yoeup; Hotz, Richard P.; Pinhas, Allan R.

    2011-01-01

    An experiment has been developed in which the hydrogen-atom abstraction and the coupling of propionitrile, using Fenton's reagent, are investigated. Students learn about the regiochemistry of radical formation, the stereochemistry of product formation, and the interpretation of GC-MS data, in a safe reaction that can be easily completed in one…

  7. An Eye-Tracking Study of Learning from Science Text with Concrete and Abstract Illustrations

    ERIC Educational Resources Information Center

    Mason, Lucia; Pluchino, Patrik; Tornatora, Maria Caterina; Ariasi, Nicola

    2013-01-01

    This study investigated the online process of reading and the offline learning from an illustrated science text. The authors examined the effects of using a concrete or abstract picture to illustrate a text and adopted eye-tracking methodology to trace text and picture processing. They randomly assigned 59 eleventh-grade students to 3 reading…

  8. Rule-based category learning in Down syndrome.

    PubMed

    Phillips, B Allyson; Conners, Frances A; Merrill, Edward; Klinger, Mark R

    2014-05-01

    Rule-based category learning was examined in youths with Down syndrome (DS), youths with intellectual disability (ID), and typically developing (TD) youths. Two tasks measured category learning: the Modified Card Sort task (MCST) and the Concept Formation test of the Woodcock-Johnson-III ( Woodock, McGrew, & Mather, 2001 ). In regression-based analyses, DS and ID groups performed below the level expected for their nonverbal ability. In cross-sectional developmental trajectory analyses, results depended on the task. On the MCST, the DS and ID groups were similar to the TD group. On the Concept Formation test, the DS group had slower cross-sectional change than the other 2 groups. Category learning may be an area of difficulty for those with ID, but task-related factors may affect trajectories for youths with DS.

  9. Some aspects of using new techniques of teaching/learning in education in optics (Abstract only)

    NASA Astrophysics Data System (ADS)

    Suchanska, Malgorzata

    2003-11-01

    The deep learning in Optics can be encouraged by stimulating and considerate teaching. It means that teacher should demonstrate his/her personal commitment to the subject and stress its meaning, relevance and importance to the students. It is also important to allow students to be creative in solving problems and in interpretation of its contents. In order to help the students to become more creative persons it is necessary to enhance the learning process of modern knowledge in Optics, to design and conduct experiments, stimulate passions and interests, allow an access to the e-learning system (Internet) and introduce the psychological training (creativity, communication, lateral thinking etc.) (Abstract only available)

  10. Recommendation System Based On Association Rules For Distributed E-Learning Management Systems

    NASA Astrophysics Data System (ADS)

    Mihai, Gabroveanu

    2015-09-01

    Traditional Learning Management Systems are installed on a single server where learning materials and user data are kept. To increase its performance, the Learning Management System can be installed on multiple servers; learning materials and user data could be distributed across these servers obtaining a Distributed Learning Management System. In this paper is proposed the prototype of a recommendation system based on association rules for Distributed Learning Management System. Information from LMS databases is analyzed using distributed data mining algorithms in order to extract the association rules. Then the extracted rules are used as inference rules to provide personalized recommendations. The quality of provided recommendations is improved because the rules used to make the inferences are more accurate, since these rules aggregate knowledge from all e-Learning systems included in Distributed Learning Management System.

  11. Finding Influential Users in Social Media Using Association Rule Learning

    NASA Astrophysics Data System (ADS)

    Erlandsson, Fredrik; Bródka, Piotr; Borg, Anton; Johnson, Henric

    2016-04-01

    Influential users play an important role in online social networks since users tend to have an impact on one other. Therefore, the proposed work analyzes users and their behavior in order to identify influential users and predict user participation. Normally, the success of a social media site is dependent on the activity level of the participating users. For both online social networking sites and individual users, it is of interest to find out if a topic will be interesting or not. In this article, we propose association learning to detect relationships between users. In order to verify the findings, several experiments were executed based on social network analysis, in which the most influential users identified from association rule learning were compared to the results from Degree Centrality and Page Rank Centrality. The results clearly indicate that it is possible to identify the most influential users using association rule learning. In addition, the results also indicate a lower execution time compared to state-of-the-art methods.

  12. A neuronal learning rule for sub-millisecond temporal coding

    NASA Astrophysics Data System (ADS)

    Gerstner, Wulfram; Kempter, Richard; van Hemmen, J. Leo; Wagner, Hermann

    1996-09-01

    A PARADOX that exists in auditory and electrosensory neural systems1,2 is that they encode behaviourally relevant signals in the range of a few microseconds with neurons that are at least one order of magnitude slower. The importance of temporal coding in neural information processing is not clear yet3-8. A central question is whether neuronal firing can be more precise than the time constants of the neuronal processes involved9. Here we address this problem using the auditory system of the barn owl as an example. We present a modelling study based on computer simulations of a neuron in the laminar nucleus. Three observations explain the paradox. First, spiking of an 'integrate-and-fire' neuron driven by excitatory postsynaptic potentials with a width at half-maximum height of 250 μs, has an accuracy of 25 μs if the presynaptic signals arrive coherently. Second, the necessary degree of coherence in the signal arrival times can be attained during ontogenetic development by virtue of an unsupervised hebbian learning rule. Learning selects connections with matching delays from a broad distribution of axons with random delays. Third, the learning rule also selects the correct delays from two independent groups of inputs, for example, from the left and right ear.

  13. Memory Span, IQ and Memory Aids Effects on Learning of Logico-Conceptual Rules.

    ERIC Educational Resources Information Center

    Lee, Seong-Soo

    1979-01-01

    A set of immediate memory-span tests, concept- and rule-learning tasks, and an IQ test were administered to adolescents. A color-form memory factor and IQ substantially predicted rule-learning proficiency. Effects of memory aids appeared to induce conceptual rules and serve as a base for rehearsing information. (Author/RD)

  14. Learning reactive and planning rules in a motivationally autonomous animat.

    PubMed

    Donnart, J Y; Meyer, J A

    1996-01-01

    This work describes a control architecture based on a hierarchical classifier system. This system, which learns both reactive and planning rules, implements a motivationally autonomous animat that chooses the actions it performs according to its perception of the external environment, to its physiological or internal state, to the consequences of its current behavior, and to the expected consequences of its future behavior. The adaptive faculties of this architecture are illustrated within the context of a navigation task, through various experiments with a simulated and a real robot.

  15. Neotropical wrens learn new duet rules as adults.

    PubMed

    Rivera-Cáceres, Karla D; Quirós-Guerrero, Esmeralda; Araya-Salas, Marcelo; Searcy, William A

    2016-11-30

    Although song development in songbirds has been much studied as an analogue of language development in humans, the development of vocal interaction rules has been relatively neglected in both groups. Duetting avian species provide an ideal model to address the acquisition of interaction rules as duet structure involves time and pattern-specific relationships among the vocalizations from different individuals. In this study, we address the development of the most striking properties of duets: the specific answering rules that individuals use to link their own phrase types to those of their partners (duet codes) and precise temporal coordination. By performing two removal experiments in canebrake wrens (Cantorchilus zeledoni), we show that individuals use a fixed phrase repertoire to create new phrase pairings when they acquire a new partner. Furthermore, immediately after pairing, individuals perform duets with poor coordination and poor duet code adherence, but both aspects improve with time. These results indicate that individuals need a learning period to be able to perform well-coordinated duets that follow a consistent duet code. We conclude that both duet coordination and duet code adherence are honest indicators of pair-bond duration.

  16. Rule-Based and Information-Integration Category Learning in Normal Aging

    ERIC Educational Resources Information Center

    Maddox, W. Todd; Pacheco, Jennifer; Reeves, Maia; Zhu, Bo; Schnyer, David M.

    2010-01-01

    The basal ganglia and prefrontal cortex play critical roles in category learning. Both regions evidence age-related structural and functional declines. The current study examined rule-based and information-integration category learning in a group of older and younger adults. Rule-based learning is thought to involve explicit, frontally mediated…

  17. Fifty years of computer analysis in chest imaging: rule-based, machine learning, deep learning.

    PubMed

    van Ginneken, Bram

    2017-03-01

    Half a century ago, the term "computer-aided diagnosis" (CAD) was introduced in the scientific literature. Pulmonary imaging, with chest radiography and computed tomography, has always been one of the focus areas in this field. In this study, I describe how machine learning became the dominant technology for tackling CAD in the lungs, generally producing better results than do classical rule-based approaches, and how the field is now rapidly changing: in the last few years, we have seen how even better results can be obtained with deep learning. The key differences among rule-based processing, machine learning, and deep learning are summarized and illustrated for various applications of CAD in the chest.

  18. Genetic learning in rule-based and neural systems

    NASA Technical Reports Server (NTRS)

    Smith, Robert E.

    1993-01-01

    The design of neural networks and fuzzy systems can involve complex, nonlinear, and ill-conditioned optimization problems. Often, traditional optimization schemes are inadequate or inapplicable for such tasks. Genetic Algorithms (GA's) are a class of optimization procedures whose mechanics are based on those of natural genetics. Mathematical arguments show how GAs bring substantial computational leverage to search problems, without requiring the mathematical characteristics often necessary for traditional optimization schemes (e.g., modality, continuity, availability of derivative information, etc.). GA's have proven effective in a variety of search tasks that arise in neural networks and fuzzy systems. This presentation begins by introducing the mechanism and theoretical underpinnings of GA's. GA's are then related to a class of rule-based machine learning systems called learning classifier systems (LCS's). An LCS implements a low-level production-system that uses a GA as its primary rule discovery mechanism. This presentation illustrates how, despite its rule-based framework, an LCS can be thought of as a competitive neural network. Neural network simulator code for an LCS is presented. In this context, the GA is doing more than optimizing and objective function. It is searching for an ecology of hidden nodes with limited connectivity. The GA attempts to evolve this ecology such that effective neural network performance results. The GA is particularly well adapted to this task, given its naturally-inspired basis. The LCS/neural network analogy extends itself to other, more traditional neural networks. Conclusions to the presentation discuss the implications of using GA's in ecological search problems that arise in neural and fuzzy systems.

  19. Abstract or Concrete Examples in Learning Mathematics? A Replication and Elaboration of Kaminski, Sloutsky, and Heckler's Study

    ERIC Educational Resources Information Center

    De Bock, Dirk; Deprez, Johan; Van Dooren, Wim; Roelens, Michel; Verschaffel, Lieven

    2011-01-01

    Kaminski, Sloutsky, and Heckler (2008a) published in "Science" a study on "The advantage of abstract examples in learning math," in which they claim that students may benefit more from learning mathematics through a single abstract, symbolic representation than from multiple concrete examples. This publication elicited both enthusiastic and…

  20. Bothered by abstractness or engaged by cohesion? Experts' explanations enhance novices' deep-learning.

    PubMed

    Lachner, Andreas; Nückles, Matthias

    2015-03-01

    Experts' explanations have been shown to better enhance novices' transfer as compared with advanced students' explanations. Based on research on expertise and text comprehension, we investigated whether the abstractness or the cohesion of experts' and intermediates' explanations accounted for novices' learning. In Study 1, we showed that the superior cohesion of experts' explanations accounted for most of novices' transfer, whereas the degree of abstractness did not impact novices' transfer performance. In Study 2, we investigated novices' processing while learning with experts' and intermediates' explanations. We found that novices studying experts' explanations actively self-regulated their processing of the explanations, as they showed mainly deep-processing activities, whereas novices learning with intermediates' explanations were mainly engaged in shallow-processing activities by paraphrasing the explanations. Thus, we concluded that subject-matter expertise is a crucial prerequisite for instructors. Despite the abstract character of experts' explanations, their subject-matter expertise enables them to generate highly cohesive explanations that serve as a valuable scaffold for students' construction of flexible knowledge by engaging them in deep-level processing.

  1. High stimulus variability in nonnative speech learning supports formation of abstract categories: evidence from Japanese geminates.

    PubMed

    Sadakata, Makiko; McQueen, James M

    2013-08-01

    This study reports effects of a high-variability training procedure on nonnative learning of a Japanese geminate-singleton fricative contrast. Thirty native speakers of Dutch took part in a 5-day training procedure in which they identified geminate and singleton variants of the Japanese fricative /s/. Participants were trained with either many repetitions of a limited set of words recorded by a single speaker (low-variability training) or with fewer repetitions of a more variable set of words recorded by multiple speakers (high-variability training). Both types of training enhanced identification of speech but not of nonspeech materials, indicating that learning was domain specific. High-variability training led to superior performance in identification but not in discrimination tests, and supported better generalization of learning as shown by transfer from the trained fricatives to the identification of untrained stops and affricates. Variability thus helps nonnative listeners to form abstract categories rather than to enhance early acoustic analysis.

  2. Learning trees and rules with set-valued features

    SciTech Connect

    Cohen, W.W.

    1996-12-31

    In most learning systems examples are represented as fixed-length {open_quotes}feature vectors{close_quotes}, the components of which are either real numbers or nominal values. We propose an extension of the feature-vector representation that allows the value of a feature to be a set of strings; for instance, to represent a small white and black dog with the nominal features size and species and the set-valued feature color, one might use a feature vector with size-small, species-canis-familiaris and color-(white, black). Since we make no assumptions about the number of possible set elements, this extension of the traditional feature-vector representation is closely connected to Blum`s {open_quotes}infinite attribute{close_quotes} representation. We argue that many decision tree and rule learning algorithms can be easily extended to set-valued features. We also show by example that many real-world learning problems can be efficiently and naturally represented with set-valued features; in particular, text categorization problems and problems that arise in propositionalizing first-order representations lend themselves to set-valued features.

  3. Does hearing two dialects at different times help infants learn dialect-specific rules?

    PubMed Central

    Gonzales, Kalim; Gerken, LouAnn; Gómez, Rebecca L.

    2015-01-01

    Infants might be better at teasing apart dialects with different language rules when hearing the dialects at different times, since language learners do not always combine input heard at different times. However, no previous research has independently varied the temporal distribution of conflicting language input. Twelve-month-olds heard two artificial language streams representing different dialects—a “pure stream” whose sentences adhered to abstract grammar rules like aX bY, and a “mixed stream” wherein any a- or b-word could precede any X- or Y-word. Infants were then tested for generalization of the pure stream’s rules to novel sentences. Supporting our hypothesis, infants showed generalization when the two streams’ sentences alternated in minutes-long intervals without any perceptually salient change across streams (Experiment 2), but not when all sentences from these same streams were randomly interleaved (Experiment 3). Results are interpreted in light of temporal context effects in word learning. PMID:25880342

  4. Analogical scaffolding and the learning of abstract ideas in physics: Empirical studies

    NASA Astrophysics Data System (ADS)

    Podolefsky, Noah S.; Finkelstein, Noah D.

    2007-12-01

    Previously, we proposed a model of student reasoning which combines the roles of representation, analogy, and layering of meaning—analogical scaffolding [Podolefsky and Finkelstein, Phys. Rev. ST Phys. Educ. Res. 3, 010109 (2007)]. The present empirical studies build on this model to examine its utility and demonstrate the vital intertwining of representation, analogy, and conceptual learning in physics. In two studies of student reasoning using analogy, we show that representations couple to students’ existing prior knowledge and also lead to the dynamic formation of new knowledge. Students presented with abstract, concrete, or blended (both abstract and concrete) representations produced markedly different response patterns. In the first study, using analogies to scaffold understanding of electromagnetic (EM) waves, students in the blend group were more likely to reason productively about EM waves than students in the abstract group by as much as a factor of 3 (73% vs 24% correct, p=0.002 ). In the second study, examining representation use within one domain (sound waves), the blend group was more likely to reason productively about sound waves than the abstract group by as much as a factor of 2 (48% vs 23% correct, p=0.002 ). Using the analogical scaffolding model we examine when and why students succeed and fail to use analogies and interpret representations appropriately.

  5. Rule learning enhances structural plasticity of long-range axons in frontal cortex

    PubMed Central

    Johnson, Carolyn M.; Peckler, Hannah; Tai, Lung-Hao; Wilbrecht, Linda

    2016-01-01

    Rules encompass cue-action-outcome associations used to guide decisions and strategies in a specific context. Subregions of the frontal cortex including the orbitofrontal cortex (OFC) and dorsomedial prefrontal cortex (dmPFC) are implicated in rule learning, although changes in structural connectivity underlying rule learning are poorly understood. We imaged OFC axonal projections to dmPFC during training in a multiple choice foraging task and used a reinforcement learning model to quantify explore–exploit strategy use and prediction error magnitude. Here we show that rule training, but not experience of reward alone, enhances OFC bouton plasticity. Baseline bouton density and gains during training correlate with rule exploitation, while bouton loss correlates with exploration and scales with the magnitude of experienced prediction errors. We conclude that rule learning sculpts frontal cortex interconnectivity and adjusts a thermostat for the explore–exploit balance. PMID:26949122

  6. Learning Problem-Solving Rules as Search through a Hypothesis Space

    ERIC Educational Resources Information Center

    Lee, Hee Seung; Betts, Shawn; Anderson, John R.

    2016-01-01

    Learning to solve a class of problems can be characterized as a search through a space of hypotheses about the rules for solving these problems. A series of four experiments studied how different learning conditions affected the search among hypotheses about the solution rule for a simple computational problem. Experiment 1 showed that a problem…

  7. A self-learning rule base for command following in dynamical systems

    NASA Technical Reports Server (NTRS)

    Tsai, Wei K.; Lee, Hon-Mun; Parlos, Alexander

    1992-01-01

    In this paper, a self-learning Rule Base for command following in dynamical systems is presented. The learning is accomplished though reinforcement learning using an associative memory called SAM. The main advantage of SAM is that it is a function approximator with explicit storage of training samples. A learning algorithm patterned after the dynamic programming is proposed. Two artificially created, unstable dynamical systems are used for testing, and the Rule Base was used to generate a feedback control to improve the command following ability of the otherwise uncontrolled systems. The numerical results are very encouraging. The controlled systems exhibit a more stable behavior and a better capability to follow reference commands. The rules resulting from the reinforcement learning are explicitly stored and they can be modified or augmented by human experts. Due to overlapping storage scheme of SAM, the stored rules are similar to fuzzy rules.

  8. Imitation as a mechanism in cognitive development: a cross-cultural investigation of 4-year-old children's rule learning.

    PubMed

    Wang, Zhidan; Williamson, Rebecca A; Meltzoff, Andrew N

    2015-01-01

    Children learn about the social and physical world by observing other people's acts. This experiment tests both Chinese and American children's learning of a rule. For theoretical reasons we chose the rule of categorizing objects by the weight. Children, age 4 years, saw an adult heft four visually-identical objects and sort them into two bins based on an invisible property-the object's weight. Children who saw this categorization behavior were more likely to sort those objects by weight than were children who saw control actions using the same objects and the same bins. Crucially, children also generalized to a novel set of objects with no further demonstration, suggesting rule learning. We also report that high-fidelity imitation of the adult's "hefting" acts may give children crucial experience with the objects' weights, which could then be used to infer the more abstract rule. The connection of perception, action, and cognition was found in children from both cultures, which leads to broad implications for how the imitation of adults' acts functions as a lever in cognitive development.

  9. Posterror slowing predicts rule-based but not information-integration category learning.

    PubMed

    Tam, Helen; Maddox, W Todd; Huang-Pollock, Cynthia L

    2013-12-01

    We examined whether error monitoring, operationalized as the degree to which individuals slow down after committing an error (i.e., posterror slowing), is differentially important in the learning of rule-based versus information-integration category structures. Rule-based categories are most efficiently solved through the application of an explicit verbal strategy (e.g., "sort by color"). In contrast, information-integration categories are believed to be learned in a trial-by-trial, associative manner. Our results indicated that posterror slowing predicts enhanced rule-based but not information-integration category learning. Implications for multiple category-learning systems are discussed.

  10. Multivariate cross-classification: applying machine learning techniques to characterize abstraction in neural representations

    PubMed Central

    Kaplan, Jonas T.; Man, Kingson; Greening, Steven G.

    2015-01-01

    Here we highlight an emerging trend in the use of machine learning classifiers to test for abstraction across patterns of neural activity. When a classifier algorithm is trained on data from one cognitive context, and tested on data from another, conclusions can be drawn about the role of a given brain region in representing information that abstracts across those cognitive contexts. We call this kind of analysis Multivariate Cross-Classification (MVCC), and review several domains where it has recently made an impact. MVCC has been important in establishing correspondences among neural patterns across cognitive domains, including motor-perception matching and cross-sensory matching. It has been used to test for similarity between neural patterns evoked by perception and those generated from memory. Other work has used MVCC to investigate the similarity of representations for semantic categories across different kinds of stimulus presentation, and in the presence of different cognitive demands. We use these examples to demonstrate the power of MVCC as a tool for investigating neural abstraction and discuss some important methodological issues related to its application. PMID:25859202

  11. Concurrence of rule- and similarity-based mechanisms in artificial grammar learning.

    PubMed

    Opitz, Bertram; Hofmann, Juliane

    2015-03-01

    A current theoretical debate regards whether rule-based or similarity-based learning prevails during artificial grammar learning (AGL). Although the majority of findings are consistent with a similarity-based account of AGL it has been argued that these results were obtained only after limited exposure to study exemplars, and performance on subsequent grammaticality judgment tests has often been barely above chance level. In three experiments the conditions were investigated under which rule- and similarity-based learning could be applied. Participants were exposed to exemplars of an artificial grammar under different (implicit and explicit) learning instructions. The analysis of receiver operating characteristics (ROC) during a final grammaticality judgment test revealed that explicit but not implicit learning led to rule knowledge. It also demonstrated that this knowledge base is built up gradually while similarity knowledge governed the initial state of learning. Together these results indicate that rule- and similarity-based mechanisms concur during AGL. Moreover, it could be speculated that two different rule processes might operate in parallel; bottom-up learning via gradual rule extraction and top-down learning via rule testing. Crucially, the latter is facilitated by performance feedback that encourages explicit hypothesis testing.

  12. Learning Syntactic Rules and Tags with Genetic Algorithms for Information Retrieval and Filtering: An Empirical Basis for Grammatical Rules.

    ERIC Educational Resources Information Center

    Losee, Robert M.

    1996-01-01

    The grammars of natural languages may be learned by using genetic algorithm systems such as LUST (Linguistics Using Sexual Techniques) that reproduce and mutate grammatical rules and parts-of-speech tags. In document retrieval or filtering systems, applying tags to the list of terms representing a document provides additional information about…

  13. Rule learning over consonants and vowels in a non-human animal

    PubMed Central

    de la Mora, Daniela M.; Toro, Juan M.

    2014-01-01

    Perception studies have shown similarities between humans and other animals in a wide array of language-related processes. However, the components of language that make it uniquely human have not been fully identified. Here we show that nonhuman animals extract rules over speech sequences that are difficult for humans. Specifically, animals easily learn rules over both consonants and vowels, while humans do it only over vowels. In Experiment 1, rats learned a rule implemented over vowels in CVCVCV nonsense words. In Experiment 2, rats learned the rule when it was implemented over the consonants. In both experiments, rats generalized such knowledge to novel words they had not heard before. Using the same stimuli, human adults learned the rules over the vowels but not over the consonants. These results suggest differences between humans and animals on speech processing might lie on the constraints they face while extracting information from the signal. PMID:23121712

  14. Rule learning over consonants and vowels in a non-human animal.

    PubMed

    de la Mora, Daniela M; Toro, Juan M

    2013-02-01

    Perception studies have shown similarities between humans and other animals in a wide array of language-related processes. However, the components of language that make it uniquely human have not been fully identified. Here we show that nonhuman animals extract rules over speech sequences that are difficult for humans. Specifically, animals easily learn rules over both consonants and vowels, while humans do it only over vowels. In Experiment 1, rats learned a rule implemented over vowels in CVCVCV nonsense words. In Experiment 2, rats learned the rule when it was implemented over the consonants. In both experiments, rats generalized such knowledge to novel words they had not heard before. Using the same stimuli, human adults learned the rules over the vowels but not over the consonants. These results suggest differences between humans and animals on speech processing might lie on the constraints they face while extracting information from the signal.

  15. Costs and benefits of automatization in category learning of ill-defined rules.

    PubMed

    Raijmakers, Maartje E J; Schmittmann, Verena D; Visser, Ingmar

    2014-03-01

    Learning ill-defined categories (such as the structure of Medin & Schaffer, 1978) involves multiple learning systems and different corresponding category representations, which are difficult to detect. Application of latent Markov analysis allows detection and investigation of such multiple latent category representations in a statistically robust way, isolating low performers and quantifying shifts between latent strategies. We reanalyzed data from three experiments presented in Johansen and Palmeri (2002), which comprised prolonged training of ill-defined categories, with the aim of studying the changing interactions between underlying learning systems. Our results broadly confirm the original conclusion that, in most participants, learning involved a shift from a rule-based to an exemplar-based strategy. Separate analyses of latent strategies revealed that (a) shifts from a rule-based to an exemplar-based strategy resulted in an initial decrease of speed and an increase of accuracy; (b) exemplar-based strategies followed a power law of learning, indicating automatization once an exemplar-based strategy was used; (c) rule-based strategies changed from using pure rules to rules-plus-exceptions, which appeared as a dual processes as indicated by the accuracy and response-time profiles. Results suggest an additional pathway of learning ill-defined categories, namely involving a shift from a simple rule to a complex rule after which this complex rule is automatized as an exemplar-based strategy.

  16. Teaching with Concrete and Abstract Visual Representations: Effects on Students' Problem Solving, Problem Representations, and Learning Perceptions

    ERIC Educational Resources Information Center

    Moreno, Roxana; Ozogul, Gamze; Reisslein, Martin

    2011-01-01

    In 3 experiments, we examined the effects of using concrete and/or abstract visual problem representations during instruction on students' problem-solving practice, near transfer, problem representations, and learning perceptions. In Experiments 1 and 2, novice students learned about electrical circuit analysis with an instructional program that…

  17. Bigger Knows Better: Young Children Selectively Learn Rule Games from Adults Rather than from Peers

    ERIC Educational Resources Information Center

    Rakoczy, Hannes; Hamann, Katharina; Warneken, Felix; Tomasello, Michael

    2010-01-01

    Preschoolers' selective learning from adult versus peer models was investigated. Extending previous research, children from age 3 were shown to selectively learn simple rule games from adult rather than peer models. Furthermore, this selective learning was not confined to preferentially performing certain acts oneself, but more specifically had a…

  18. The evolution of social learning rules: payoff-biased and frequency-dependent biased transmission.

    PubMed

    Kendal, Jeremy; Giraldeau, Luc-Alain; Laland, Kevin

    2009-09-21

    Humans and other animals do not use social learning indiscriminately, rather, natural selection has favoured the evolution of social learning rules that make selective use of social learning to acquire relevant information in a changing environment. We present a gene-culture coevolutionary analysis of a small selection of such rules (unbiased social learning, payoff-biased social learning and frequency-dependent biased social learning, including conformism and anti-conformism) in a population of asocial learners where the environment is subject to a constant probability of change to a novel state. We define conditions under which each rule evolves to a genetically polymorphic equilibrium. We find that payoff-biased social learning may evolve under high levels of environmental variation if the fitness benefit associated with the acquired behaviour is either high or low but not of intermediate value. In contrast, both conformist and anti-conformist biases can become fixed when environment variation is low, whereupon the mean fitness in the population is higher than for a population of asocial learners. Our examination of the population dynamics reveals stable limit cycles under conformist and anti-conformist biases and some highly complex dynamics including chaos. Anti-conformists can out-compete conformists when conditions favour a low equilibrium frequency of the learned behaviour. We conclude that evolution, punctuated by the repeated successful invasion of different social learning rules, should continuously favour a reduction in the equilibrium frequency of asocial learning, and propose that, among competing social learning rules, the dominant rule will be the one that can persist with the lowest frequency of asocial learning.

  19. Reinforcement learning, spike-time-dependent plasticity, and the BCM rule.

    PubMed

    Baras, Dorit; Meir, Ron

    2007-08-01

    Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is influenced by an environmental signal, termed a reward, that directs the changes in appropriate directions. We apply a recently introduced policy learning algorithm from machine learning to networks of spiking neurons and derive a spike-time-dependent plasticity rule that ensures convergence to a local optimum of the expected average reward. The approach is applicable to a broad class of neuronal models, including the Hodgkin-Huxley model. We demonstrate the effectiveness of the derived rule in several toy problems. Finally, through statistical analysis, we show that the synaptic plasticity rule established is closely related to the widely used BCM rule, for which good biological evidence exists.

  20. Developing a Learning Progression for Number Sense Based on the Rule Space Model in China

    ERIC Educational Resources Information Center

    Chen, Fu; Yan, Yue; Xin, Tao

    2017-01-01

    The current study focuses on developing the learning progression of number sense for primary school students, and it applies a cognitive diagnostic model, the rule space model, to data analysis. The rule space model analysis firstly extracted nine cognitive attributes and their hierarchy model from the analysis of previous research and the…

  1. The Effect of Adaptive, Advisement, and Linear CAI Control Strategies on the Learning of Mathematics Rules.

    ERIC Educational Resources Information Center

    Goetzfried, Leslie; Hannafin, Michael

    This study examined the effects of the locus of three computer assisted instruction (CAI) strategies on the accuracy and efficiency of mathematics rule and application learning of 47 low-achieving seventh grade students in remedial mathematics classes. The instructional task was a mathematics rule lesson concerning divisibility by the numbers two,…

  2. Ensemble learning with trees and rules: supervised, semi-supervised, unsupervised

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In this article, we propose several new approaches for post processing a large ensemble of conjunctive rules for supervised and semi-supervised learning problems. We show with various examples that for high dimensional regression problems the models constructed by the post processing the rules with ...

  3. RuleML-Based Learning Object Interoperability on the Semantic Web

    ERIC Educational Resources Information Center

    Biletskiy, Yevgen; Boley, Harold; Ranganathan, Girish R.

    2008-01-01

    Purpose: The present paper aims to describe an approach for building the Semantic Web rules for interoperation between heterogeneous learning objects, namely course outlines from different universities, and one of the rule uses: identifying (in)compatibilities between course descriptions. Design/methodology/approach: As proof of concept, a rule…

  4. A universal learning rule that minimizes well-formed cost functions.

    PubMed

    Mora-Jiménez, Inma; Cid-Sueiro, Jesús

    2005-07-01

    In this paper, we analyze stochastic gradient learning rules for posterior probability estimation using networks with a single layer of weights and a general nonlinear activation function. We provide necessary and sufficient conditions on the learning rules and the activation function to obtain probability estimates. Also, we extend the concept of well-formed cost function, proposed by Wittner and Denker, to multiclass problems, and we provide theoretical results showing the advantages of this kind of objective functions.

  5. Rule-based and information-integration category learning in normal aging.

    PubMed

    Maddox, W Todd; Pacheco, Jennifer; Reeves, Maia; Zhu, Bo; Schnyer, David M

    2010-08-01

    The basal ganglia and prefrontal cortex play critical roles in category learning. Both regions evidence age-related structural and functional declines. The current study examined rule-based and information-integration category learning in a group of older and younger adults. Rule-based learning is thought to involve explicit, frontally mediated processes, whereas information-integration is thought to involve implicit, striatally mediated processes. As a group, older adults showed rule-based and information-integration deficits. A series of models were applied that provided insights onto the type of strategy used to solve the task. Interestingly, when the analyses focused only on participants who used the task appropriate strategy in the final block of trials, the age-related rule-based deficit disappeared whereas the information-integration deficit remained. For this group of individuals, the final block information-integration deficit was due to less consistent application of the task appropriate strategy by older adults, and over the course of learning these older adults shifted from an explicit hypothesis-testing strategy to the task appropriate strategy later in learning. In addition, the use of the task appropriate strategy was associated with less interference and better inhibitory control for rule-based and information-information learning, whereas use of the task appropriate strategy was associated with greater working memory and better new verbal learning only for the rule-based task. These results suggest that normal aging impacts both forms of category learning and that there are some important similarities and differences in the explanatory locus of these deficits. The data also support a two-component model of information-integration category learning that includes a striatal component that mediated procedural-based learning, and a prefrontal cortical component that mediates the transition from hypothesis-testing to procedural-based strategies

  6. A Computational Framework for Understanding Decision Making through Integration of Basic Learning Rules

    PubMed Central

    Bazhenov, Maxim; Huerta, Ramon; Smith, Brian H.

    2013-01-01

    Nonassociative and associative learning rules simultaneously modify neural circuits. However, it remains unclear how these forms of plasticity interact to produce conditioned responses. Here we integrate nonassociative and associative conditioning within a uniform model of olfactory learning in the honeybee. Honeybees show a fairly abrupt increase in response after a number of conditioning trials. The occurrence of this abrupt change takes many more trials after exposure to nonassociative trials than just using associative conditioning. We found that the interaction of unsupervised and supervised learning rules is critical for explaining latent inhibition phenomenon. Associative conditioning combined with the mutual inhibition between the output neurons produces an abrupt increase in performance despite smooth changes of the synaptic weights. The results show that an integrated set of learning rules implemented using fan-out connectivities together with neural inhibition can explain the broad range of experimental data on learning behaviors. PMID:23536082

  7. Age affects chunk-based, but not rule-based learning in artificial grammar acquisition.

    PubMed

    Kürten, Julia; De Vries, Meinou H; Kowal, Kristina; Zwitserlood, Pienie; Flöel, Agnes

    2012-07-01

    Explicit learning is well known to decline with age, but divergent results have been reported for implicit learning. Here, we assessed the effect of aging on implicit vs. explicit learning within the same task. Fifty-five young (mean 32 years) and 55 elderly (mean 64 years) individuals were exposed to letter strings generated by an artificial grammar. Subsequently, participants classified novel strings as grammatical or nongrammatical. Acquisition of superficial ("chunk-based") and structural ("rule-based") features of the grammar were analyzed separately. We found that overall classification accuracy was diminished in the elderly, driven by decreased performance on items that required chunk-based knowledge. Performance on items requiring rule-based knowledge was comparable between groups. Results indicate that rule-based and chunk-based learning are differentially affected by age: while rule-based learning, reflecting implicit learning, is preserved, chunk-based learning, which contains at least some explicit learning aspects, declines with age. Our findings may explain divergent results on implicit learning tasks in previous studies on aging. They may also help to better understand compensatory mechanisms during the aging process.

  8. 8-Month-Old Infants Spontaneously Learn and Generalize Hierarchical Rules

    PubMed Central

    Werchan, Denise M.; Collins, Anne G. E.; Frank, Michael J.; Amso, Dima

    2015-01-01

    The ability to extract hierarchically organized rule structures from noisy environments is critical to human cognitive, social, and emotional intelligence. Adults spontaneously create hierarchical rule structures of this sort. In the present research, we conducted two experiments to examine the previously unknown developmental origins of this hallmark skill. In Experiment 1, we exploited a visual paradigm previously shown to elicit incidental hierarchical rule learning in adults. In Experiment 2, we used the same learning structure to examine whether these hierarchical-rule-learning mechanisms are domain general and can help infants learn spoken object-label mappings across different speaker contexts. In both experiments, we found that 8-month-olds created and generalized hierarchical rules during learning. Eyeblink rate, an exploratory indicator of striatal dopamine activity, mirrored behavioral-learning patterns. Our results provide direct evidence that the human brain is predisposed to extract knowledge from noisy environments, and they add a fundamental learning mechanism to what is currently known about the neurocognitive toolbox available to infants. PMID:25878172

  9. 8-month-old infants spontaneously learn and generalize hierarchical rules.

    PubMed

    Werchan, Denise M; Collins, Anne G E; Frank, Michael J; Amso, Dima

    2015-06-01

    The ability to extract hierarchically organized rule structures from noisy environments is critical to human cognitive, social, and emotional intelligence. Adults spontaneously create hierarchical rule structures of this sort. In the present research, we conducted two experiments to examine the previously unknown developmental origins of this hallmark skill. In Experiment 1, we exploited a visual paradigm previously shown to elicit incidental hierarchical rule learning in adults. In Experiment 2, we used the same learning structure to examine whether these hierarchical-rule-learning mechanisms are domain general and can help infants learn spoken object-label mappings across different speaker contexts. In both experiments, we found that 8-month-olds created and generalized hierarchical rules during learning. Eyeblink rate, an exploratory indicator of striatal dopamine activity, mirrored behavioral-learning patterns. Our results provide direct evidence that the human brain is predisposed to extract knowledge from noisy environments, and they add a fundamental learning mechanism to what is currently known about the neurocognitive toolbox available to infants.

  10. Concurrent cognitive processes in rat serial pattern learning: II. Discrimination learning, rule learning, chunk length, and multiple-item memories.

    PubMed

    Muller, Melissa D; Fountain, Stephen B

    2016-01-01

    The current experiment examined the factors that determine acquisition for elements of highly structured serial patterns. Three groups of rats were trained on three patterns with parallel rule-based hierarchical structure, but with 3-, 4-, or 5-element chunks, each with a final violation element. Once rats mastered their patterns, probe patterns were introduced to answer several questions. To assess the extent to which the learned response pattern depended on intrachamber location cues for anticipating different element types, Spatial Shift Probes shifted the starting lever of patterns to locations that positioned chunk boundaries where they had never been experienced during training. To assess the extent to which a phrasing cue is necessary for rats to perform a chunk-boundary response, a Cue Removal Probe tested whether rats would produce a chunk-boundary response in the correct serial position if the phrasing cue was omitted. To assess the extent to which cues from multiple trials leading up to the violation element are required to anticipate the violation element, Multiple-Item Memory Probes required rats to make an unexpected response on one of the elements in the last two chunks of the pattern prior to the violation element. The results indicated that rats used multiple concurrent learning and memory processes to master serial patterns, including discrimination learning, rule learning, encoding of chunk length, and multiple-item memories.

  11. Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

    NASA Technical Reports Server (NTRS)

    Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

    1988-01-01

    Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

  12. Prefrontal Contributions to Rule-Based and Information-Integration Category Learning

    ERIC Educational Resources Information Center

    Schnyer, David M.; Maddox, W. Todd; Ell, Shawn; Davis, Sarah; Pacheco, Jenni; Verfaellie, Mieke

    2009-01-01

    Previous research revealed that the basal ganglia play a critical role in category learning [Ell, S. W., Marchant, N. L., & Ivry, R. B. (2006). "Focal putamen lesions impair learning in rule-based, but not information-integration categorization tasks." "Neuropsychologia", 44(10), 1737-1751; Maddox, W. T. & Filoteo, J.…

  13. How Do Infants and Toddlers Learn the Rules? Family Discipline and Young Children

    ERIC Educational Resources Information Center

    Smith, Anne B.

    2004-01-01

    This paper examines the issue of how under three year-olds learn the rules of appropriate behaviour in the light of sociocultural, attachment, social learning, ecological theory and sociology of childhood theories. Discipline involves teaching children how to behave acceptably in their family and society, while physical punishment is the use of…

  14. Dog Is a Dog Is a Dog: Infant Rule Learning Is Not Specific to Language

    ERIC Educational Resources Information Center

    Saffran, Jenny R.; Pollak, Seth D.; Seibel, Rebecca L.; Shkolnik, Anna

    2007-01-01

    Human infants possess powerful learning mechanisms used for the acquisition of language. To what extent are these mechanisms domain specific? One well-known infant language learning mechanism is the ability to detect and generalize rule-like similarity patterns, such as ABA or ABB [Marcus, G. F., Vijayan, S., Rao, S. B., & Vishton, P. M. (1999).…

  15. Research Abstracts.

    ERIC Educational Resources Information Center

    Plotnick, Eric

    2001-01-01

    Presents research abstracts from the ERIC Clearinghouse on Information and Technology. Topics include: classroom communication apprehension and distance education; outcomes of a distance-delivered science course; the NASA/Kennedy Space Center Virtual Science Mentor program; survey of traditional and distance learning higher education members;…

  16. Research Abstracts.

    ERIC Educational Resources Information Center

    Plotnik, Eric

    2001-01-01

    Presents six research abstracts from the ERIC (Educational Resources Information Center) database. Topics include: effectiveness of distance versus traditional on-campus education; improved attribution recall from diversification of environmental context during computer-based instruction; qualitative analysis of situated Web-based learning;…

  17. Multi Objective Dynamic Job Shop Scheduling using Composite Dispatching Rule and Reinforcement Learning

    NASA Astrophysics Data System (ADS)

    Chen, Xili; Hao, Xinchang; Lin, Hao Wen; Murata, Tomohiro

    The applications of composite dispatching rules for multi objective dynamic scheduling have been widely studied in literature. In general, a composite dispatching rule is a combination of several elementary dispatching rules, which is designed to optimize multiple objectives of interest under a certain scheduling environment. The relative importance of elementary dispatching rules is modeled by weight factors. A critical issue for implementation of composite dispatching rule is that the inappropriate weight values may result in poor performance. This paper presents an offline scheduling knowledge acquisition method based on reinforcement learning using simulation technique. The scheduling knowledge is applied to adjust the appropriate weight values of elementary dispatching rules in composite manner with respect to work in process fluctuation of machines during online scheduling. Implementation of the proposed method in a two objectives dynamic job shop scheduling problem is demonstrated and the results are satisfactory.

  18. Rule-based mechanisms of learning for intelligent adaptive flight control

    NASA Technical Reports Server (NTRS)

    Handelman, David A.; Stengel, Robert F.

    1990-01-01

    How certain aspects of human learning can be used to characterize learning in intelligent adaptive control systems is investigated. Reflexive and declarative memory and learning are described. It is shown that model-based systems-theoretic adaptive control methods exhibit attributes of reflexive learning, whereas the problem-solving capabilities of knowledge-based systems of artificial intelligence are naturally suited for implementing declarative learning. Issues related to learning in knowledge-based control systems are addressed, with particular attention given to rule-based systems. A mechanism for real-time rule-based knowledge acquisition is suggested, and utilization of this mechanism within the context of failure diagnosis for fault-tolerant flight control is demonstrated.

  19. Birth of an Abstraction: A Dynamical Systems Account of the Discovery of an Elsewhere Principle in a Category Learning Task

    ERIC Educational Resources Information Center

    Tabor, Whitney; Cho, Pyeong W.; Dankowicz, Harry

    2013-01-01

    Human participants and recurrent ("connectionist") neural networks were both trained on a categorization system abstractly similar to natural language systems involving irregular ("strong") classes and a default class. Both the humans and the networks exhibited staged learning and a generalization pattern reminiscent of the…

  20. Mathematical properties of neuronal TD-rules and differential Hebbian learning: a comparison.

    PubMed

    Kolodziejski, Christoph; Porr, Bernd; Wörgötter, Florentin

    2008-03-01

    A confusingly wide variety of temporally asymmetric learning rules exists related to reinforcement learning and/or to spike-timing dependent plasticity, many of which look exceedingly similar, while displaying strongly different behavior. These rules often find their use in control tasks, for example in robotics and for this rigorous convergence and numerical stability is required. The goal of this article is to review these rules and compare them to provide a better overview over their different properties. Two main classes will be discussed: temporal difference (TD) rules and correlation based (differential hebbian) rules and some transition cases. In general we will focus on neuronal implementations with changeable synaptic weights and a time-continuous representation of activity. In a machine learning (non-neuronal) context, for TD-learning a solid mathematical theory has existed since several years. This can partly be transferred to a neuronal framework, too. On the other hand, only now a more complete theory has also emerged for differential Hebb rules. In general rules differ by their convergence conditions and their numerical stability, which can lead to very undesirable behavior, when wanting to apply them. For TD, convergence can be enforced with a certain output condition assuring that the delta-error drops on average to zero (output control). Correlation based rules, on the other hand, converge when one input drops to zero (input control). Temporally asymmetric learning rules treat situations where incoming stimuli follow each other in time. Thus, it is necessary to remember the first stimulus to be able to relate it to the later occurring second one. To this end different types of so-called eligibility traces are being used by these two different types of rules. This aspect leads again to different properties of TD and differential Hebbian learning as discussed here. Thus, this paper, while also presenting several novel mathematical results, is mainly

  1. Transfer in Rule-Based Category Learning Depends on the Training Task

    PubMed Central

    Kattner, Florian; Cox, Christopher R.; Green, C. Shawn

    2016-01-01

    While learning is often highly specific to the exact stimuli and tasks used during training, there are cases where training results in learning that generalizes more broadly. It has been previously argued that the degree of specificity can be predicted based upon the learning solution(s) dictated by the particular demands of the training task. Here we applied this logic in the domain of rule-based categorization learning. Participants were presented with stimuli corresponding to four different categories and were asked to perform either a category discrimination task (which permits learning specific rule to discriminate two categories) or a category identification task (which does not permit learning a specific discrimination rule). In a subsequent transfer stage, all participants were asked to discriminate stimuli belonging to two of the categories which they had seen, but had never directly discriminated before (i.e., this particular discrimination was omitted from training). As predicted, learning in the category-discrimination tasks tended to be specific, while the category-identification task produced learning that transferred to the transfer discrimination task. These results suggest that the discrimination and identification tasks fostered the acquisition of different category representations which were more or less generalizable. PMID:27764221

  2. Using Rules and Task Division to Augment Connectionist Learning

    DTIC Science & Technology

    1988-07-01

    and an output layer. During training , each module received input and output information for each stage and propagated error only within its own stage...variables input condition and 50-trial block did not significantly interact, F(5,75)=1.15, p>.34. In summary, the initial 216 trials of training brought the...learning, we modelled learning of 2-, 4- and 6-input gates. The networks trained with backpropagation were feed-forward networks having either 6, 8 or

  3. Wavefront reconstruction by machine learning using the delta rule

    NASA Astrophysics Data System (ADS)

    Angel, J. Roger P.

    1994-05-01

    In this paper we use phase screen models to illustrate the power of the delta rule, by obtaining the optimum reconstructor for a Shack-Hartmann sensor with just 6 subapertures in the form of pie segments. The dependence of the matrix elements and residual error on measurement noise is determined, and the accuracy compared with theoretical limits. Reconstructors for more complex problems involving time dependence and multiple laser spots are ideal applications for the method.

  4. An Approach to the Design of Mathematical Task Sequences: Conceptual Learning as Abstraction

    ERIC Educational Resources Information Center

    Simon, Martin A.

    2016-01-01

    This paper describes an emerging approach to the design of task sequences and the theory that undergirds it. The approach aims at promoting particular mathematical concepts, understood as the result of reflective abstraction. Central to this approach is the identification of available student activities from which students can abstract the…

  5. Inferring learning rules from distribution of firing rates in cortical neurons

    PubMed Central

    Lim, Sukbin; McKee, Jillian L.; Woloszyn, Luke; Amit, Yali; Freedman, David J.; Sheinberg, David L.; Brunel, Nicolas

    2015-01-01

    Information about external stimuli is thought to be stored in cortical circuits through experience-dependent modifications of synaptic connectivity. These modifications of network connectivity should lead to changes in neuronal activity, as a particular stimulus is repeatedly encountered. Here, we ask what plasticity rules are consistent with the differences in the statistics of the visual response to novel and familiar stimuli in inferior temporal cortex, an area underlying visual object recognition. We introduce a method that allows inferring the dependence of the ‘learning rule’ on post-synaptic firing rate, and show that the inferred learning rule exhibits depression for low post-synaptic rates and potentiation for high rates. The threshold separating depression from potentiation is strongly correlated with both mean and standard deviation of the firing rate distribution. Finally, we show that network models implementing a rule extracted from data show stable learning dynamics, and lead to sparser representations of stimuli. PMID:26523643

  6. Rule Based Category Learning in Patients with Parkinson’s Disease

    PubMed Central

    Price, Amanda; Filoteo, J. Vincent; Maddox, W. Todd

    2009-01-01

    Measures of explicit rule-based category learning are commonly used in neuropsychological evaluation of individuals with Parkinson’s disease (PD) and the pattern of PD performance on these measures tends to be highly varied. We review the neuropsychological literature to clarify the manner in which PD affects the component processes of rule-based category learning and work to identify and resolve discrepancies within this literature. In particular, we address the manner in which PD and its common treatments affect the processes of rule generation, maintenance, shifting and selection. We then integrate the neuropsychological research with relevant neuroimaging and computational modeling evidence to clarify the neurobiological impact of PD on each process. Current evidence indicates that neurochemical changes associated with PD primarily disrupt rule shifting, and may disturb feedback-mediated learning processes that guide rule selection. Although surgical and pharmacological therapies remediate this deficit, it appears that the same treatments may contribute to impaired rule generation, maintenance and selection processes. These data emphasize the importance of distinguishing between the impact of PD and its common treatments when considering the neuropsychological profile of the disease. PMID:19428385

  7. Neural learning rules for the vestibulo-ocular reflex

    NASA Technical Reports Server (NTRS)

    Raymond, J. L.; Lisberger, S. G.

    1998-01-01

    Mechanisms for the induction of motor learning in the vestibulo-ocular reflex (VOR) were evaluated by recording the patterns of neural activity elicited in the cerebellum by a range of stimuli that induce learning. Patterns of climbing-fiber, vestibular, and Purkinje cell simple-spike signals were examined during sinusoidal head movement paired with visual image movement at stimulus frequencies from 0.5 to 10 Hz. A comparison of simple-spike and vestibular signals contained the information required to guide learning only at low stimulus frequencies, and a comparison of climbing-fiber and simple-spike signals contained the information required to guide learning only at high stimulus frequencies. Learning could be guided by comparison of climbing-fiber and vestibular signals at all stimulus frequencies tested, but only if climbing fiber responses were compared with the vestibular signals present 100 msec earlier. Computational analysis demonstrated that this conclusion is valid even if there is a broad range of vestibular signals at the site of plasticity. Simulations also indicated that the comparison of vestibular and climbing-fiber signals across the 100 msec delay must be implemented by a subcellular "eligibility" trace rather than by neural circuits that delay the vestibular inputs to the site of plasticity. The results suggest two alternative accounts of learning in the VOR. Either there are multiple mechanisms of learning that use different combinations of neural signals to drive plasticity, or there is a single mechanism tuned to climbing-fiber activity that follows activity in vestibular pathways by approximately 100 msec.

  8. Lexical distributional cues, but not situational cues, are readily used to learn abstract locative verb-structure associations.

    PubMed

    Twomey, Katherine E; Chang, Franklin; Ambridge, Ben

    2016-08-01

    Children must learn the structural biases of locative verbs in order to avoid making overgeneralisation errors (e.g., (∗)I filled water into the glass). It is thought that they use linguistic and situational information to learn verb classes that encode structural biases. In addition to situational cues, we examined whether children and adults could use the lexical distribution of nouns in the post-verbal noun phrase of transitive utterances to assign novel verbs to locative classes. In Experiment 1, children and adults used lexical distributional cues to assign verb classes, but were unable to use situational cues appropriately. In Experiment 2, adults generalised distributionally-learned classes to novel verb arguments, demonstrating that distributional information can cue abstract verb classes. Taken together, these studies show that human language learners can use a lexical distributional mechanism that is similar to that used by computational linguistic systems that use large unlabelled corpora to learn verb meaning.

  9. Learning and innovative elements of strategy adoption rules expand cooperative network topologies.

    PubMed

    Wang, Shijun; Szalay, Máté S; Zhang, Changshui; Csermely, Peter

    2008-04-09

    Cooperation plays a key role in the evolution of complex systems. However, the level of cooperation extensively varies with the topology of agent networks in the widely used models of repeated games. Here we show that cooperation remains rather stable by applying the reinforcement learning strategy adoption rule, Q-learning on a variety of random, regular, small-word, scale-free and modular network models in repeated, multi-agent Prisoner's Dilemma and Hawk-Dove games. Furthermore, we found that using the above model systems other long-term learning strategy adoption rules also promote cooperation, while introducing a low level of noise (as a model of innovation) to the strategy adoption rules makes the level of cooperation less dependent on the actual network topology. Our results demonstrate that long-term learning and random elements in the strategy adoption rules, when acting together, extend the range of network topologies enabling the development of cooperation at a wider range of costs and temptations. These results suggest that a balanced duo of learning and innovation may help to preserve cooperation during the re-organization of real-world networks, and may play a prominent role in the evolution of self-organizing, complex systems.

  10. A Machine Learning Approach to Discover Rules for Expressive Performance Actions in Jazz Guitar Music

    PubMed Central

    Giraldo, Sergio I.; Ramirez, Rafael

    2016-01-01

    Expert musicians introduce expression in their performances by manipulating sound properties such as timing, energy, pitch, and timbre. Here, we present a data driven computational approach to induce expressive performance rule models for note duration, onset, energy, and ornamentation transformations in jazz guitar music. We extract high-level features from a set of 16 commercial audio recordings (and corresponding music scores) of jazz guitarist Grant Green in order to characterize the expression in the pieces. We apply machine learning techniques to the resulting features to learn expressive performance rule models. We (1) quantitatively evaluate the accuracy of the induced models, (2) analyse the relative importance of the considered musical features, (3) discuss some of the learnt expressive performance rules in the context of previous work, and (4) assess their generailty. The accuracies of the induced predictive models is significantly above base-line levels indicating that the audio performances and the musical features extracted contain sufficient information to automatically learn informative expressive performance patterns. Feature analysis shows that the most important musical features for predicting expressive transformations are note duration, pitch, metrical strength, phrase position, Narmour structure, and tempo and key of the piece. Similarities and differences between the induced expressive rules and the rules reported in the literature were found. Differences may be due to the fact that most previously studied performance data has consisted of classical music recordings. Finally, the rules' performer specificity/generality is assessed by applying the induced rules to performances of the same pieces performed by two other professional jazz guitar players. Results show a consistency in the ornamentation patterns between Grant Green and the other two musicians, which may be interpreted as a good indicator for generality of the ornamentation rules

  11. A Machine Learning Approach to Discover Rules for Expressive Performance Actions in Jazz Guitar Music.

    PubMed

    Giraldo, Sergio I; Ramirez, Rafael

    2016-01-01

    Expert musicians introduce expression in their performances by manipulating sound properties such as timing, energy, pitch, and timbre. Here, we present a data driven computational approach to induce expressive performance rule models for note duration, onset, energy, and ornamentation transformations in jazz guitar music. We extract high-level features from a set of 16 commercial audio recordings (and corresponding music scores) of jazz guitarist Grant Green in order to characterize the expression in the pieces. We apply machine learning techniques to the resulting features to learn expressive performance rule models. We (1) quantitatively evaluate the accuracy of the induced models, (2) analyse the relative importance of the considered musical features, (3) discuss some of the learnt expressive performance rules in the context of previous work, and (4) assess their generailty. The accuracies of the induced predictive models is significantly above base-line levels indicating that the audio performances and the musical features extracted contain sufficient information to automatically learn informative expressive performance patterns. Feature analysis shows that the most important musical features for predicting expressive transformations are note duration, pitch, metrical strength, phrase position, Narmour structure, and tempo and key of the piece. Similarities and differences between the induced expressive rules and the rules reported in the literature were found. Differences may be due to the fact that most previously studied performance data has consisted of classical music recordings. Finally, the rules' performer specificity/generality is assessed by applying the induced rules to performances of the same pieces performed by two other professional jazz guitar players. Results show a consistency in the ornamentation patterns between Grant Green and the other two musicians, which may be interpreted as a good indicator for generality of the ornamentation rules.

  12. Learning rules for social foragers: implications for the producer-scrounger game and ideal free distribution theory.

    PubMed

    Beauchamp, G

    2000-11-07

    In population games, the optimal behaviour of a forager depends partly on courses of action selected by other individuals in the population. How individuals learn to allocate effort in foraging games involving frequency-dependent payoffs has been little examined. The performance of three different learning rules was investigated in several types of habitats in each of two population games. Learning rules allow individuals to weigh information about the past and the present and to choose among alternative patterns of behaviour. In the producer-scrounger game, foragers use producer to locate food patches and scrounger to exploit the food discoveries of others. In the ideal free distribution game, foragers that experience feeding interference from companions distribute themselves among heterogeneous food patches. In simulations of each population game, the use of different learning rules induced large variation in foraging behaviour, thus providing a tool to assess the relevance of each learning rule in experimental systems. Rare mutants using alternative learning rules often successfully invaded populations of foragers using other rules indicating that some learning rules are not stable when pitted against each other. Learning rules often closely approximated optimal behaviour in each population game suggesting that stimulus-response learning of contingencies created by foraging companions could be sufficient to perform at near-optimal level in two population games.

  13. Learning "Rules" of Practice within the Context of the Practicum Triad: A Case Study of Learning to Teach

    ERIC Educational Resources Information Center

    Chalies, Sebastien; Escalie, Guillaume; Stefano, Bertone; Clarke, Anthony

    2012-01-01

    This case study sought to determine the professional development circumstances in which a preservice teacher learned rules of practice (Wittgenstein, 1996) on practicum while interacting with a cooperating teacher and university supervisor. Borrowing from a theoretical conceptualization of teacher professional development based on the postulates…

  14. Fuzzy OLAP association rules mining-based modular reinforcement learning approach for multiagent systems.

    PubMed

    Kaya, Mehmet; Alhajj, Reda

    2005-04-01

    Multiagent systems and data mining have recently attracted considerable attention in the field of computing. Reinforcement learning is the most commonly used learning process for multiagent systems. However, it still has some drawbacks, including modeling other learning agents present in the domain as part of the state of the environment, and some states are experienced much less than others, or some state-action pairs are never visited during the learning phase. Further, before completing the learning process, an agent cannot exhibit a certain behavior in some states that may be experienced sufficiently. In this study, we propose a novel multiagent learning approach to handle these problems. Our approach is based on utilizing the mining process for modular cooperative learning systems. It incorporates fuzziness and online analytical processing (OLAP) based mining to effectively process the information reported by agents. First, we describe a fuzzy data cube OLAP architecture which facilitates effective storage and processing of the state information reported by agents. This way, the action of the other agent, not even in the visual environment. of the agent under consideration, can simply be predicted by extracting online association rules, a well-known data mining technique, from the constructed data cube. Second, we present a new action selection model, which is also based on association rules mining. Finally, we generalize not sufficiently experienced states, by mining multilevel association rules from the proposed fuzzy data cube. Experimental results obtained on two different versions of a well-known pursuit domain show the robustness and effectiveness of the proposed fuzzy OLAP mining based modular learning approach. Finally, we tested the scalability of the approach presented in this paper and compared it with our previous work on modular-fuzzy Q-learning and ordinary Q-learning.

  15. A biologically plausible learning rule for the Infomax on recurrent neural networks

    PubMed Central

    Hayakawa, Takashi; Kaneko, Takeshi; Aoyagi, Toshio

    2014-01-01

    A fundamental issue in neuroscience is to understand how neuronal circuits in the cerebral cortex play their functional roles through their characteristic firing activity. Several characteristics of spontaneous and sensory-evoked cortical activity have been reproduced by Infomax learning of neural networks in computational studies. There are, however, still few models of the underlying learning mechanisms that allow cortical circuits to maximize information and produce the characteristics of spontaneous and sensory-evoked cortical activity. In the present article, we derive a biologically plausible learning rule for the maximization of information retained through time in dynamics of simple recurrent neural networks. Applying the derived learning rule in a numerical simulation, we reproduce the characteristics of spontaneous and sensory-evoked cortical activity: cell-assembly-like repeats of precise firing sequences, neuronal avalanches, spontaneous replays of learned firing sequences and orientation selectivity observed in the primary visual cortex. We further discuss the similarity between the derived learning rule and the spike timing-dependent plasticity of cortical neurons. PMID:25505404

  16. A biologically plausible learning rule for the Infomax on recurrent neural networks.

    PubMed

    Hayakawa, Takashi; Kaneko, Takeshi; Aoyagi, Toshio

    2014-01-01

    A fundamental issue in neuroscience is to understand how neuronal circuits in the cerebral cortex play their functional roles through their characteristic firing activity. Several characteristics of spontaneous and sensory-evoked cortical activity have been reproduced by Infomax learning of neural networks in computational studies. There are, however, still few models of the underlying learning mechanisms that allow cortical circuits to maximize information and produce the characteristics of spontaneous and sensory-evoked cortical activity. In the present article, we derive a biologically plausible learning rule for the maximization of information retained through time in dynamics of simple recurrent neural networks. Applying the derived learning rule in a numerical simulation, we reproduce the characteristics of spontaneous and sensory-evoked cortical activity: cell-assembly-like repeats of precise firing sequences, neuronal avalanches, spontaneous replays of learned firing sequences and orientation selectivity observed in the primary visual cortex. We further discuss the similarity between the derived learning rule and the spike timing-dependent plasticity of cortical neurons.

  17. Meaningful Cultural Learning by Imitative Participation: The Case of Abstract Thinking in Primary School

    ERIC Educational Resources Information Center

    van Oers, Bert

    2012-01-01

    The article describes a theory-driven approach to meaningful learning in primary schools, based on the Vygotskian cultural-historical theory of human development and learning. This approach is elaborated into an educational concept called "developmental education" that is implemented in the Netherlands in many primary schools. In this…

  18. The Distributed Learning Effect for Children's Acquisition of an Abstract Syntactic Construction

    ERIC Educational Resources Information Center

    Ambridge, Ben; Theakston, Anna L.; Lieven, Elena V. M.; Tomasello, Michael

    2006-01-01

    In many cognitive domains, learning is more effective when exemplars are distributed over a number of sessions than when they are all presented within one session. The present study investigated this "distributed learning effect" with respect to English-speaking children's acquisition of a complex grammatical construction. Forty-eight children…

  19. An Examination of Strategy Implementation during Abstract Nonlinguistic Category Learning in Aphasia

    ERIC Educational Resources Information Center

    Vallila-Rohter, Sofia; Kiran, Swathi

    2015-01-01

    Purpose: Our purpose was to study strategy use during nonlinguistic category learning in aphasia. Method: Twelve control participants without aphasia and 53 participants with aphasia (PWA) completed a computerized feedback-based category learning task consisting of training and testing phases. Accuracy rates of categorization in testing phases…

  20. Enabling Active Learning. Conference Programme and Abstracts of the Association for Learning Technology Conference (1st, Hull, England, United Kingdom, September 19-21, 1994).

    ERIC Educational Resources Information Center

    Heath, Simon, Ed.

    This program for the 1994 Association for Learning Technology Conference provides a conference schedule and summarizes the presentations of the discussion workshops, hands-on workshops, live demonstrations, and poster sessions. Abstracts of the following papers presented at the conference are included: "The Conceptualisation Cycle" (J.…

  1. The Effectiveness of Education and Schooling Activities with Respect to Learning Styles on the Learning of Abstract and Tangible Concepts of Social Studies by Students

    ERIC Educational Resources Information Center

    Seker, Mustafa

    2013-01-01

    This research reviews the effects of education and schooling activities that are conducted with respect to different learning styles on the success of teaching abstract and tangible concepts of 6th Grade Social Studies, and researches whether the demographic variables (age, gender) of the students had any effect on this success levels. To do so, 2…

  2. Search for Minimal and Semi-Minimal Rule Sets in Incremental Learning of Context-Free and Definite Clause Grammars

    NASA Astrophysics Data System (ADS)

    Imada, Keita; Nakamura, Katsuhiko

    This paper describes recent improvements to Synapse system for incremental learning of general context-free grammars (CFGs) and definite clause grammars (DCGs) from positive and negative sample strings. An important feature of our approach is incremental learning, which is realized by a rule generation mechanism called “bridging” based on bottom-up parsing for positive samples and the search for rule sets. The sizes of rule sets and the computation time depend on the search strategies. In addition to the global search for synthesizing minimal rule sets and serial search, another method for synthesizing semi-optimum rule sets, we incorporate beam search to the system for synthesizing semi-minimal rule sets. The paper shows several experimental results on learning CFGs and DCGs, and we analyze the sizes of rule sets and the computation time.

  3. Beyond Motivation: History as a Method for Learning Meta-Discursive Rules in Mathematics

    ERIC Educational Resources Information Center

    Kjeldsen, Tinne Hoff; Blomhoj, Morten

    2012-01-01

    In this paper, we argue that history might have a profound role to play for learning mathematics by providing a self-evident (if not indispensable) strategy for revealing meta-discursive rules in mathematics and turning them into explicit objects of reflection for students. Our argument is based on Sfard's theory of "Thinking as Communicating",…

  4. Applying the Rule Space Model to Develop a Learning Progression for Thermochemistry

    NASA Astrophysics Data System (ADS)

    Chen, Fu; Zhang, Shanshan; Guo, Yanfang; Xin, Tao

    2016-11-01

    We used the Rule Space Model, a cognitive diagnostic model, to measure the learning progression for thermochemistry for senior high school students. We extracted five attributes and proposed their hierarchical relationships to model the construct of thermochemistry at four levels using a hypothesized learning progression. For this study, we developed 24 test items addressing the attributes of exothermic and endothermic reactions, chemical bonds and heat quantity change, reaction heat and enthalpy, thermochemical equations, and Hess's law. The test was administered to a sample base of 694 senior high school students taught in 3 schools across 2 cities. Results based on the Rule Space Model analysis indicated that (1) the test items developed by the Rule Space Model were of high psychometric quality for good analysis of difficulties, discriminations, reliabilities, and validities; (2) the Rule Space Model analysis classified the students into seven different attribute mastery patterns; and (3) the initial hypothesized learning progression was modified by the attribute mastery patterns and the learning paths to be more precise and detailed.

  5. The Aptitude-Treatment Interaction Effects on the Learning of Grammar Rules

    ERIC Educational Resources Information Center

    Hwu, Fenfang; Sun, Shuyan

    2012-01-01

    The present study investigates the interaction between two types of explicit instructional approaches, deduction and explicit-induction, and the level of foreign language aptitude in the learning of grammar rules. Results indicate that on the whole the two equally explicit instructional approaches did not differentially affect learning…

  6. Effectiveness of Visual Imagery versus Rule-Based Strategies in Teaching Spelling to Learning Disabled Students.

    ERIC Educational Resources Information Center

    Darch, Craig; Simpson, Robert G.

    1990-01-01

    Among 28 upper elementary learning-disabled students in a summer remedial program, those that were taught spelling with explicit rule-based strategies out-performed students presented with a visual imagery mnemonic on unit tests, a posttest, and a standardized spelling test. Contains 20 references. (SV)

  7. Perceptual Learning Improves Adult Amblyopic Vision Through Rule-Based Cognitive Compensation

    PubMed Central

    Zhang, Jun-Yun; Cong, Lin-Juan; Klein, Stanley A.; Levi, Dennis M.; Yu, Cong

    2014-01-01

    Purpose. We investigated whether perceptual learning in adults with amblyopia could be enabled to transfer completely to an orthogonal orientation, which would suggest that amblyopic perceptual learning results mainly from high-level cognitive compensation, rather than plasticity in the amblyopic early visual brain. Methods. Nineteen adults (mean age = 22.5 years) with anisometropic and/or strabismic amblyopia were trained following a training-plus-exposure (TPE) protocol. The amblyopic eyes practiced contrast, orientation, or Vernier discrimination at one orientation for six to eight sessions. Then the amblyopic or nonamblyopic eyes were exposed to an orthogonal orientation via practicing an irrelevant task. Training was first performed at a lower spatial frequency (SF), then at a higher SF near the cutoff frequency of the amblyopic eye. Results. Perceptual learning was initially orientation specific. However, after exposure to the orthogonal orientation, learning transferred to an orthogonal orientation completely. Reversing the exposure and training order failed to produce transfer. Initial lower SF training led to broad improvement of contrast sensitivity, and later higher SF training led to more specific improvement at high SFs. Training improved visual acuity by 1.5 to 1.6 lines (P < 0.001) in the amblyopic eyes with computerized tests and a clinical E acuity chart. It also improved stereoacuity by 53% (P < 0.001). Conclusions. The complete transfer of learning suggests that perceptual learning in amblyopia may reflect high-level learning of rules for performing a visual discrimination task. These rules are applicable to new orientations to enable learning transfer. Therefore, perceptual learning may improve amblyopic vision mainly through rule-based cognitive compensation. PMID:24550359

  8. Strategy-effects in prefrontal cortex during learning of higher-order S-R rules.

    PubMed

    Wolfensteller, Uta; von Cramon, D Yves

    2011-07-15

    All of us regularly face situations that require the integration of the available information at hand with the established rules that guide behavior in order to generate the most appropriate action. But where individuals differ from one another is most certainly in terms of the different strategies that are adopted during this process. A previous study revealed differential brain activation patterns for the implementation of well established higher-order stimulus-response (S-R) rules depending on inter-individual strategy differences (Wolfensteller and von Cramon, 2010). This raises the question of how these strategies evolve or which neurocognitive mechanisms underlie these inter-individual strategy differences. Using functional magnetic resonance imaging (fMRI), the present study revealed striking strategy-effects across regions of the lateral prefrontal cortex during the implementation of higher-order S-R rules at an early stage of learning. The left rostrolateral prefrontal cortex displayed a quantitative strategy-effect, such that activation during rule integration based on a mismatch was related to the degree to which participants continued to rely on rule integration. A quantitative strategy ceiling effect was observed for the left inferior frontal junction area. Conversely, the right inferior frontal gyrus displayed a qualitative strategy-effect such that participants who at a later point relied on an item-based strategy showed stronger activations in this region compared to those who continued with the rule integration strategy. Together, the present findings suggest that a certain amount of rule integration is mandatory when participants start to learn higher-order rules. The more efficient item-based strategy that evolves later appears to initially require the recruitment of additional cognitive resources in order to shield the currently relevant S-R association from interfering information.

  9. Imitation as a mechanism in cognitive development: a cross-cultural investigation of 4-year-old children’s rule learning

    PubMed Central

    Wang, Zhidan; Williamson, Rebecca A.; Meltzoff, Andrew N.

    2015-01-01

    Children learn about the social and physical world by observing other people’s acts. This experiment tests both Chinese and American children’s learning of a rule. For theoretical reasons we chose the rule of categorizing objects by the weight. Children, age 4 years, saw an adult heft four visually-identical objects and sort them into two bins based on an invisible property—the object’s weight. Children who saw this categorization behavior were more likely to sort those objects by weight than were children who saw control actions using the same objects and the same bins. Crucially, children also generalized to a novel set of objects with no further demonstration, suggesting rule learning. We also report that high-fidelity imitation of the adult’s “hefting” acts may give children crucial experience with the objects’ weights, which could then be used to infer the more abstract rule. The connection of perception, action, and cognition was found in children from both cultures, which leads to broad implications for how the imitation of adults’ acts functions as a lever in cognitive development. PMID:26029132

  10. Immediate return preference emerged from a synaptic learning rule for return maximization.

    PubMed

    Yamaguchi, Yoshiya; Aihara, Takeshi; Sakai, Yutaka

    2015-02-01

    Animals including human often prefer immediate returns to larger delayed returns. It holds true in the human communications. Standard interpretation of the immediate return preference is that an animal might subjectively discount the value of a delayed reward, and that might choose the larger valued one. The interpretation has been successfully applied to explain behavior of many species including human. However, the description is not necessarily sufficient to apply for interactions of individuals. This study adopts a different approach to seek a possibility that immediate return preference may be reproduced by learning rule to maximize objective outcomes. We show that a synaptic learning rule to achieve the temporal difference (TD) learning for outcome maximization fails the maximization and exhibits immediate return preference if the context is not properly represented as a internal state.

  11. The application of top-down abstraction learning using prediction as a supervisory signal to cyber security

    NASA Astrophysics Data System (ADS)

    Mugan, Jonathan; Khalili, Aram E.

    2014-05-01

    Current computer systems are dumb automatons, and their blind execution of instructions makes them open to attack. Their inability to reason means that they don't consider the larger, constantly changing context outside their immediate inputs. Their nearsightedness is particularly dangerous because, in our complex systems, it is difficult to prevent all exploitable situations. Additionally, the lack of autonomous oversight of our systems means they are unable to fight through attacks. Keeping adversaries completely out of systems may be an unreasonable expectation, and our systems need to adapt to attacks and other disruptions to achieve their objectives. What is needed is an autonomous controller within the computer system that can sense the state of the system and reason about that state. In this paper, we present Self-Awareness Through Predictive Abstraction Modeling (SATPAM). SATPAM uses prediction to learn abstractions that allow it to recognize the right events at the right level of detail. These abstractions allow SATPAM to break the world into small, relatively independent, pieces that allow employment of existing reasoning methods. SATPAM goes beyond classification-based machine learning and statistical anomaly detection to be able to reason about the system, and SATPAM's knowledge representation and reasoning is more like that of a human. For example, humans intuitively know that the color of a car is not relevant to any mechanical problem, and SATPAM provides a plausible method whereby a machine can acquire such reasoning patterns. In this paper, we present the initial experimental results using SATPAM.

  12. Topic Categorisation of Statements in Suicide Notes with Integrated Rules and Machine Learning

    PubMed Central

    Kovačević, Aleksandar; Dehghan, Azad; Keane, John A.; Nenadic, Goran

    2012-01-01

    We describe and evaluate an automated approach used as part of the i2b2 2011 challenge to identify and categorise statements in suicide notes into one of 15 topics, including Love, Guilt, Thankfulness, Hopelessness and Instructions. The approach combines a set of lexico-syntactic rules with a set of models derived by machine learning from a training dataset. The machine learning models rely on named entities, lexical, lexico-semantic and presentation features, as well as the rules that are applicable to a given statement. On a testing set of 300 suicide notes, the approach showed the overall best micro F-measure of up to 53.36%. The best precision achieved was 67.17% when only rules are used, whereas best recall of 50.57% was with integrated rules and machine learning. While some topics (eg, Sorrow, Anger, Blame) prove challenging, the performance for relatively frequent (eg, Love) and well-scoped categories (eg, Thankfulness) was comparatively higher (precision between 68% and 79%), suggesting that automated text mining approaches can be effective in topic categorisation of suicide notes. PMID:22879767

  13. Abstract reasoning in a specific group of perceptually impaired children: namely, the learning-disabled.

    PubMed

    Meltzer, L J

    1978-06-01

    The present study was designed to investigate whether learning-disabled children differ from normal achievers in terms of logical thought and wheter they exhibit décalages intheir acquisition of Piagetian concepts. The Ss comprised 35 learning-disabled boys attending full-time remedial schools and 35 matched normal achievers. The group mean was 9 years 1 month and the mean IQ was 109. S s were tested on a measure of visual perception and on 11 Piagetian tasks measuring conservation of quantitiy and number, seriation, and classification. Results indicated a significant difference between the groups in terms of perception but not in terms of logical thought. The rank order of the 11 Piagetain tasks was significantly correlated for the two groups (r = .89). It was concluded that the perceptual problems of the learning-disabled reside at a functional rather than at an organizational level, thus effecting only specific congnitive activities.

  14. Effects of Inter- and Intra-Modal Redundancy on Infants' Rule Learning

    ERIC Educational Resources Information Center

    Thiessen, Erik D.

    2012-01-01

    Previous research indicates that infants generalize syntactic-like structures to novel exemplars in a way that has been characterized as abstract and algebraic (Marcus et al., 1999). Infants appear to learn and generalize from speech more successfully than from nonspeech stimuli (Marcus, Fernandes, & Johnson, 2007). In this series of experiments,…

  15. Children with Specific Language Impairment Show Rapid, Implicit Learning of Stress Assignment Rules

    ERIC Educational Resources Information Center

    Plante, Elena; Bahl, Megha; Vance, Rebecca; Gerken, LouAnn

    2010-01-01

    An implicit learning paradigm was used to assess children's sensitivity to syllable stress information in an artificial language. Study 1 demonstrated that preschool children, with and without specific language impairment (SLI), can generalize patterns of stress heard during a brief period of familiarization, and can also abstract underlying…

  16. Analogical Scaffolding and the Learning of Abstract Ideas in Physics: An Example from Electromagnetic Waves

    ERIC Educational Resources Information Center

    Podolefsky, Noah S.; Finkelstein, Noah D.

    2007-01-01

    This paper describes a model of analogy, analogical scaffolding, which explains present and prior results of student learning with analogies. We build on prior models of representation, blending, and layering of ideas. Extending this model's explanatory power, we propose ways in which the model can be applied to design a curriculum directed at…

  17. Implementation of Abstract Data Types in Dynamic Sketches for Learning Geometry

    ERIC Educational Resources Information Center

    Jasute, Egle; Dagiene, Valentina

    2014-01-01

    A long-term observation of students' usage of a dynamic geometry in a classroom at all grade levels has challenged to develop an approach for learning and understanding mathematics in an easier way for both students and teachers. The paper deals with the results of a study that investigates the process and outcomes of the implementation of…

  18. Mining Formative Evaluation Rules Using Web-Based Learning Portfolios for Web-Based Learning Systems

    ERIC Educational Resources Information Center

    Chen, Chih-Ming; Hong, Chin-Ming; Chen, Shyuan-Yi; Liu, Chao-Yu

    2006-01-01

    Learning performance assessment aims to evaluate what knowledge learners have acquired from teaching activities. Objective technical measures of learning performance are difficult to develop, but are extremely important for both teachers and learners. Learning performance assessment using learning portfolios or web server log data is becoming an…

  19. Evolving learning rules and emergence of cooperation in spatial prisoner's dilemma.

    PubMed

    Moyano, Luis G; Sánchez, Angel

    2009-07-07

    In the evolutionary Prisoner's dilemma (PD) game, agents play with each other and update their strategies in every generation according to some microscopic dynamical rule. In its spatial version, agents do not play with every other but, instead, interact only with their neighbours, thus mimicking the existing of a social or contact network that defines who interacts with whom. In this work, we explore evolutionary, spatial PD systems consisting of two types of agents, each with a certain update (reproduction, learning) rule. We investigate two different scenarios: in the first case, update rules remain fixed for the entire evolution of the system; in the second case, agents update both strategy and update rule in every generation. We show that in a well-mixed population the evolutionary outcome is always full defection. We subsequently focus on two-strategy competition with nearest-neighbour interactions on the contact network and synchronised update of strategies. Our results show that, for an important range of the parameters of the game, the final state of the system is largely different from that arising from the usual setup of a single, fixed dynamical rule. Furthermore, the results are also very different if update rules are fixed or evolve with the strategies. In these respect, we have studied representative update rules, finding that some of them may become extinct while others prevail. We describe the new and rich variety of final outcomes that arise from this co-evolutionary dynamics. We include examples of other neighbourhoods and asynchronous updating that confirm the robustness of our conclusions. Our results pave the way to an evolutionary rationale for modelling social interactions through game theory with a preferred set of update rules.

  20. Learning new movement patterns: a study on good and poor writers comparing learning conditions emphasizing spatial, timing or abstract characteristics.

    PubMed

    Overvelde, Anneloes; Hulstijn, Wouter

    2011-08-01

    In the earliest stages of motor-skill learning cognitive, visuo-spatial and dynamic processes play an important role. Which of these should be addressed first when children need to learn a new complex movement sequence? This study compares three learning methods in a within-subject design by having 18 good and 18 poor 8-year-old writers master unfamiliar, letter-like patterns by (1) tracing a trajectory on a screen, (2) tracking a moving target (pursuit), and (3) performing the pattern using written explicit instructions. Following each 10-trial learning phase, the children completed a short test phase. Besides errors and kinematic data, Dynamic Time Warping (DTW) was used to calculate the deviation for each pattern from the ideal shape (DTW-distance). As predicted, the number of errors and DTW-distance were very low during the learning phase of the tracing and pursuit conditions and higher in the explicit condition. Conversely, in the test phase, tracing yielded the highest DTW-distance and the explicit condition the lowest DTW-distance and error percentages. The results were remarkably similar for the good and poor writers. The poor learning results of the tracing condition and the good results of the explicit condition have important implications for the teaching of handwriting and remedial therapy.

  1. Compensatory processing during rule-based category learning in older adults.

    PubMed

    Bharani, Krishna L; Paller, Ken A; Reber, Paul J; Weintraub, Sandra; Yanar, Jorge; Morrison, Robert G

    2016-01-01

    Healthy older adults typically perform worse than younger adults at rule-based category learning, but better than patients with Alzheimer's or Parkinson's disease. To further investigate aging's effect on rule-based category learning, we monitored event-related potentials (ERPs) while younger and neuropsychologically typical older adults performed a visual category-learning task with a rule-based category structure and trial-by-trial feedback. Using these procedures, we previously identified ERPs sensitive to categorization strategy and accuracy in young participants. In addition, previous studies have demonstrated the importance of neural processing in the prefrontal cortex and the medial temporal lobe for this task. In this study, older adults showed lower accuracy and longer response times than younger adults, but there were two distinct subgroups of older adults. One subgroup showed near-chance performance throughout the procedure, never categorizing accurately. The other subgroup reached asymptotic accuracy that was equivalent to that in younger adults, although they categorized more slowly. These two subgroups were further distinguished via ERPs. Consistent with the compensation theory of cognitive aging, older adults who successfully learned showed larger frontal ERPs when compared with younger adults. Recruitment of prefrontal resources may have improved performance while slowing response times. Additionally, correlations of feedback-locked P300 amplitudes with category-learning accuracy differentiated successful younger and older adults. Overall, the results suggest that the ability to adapt one's behavior in response to feedback during learning varies across older individuals, and that the failure of some to adapt their behavior may reflect inadequate engagement of prefrontal cortex.

  2. Learning the exception to the rule: model-based FMRI reveals specialized representations for surprising category members.

    PubMed

    Davis, Tyler; Love, Bradley C; Preston, Alison R

    2012-02-01

    Category knowledge can be explicit, yet not conform to a perfect rule. For example, a child may acquire the rule "If it has wings, then it is a bird," but then must account for exceptions to this rule, such as bats. The current study explored the neurobiological basis of rule-plus-exception learning by using quantitative predictions from a category learning model, SUSTAIN, to analyze behavioral and functional magnetic resonance imaging (fMRI) data. SUSTAIN predicts that exceptions require formation of specialized representations to distinguish exceptions from rule-following items in memory. By incorporating quantitative trial-by-trial predictions from SUSTAIN directly into fMRI analyses, we observed medial temporal lobe (MTL) activation consistent with 2 predicted psychological processes that enable exception learning: item recognition and error correction. SUSTAIN explains how these processes vary in the MTL across learning trials as category knowledge is acquired. Importantly, MTL engagement during exception learning was not captured by an alternate exemplar-based model of category learning or by standard contrasts comparing exception and rule-following items. The current findings thus provide a well-specified theory for the role of the MTL in category learning, where the MTL plays an important role in forming specialized category representations appropriate for the learning context.

  3. A cortico-hippocampal learning rule shapes inhibitory microcircuit activity to enhance hippocampal information flow.

    PubMed

    Basu, Jayeeta; Srinivas, Kalyan V; Cheung, Stephanie K; Taniguchi, Hiroki; Huang, Z Josh; Siegelbaum, Steven A

    2013-09-18

    How does coordinated activity between distinct brain regions implement a set of learning rules to sculpt information processing in a given neural circuit? Using interneuron cell-type-specific optical activation and pharmacogenetic silencing in vitro, we show that temporally precise pairing of direct entorhinal perforant path (PP) and hippocampal Schaffer collateral (SC) inputs to CA1 pyramidal cells selectively suppresses SC-associated perisomatic inhibition from cholecystokinin (CCK)-expressing interneurons. The CCK interneurons provide a surprisingly strong feedforward inhibitory drive to effectively control the coincident excitation of CA1 pyramidal neurons by convergent inputs. Thus, in-phase cortico-hippocampal activity provides a powerful heterosynaptic learning rule for long-term gating of information flow through the hippocampal excitatory macrocircuit by the silencing of the CCK inhibitory microcircuit.

  4. Explicit category learning in Parkinson's disease: deficits related to impaired rule generation and selection processes.

    PubMed

    Price, Amanda L

    2006-03-01

    The present study examined the source of explicit category learning deficits previously noted in patients with Parkinson's disease (PD). Task stimuli consisted of 4 binary-valued cues that together determined category assignment, although some cues were more important for the categorization decision. Participants verbalized the hypotheses being tested to provide several measures of the hypothesis testing. Analyses of these verbal protocols indicated that PD patients were impaired on rule generation and selection but not rule shifting. Patients had particular difficulty noting the relative importance of the cues. Specific aspects of performance were differently correlated with neuropsychological measures of working memory and hypothesis testing ability. Together, the results suggest that the cognitive processes required for explicit category learning are mediated by partially distinct neural mechanisms.

  5. Identifying relevant data for a biological database: handcrafted rules versus machine learning.

    PubMed

    Sehgal, Aditya Kumar; Das, Sanmay; Noto, Keith; Saier, Milton H; Elkan, Charles

    2011-01-01

    With well over 1,000 specialized biological databases in use today, the task of automatically identifying novel, relevant data for such databases is increasingly important. In this paper, we describe practical machine learning approaches for identifying MEDLINE documents and Swiss-Prot/TrEMBL protein records, for incorporation into a specialized biological database of transport proteins named TCDB. We show that both learning approaches outperform rules created by hand by a human expert. As one of the first case studies involving two different approaches to updating a deployed database, both the methods compared and the results will be of interest to curators of many specialized databases.

  6. Logic Learning Machine creates explicit and stable rules stratifying neuroblastoma patients

    PubMed Central

    2013-01-01

    Background Neuroblastoma is the most common pediatric solid tumor. About fifty percent of high risk patients die despite treatment making the exploration of new and more effective strategies for improving stratification mandatory. Hypoxia is a condition of low oxygen tension occurring in poorly vascularized areas of the tumor associated with poor prognosis. We had previously defined a robust gene expression signature measuring the hypoxic component of neuroblastoma tumors (NB-hypo) which is a molecular risk factor. We wanted to develop a prognostic classifier of neuroblastoma patients' outcome blending existing knowledge on clinical and molecular risk factors with the prognostic NB-hypo signature. Furthermore, we were interested in classifiers outputting explicit rules that could be easily translated into the clinical setting. Results Shadow Clustering (SC) technique, which leads to final models called Logic Learning Machine (LLM), exhibits a good accuracy and promises to fulfill the aims of the work. We utilized this algorithm to classify NB-patients on the bases of the following risk factors: Age at diagnosis, INSS stage, MYCN amplification and NB-hypo. The algorithm generated explicit classification rules in good agreement with existing clinical knowledge. Through an iterative procedure we identified and removed from the dataset those examples which caused instability in the rules. This workflow generated a stable classifier very accurate in predicting good and poor outcome patients. The good performance of the classifier was validated in an independent dataset. NB-hypo was an important component of the rules with a strength similar to that of tumor staging. Conclusions The novelty of our work is to identify stability, explicit rules and blending of molecular and clinical risk factors as the key features to generate classification rules for NB patients to be conveyed to the clinic and to be used to design new therapies. We derived, through LLM, a set of four

  7. Are word representations abstract or instance-based? Effects of spelling inconsistency in orthographic learning.

    PubMed

    Burt, Jennifer S; Long, Julia

    2011-09-01

    In Experiment 1, 62 10-year-old children studied printed pseudowords with semantic information. The items were later represented in a different format for reading, with half of the items spelled in the same way as before and half displayed in a new phonologically equivalent spelling. In a dictation test, the exposure to an alternative spelling substantially increased the number of errors that matched the alternative spelling, especially in good spellers. Orthographic learning predicted word identification when accuracy on orthographic choice for words was controlled. In Experiment 2, the effects on dictation responses of exposure to a misspelling versus the correct spelling, and the interactive effect of spelling ability, were confirmed relative to a no-exposure control in adults. The results support a single-lexicon view of reading and spelling and have implications for abstractionist and instance-based theories of orthographic representations.

  8. Abstract Thinking in Space and Time: Using The Environment to Learn Words.

    PubMed

    Samuelson, Larissa K

    2011-12-01

    A substantial body of work has examined the gestures children and adults make when they talk and found them to be a revealing window on the processes of cognitive change. In her paper, Susan Wagner Cook (this volume) reviews this work along with her own recent work examining the gestures children and adults produce when they talk about math. She argues that the combined data point to a new view of our mathematical knowledge as embodied. Here I comment on Cook's arguments, highlighting how this view of math as embodied offers new insights for our understanding of classic developmental themes, in particular, the continuity versus discontinuity dichotomy. In addition, I present a brief summary of recent work on how children use their bodies in another realm typically thought of as abstract-understanding referential intent. I present an embodied account of how children disambiguate speaker intent in novel naming situations and argue that, as in the case of embodied math, an embodied view of cognition can help elucidate developmental mechanism.

  9. Category Number Impacts Rule-Based "and" Information-Integration Category Learning: A Reassessment of Evidence for Dissociable Category-Learning Systems

    ERIC Educational Resources Information Center

    Stanton, Roger D.; Nosofsky, Robert M.

    2013-01-01

    Researchers have proposed that an explicit reasoning system is responsible for learning rule-based category structures and that a separate implicit, procedural-learning system is responsible for learning information-integration category structures. As evidence for this multiple-system hypothesis, researchers report a dissociation based on…

  10. Mixing Languages during Learning? Testing the One Subject—One Language Rule

    PubMed Central

    2015-01-01

    In bilingual communities, mixing languages is avoided in formal schooling: even if two languages are used on a daily basis for teaching, only one language is used to teach each given academic subject. This tenet known as the one subject-one language rule avoids mixing languages in formal schooling because it may hinder learning. The aim of this study was to test the scientific ground of this assumption by investigating the consequences of acquiring new concepts using a method in which two languages are mixed as compared to a purely monolingual method. Native balanced bilingual speakers of Basque and Spanish—adults (Experiment 1) and children (Experiment 2)—learnt new concepts by associating two different features to novel objects. Half of the participants completed the learning process in a multilingual context (one feature was described in Basque and the other one in Spanish); while the other half completed the learning phase in a purely monolingual context (both features were described in Spanish). Different measures of learning were taken, as well as direct and indirect indicators of concept consolidation. We found no evidence in favor of the non-mixing method when comparing the results of two groups in either experiment, and thus failed to give scientific support for the educational premise of the one subject—one language rule. PMID:26107624

  11. Mixing Languages during Learning? Testing the One Subject-One Language Rule.

    PubMed

    Antón, Eneko; Thierry, Guillaume; Duñabeitia, Jon Andoni

    2015-01-01

    In bilingual communities, mixing languages is avoided in formal schooling: even if two languages are used on a daily basis for teaching, only one language is used to teach each given academic subject. This tenet known as the one subject-one language rule avoids mixing languages in formal schooling because it may hinder learning. The aim of this study was to test the scientific ground of this assumption by investigating the consequences of acquiring new concepts using a method in which two languages are mixed as compared to a purely monolingual method. Native balanced bilingual speakers of Basque and Spanish-adults (Experiment 1) and children (Experiment 2)-learnt new concepts by associating two different features to novel objects. Half of the participants completed the learning process in a multilingual context (one feature was described in Basque and the other one in Spanish); while the other half completed the learning phase in a purely monolingual context (both features were described in Spanish). Different measures of learning were taken, as well as direct and indirect indicators of concept consolidation. We found no evidence in favor of the non-mixing method when comparing the results of two groups in either experiment, and thus failed to give scientific support for the educational premise of the one subject-one language rule.

  12. A stimulus-location effect in contingency-governed, but not rule-based, discrimination learning.

    PubMed

    Meier, Christina; Lea, Stephen E G; McLaren, Ian P L

    2016-04-01

    We tested pigeons' acquisition of a conditional discrimination task between colored grating stimuli that included choosing 1 of 2 response keys, which either appeared as white keys to the left and right of the discriminative stimulus, or were replicas of the stimulus. Pigeons failed to acquire the discrimination when the response keys were white disks but succeeded when directly responding to a replica of the stimulus. These results highlight how conditioning processes shape learning in pigeons: The results can be accounted for by supposing that, when pigeons were allowed to respond directly toward the stimulus, learning was guided by classical conditioning, but that responding to white keys demanded instrumental learning, which impaired task acquisition for pigeons. In contrast, humans completing the same paradigm showed no differential learning success depending on whether figure or position indicated the correct key. However, only participants who could state the underlying discrimination rule acquired the task, which implies that human performance in this situation relied on the deduction and application of task rules instead of associative processes.

  13. A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks

    PubMed Central

    Alemi, Alireza; Baldassi, Carlo; Brunel, Nicolas; Zecchina, Riccardo

    2015-01-01

    Understanding the theoretical foundations of how memories are encoded and retrieved in neural populations is a central challenge in neuroscience. A popular theoretical scenario for modeling memory function is the attractor neural network scenario, whose prototype is the Hopfield model. The model simplicity and the locality of the synaptic update rules come at the cost of a poor storage capacity, compared with the capacity achieved with perceptron learning algorithms. Here, by transforming the perceptron learning rule, we present an online learning rule for a recurrent neural network that achieves near-maximal storage capacity without an explicit supervisory error signal, relying only upon locally accessible information. The fully-connected network consists of excitatory binary neurons with plastic recurrent connections and non-plastic inhibitory feedback stabilizing the network dynamics; the memory patterns to be memorized are presented online as strong afferent currents, producing a bimodal distribution for the neuron synaptic inputs. Synapses corresponding to active inputs are modified as a function of the value of the local fields with respect to three thresholds. Above the highest threshold, and below the lowest threshold, no plasticity occurs. In between these two thresholds, potentiation/depression occurs when the local field is above/below an intermediate threshold. We simulated and analyzed a network of binary neurons implementing this rule and measured its storage capacity for different sizes of the basins of attraction. The storage capacity obtained through numerical simulations is shown to be close to the value predicted by analytical calculations. We also measured the dependence of capacity on the strength of external inputs. Finally, we quantified the statistics of the resulting synaptic connectivity matrix, and found that both the fraction of zero weight synapses and the degree of symmetry of the weight matrix increase with the number of stored

  14. A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks.

    PubMed

    Alemi, Alireza; Baldassi, Carlo; Brunel, Nicolas; Zecchina, Riccardo

    2015-08-01

    Understanding the theoretical foundations of how memories are encoded and retrieved in neural populations is a central challenge in neuroscience. A popular theoretical scenario for modeling memory function is the attractor neural network scenario, whose prototype is the Hopfield model. The model simplicity and the locality of the synaptic update rules come at the cost of a poor storage capacity, compared with the capacity achieved with perceptron learning algorithms. Here, by transforming the perceptron learning rule, we present an online learning rule for a recurrent neural network that achieves near-maximal storage capacity without an explicit supervisory error signal, relying only upon locally accessible information. The fully-connected network consists of excitatory binary neurons with plastic recurrent connections and non-plastic inhibitory feedback stabilizing the network dynamics; the memory patterns to be memorized are presented online as strong afferent currents, producing a bimodal distribution for the neuron synaptic inputs. Synapses corresponding to active inputs are modified as a function of the value of the local fields with respect to three thresholds. Above the highest threshold, and below the lowest threshold, no plasticity occurs. In between these two thresholds, potentiation/depression occurs when the local field is above/below an intermediate threshold. We simulated and analyzed a network of binary neurons implementing this rule and measured its storage capacity for different sizes of the basins of attraction. The storage capacity obtained through numerical simulations is shown to be close to the value predicted by analytical calculations. We also measured the dependence of capacity on the strength of external inputs. Finally, we quantified the statistics of the resulting synaptic connectivity matrix, and found that both the fraction of zero weight synapses and the degree of symmetry of the weight matrix increase with the number of stored

  15. Assessment of Matrix Multiplication Learning with a Rule-Based Analytical Model--"A Bayesian Network Representation"

    ERIC Educational Resources Information Center

    Zhang, Zhidong

    2016-01-01

    This study explored an alternative assessment procedure to examine learning trajectories of matrix multiplication. It took rule-based analytical and cognitive task analysis methods specifically to break down operation rules for a given matrix multiplication. Based on the analysis results, a hierarchical Bayesian network, an assessment model,…

  16. Learning grammar rules of building parts from precise models and noisy observations

    NASA Astrophysics Data System (ADS)

    Dehbi, Y.; Plümer, L.

    The automatic interpretation of dense three-dimensional (3D) point clouds is still an open research problem. The quality and usability of the derived models depend to a large degree on the availability of highly structured models which represent semantics explicitly and provide a priori knowledge to the interpretation process. The usage of formal grammars for modelling man-made objects has gained increasing interest in the last few years. In order to cope with the variety and complexity of buildings, a large number of fairly sophisticated grammar rules are needed. As yet, such rules mostly have to be designed by human experts. This article describes a novel approach to machine learning of attribute grammar rules based on the Inductive Logic Programming paradigm. Apart from syntactic differences, logic programs and attribute grammars are basically the same language. Attribute grammars extend context-free grammars by attributes and semantic rules and provide a much larger expressive power. Our approach to derive attribute grammars is able to deal with two kinds of input data. On the one hand, we show how attribute grammars can be derived from precise descriptions in the form of examples provided by a human user as the teacher. On the other hand, we present the acquisition of models from noisy observations such as 3D point clouds. This includes the learning of geometric and topological constraints by taking measurement errors into account. The feasibility of our approach is proven exemplarily by stairs, and a generic framework for learning other building parts is discussed. Stairs aggregate an arbitrary number of steps in a manner which is specified by topological and geometric constraints and can be modelled in a recursive way. Due to this recursion, they pose a special challenge to machine learning. In order to learn the concept of stairs, only a small number of examples were required. Our approach represents and addresses the quality of the given observations and

  17. Reading to learn experimental practice: The role of text and firsthand experience in the acquisition of an abstract science principle

    NASA Astrophysics Data System (ADS)

    Richmond, Erica Kesin

    2008-10-01

    From the onset of schooling, texts are used as important educational tools. In the primary years, they are integral to learning how to decode and develop fluency. In the later elementary years, they are often essential to the acquisition of academic content. Unfortunately, many children experience difficulties with this process, which is due in large part to their unfamiliarity with the genre of academic texts. The articles presented in this dissertation share an underlying theme of how to develop children's ability to comprehend and learn from academic, and specifically, non-narrative texts. The first article reviews research on the development of non-narrative discourse to elucidate the linguistic precursors to non-narrative text comprehension. The second and third articles draw from an empirical study that investigated the best way to integrate text, manipulation, and first-hand experience for children's acquisition and application of an abstract scientific principle. The scientific principle introduced in the study was the Control of Variables Strategy (CVS), a fundamental idea underlying scientific reasoning and a strategy for designing unconfounded experiments. Eight grade 4 classes participated in the study (N = 129), in one of three conditions: (a) read procedural text and manipulate experimental materials, (b) listen to procedural text and manipulate experimental materials, or (c) read procedural text with no opportunity to manipulate experimental materials. Findings from the study indicate that children who had the opportunity to read and manipulate materials were most effective at applying the strategy to designing and justifying unconfounded experiments, and evaluating written and physical experimental designs; however, there was no effect of instructional condition on a written assessment of evaluating familiar and unfamiliar experimental designs one week after the intervention. These results suggest that the acquisition and application of an abstract

  18. Neuromodulated Spike-Timing-Dependent Plasticity, and Theory of Three-Factor Learning Rules

    PubMed Central

    Frémaux, Nicolas; Gerstner, Wulfram

    2016-01-01

    Classical Hebbian learning puts the emphasis on joint pre- and postsynaptic activity, but neglects the potential role of neuromodulators. Since neuromodulators convey information about novelty or reward, the influence of neuromodulators on synaptic plasticity is useful not just for action learning in classical conditioning, but also to decide “when” to create new memories in response to a flow of sensory stimuli. In this review, we focus on timing requirements for pre- and postsynaptic activity in conjunction with one or several phasic neuromodulatory signals. While the emphasis of the text is on conceptual models and mathematical theories, we also discuss some experimental evidence for neuromodulation of Spike-Timing-Dependent Plasticity. We highlight the importance of synaptic mechanisms in bridging the temporal gap between sensory stimulation and neuromodulatory signals, and develop a framework for a class of neo-Hebbian three-factor learning rules that depend on presynaptic activity, postsynaptic variables as well as the influence of neuromodulators. PMID:26834568

  19. Striving for Excellence. The International Conference of the Learning Disabilities Association of America (Atlanta, Georgia, March 4-7, 1992). Research Poster Session Abstract. Volume 1.

    ERIC Educational Resources Information Center

    Russell, Steven C., Comp.

    Eleven abstracts of research projects related to individuals with learning disabilities are compiled in this booklet. The research projects were presented in poster sessions at the March 1992 International Conference of the Learning Disabilities Association of America. Titles and authors of poster sessions include: "Perceptual and Verbal Skills of…

  20. Rules and mechanisms for efficient two-stage learning in neural circuits.

    PubMed

    Teşileanu, Tiberiu; Ölveczky, Bence; Balasubramanian, Vijay

    2017-04-04

    Trial-and-error learning requires evaluating variable actions and reinforcing successful variants. In songbirds, vocal exploration is induced by LMAN, the output of a basal ganglia-related circuit that also contributes a corrective bias to the vocal output. This bias is gradually consolidated in RA, a motor cortex analogue downstream of LMAN. We develop a new model of such two-stage learning. Using stochastic gradient descent, we derive how the activity in 'tutor' circuits (e.g., LMAN) should match plasticity mechanisms in 'student' circuits (e.g., RA) to achieve efficient learning. We further describe a reinforcement learning framework through which the tutor can build its teaching signal. We show that mismatches between the tutor signal and the plasticity mechanism can impair learning. Applied to birdsong, our results predict the temporal structure of the corrective bias from LMAN given a plasticity rule in RA. Our framework can be applied predictively to other paired brain areas showing two-stage learning.

  1. Rules and mechanisms for efficient two-stage learning in neural circuits

    PubMed Central

    Teşileanu, Tiberiu; Ölveczky, Bence; Balasubramanian, Vijay

    2017-01-01

    Trial-and-error learning requires evaluating variable actions and reinforcing successful variants. In songbirds, vocal exploration is induced by LMAN, the output of a basal ganglia-related circuit that also contributes a corrective bias to the vocal output. This bias is gradually consolidated in RA, a motor cortex analogue downstream of LMAN. We develop a new model of such two-stage learning. Using stochastic gradient descent, we derive how the activity in ‘tutor’ circuits (e.g., LMAN) should match plasticity mechanisms in ‘student’ circuits (e.g., RA) to achieve efficient learning. We further describe a reinforcement learning framework through which the tutor can build its teaching signal. We show that mismatches between the tutor signal and the plasticity mechanism can impair learning. Applied to birdsong, our results predict the temporal structure of the corrective bias from LMAN given a plasticity rule in RA. Our framework can be applied predictively to other paired brain areas showing two-stage learning. DOI: http://dx.doi.org/10.7554/eLife.20944.001 PMID:28374674

  2. Learning Parsimonious Classification Rules from Gene Expression Data Using Bayesian Networks with Local Structure.

    PubMed

    Lustgarten, Jonathan Lyle; Balasubramanian, Jeya Balaji; Visweswaran, Shyam; Gopalakrishnan, Vanathi

    2017-03-01

    The comprehensibility of good predictive models learned from high-dimensional gene expression data is attractive because it can lead to biomarker discovery. Several good classifiers provide comparable predictive performance but differ in their abilities to summarize the observed data. We extend a Bayesian Rule Learning (BRL-GSS) algorithm, previously shown to be a significantly better predictor than other classical approaches in this domain. It searches a space of Bayesian networks using a decision tree representation of its parameters with global constraints, and infers a set of IF-THEN rules. The number of parameters and therefore the number of rules are combinatorial to the number of predictor variables in the model. We relax these global constraints to a more generalizable local structure (BRL-LSS). BRL-LSS entails more parsimonious set of rules because it does not have to generate all combinatorial rules. The search space of local structures is much richer than the space of global structures. We design the BRL-LSS with the same worst-case time-complexity as BRL-GSS while exploring a richer and more complex model space. We measure predictive performance using Area Under the ROC curve (AUC) and Accuracy. We measure model parsimony performance by noting the average number of rules and variables needed to describe the observed data. We evaluate the predictive and parsimony performance of BRL-GSS, BRL-LSS and the state-of-the-art C4.5 decision tree algorithm, across 10-fold cross-validation using ten microarray gene-expression diagnostic datasets. In these experiments, we observe that BRL-LSS is similar to BRL-GSS in terms of predictive performance, while generating a much more parsimonious set of rules to explain the same observed data. BRL-LSS also needs fewer variables than C4.5 to explain the data with similar predictive performance. We also conduct a feasibility study to demonstrate the general applicability of our BRL methods on the newer RNA sequencing gene

  3. Learning Parsimonious Classification Rules from Gene Expression Data Using Bayesian Networks with Local Structure

    PubMed Central

    Lustgarten, Jonathan Lyle; Balasubramanian, Jeya Balaji; Visweswaran, Shyam; Gopalakrishnan, Vanathi

    2017-01-01

    The comprehensibility of good predictive models learned from high-dimensional gene expression data is attractive because it can lead to biomarker discovery. Several good classifiers provide comparable predictive performance but differ in their abilities to summarize the observed data. We extend a Bayesian Rule Learning (BRL-GSS) algorithm, previously shown to be a significantly better predictor than other classical approaches in this domain. It searches a space of Bayesian networks using a decision tree representation of its parameters with global constraints, and infers a set of IF-THEN rules. The number of parameters and therefore the number of rules are combinatorial to the number of predictor variables in the model. We relax these global constraints to a more generalizable local structure (BRL-LSS). BRL-LSS entails more parsimonious set of rules because it does not have to generate all combinatorial rules. The search space of local structures is much richer than the space of global structures. We design the BRL-LSS with the same worst-case time-complexity as BRL-GSS while exploring a richer and more complex model space. We measure predictive performance using Area Under the ROC curve (AUC) and Accuracy. We measure model parsimony performance by noting the average number of rules and variables needed to describe the observed data. We evaluate the predictive and parsimony performance of BRL-GSS, BRL-LSS and the state-of-the-art C4.5 decision tree algorithm, across 10-fold cross-validation using ten microarray gene-expression diagnostic datasets. In these experiments, we observe that BRL-LSS is similar to BRL-GSS in terms of predictive performance, while generating a much more parsimonious set of rules to explain the same observed data. BRL-LSS also needs fewer variables than C4.5 to explain the data with similar predictive performance. We also conduct a feasibility study to demonstrate the general applicability of our BRL methods on the newer RNA sequencing gene

  4. Category Number Impacts Rule-Based but Not Information-Integration Category Learning: Further Evidence for Dissociable Category-Learning Systems

    ERIC Educational Resources Information Center

    Maddox, W. Todd; Filoteo, J. Vincent; Hejl, Kelli D.; Ing, A. David

    2004-01-01

    Category number effects on rule-based and information-integration category learning were investigated. Category number affected accuracy and the distribution of best-fitting models in the rule-based task but had no effect on accuracy and little effect on the distribution of best-fining models in the information-integration task. In the 2 category…

  5. Applying cognitive developmental psychology to middle school physics learning: The rule assessment method

    NASA Astrophysics Data System (ADS)

    Hallinen, Nicole R.; Chi, Min; Chin, Doris B.; Prempeh, Joe; Blair, Kristen P.; Schwartz, Daniel L.

    2013-01-01

    Cognitive developmental psychology often describes children's growing qualitative understanding of the physical world. Physics educators may be able to use the relevant methods to advantage for characterizing changes in students' qualitative reasoning. Siegler developed the "rule assessment" method for characterizing levels of qualitative understanding for two factor situations (e.g., volume and mass for density). The method assigns children to rule levels that correspond to the degree they notice and coordinate the two factors. Here, we provide a brief tutorial plus a demonstration of how we have used this method to evaluate instructional outcomes with middle-school students who learned about torque, projectile motion, and collisions using different instructional methods with simulations.

  6. Cerebellar contribution to higher and lower order rule learning and cognitive flexibility in mice.

    PubMed

    Dickson, P E; Cairns, J; Goldowitz, D; Mittleman, G

    2017-03-14

    Cognitive flexibility has traditionally been considered a frontal lobe function. However, converging evidence suggests involvement of a larger brain circuit which includes the cerebellum. Reciprocal pathways connecting the cerebellum to the prefrontal cortex provide a biological substrate through which the cerebellum may modulate higher cognitive functions, and it has been observed that cognitive inflexibility and cerebellar pathology co-occur in psychiatric disorders (e.g., autism, schizophrenia, addiction). However, the degree to which the cerebellum contributes to distinct forms of cognitive flexibility and rule learning is unknown. We tested lurcher↔wildtype aggregation chimeras which lose 0-100% of cerebellar Purkinje cells during development on a touchscreen-mediated attentional set-shifting task to assess the contribution of the cerebellum to higher and lower order rule learning and cognitive flexibility. Purkinje cells, the sole output of the cerebellar cortex, ranged from 0 to 108,390 in tested mice. Reversal learning and extradimensional set-shifting were impaired in mice with⩾95% Purkinje cell loss. Cognitive deficits were unrelated to motor deficits in ataxic mice. Acquisition of a simple visual discrimination and an attentional-set were unrelated to Purkinje cells. A positive relationship was observed between Purkinje cells and errors when exemplars from a novel, non-relevant dimension were introduced. Collectively, these data suggest that the cerebellum contributes to higher order cognitive flexibility, lower order cognitive flexibility, and attention to novel stimuli, but not the acquisition of higher and lower order rules. These data indicate that the cerebellar pathology observed in psychiatric disorders may underlie deficits involving cognitive flexibility and attention to novel stimuli.

  7. Modulated Hebb-Oja learning rule--a method for principal subspace analysis.

    PubMed

    Jankovic, Marko V; Ogawa, Hidemitsu

    2006-03-01

    This paper presents analysis of the recently proposed modulated Hebb-Oja (MHO) method that performs linear mapping to a lower-dimensional subspace. Principal component subspace is the method that will be analyzed. Comparing to some other well-known methods for yielding principal component subspace (e.g., Oja's Subspace Learning Algorithm), the proposed method has one feature that could be seen as desirable from the biological point of view--synaptic efficacy learning rule does not need the explicit information about the value of the other efficacies to make individual efficacy modification. Also, the simplicity of the "neural circuits" that perform global computations and a fact that their number does not depend on the number of input and output neurons, could be seen as good features of the proposed method.

  8. Trading Rules on Stock Markets Using Genetic Network Programming with Reinforcement Learning and Importance Index

    NASA Astrophysics Data System (ADS)

    Mabu, Shingo; Hirasawa, Kotaro; Furuzuki, Takayuki

    Genetic Network Programming (GNP) is an evolutionary computation which represents its solutions using graph structures. Since GNP can create quite compact programs and has an implicit memory function, it has been clarified that GNP works well especially in dynamic environments. In addition, a study on creating trading rules on stock markets using GNP with Importance Index (GNP-IMX) has been done. IMX is a new element which is a criterion for decision making. In this paper, we combined GNP-IMX with Actor-Critic (GNP-IMX&AC) and create trading rules on stock markets. Evolution-based methods evolve their programs after enough period of time because they must calculate fitness values, however reinforcement learning can change programs during the period, therefore the trading rules can be created efficiently. In the simulation, the proposed method is trained using the stock prices of 10 brands in 2002 and 2003. Then the generalization ability is tested using the stock prices in 2004. The simulation results show that the proposed method can obtain larger profits than GNP-IMX without AC and Buy&Hold.

  9. Mimicking of pulse shape-dependent learning rules with a quantum dot memristor

    NASA Astrophysics Data System (ADS)

    Maier, P.; Hartmann, F.; Rebello Sousa Dias, M.; Emmerling, M.; Schneider, C.; Castelano, L. K.; Kamp, M.; Marques, G. E.; Lopez-Richard, V.; Worschech, L.; Höfling, S.

    2016-10-01

    We present the realization of four different learning rules with a quantum dot memristor by tuning the shape, the magnitude, the polarity and the timing of voltage pulses. The memristor displays a large maximum to minimum conductance ratio of about 57 000 at zero bias voltage. The high and low conductances correspond to different amounts of electrons localized in quantum dots, which can be successively raised or lowered by the timing and shapes of incoming voltage pulses. Modifications of the pulse shapes allow altering the conductance change in dependence on the time difference. Hence, we are able to mimic different learning processes in neural networks with a single device. In addition, the device performance under pulsed excitation is emulated combining the Landauer-Büttiker formalism with a dynamic model for the quantum dot charging, which allows explaining the whole spectrum of learning responses in terms of structural parameters that can be adjusted during fabrication, such as gating efficiencies and tunneling rates. The presented memristor may pave the way for future artificial synapses with a stimulus-dependent capability of learning.

  10. Inter-synaptic learning of combination rules in a cortical network model

    PubMed Central

    Lavigne, Frédéric; Avnaïm, Francis; Dumercy, Laurent

    2014-01-01

    Selecting responses in working memory while processing combinations of stimuli depends strongly on their relations stored in long-term memory. However, the learning of XOR-like combinations of stimuli and responses according to complex rules raises the issue of the non-linear separability of the responses within the space of stimuli. One proposed solution is to add neurons that perform a stage of non-linear processing between the stimuli and responses, at the cost of increasing the network size. Based on the non-linear integration of synaptic inputs within dendritic compartments, we propose here an inter-synaptic (IS) learning algorithm that determines the probability of potentiating/depressing each synapse as a function of the co-activity of the other synapses within the same dendrite. The IS learning is effective with random connectivity and without either a priori wiring or additional neurons. Our results show that IS learning generates efficacy values that are sufficient for the processing of XOR-like combinations, on the basis of the sole correlational structure of the stimuli and responses. We analyze the types of dendrites involved in terms of the number of synapses from pre-synaptic neurons coding for the stimuli and responses. The synaptic efficacy values obtained show that different dendrites specialize in the detection of different combinations of stimuli. The resulting behavior of the cortical network model is analyzed as a function of inter-synaptic vs. Hebbian learning. Combinatorial priming effects show that the retrospective activity of neurons coding for the stimuli trigger XOR-like combination-selective prospective activity of neurons coding for the expected response. The synergistic effects of inter-synaptic learning and of mixed-coding neurons are simulated. The results show that, although each mechanism is sufficient by itself, their combined effects improve the performance of the network. PMID:25221529

  11. A reward-modulated hebbian learning rule can explain experimentally observed network reorganization in a brain control task.

    PubMed

    Legenstein, Robert; Chase, Steven M; Schwartz, Andrew B; Maass, Wolfgang

    2010-06-23

    It has recently been shown in a brain-computer interface experiment that motor cortical neurons change their tuning properties selectively to compensate for errors induced by displaced decoding parameters. In particular, it was shown that the three-dimensional tuning curves of neurons whose decoding parameters were reassigned changed more than those of neurons whose decoding parameters had not been reassigned. In this article, we propose a simple learning rule that can reproduce this effect. Our learning rule uses Hebbian weight updates driven by a global reward signal and neuronal noise. In contrast to most previously proposed learning rules, this approach does not require extrinsic information to separate noise from signal. The learning rule is able to optimize the performance of a model system within biologically realistic periods of time under high noise levels. Furthermore, when the model parameters are matched to data recorded during the brain-computer interface learning experiments described above, the model produces learning effects strikingly similar to those found in the experiments.

  12. Is It Really Abstract?

    ERIC Educational Resources Information Center

    Kernan, Christine

    2011-01-01

    For this author, one of the most enjoyable aspects of teaching elementary art is the willingness of students to embrace the different styles of art introduced to them. In this article, she describes a project that allows upper-elementary students to learn about abstract art and the lives of some of the master abstract artists, implement the idea…

  13. A constrained neural learning rule for eliminating the border effect in online self-organising maps

    NASA Astrophysics Data System (ADS)

    Hung, Chihli

    2008-03-01

    The self-organising map (SOM) is a concise and powerful algorithm for clustering and visualisation of high-dimensional data. However, this robust algorithm still suffers from the border effect. Most of the approaches proposed to eliminate this effect use a borderless topological structure. We prefer to keep the original topological structure of the SOM for visualisation. A novel approach is proposed for the elimination of the border effect from the perspective of self-organising learning. Based on an assumption that the best matching unit (BMU) should be the most active unit, the approach proposes that the BMU should move more towards its associated input sample than its neighbours in the fine-tuned learning stage. Our constrained approach emphasises the effect of the lateral connections and neutralises the effect on the distance between the input sample and units. This approach is able to make units of the map stretch wider than the traditional SOM and thus the border effect is alleviated. Our proposed approach is proved to satisfy the requirements of the topologically ordered neural networks and is evaluated by both qualitative and quantitative criteria. All experiments conclude that performance is improved if the proposed constrained learning rule is used.

  14. The Effects of the Concrete-Representational-Abstract Integration Strategy on the Ability of Students with Learning Disabilities to Multiply Linear Expressions within Area Problems

    ERIC Educational Resources Information Center

    Strickland, Tricia K.; Maccini, Paula

    2013-01-01

    We examined the effects of the Concrete-Representational-Abstract Integration strategy on the ability of secondary students with learning disabilities to multiply linear algebraic expressions embedded within contextualized area problems. A multiple-probe design across three participants was used. Results indicated that the integration of the…

  15. Abstraction in mathematics.

    PubMed Central

    Ferrari, Pier Luigi

    2003-01-01

    Some current interpretations of abstraction in mathematical settings are examined from different perspectives, including history and learning. It is argued that abstraction is a complex concept and that it cannot be reduced to generalization or decontextualization only. In particular, the links between abstraction processes and the emergence of new objects are shown. The role that representations have in abstraction is discussed, taking into account both the historical and the educational perspectives. As languages play a major role in mathematics, some ideas from functional linguistics are applied to explain to what extent mathematical notations are to be considered abstract. Finally, abstraction is examined from the perspective of mathematics education, to show that the teaching ideas resulting from one-dimensional interpretations of abstraction have proved utterly unsuccessful. PMID:12903658

  16. The Roles of Innate Information, Learning Rules and Plasticity in Migratory Bird Orientation

    NASA Astrophysics Data System (ADS)

    Able, Kenneth P.; Able, Mary A.

    This paper and the following three papers were presented at the RIN97 Conference held in Oxford under the auspices of the Animal Navigation Special Interest Group, April 1997. The full proceedings, under the title Orientation and Navigation - Birds, Humans and Other Animals, can be obtained from the Director (£30 to Members, £50 to non-Members).Studies of the compass mechanisms involved in the migratory orientation of birds have revealed a complex web of interactions, both during the development of orientation behaviour in young birds and in mature individuals exhibiting migratory activity. In young birds, the acquisition of compass orientation capabilities involves the interplay of apparently genetically programmed information with a suite of innate learning rules. The latter canalise the ways in which experience with relevant orientation information from the environment impinges on development. There are many general similarities with the development of singing behaviour in songbirds, although that system is more thoroughly understood, especially at the neuronal level.Here we shall attempt to synthesise what is known about the development of compass mechanisms in a framework of innate information and learning rules. The way in which orientation behaviour develops leaves open the possibility for plasticity that enables birds to compensate for variability in the environmental cues that form the basis of their compasses. For at least some components of the system, behavioural plasticity remains into adulthood, allowing the bird on migration to respond in apparently adaptive ways to spatial and temporal variability in orientation information that it may encounter while enroute. We have studied these questions in the Savannah sparrow (Passerculus sandwichensis), a medium-distance North American emberizine nocturnal migrant. We will focus on that species, relating the results of our work to relevant studies on others.

  17. Transcranial infrared laser stimulation improves rule-based, but not information-integration, category learning in humans.

    PubMed

    Blanco, Nathaniel J; Saucedo, Celeste L; Gonzalez-Lima, F

    2017-03-01

    This is the first randomized, controlled study comparing the cognitive effects of transcranial laser stimulation on category learning tasks. Transcranial infrared laser stimulation is a new non-invasive form of brain stimulation that shows promise for wide-ranging experimental and neuropsychological applications. It involves using infrared laser to enhance cerebral oxygenation and energy metabolism through upregulation of the respiratory enzyme cytochrome oxidase, the primary infrared photon acceptor in cells. Previous research found that transcranial infrared laser stimulation aimed at the prefrontal cortex can improve sustained attention, short-term memory, and executive function. In this study, we directly investigated the influence of transcranial infrared laser stimulation on two neurobiologically dissociable systems of category learning: a prefrontal cortex mediated reflective system that learns categories using explicit rules, and a striatally mediated reflexive learning system that forms gradual stimulus-response associations. Participants (n=118) received either active infrared laser to the lateral prefrontal cortex or sham (placebo) stimulation, and then learned one of two category structures-a rule-based structure optimally learned by the reflective system, or an information-integration structure optimally learned by the reflexive system. We found that prefrontal rule-based learning was substantially improved following transcranial infrared laser stimulation as compared to placebo (treatment X block interaction: F(1, 298)=5.117, p=0.024), while information-integration learning did not show significant group differences (treatment X block interaction: F(1, 288)=1.633, p=0.202). These results highlight the exciting potential of transcranial infrared laser stimulation for cognitive enhancement and provide insight into the neurobiological underpinnings of category learning.

  18. Brain Regions Involved in the Learning and Application of Reward Rules in a Two-Deck Gambling Task

    ERIC Educational Resources Information Center

    Hartstra, E.; Oldenburg, J. F. E.; Van Leijenhorst, L.; Rombouts, S. A. R. B.; Crone, E. A.

    2010-01-01

    Decision-making involves the ability to choose between competing actions that are associated with uncertain benefits and penalties. The Iowa Gambling Task (IGT), which mimics real-life decision-making, involves learning a reward-punishment rule over multiple trials. Patients with damage to ventromedial prefrontal cortex (VMPFC) show deficits…

  19. Automatic de-identification of French clinical records: comparison of rule-based and machine-learning approaches.

    PubMed

    Grouin, Cyril; Zweigenbaum, Pierre

    2013-01-01

    In this paper, we present a comparison of two approaches to automatically de-identify medical records written in French: a rule-based system and a machine-learning based system using a conditional random fields (CRF) formalism. Both systems have been designed to process nine identifiers in a corpus of medical records in cardiology. We performed two evaluations: first, on 62 documents in cardiology, and on 10 documents in foetopathology - produced by optical character recognition (OCR) - to evaluate the robustness of our systems. We achieved a 0.843 (rule-based) and 0.883 (machine-learning) exact match overall F-measure in cardiology. While the rule-based system allowed us to achieve good results on nominative (first and last names) and numerical data (dates, phone numbers, and zip codes), the machine-learning approach performed best on more complex categories (postal addresses, hospital names, medical devices, and towns). On the foetopathology corpus, although our systems have not been designed for this corpus and despite OCR character recognition errors, we obtained promising results: a 0.681 (rule-based) and 0.638 (machine-learning) exact-match overall F-measure. This demonstrates that existing tools can be applied to process new documents of lower quality.

  20. Making Implicit Metalevel Rules of the Discourse on Function Explicit Topics of Reflection in the Classroom to Foster Student Learning

    ERIC Educational Resources Information Center

    Güçler, Beste

    2016-01-01

    Despite the existence of extensive literature on functions, fewer studies used sociocultural views to explore the development of student learning about the concept. This study uses a discursive lens to examine whether an instructional approach that specifically attends to particular metalevel rules in the mathematical discourse on functions…

  1. Effects of neonatal inferior prefrontal and medial temporal lesions on learning the rule for delayed nonmatching-to-sample.

    PubMed

    Málková, L; Bachevalier, J; Webster, M; Mishkin, M

    2000-01-01

    The ability of rhesus monkeys to master the rule for delayed nonmatching-to-sample (DNMS) has a protracted ontogenetic development, reaching adult levels of proficiency around 4 to 5 years of age (Bachevalier, 1990). To test the possibility that this slow development could be due, at least in part, to immaturity of the prefrontal component of a temporo-prefrontal circuit important for DNMS rule learning (Kowalska, Bachevalier, & Mishkin, 1991; Weinstein, Saunders, & Mishkin, 1988), monkeys with neonatal lesions of the inferior prefrontal convexity were compared on DNMS with both normal controls and animals given neonatal lesions of the medial temporal lobe. Consistent with our previous results (Bachevalier & Mishkin, 1994; Málková, Mishkin, & Bachevalier, 1995), the neonatal medial temporal lesions led to marked impairment in rule learning (as well as in recognition memory with long delays and list lengths) at both 3 months and 2 years of age. By contrast, the neonatal inferior convexity lesions yielded no impairment in rule-learning at 3 months and only a mild impairment at 2 years, a finding that also contrasts sharply with the marked effects of the same lesion made in adulthood. This pattern of sparing closely resembles the one found earlier after neonatal lesions to the cortical visual area TE (Bachevalier & Mishkin, 1994; Málková et al., 1995). The functional sparing at 3 months probably reflects the fact that the temporo-prefrontal circuit is nonfunctional at this early age, resulting in a total dependency on medial temporal contributions to rule learning. With further development, however, this circuit begins to provide a supplementary route for learning.

  2. Input-specific learning rules at excitatory synapses onto hippocampal parvalbumin-expressing interneurons.

    PubMed

    Le Roux, Nicolas; Cabezas, Carolina; Böhm, Urs Lucas; Poncer, Jean Christophe

    2013-04-01

    Hippocampal parvalbumin-expressing interneurons (PV INs) provide fast and reliable GABAergic signalling to principal cells and orchestrate hippocampal ensemble activities. Precise coordination of principal cell activity by PV INs relies in part on the efficacy of excitatory afferents that recruit them in the hippocampal network. Feed-forward (FF) inputs in particular from Schaffer collaterals influence spike timing precision in CA1 principal cells whereas local feedback (FB) inputs may contribute to pacemaker activities. Although PV INs have been shown to undergo activity-dependent long term plasticity, how both inputs are modulated during principal cell firing is unknown. Here we show that FF and FB synapses onto PV INs are endowed with distinct postsynaptic glutamate receptors which set opposing long-term plasticity rules. Inward-rectifying AMPA receptors (AMPARs) expressed at both FF and FB inputs mediate a form of anti-Hebbian long term potentiation (LTP), relying on coincident membrane hyperpolarization and synaptic activation. In contrast, FF inputs are largely devoid of NMDA receptors (NMDARs) which are more abundant at FB afferents and confer on them an additional form of LTP with Hebbian properties. Both forms of LTP are expressed with no apparent change in presynaptic function. The specific endowment of FF and FB inputs with distinct coincidence detectors allow them to be differentially tuned upon high frequency afferent activity. Thus, high frequency (>20 Hz) stimulation specifically potentiates FB, but not FF afferents. We propose that these differential, input-specific learning rules may allow PV INs to adapt to changes in hippocampal activity while preserving their precisely timed, clockwork operation.

  3. Combining rules and machine learning for extraction of temporal expressions and events from clinical narratives

    PubMed Central

    Kovačević, Aleksandar; Dehghan, Azad; Filannino, Michele; Keane, John A; Nenadic, Goran

    2013-01-01

    Objective Identification of clinical events (eg, problems, tests, treatments) and associated temporal expressions (eg, dates and times) are key tasks in extracting and managing data from electronic health records. As part of the i2b2 2012 Natural Language Processing for Clinical Data challenge, we developed and evaluated a system to automatically extract temporal expressions and events from clinical narratives. The extracted temporal expressions were additionally normalized by assigning type, value, and modifier. Materials and methods The system combines rule-based and machine learning approaches that rely on morphological, lexical, syntactic, semantic, and domain-specific features. Rule-based components were designed to handle the recognition and normalization of temporal expressions, while conditional random fields models were trained for event and temporal recognition. Results The system achieved micro F scores of 90% for the extraction of temporal expressions and 87% for clinical event extraction. The normalization component for temporal expressions achieved accuracies of 84.73% (expression's type), 70.44% (value), and 82.75% (modifier). Discussion Compared to the initial agreement between human annotators (87–89%), the system provided comparable performance for both event and temporal expression mining. While (lenient) identification of such mentions is achievable, finding the exact boundaries proved challenging. Conclusions The system provides a state-of-the-art method that can be used to support automated identification of mentions of clinical events and temporal expressions in narratives either to support the manual review process or as a part of a large-scale processing of electronic health databases. PMID:23605114

  4. Abstraction and Problem Reformulation

    NASA Technical Reports Server (NTRS)

    Giunchiglia, Fausto

    1992-01-01

    In work done jointly with Toby Walsh, the author has provided a sound theoretical foundation to the process of reasoning with abstraction (GW90c, GWS9, GW9Ob, GW90a). The notion of abstraction formalized in this work can be informally described as: (property 1), the process of mapping a representation of a problem, called (following historical convention (Sac74)) the 'ground' representation, onto a new representation, called the 'abstract' representation, which, (property 2) helps deal with the problem in the original search space by preserving certain desirable properties and (property 3) is simpler to handle as it is constructed from the ground representation by "throwing away details". One desirable property preserved by an abstraction is provability; often there is a relationship between provability in the ground representation and provability in the abstract representation. Another can be deduction or, possibly inconsistency. By 'throwing away details' we usually mean that the problem is described in a language with a smaller search space (for instance a propositional language or a language without variables) in which formulae of the abstract representation are obtained from the formulae of the ground representation by the use of some terminating rewriting technique. Often we require that the use of abstraction results in more efficient .reasoning. However, it might simply increase the number of facts asserted (eg. by allowing, in practice, the exploration of deeper search spaces or by implementing some form of learning). Among all abstractions, three very important classes have been identified. They relate the set of facts provable in the ground space to those provable in the abstract space. We call: TI abstractions all those abstractions where the abstractions of all the provable facts of the ground space are provable in the abstract space; TD abstractions all those abstractions wllere the 'unabstractions' of all the provable facts of the abstract space are

  5. Brain regions involved in the learning and application of reward rules in a two-deck gambling task.

    PubMed

    Hartstra, E; Oldenburg, J F E; Van Leijenhorst, L; Rombouts, S A R B; Crone, E A

    2010-04-01

    Decision-making involves the ability to choose between competing actions that are associated with uncertain benefits and penalties. The Iowa Gambling Task (IGT), which mimics real-life decision-making, involves learning a reward-punishment rule over multiple trials. Patients with damage to ventromedial prefrontal cortex (VMPFC) show deficits learning these rules, although this performance deficit is not exclusively associated with VMPFC damage. In this study, we used functional Magnetic Resonance Imaging (fMRI) to study the roles of prefrontal cortex regions involved in rule learning and rule application in healthy adults using an adapted version of the Iowa Gambling Task. Participants (N=20) were asked to infer rules over series of 16 trials in a two-deck card game. Rewards were given on each trial and punishment was unpredictable. For half of the series, those decks that gave high rewards were also better decks in the long run. For the other half of the series, the decks that gave low rewards were better decks in the long run. Behaviorally, participants started to differentiate between advantageous and disadvantageous decks after approximately four/six trials, and learning occurred faster for high-reward decks. Lateral PFC (lat-PFC) and Anterior Cingulate Coretex (ACC)/pre-supplementary motor area (pre-SMA) were most active for early decisions, whereas medial orbital frontal cortex (med-OFC) was most active for decisions made later in the series. These results suggest that lat-PFC and ACC/pre-SMA are important for directing behavior towards long-term goals, whereas med-OFC represents reward values towards which behavior should be directed.

  6. "Stars Shine Bright Deep in the Heart of LDA." Poster Session Abstracts of the International Conference of the Learning Disabilities Association of America (Dallas, Texas, March 6-9, 1996).

    ERIC Educational Resources Information Center

    Russell, Steven C., Comp.

    This monograph brings together 16 one- to two-page abstracts from research poster sessions held at the March 1996 international conference of the Learning Disabilities Association of America. The first section, addressing research on assessment and characteristics of students with learning disabilities, includes abstracts on the Woodcock-Johnson…

  7. Automated Assume-Guarantee Reasoning by Abstraction Refinement

    NASA Technical Reports Server (NTRS)

    Pasareanu, Corina S.; Giannakopoulous, Dimitra; Glannakopoulou, Dimitra

    2008-01-01

    Current automated approaches for compositional model checking in the assume-guarantee style are based on learning of assumptions as deterministic automata. We propose an alternative approach based on abstraction refinement. Our new method computes the assumptions for the assume-guarantee rules as conservative and not necessarily deterministic abstractions of some of the components, and refines those abstractions using counter-examples obtained from model checking them together with the other components. Our approach also exploits the alphabets of the interfaces between components and performs iterative refinement of those alphabets as well as of the abstractions. We show experimentally that our preliminary implementation of the proposed alternative achieves similar or better performance than a previous learning-based implementation.

  8. Rules, Technique, and Practical Knowledge: A Wittgensteinian Exploration of Vocational Learning

    ERIC Educational Resources Information Center

    Winch, Christopher

    2006-01-01

    In this essay, Christopher Winch explores the relevance of Ludwig Wittgenstein's account of rule-following to vocational education with particular reference to the often-made claim that any account of an activity in terms of rule-following implies rigidity and inflexibility. He argues that most rule-following is only successful when it involves a…

  9. Category number impacts rule-based and information-integration category learning: a reassessment of evidence for dissociable category-learning systems.

    PubMed

    Stanton, Roger D; Nosofsky, Robert M

    2013-07-01

    Researchers have proposed that an explicit reasoning system is responsible for learning rule-based category structures and that a separate implicit, procedural-learning system is responsible for learning information-integration category structures. As evidence for this multiple-system hypothesis, researchers report a dissociation based on category-number manipulations in which rule-based category learning is worse when the category is composed of 4, rather than 2, response categories; however, information-integration category learning is unaffected by category-number manipulations. We argue that within the reported category-number manipulations, there exists a critical confound: Perceptual clusters used to construct the categories are spread apart in the 4-category condition relative to the 2-category one. The present research shows that when this confound is eliminated, performance on information-integration category learning is worse for 4 categories than for 2 categories, and this finding is demonstrated across 2 different information-integration category structures. Furthermore, model-based analyses indicate that a single-system learning model accounts well for both the original findings and the updated experimental findings reported here.

  10. Abstract Constructions.

    ERIC Educational Resources Information Center

    Pietropola, Anne

    1998-01-01

    Describes a lesson designed to culminate a year of eighth-grade art classes in which students explore elements of design and space by creating 3-D abstract constructions. Outlines the process of using foam board and markers to create various shapes and optical effects. (DSK)

  11. Habituation: a non-associative learning rule design for spiking neurons and an autonomous mobile robots implementation.

    PubMed

    Cyr, André; Boukadoum, Mounir

    2013-03-01

    This paper presents a novel bio-inspired habituation function for robots under control by an artificial spiking neural network. This non-associative learning rule is modelled at the synaptic level and validated through robotic behaviours in reaction to different stimuli patterns in a dynamical virtual 3D world. Habituation is minimally represented to show an attenuated response after exposure to and perception of persistent external stimuli. Based on current neurosciences research, the originality of this rule includes modulated response to variable frequencies of the captured stimuli. Filtering out repetitive data from the natural habituation mechanism has been demonstrated to be a key factor in the attention phenomenon, and inserting such a rule operating at multiple temporal dimensions of stimuli increases a robot's adaptive behaviours by ignoring broader contextual irrelevant information.

  12. Rule Extraction Based on Extreme Learning Machine and an Improved Ant-Miner Algorithm for Transient Stability Assessment.

    PubMed

    Li, Yang; Li, Guoqing; Wang, Zhenhao

    2015-01-01

    In order to overcome the problems of poor understandability of the pattern recognition-based transient stability assessment (PRTSA) methods, a new rule extraction method based on extreme learning machine (ELM) and an improved Ant-miner (IAM) algorithm is presented in this paper. First, the basic principles of ELM and Ant-miner algorithm are respectively introduced. Then, based on the selected optimal feature subset, an example sample set is generated by the trained ELM-based PRTSA model. And finally, a set of classification rules are obtained by IAM algorithm to replace the original ELM network. The novelty of this proposal is that transient stability rules are extracted from an example sample set generated by the trained ELM-based transient stability assessment model by using IAM algorithm. The effectiveness of the proposed method is shown by the application results on the New England 39-bus power system and a practical power system--the southern power system of Hebei province.

  13. Innovation Abstracts, Volume XV, 1993.

    ERIC Educational Resources Information Center

    Roueche, Suanne D., Ed.

    1993-01-01

    This volume of 30 one- to two-page abstracts from 1993 highlights a variety of innovative approaches to teaching and learning in the community college. Topics covered in the abstracts include: (1) role-playing to encourage critical thinking; (2) team learning techniques to cultivate business skills; (3) librarian-instructor partnerships to create…

  14. Learning with Technology: Video Modeling with Concrete-Representational-Abstract Sequencing for Students with Autism Spectrum Disorder

    ERIC Educational Resources Information Center

    Yakubova, Gulnoza; Hughes, Elizabeth M.; Shinaberry, Megan

    2016-01-01

    The purpose of this study was to determine the effectiveness of a video modeling intervention with concrete-representational-abstract instructional sequence in teaching mathematics concepts to students with autism spectrum disorder (ASD). A multiple baseline across skills design of single-case experimental methodology was used to determine the…

  15. A new modulated Hebbian learning rule--biologically plausible method for local computation of a principal subspace.

    PubMed

    Jankovic, Marko; Ogawa, Hidemitsu

    2003-08-01

    This paper presents one possible implementation of a transformation that performs linear mapping to a lower-dimensional subspace. Principal component subspace will be the one that will be analyzed. Idea implemented in this paper represents generalization of the recently proposed infinity OH neural method for principal component extraction. The calculations in the newly proposed method are performed locally--a feature which is usually considered as desirable from the biological point of view. Comparing to some other wellknown methods, proposed synaptic efficacy learning rule requires less information about the value of the other efficacies to make single efficacy modification. Synaptic efficacies are modified by implementation of Modulated Hebb-type (MH) learning rule. Slightly modified MH algorithm named Modulated Hebb Oja (MHO) algorithm, will be also introduced. Structural similarity of the proposed network with part of the retinal circuit will be presented, too.

  16. Physiological expression of olfactory discrimination rule learning balances whole-population modulation and circuit stability in the piriform cortex network.

    PubMed

    Jammal, Luna; Whalley, Ben; Ghosh, Sourav; Lamrecht, Raphael; Barkai, Edi

    2016-07-01

    Once trained, rats are able to execute particularly difficult olfactory discrimination tasks with exceptional accuracy. Such skill acquisition, termed "rule learning", is accompanied by a series of long-lasting modifications to three cellular properties which modulate pyramidal neuron activity in piriform cortex; intrinsic excitability, synaptic excitation, and synaptic inhibition. Here, we explore how these changes, which are seemingly contradictory at the single-cell level in terms of their effect on neuronal excitation, are manifested within the piriform cortical neuronal network to store the memory of the rule, while maintaining network stability. To this end, we monitored network activity via multisite extracellular recordings of field postsynaptic potentials (fPSPS) and with single-cell recordings of miniature inhibitory and excitatory synaptic events in piriform cortex slices. We show that although 5 days after rule learning the cortical network maintains its basic activity patterns, synaptic connectivity is strengthened specifically between spatially proximal cells. Moreover, while the enhancement of inhibitory and excitatory synaptic connectivity is nearly identical, strengthening of synaptic inhibition is equally distributed between neurons while synaptic excitation is particularly strengthened within a specific subgroup of cells. We suggest that memory for the acquired rule is stored mainly by strengthening excitatory synaptic connection between close pyramidal neurons and runaway synaptic activity arising from this change is prevented by a nonspecific enhancement of synaptic inhibition.

  17. Event-related potentials reveal the relations between feature representations at different levels of abstraction.

    PubMed

    Hannah, Samuel D; Shedden, Judith M; Brooks, Lee R; Grundy, John G

    2016-11-01

    In this paper, we use behavioural methods and event-related potentials (ERPs) to explore the relations between informational and instantiated features, as well as the relation between feature abstraction and rule type. Participants are trained to categorize two species of fictitious animals and then identify perceptually novel exemplars. Critically, two groups are given a perfectly predictive counting rule that, according to Hannah and Brooks (2009. Featuring familiarity: How a familiar feature instantiation influences categorization. Canadian Journal of Experimental Psychology/Revue Canadienne de Psychologie Expérimentale, 63, 263-275. Retrieved from http://doi.org/10.1037/a0017919), should orient them to using abstract informational features when categorizing the novel transfer items. A third group is taught a feature list rule, which should orient them to using detailed instantiated features. One counting-rule group were taught their rule before any exposure to the actual stimuli, and the other immediately after training, having learned the instantiations first. The feature-list group were also taught their rule after training. The ERP results suggest that at test, the two counting-rule groups processed items differently, despite their identical rule. This not only supports the distinction that informational and instantiated features are qualitatively different feature representations, but also implies that rules can readily operate over concrete inputs, in contradiction to traditional approaches that assume that rules necessarily act on abstract inputs.

  18. Implementation of a spike-based perceptron learning rule using TiO2−x memristors

    PubMed Central

    Mostafa, Hesham; Khiat, Ali; Serb, Alexander; Mayr, Christian G.; Indiveri, Giacomo; Prodromakis, Themis

    2015-01-01

    Synaptic plasticity plays a crucial role in allowing neural networks to learn and adapt to various input environments. Neuromorphic systems need to implement plastic synapses to obtain basic “cognitive” capabilities such as learning. One promising and scalable approach for implementing neuromorphic synapses is to use nano-scale memristors as synaptic elements. In this paper we propose a hybrid CMOS-memristor system comprising CMOS neurons interconnected through TiO2−x memristors, and spike-based learning circuits that modulate the conductance of the memristive synapse elements according to a spike-based Perceptron plasticity rule. We highlight a number of advantages for using this spike-based plasticity rule as compared to other forms of spike timing dependent plasticity (STDP) rules. We provide experimental proof-of-concept results with two silicon neurons connected through a memristive synapse that show how the CMOS plasticity circuits can induce stable changes in memristor conductances, giving rise to increased synaptic strength after a potentiation episode and to decreased strength after a depression episode. PMID:26483629

  19. Differential modifications of synaptic weights during odor rule learning: dynamics of interaction between the piriform cortex with lower and higher brain areas.

    PubMed

    Cohen, Yaniv; Wilson, Donald A; Barkai, Edi

    2015-01-01

    Learning of a complex olfactory discrimination (OD) task results in acquisition of rule learning after prolonged training. Previously, we demonstrated enhanced synaptic connectivity between the piriform cortex (PC) and its ascending and descending inputs from the olfactory bulb (OB) and orbitofrontal cortex (OFC) following OD rule learning. Here, using recordings of evoked field postsynaptic potentials in behaving animals, we examined the dynamics by which these synaptic pathways are modified during rule acquisition. We show profound differences in synaptic connectivity modulation between the 2 input sources. During rule acquisition, the ascending synaptic connectivity from the OB to the anterior and posterior PC is simultaneously enhanced. Furthermore, post-training stimulation of the OB enhanced learning rate dramatically. In sharp contrast, the synaptic input in the descending pathway from the OFC was significantly reduced until training completion. Once rule learning was established, the strength of synaptic connectivity in the 2 pathways resumed its pretraining values. We suggest that acquisition of olfactory rule learning requires a transient enhancement of ascending inputs to the PC, synchronized with a parallel decrease in the descending inputs. This combined short-lived modulation enables the PC network to reorganize in a manner that enables it to first acquire and then maintain the rule.

  20. 2002 NASPSA Conference Abstracts.

    ERIC Educational Resources Information Center

    Journal of Sport & Exercise Psychology, 2002

    2002-01-01

    Contains abstracts from the 2002 conference of the North American Society for the Psychology of Sport and Physical Activity. The publication is divided into three sections: the preconference workshop, "Effective Teaching Methods in the Classroom;" symposia (motor development, motor learning and control, and sport psychology); and free…

  1. Effects of abstract versus concrete visual representations in an instructional simulation on students' declarative knowledge, learning transfer, and perceptions of the simulation

    NASA Astrophysics Data System (ADS)

    Mejia, William Ernesto

    2011-12-01

    Thanks to different multimedia authoring tools and specialized software that facilitate the design and development of computer-based simulations, science teachers and instructional media designers have a variety of simulations to support instructional delivery. However, there is a lack of research on how instructional designers and science teachers can select, design, and implement science simulations most effectively based on the simulations' visual attributes. One of the design principles that play an important part in the simulation design process is the visual representation of on-screen objects used to describe science concepts or principles. The purpose of this study was to investigate the effects of abstract and concrete visual representation of electricity concepts and principles in an instructional simulation on students' declarative knowledge, learning transfer, and perceptions of the simulation. The participants in this study were 39 elementary education pre-service teachers who were randomly assigned to either the concrete or the abstract treatment. The educational intervention was conducted over three 100-minute sessions. Since the sample violated the normality assumption, Mann-Whitney tests were conducted to verify whether the independent variable had significant effects on the three dependent variables. The data analysis found no statistically significant difference on learners' declarative knowledge, learning transfer, and perceptions about the simulation's attributes between those assigned to the concrete treatment and those assigned to the abstract treatment (p>.05). This finding did not favor one type of visual representation over the other.

  2. Department of Physics, Nara Women's University, Nara 630, Japan: Learning from stochastic rules under finite temperature - optimal temperature and asymptotic learning curve

    NASA Astrophysics Data System (ADS)

    Uezu, Tatsuya

    1997-11-01

    In learning under external disturbance, it is expected that some tolerance in the system will optimize the learning process. In this paper, we give one example of this in learning from stochastic rules by the Gibbs algorithm. Using the replica method, we show that for the case of output noise, there exists an optimal temperature at which the generalization error is a minimum. This temperature exists even in the limit of large training sets and is determined by the stable replica symmetric solution. On the other hand, for other types of noise no such temperature exists and the asymptotic behaviour is determined by the one-step replica symmetric breaking solution. Further, the asymptotic expressions for learning curves are derived. They are precisely the same as those for the minimum-error algorithm.

  3. A Concrete-to-Abstract Software Ramp: Environments for Learning Multiplication, Division and Intensive Quantity. Technical Report 87-8.

    ERIC Educational Resources Information Center

    Kaput, James J.; Pattison-Gordon, Laurie

    This document is intended to describe several software learning environments in an order that parallels a reasonable sequence of use by students. It also describes a planned an designed, but not yet implemented, extension of these environments from the discrete to the continuous case. Each of the implemented environments was developed in…

  4. A Rule-Based System for Hybrid Search and Delivery of Learning Objects to Learners

    ERIC Educational Resources Information Center

    Biletskiy, Yevgen; Baghi, Hamidreza; Steele, Jarrett; Vovk, Ruslan

    2012-01-01

    Purpose: Presently, searching the internet for learning material relevant to ones own interest continues to be a time-consuming task. Systems that can suggest learning material (learning objects) to a learner would reduce time spent searching for material, and enable the learner to spend more time for actual learning. The purpose of this paper is…

  5. Multimedia Football Viewing: Embedded Rules, Practice, and Video Context in IVD Procedural Learning.

    ERIC Educational Resources Information Center

    Kim, Eunsoon; Young, Michael F.

    This study investigated the effects of interactive video (IVD) instruction with embedded rules (production system rules) and practice with feedback on learners' academic achievement and perceived self efficacy in the domain of procedural knowledge for watching professional football. Subjects were 71 female volunteers from undergraduate education…

  6. Aqui y Alla (Here and There) Information-Based Learning Corridors between Tennessee and Puerto Rico: The Five Golden Rules in Intercultural Education

    ERIC Educational Resources Information Center

    Mehra, Bharat; Allard, Suzie; Qayyum, M. Asim; Barclay-McLaughlin, Gina

    2008-01-01

    This article proposes five information-based Golden Rules in intercultural education that represent a holistic approach to creating learning corridors across geographically dispersed academic communities. The Golden Rules are generated through qualitative analysis, grounded theory application, reflective practice, and critical research to…

  7. Learning with Technology: Video Modeling with Concrete-Representational-Abstract Sequencing for Students with Autism Spectrum Disorder.

    PubMed

    Yakubova, Gulnoza; Hughes, Elizabeth M; Shinaberry, Megan

    2016-07-01

    The purpose of this study was to determine the effectiveness of a video modeling intervention with concrete-representational-abstract instructional sequence in teaching mathematics concepts to students with autism spectrum disorder (ASD). A multiple baseline across skills design of single-case experimental methodology was used to determine the effectiveness of the intervention on the acquisition and maintenance of addition, subtraction, and number comparison skills for four elementary school students with ASD. Findings supported the effectiveness of the intervention in improving skill acquisition and maintenance at a 3-week follow-up. Implications for practice and future research are discussed.

  8. Should there be a three-strikes rule against pure discovery learning? The case for guided methods of instruction.

    PubMed

    Mayer, Richard E

    2004-01-01

    The author's thesis is that there is sufficient research evidence to make any reasonable person skeptical about the benefits of discovery learning--practiced under the guise of cognitive constructivism or social constructivism--as a preferred instructional method. The author reviews research on discovery of problem-solving rules culminating in the 1960s, discovery of conservation strategies culminating in the 1970s, and discovery of LOGO programming strategies culminating in the 1980s. In each case, guided discovery was more effective than pure discovery in helping students learn and transfer. Overall, the constructivist view of learning may be best supported by methods of instruction that involve cognitive activity rather than behavioral activity, instructional guidance rather than pure discovery, and curricular focus rather than unstructured exploration.

  9. Modeling fast stimulus-response association learning along the occipito-parieto-frontal pathway following rule instructions.

    PubMed

    Bugmann, Guido

    2012-01-24

    On the basis of instructions, humans are able to set up associations between sensory and motor areas of the brain separated by several neuronal relays, within a few seconds. This paper proposes a model of fast learning along the dorsal pathway, from primary visual areas to pre-motor cortex. A new synaptic learning rule is proposed where synaptic efficacies converge rapidly toward a specific value determined by the number of active inputs of a neuron, respecting a principle of resource limitation in terms of total synaptic input efficacy available to a neuron. The efficacies are stable with regards to repeated arrival of spikes in a spike train. This rule reproduces the inverse relationship between initial and final synaptic efficacy observed in long-term potentiation (LTP) experiments. Simulations of learning experiments are conducted in a multilayer network of leaky integrate-and-fire (LIF) spiking neuron models. It is proposed that cortical feedback connections convey a top-down learning-enabling signal that guides bottom-up learning in "hidden" neurons that are not directly exposed to input or output activity. Simulations of repeated presentation of the same stimulus-response pair, show that, under conditions of fast learning with probabilistic synaptic transmission, the networks tend to recruit a new sub-network at each presentation to represent the association, rather than re-using a previously trained one. This increasing allocation of neural resources results in progressively shorter execution times, in line with experimentally observed reduction in response time with practice. This article is part of a Special Issue entitled: Neural Coding.

  10. Rules and mechanisms of punishment learning in honey bees: the aversive conditioning of the sting extension response.

    PubMed

    Tedjakumala, Stevanus Rio; Giurfa, Martin

    2013-08-15

    Honeybees constitute established model organisms for the study of appetitive learning and memory. In recent years, the establishment of the technique of olfactory conditioning of the sting extension response (SER) has yielded new insights into the rules and mechanisms of aversive learning in insects. In olfactory SER conditioning, a harnessed bee learns to associate an olfactory stimulus as the conditioned stimulus with the noxious stimulation of an electric shock as the unconditioned stimulus. Here, we review the multiple aspects of honeybee aversive learning that have been uncovered using Pavlovian conditioning of the SER. From its behavioral principles and sensory variants to its cellular bases and implications for understanding social organization, we present the latest advancements in the study of punishment learning in bees and discuss its perspectives in order to define future research avenues and necessary improvements. The studies presented here underline the importance of studying honeybee learning not only from an appetitive but also from an aversive perspective, in order to uncover behavioral and cellular mechanisms of individual and social plasticity.

  11. Developmental changes between childhood and adulthood in passive observational and interactive feedback-based categorization rule learning.

    PubMed

    Hammer, Rubi; Kloet, Jim; Booth, James R

    2016-11-01

    As children start attending school they are more likely to face situations where they have to autonomously learn about novel object categories (e.g. by reading a picture book with descriptions of novel animals). Such autonomous observational category learning (OCL) gradually complements interactive feedback-based category learning (FBCL), where a child hypothesizes about the nature of a novel object, acts based on his prediction, and then receives feedback indicating the correctness of his prediction. Here we tested OCL and FBCL skills of elementary school children and adults. In both conditions, participants performed complex rule-based categorization tasks that required associating novel objects with novel category-labels. We expected children to perform better in FBCL tasks than in OCL tasks, whereas adults to be skilled in both tasks. As hypothesized, in early-phase learning children performed better in FBCL tasks than in OCL tasks. Unexpectedly, adults performed somewhat better in OCL tasks. Early-phase FBCL performance in the two age groups was matched, but the OCL performance of adults was higher than that of children. In late-phase learning there was only an age group main effect (adults > children). Moreover, performance in post-learning categorization tasks, that did not require label recollection, indicated that in FBCL tasks children were likely to directly learn the associations between an object and a category label, whereas in the OCL tasks they were likely to first learn which feature-dimensions were relevant. These findings shed light on developmental changes in cognitive control and learning mechanisms. Implications for educational settings are discussed.

  12. General asymmetric neutral networks and structure design by genetic algorithms: A learning rule for temporal patterns

    SciTech Connect

    Bornholdt, S.; Graudenz, D.

    1993-07-01

    A learning algorithm based on genetic algorithms for asymmetric neural networks with an arbitrary structure is presented. It is suited for the learning of temporal patterns and leads to stable neural networks with feedback.

  13. Automatic Learning of Fine Operating Rules for Online Power System Security Control.

    PubMed

    Sun, Hongbin; Zhao, Feng; Wang, Hao; Wang, Kang; Jiang, Weiyong; Guo, Qinglai; Zhang, Boming; Wehenkel, Louis

    2016-08-01

    Fine operating rules for security control and an automatic system for their online discovery were developed to adapt to the development of smart grids. The automatic system uses the real-time system state to determine critical flowgates, and then a continuation power flow-based security analysis is used to compute the initial transfer capability of critical flowgates. Next, the system applies the Monte Carlo simulations to expected short-term operating condition changes, feature selection, and a linear least squares fitting of the fine operating rules. The proposed system was validated both on an academic test system and on a provincial power system in China. The results indicated that the derived rules provide accuracy and good interpretability and are suitable for real-time power system security control. The use of high-performance computing systems enables these fine operating rules to be refreshed online every 15 min.

  14. Comparing Product Category Rules from Different Programs: Learned Outcomes Towards Global Alignment

    EPA Science Inventory

    Purpose Product category rules (PCRs) provide category-specific guidance for estimating and reporting product life cycle environmental impacts, typically in the form of environmental product declarations and product carbon footprints. Lack of global harmonization between PCRs or ...

  15. Comparing Product Category Rules from Different Programs: Learned Outcomes Towards Global Alignment (Presentation)

    EPA Science Inventory

    Purpose Product category rules (PCRs) provide category-specific guidance for estimating and reporting product life cycle environmental impacts, typically in the form of environmental product declarations and product carbon footprints. Lack of global harmonization between PCRs or ...

  16. Online Learning Behaviors for Radiology Interns Based on Association Rules and Clustering Technique

    ERIC Educational Resources Information Center

    Chen, Hsing-Shun; Liou, Chuen-He

    2014-01-01

    In a hospital, clinical teachers must also care for patients, so there is less time for the teaching of clinical courses, or for discussing clinical cases with interns. However, electronic learning (e-learning) can complement clinical skills education for interns in a blended-learning process. Students discuss and interact with classmates in an…

  17. Young Children's Selective Learning of Rule Games from Reliable and Unreliable Models

    ERIC Educational Resources Information Center

    Rakoczy, Hannes; Warneken, Felix; Tomasello, Michael

    2009-01-01

    We investigated preschoolers' selective learning from models that had previously appeared to be reliable or unreliable. Replicating previous research, children from 4 years selectively learned novel words from reliable over unreliable speakers. Extending previous research, children also selectively learned other kinds of acts--novel games--from…

  18. Abstraction and Assume-Guarantee Reasoning for Automated Software Verification

    NASA Technical Reports Server (NTRS)

    Chaki, S.; Clarke, E.; Giannakopoulou, D.; Pasareanu, C. S.

    2004-01-01

    Compositional verification and abstraction are the key techniques to address the state explosion problem associated with model checking of concurrent software. A promising compositional approach is to prove properties of a system by checking properties of its components in an assume-guarantee style. This article proposes a framework for performing abstraction and assume-guarantee reasoning of concurrent C code in an incremental and fully automated fashion. The framework uses predicate abstraction to extract and refine finite state models of software and it uses an automata learning algorithm to incrementally construct assumptions for the compositional verification of the abstract models. The framework can be instantiated with different assume-guarantee rules. We have implemented our approach in the COMFORT reasoning framework and we show how COMFORT out-performs several previous software model checking approaches when checking safety properties of non-trivial concurrent programs.

  19. Concreteness Fading of Algebraic Instruction: Effects on Learning

    ERIC Educational Resources Information Center

    Ottmar, Erin; Landy, David

    2017-01-01

    Learning algebra is difficult for many students in part because of an emphasis on the memorization of abstract rules. Algebraic reasoners across expertise levels often rely on perceptual-motor strategies to make these rules meaningful and memorable. However, in many cases, rules are provided as patterns to be memorized verbally, with little overt…

  20. Simultaneous perturbation learning rule for recurrent neural networks and its FPGA implementation.

    PubMed

    Maeda, Yutaka; Wakamura, Masatoshi

    2005-11-01

    Recurrent neural networks have interesting properties and can handle dynamic information processing unlike ordinary feedforward neural networks. However, they are generally difficult to use because there is no convenient learning scheme. In this paper, a recursive learning scheme for recurrent neural networks using the simultaneous perturbation method is described. The detailed procedure of the scheme for recurrent neural networks is explained. Unlike ordinary correlation learning, this method is applicable to analog learning and the learning of oscillatory solutions of recurrent neural networks. Moreover, as a typical example of recurrent neural networks, we consider the hardware implementation of Hopfield neural networks using a field-programmable gate array (FPGA). The details of the implementation are described. Two examples of a Hopfield neural network system for analog and oscillatory targets are shown. These results show that the learning scheme proposed here is feasible.

  1. ALT-C 95: Changing Education, Changing Technology. Conference Abstracts of the Association for Learning Technology Conference (2nd, Milton Keynes, England, United Kingdom, September 11-13, 1995).

    ERIC Educational Resources Information Center

    Hawkridge, David, Ed.

    This program for the 1995 Association for Learning Technology Conference summarizes the presentations of the discussions, demonstrations, workshops, and poster sessions. Abstracts of the following papers presented at the conference are included: "New Structures for Learning" (Patrick Allen & Kate Sankey); "Multiple System…

  2. "Renewing the Commitment: 1963-1997." Poster Session Abstracts from the International Conference of the Learning Disabilities Association of America (Chicago, Illinois, February 19-22, 1997). Volume 6.

    ERIC Educational Resources Information Center

    Russell, Steven C., Comp.

    Extensive abstracts of papers presented at two poster sessions of a conference on learning disabilities (LD) are included. The first session of the conference focused on research on assessment and characteristics of students with learning disabilities. Individual papers covered the following topics: longitudinal case studies of college students…

  3. Rule Extraction Based on Extreme Learning Machine and an Improved Ant-Miner Algorithm for Transient Stability Assessment

    PubMed Central

    Li, Yang; Li, Guoqing; Wang, Zhenhao

    2015-01-01

    In order to overcome the problems of poor understandability of the pattern recognition-based transient stability assessment (PRTSA) methods, a new rule extraction method based on extreme learning machine (ELM) and an improved Ant-miner (IAM) algorithm is presented in this paper. First, the basic principles of ELM and Ant-miner algorithm are respectively introduced. Then, based on the selected optimal feature subset, an example sample set is generated by the trained ELM-based PRTSA model. And finally, a set of classification rules are obtained by IAM algorithm to replace the original ELM network. The novelty of this proposal is that transient stability rules are extracted from an example sample set generated by the trained ELM-based transient stability assessment model by using IAM algorithm. The effectiveness of the proposed method is shown by the application results on the New England 39-bus power system and a practical power system — the southern power system of Hebei province. PMID:26091524

  4. Rules and Construction Effects in Learning the Argument Structure of Verbs

    ERIC Educational Resources Information Center

    Demuth, Katherine; Machobane, 'Malillo; Moloi, Francina

    2003-01-01

    Theorists of language acquisition have long debated the means by which children learn the argument structure of verbs (e.g. Bowerman, 1974, 1990; Pinker, 1984, 1989; Tomasello, 1992). Central to this controversy has been the possible role of verb semantics, especially in learning which verbs undergo dative-shift alternation in languages like…

  5. Social Interaction Rules in Cooperative Learning Groups for Students at Risk for ADHD

    ERIC Educational Resources Information Center

    Kuester, Deitra A.; Zentall, Sydney S.

    2012-01-01

    This study assessed the effects of providing social participation rules on the performance and social behavior of a school-based sample of 10-14-year-old students at risk for attention deficit hyperactivity disorder (n = 34) who worked cooperatively in same-gender triads with typical peers (n = 92). The design was primarily a 2 (population group)…

  6. Automatic rule learning using decision tree for fuzzy classifier in fault diagnosis of roller bearing

    NASA Astrophysics Data System (ADS)

    Sugumaran, V.; Ramachandran, K. I.

    2007-07-01

    Roller bearing is one of the most widely used elements in rotary machines. Condition monitoring of such elements is conceived as pattern recognition problem. Pattern recognition has two main phases: feature extraction and feature classification. Statistical features like minimum value, standard error and kurtosis, etc. are widely used as features in fault diagnostics. These features are extracted from vibration signals. A rule set is formed from the extracted features and input to a fuzzy classifier. The rule set necessary for building the fuzzy classifier is obtained largely by intuition and domain knowledge. This paper presents the use of decision tree to generate the rules automatically from the feature set. The vibration signal from a piezo-electric transducer is captured for the following conditions—good bearing, bearing with inner race fault, bearing with outer race fault, and inner and outer race fault. The statistical features are extracted and good features that discriminate the different fault conditions of the bearing are selected using decision tree. The rule set for fuzzy classifier is obtained once again by using the decision tree. A fuzzy classifier is built and tested with representative data. The results are found to be encouraging.

  7. Targeted Learning of the Mean Outcome under an Optimal Dynamic Treatment Rule.

    PubMed

    van der Laan, Mark J; Luedtke, Alexander R

    2015-03-01

    We consider estimation of and inference for the mean outcome under the optimal dynamic two time-point treatment rule defined as the rule that maximizes the mean outcome under the dynamic treatment, where the candidate rules are restricted to depend only on a user-supplied subset of the baseline and intermediate covariates. This estimation problem is addressed in a statistical model for the data distribution that is nonparametric beyond possible knowledge about the treatment and censoring mechanism. This contrasts from the current literature that relies on parametric assumptions. We establish that the mean of the counterfactual outcome under the optimal dynamic treatment is a pathwise differentiable parameter under conditions, and develop a targeted minimum loss-based estimator (TMLE) of this target parameter. We establish asymptotic linearity and statistical inference for this estimator under specified conditions. In a sequentially randomized trial the statistical inference relies upon a second-order difference between the estimator of the optimal dynamic treatment and the optimal dynamic treatment to be asymptotically negligible, which may be a problematic condition when the rule is based on multivariate time-dependent covariates. To avoid this condition, we also develop TMLEs and statistical inference for data adaptive target parameters that are defined in terms of the mean outcome under the estimate of the optimal dynamic treatment. In particular, we develop a novel cross-validated TMLE approach that provides asymptotic inference under minimal conditions, avoiding the need for any empirical process conditions. We offer simulation results to support our theoretical findings.

  8. Rule Learning over Consonants and Vowels in a Non-Human Animal

    ERIC Educational Resources Information Center

    de la Mora, Daniela M.; Toro, Juan M.

    2013-01-01

    Perception studies have shown similarities between humans and other animals in a wide array of language-related processes. However, the components of language that make it uniquely human have not been fully identified. Here we show that nonhuman animals extract rules over speech sequences that are difficult for humans. Specifically, animals easily…

  9. A Comparison of the neural correlates that underlie rule-based and information-integration category learning.

    PubMed

    Carpenter, Kathryn L; Wills, Andy J; Benattayallah, Abdelmalek; Milton, Fraser

    2016-10-01

    The influential competition between verbal and implicit systems (COVIS) model proposes that category learning is driven by two competing neural systems-an explicit, verbal, system, and a procedural-based, implicit, system. In the current fMRI study, participants learned either a conjunctive, rule-based (RB), category structure that is believed to engage the explicit system, or an information-integration category structure that is thought to preferentially recruit the implicit system. The RB and information-integration category structures were matched for participant error rate, the number of relevant stimulus dimensions, and category separation. Under these conditions, considerable overlap in brain activation, including the prefrontal cortex, basal ganglia, and the hippocampus, was found between the RB and information-integration category structures. Contrary to the predictions of COVIS, the medial temporal lobes and in particular the hippocampus, key regions for explicit memory, were found to be more active in the information-integration condition than in the RB condition. No regions were more activated in RB than information-integration category learning. The implications of these results for theories of category learning are discussed. Hum Brain Mapp 37:3557-3574, 2016. © 2016 Wiley Periodicals, Inc.

  10. 37 CFR 1.438 - The abstract.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2010-07-01 2010-07-01 false The abstract. 1.438 Section 1... COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES International Processing Provisions The International Application § 1.438 The abstract. (a) Requirements as to the content and form of the abstract are set forth...

  11. 37 CFR 1.438 - The abstract.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2014-07-01 2014-07-01 false The abstract. 1.438 Section 1... COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES International Processing Provisions The International Application § 1.438 The abstract. (a) Requirements as to the content and form of the abstract are set forth...

  12. 37 CFR 1.438 - The abstract.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2012-07-01 2012-07-01 false The abstract. 1.438 Section 1... COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES International Processing Provisions The International Application § 1.438 The abstract. (a) Requirements as to the content and form of the abstract are set forth...

  13. 37 CFR 1.438 - The abstract.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2013-07-01 2013-07-01 false The abstract. 1.438 Section 1... COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES International Processing Provisions The International Application § 1.438 The abstract. (a) Requirements as to the content and form of the abstract are set forth...

  14. The drift diffusion model as the choice rule in reinforcement learning.

    PubMed

    Pedersen, Mads Lund; Frank, Michael J; Biele, Guido

    2016-12-13

    Current reinforcement-learning models often assume simplified decision processes that do not fully reflect the dynamic complexities of choice processes. Conversely, sequential-sampling models of decision making account for both choice accuracy and response time, but assume that decisions are based on static decision values. To combine these two computational models of decision making and learning, we implemented reinforcement-learning models in which the drift diffusion model describes the choice process, thereby capturing both within- and across-trial dynamics. To exemplify the utility of this approach, we quantitatively fit data from a common reinforcement-learning paradigm using hierarchical Bayesian parameter estimation, and compared model variants to determine whether they could capture the effects of stimulant medication in adult patients with attention-deficit hyperactivity disorder (ADHD). The model with the best relative fit provided a good description of the learning process, choices, and response times. A parameter recovery experiment showed that the hierarchical Bayesian modeling approach enabled accurate estimation of the model parameters. The model approach described here, using simultaneous estimation of reinforcement-learning and drift diffusion model parameters, shows promise for revealing new insights into the cognitive and neural mechanisms of learning and decision making, as well as the alteration of such processes in clinical groups.

  15. An Ensemble Rule Learning Approach for Automated Morphological Classification of Erythrocytes.

    PubMed

    Maity, Maitreya; Mungle, Tushar; Dhane, Dhiraj; Maiti, A K; Chakraborty, Chandan

    2017-04-01

    The analysis of pathophysiological change to erythrocytes is important for early diagnosis of anaemia. The manual assessment of pathology slides is time-consuming and complicated regarding various types of cell identification. This paper proposes an ensemble rule-based decision-making approach for morphological classification of erythrocytes. Firstly, the digital microscopic blood smear images are pre-processed for removal of spurious regions followed by colour normalisation and thresholding. The erythrocytes are segmented from background image using the watershed algorithm. The shape features are then extracted from the segmented image to detect shape abnormality present in microscopic blood smear images. The decision about the abnormality is taken using proposed multiple rule-based expert systems. The deciding factor is majority ensemble voting for abnormally shaped erythrocytes. Here, shape-based features are considered for nine different types of abnormal erythrocytes including normal erythrocytes. Further, the adaptive boosting algorithm is used to generate multiple decision tree models where each model tree generates an individual rule set. The supervised classification method is followed to generate rules using a C4.5 decision tree. The proposed ensemble approach is precise in detecting eight types of abnormal erythrocytes with an overall accuracy of 97.81% and weighted sensitivity of 97.33%, weighted specificity of 99.7%, and weighted precision of 98%. This approach shows the robustness of proposed strategy for erythrocytes classification into abnormal and normal class. The article also clarifies its latent quality to be incorporated in point of care technology solution targeting a rapid clinical assistance.

  16. The Effects of Variation on Learning Word Order Rules by Adults with and without Language-Based Learning Disabilities

    ERIC Educational Resources Information Center

    Grunow, Hope; Spaulding, Tammie J.; Gomez, Rebecca L.; Plante, Elena

    2006-01-01

    Non-adjacent dependencies characterize numerous features of English syntax, including certain verb tense structures and subject-verb agreement. This study utilized an artificial language paradigm to examine the contribution of item variability to the learning of these types of dependencies. Adult subjects with and without language-based learning…

  17. Discontinuous Categories Affect Information-Integration but not Rule-Based Category Learning

    ERIC Educational Resources Information Center

    Maddox, W. Todd; Filoteo, J. Vincent; Lauritzen, J. Scott; Connally, Emily; Hejl, Kelli D.

    2005-01-01

    Three experiments were conducted that provide a direct examination of within-category discontinuity manipulations on the implicit, procedural-based learning and the explicit, hypothesis-testing systems proposed in F. G. Ashby, L. A. Alfonso-Reese, A. U. Turken, and E. M. Waldron's (1998) competition between verbal and implicit systems model.…

  18. Rules, Roles and Tools: Activity Theory and the Comparative Study of E-Learning

    ERIC Educational Resources Information Center

    Benson, Angela; Lawler, Cormac; Whitworth, Andrew

    2008-01-01

    Activity theory (AT) is a powerful tool for investigating "artefacts in use", ie, the ways technologies interrelate with their local context. AT reveals the interfaces between e-learning at the macro- (strategy, policy, "campus-wide" solutions) and the micro-organisational levels (everyday working practice, iterative change, individual…

  19. Learning the Rules: Observation and Imitation of a Sorting Strategy by 36-Month-Old Children

    ERIC Educational Resources Information Center

    Williamson, Rebecca A.; Jaswal, Vikram K.; Meltzoff, Andrew N.

    2010-01-01

    Two experiments were used to investigate the scope of imitation by testing whether 36-month-olds can learn to produce a categorization strategy through observation. After witnessing an adult sort a set of objects by a visible property (their color; Experiment 1) or a nonvisible property (the particular sounds produced when the objects were shaken;…

  20. The Effects of the Locus of CAI Control Strategies on the Learning of Mathematics Rules.

    ERIC Educational Resources Information Center

    Goetzfried, Leslie; Hannafin, Michael J.

    1985-01-01

    Effects of the locus of computer assisted instruction (CAI) strategies on low achievers' learning accuracy and efficiency were studied. Externally controlled adaptive, individually based learner control with advisement, and linear control design strategies were used. Effects were examined for CAI strategy, prior achievement, and sex of student.…

  1. Stable Rules: Science and Social Transmission. Studies in the Learning Sciences.

    ERIC Educational Resources Information Center

    Nathan, Henry

    In laying the groundwork for a co-operative scientific inquiry in the field of learning sciences the following five areas of access to the study are considered in this introductory inquiry statement: 1) genetic sociology (symbolic systems and early socialization); 2) experimental ethnography (the effect of literacy on the structure of skill and…

  2. Language Abstractions for Software-Defined Networks

    DTIC Science & Technology

    2012-01-01

    monitor the total amount of web traffic, the program- mer must install rules that process (and count) traffic involv- ing TCP port 80 separately from...side-by-side with a different module. To sup- port applications whose correct operation involves a moni- toring component, Frenetic includes an...lambda:[]) for switch,learned in table.items(): patterns = false_fp() for mac, port in learned.items(): rule = Rule(dstmac_fp(mac),[forward( port

  3. Functional network construction in Arabidopsis using rule-based machine learning on large-scale data sets.

    PubMed

    Bassel, George W; Glaab, Enrico; Marquez, Julietta; Holdsworth, Michael J; Bacardit, Jaume

    2011-09-01

    The meta-analysis of large-scale postgenomics data sets within public databases promises to provide important novel biological knowledge. Statistical approaches including correlation analyses in coexpression studies of gene expression have emerged as tools to elucidate gene function using these data sets. Here, we present a powerful and novel alternative methodology to computationally identify functional relationships between genes from microarray data sets using rule-based machine learning. This approach, termed "coprediction," is based on the collective ability of groups of genes co-occurring within rules to accurately predict the developmental outcome of a biological system. We demonstrate the utility of coprediction as a powerful analytical tool using publicly available microarray data generated exclusively from Arabidopsis thaliana seeds to compute a functional gene interaction network, termed Seed Co-Prediction Network (SCoPNet). SCoPNet predicts functional associations between genes acting in the same developmental and signal transduction pathways irrespective of the similarity in their respective gene expression patterns. Using SCoPNet, we identified four novel regulators of seed germination (ALTERED SEED GERMINATION5, 6, 7, and 8), and predicted interactions at the level of transcript abundance between these novel and previously described factors influencing Arabidopsis seed germination. An online Web tool to query SCoPNet has been developed as a community resource to dissect seed biology and is available at http://www.vseed.nottingham.ac.uk/.

  4. A Hebbian learning rule gives rise to mirror neurons and links them to control theoretic inverse models.

    PubMed

    Hanuschkin, A; Ganguli, S; Hahnloser, R H R

    2013-01-01

    Mirror neurons are neurons whose responses to the observation of a motor act resemble responses measured during production of that act. Computationally, mirror neurons have been viewed as evidence for the existence of internal inverse models. Such models, rooted within control theory, map-desired sensory targets onto the motor commands required to generate those targets. To jointly explore both the formation of mirrored responses and their functional contribution to inverse models, we develop a correlation-based theory of interactions between a sensory and a motor area. We show that a simple eligibility-weighted Hebbian learning rule, operating within a sensorimotor loop during motor explorations and stabilized by heterosynaptic competition, naturally gives rise to mirror neurons as well as control theoretic inverse models encoded in the synaptic weights from sensory to motor neurons. Crucially, we find that the correlational structure or stereotypy of the neural code underlying motor explorations determines the nature of the learned inverse model: random motor codes lead to causal inverses that map sensory activity patterns to their motor causes; such inverses are maximally useful, by allowing the imitation of arbitrary sensory target sequences. By contrast, stereotyped motor codes lead to less useful predictive inverses that map sensory activity to future motor actions. Our theory generalizes previous work on inverse models by showing that such models can be learned in a simple Hebbian framework without the need for error signals or backpropagation, and it makes new conceptual connections between the causal nature of inverse models, the statistical structure of motor variability, and the time-lag between sensory and motor responses of mirror neurons. Applied to bird song learning, our theory can account for puzzling aspects of the song system, including necessity of sensorimotor gating and selectivity of auditory responses to bird's own song (BOS) stimuli.

  5. Categorization and decision-making in a neurobiologically plausible spiking network using a STDP-like learning rule.

    PubMed

    Beyeler, Michael; Dutt, Nikil D; Krichmar, Jeffrey L

    2013-12-01

    Understanding how the human brain is able to efficiently perceive and understand a visual scene is still a field of ongoing research. Although many studies have focused on the design and optimization of neural networks to solve visual recognition tasks, most of them either lack neurobiologically plausible learning rules or decision-making processes. Here we present a large-scale model of a hierarchical spiking neural network (SNN) that integrates a low-level memory encoding mechanism with a higher-level decision process to perform a visual classification task in real-time. The model consists of Izhikevich neurons and conductance-based synapses for realistic approximation of neuronal dynamics, a spike-timing-dependent plasticity (STDP) synaptic learning rule with additional synaptic dynamics for memory encoding, and an accumulator model for memory retrieval and categorization. The full network, which comprised 71,026 neurons and approximately 133 million synapses, ran in real-time on a single off-the-shelf graphics processing unit (GPU). The network was constructed on a publicly available SNN simulator that supports general-purpose neuromorphic computer chips. The network achieved 92% correct classifications on MNIST in 100 rounds of random sub-sampling, which is comparable to other SNN approaches and provides a conservative and reliable performance metric. Additionally, the model correctly predicted reaction times from psychophysical experiments. Because of the scalability of the approach and its neurobiological fidelity, the current model can be extended to an efficient neuromorphic implementation that supports more generalized object recognition and decision-making architectures found in the brain.

  6. Machine learning-, rule- and pharmacophore-based classification on the inhibition of P-glycoprotein and NorA.

    PubMed

    Ngo, T-D; Tran, T-D; Le, M-T; Thai, K-M

    2016-09-01

    The efflux pumps P-glycoprotein (P-gp) in humans and NorA in Staphylococcus aureus are of great interest for medicinal chemists because of their important roles in multidrug resistance (MDR). The high polyspecificity as well as the unavailability of high-resolution X-ray crystal structures of these transmembrane proteins lead us to combining ligand-based approaches, which in the case of this study were machine learning, perceptual mapping and pharmacophore modelling. For P-gp inhibitory activity, individual models were developed using different machine learning algorithms and subsequently combined into an ensemble model which showed a good discrimination between inhibitors and noninhibitors (acctrain-diverse = 84%; accinternal-test = 92% and accexternal-test = 100%). For ligand promiscuity between P-gp and NorA, perceptual maps and pharmacophore models were generated for the detection of rules and features. Based on these in silico tools, hit compounds for reversing MDR were discovered from the in-house and DrugBank databases through virtual screening in an attempt to restore drug sensitivity in cancer cells and bacteria.

  7. Rule-based learning of regular past tense in children with specific language impairment.

    PubMed

    Smith-Lock, Karen M

    2015-01-01

    The treatment of children with specific language impairment was used as a means to investigate whether a single- or dual-mechanism theory best conceptualizes the acquisition of English past tense. The dual-mechanism theory proposes that regular English past-tense forms are produced via a rule-based process whereas past-tense forms of irregular verbs are stored in the lexicon. Single-mechanism theories propose that both regular and irregular past-tense verbs are stored in the lexicon. Five 5-year-olds with specific language impairment received treatment for regular past tense. The children were tested on regular past-tense production and third-person singular "s" twice before treatment and once after treatment, at eight-week intervals. Treatment consisted of one-hour play-based sessions, once weekly, for eight weeks. Crucially, treatment focused on different lexical items from those in the test. Each child demonstrated significant improvement on the untreated past-tense test items after treatment, but no improvement on the untreated third-person singular "s". Generalization to untreated past-tense verbs could not be attributed to a frequency effect or to phonological similarity of trained and tested items. It is argued that the results are consistent with a dual-mechanism theory of past-tense inflection.

  8. Learning of an oddity rule by pigeons in a four-choice touch-screen procedure.

    PubMed

    Aust, Ulrike; Steurer, Michael M

    2013-05-01

    Six pigeons were trained to peck at a target (odd stimulus) that was presented on a touch-screen together with three identical distractors (non-odd stimuli). The target could be either a square or a circle that was either blue or green, and the distractors in each trial were always of the opposite form and color to the target. Thus, the birds could solve the task by attending to color, form, or both. Transfer tests showed that performance was not disrupted by novel forms, stimulus sizes, distractor numbers, and display configurations, but broke down with novel stimulus types (textured stimuli, clip art images, and photographs). Transfer to novel colors was, for the most part, restricted to trials in which only one component-target or distractors, but not both-had a novel color. This suggested that the pigeons used a couple of if-then rules rather than an oddity concept to solve the task, and that color differences between target and distractors were the only cue upon which responding was based. A control experiment with the order of color and form tests being reversed excluded the possibility of the prevalence of color being an artifact of task order and reinforcement contingencies.

  9. Abstraction and natural language semantics.

    PubMed Central

    Kayser, Daniel

    2003-01-01

    According to the traditional view, a word prototypically denotes a class of objects sharing similar features, i.e. it results from an abstraction based on the detection of common properties in perceived entities. I explore here another idea: words result from abstraction of common premises in the rules governing our actions. I first argue that taking 'inference', instead of 'reference', as the basic issue in semantics does matter. I then discuss two phenomena that are, in my opinion, particularly difficult to analyse within the scope of traditional semantic theories: systematic polysemy and plurals. I conclude by a discussion of my approach, and by a summary of its main features. PMID:12903662

  10. Modelling of classification rules on metabolic patterns including machine learning and expert knowledge.

    PubMed

    Baumgartner, Christian; Böhm, Christian; Baumgartner, Daniela

    2005-04-01

    Machine learning has a great potential to mine potential markers from high-dimensional metabolic data without any a priori knowledge. Exemplarily, we investigated metabolic patterns of three severe metabolic disorders, PAHD, MCADD, and 3-MCCD, on which we constructed classification models for disease screening and diagnosis using a decision tree paradigm and logistic regression analysis (LRA). For the LRA model-building process we assessed the relevance of established diagnostic flags, which have been developed from the biochemical knowledge of newborn metabolism, and compared the models' error rates with those of the decision tree classifier. Both approaches yielded comparable classification accuracy in terms of sensitivity (>95.2%), while the LRA models built on flags showed significantly enhanced specificity. The number of false positive cases did not exceed 0.001%.

  11. ALT-C 96: Integrating Technology into the Curriculum. Conference Programme and Abstracts of the Association for Learning Technology Conference (3rd, Glasgow, Scotland, September 16-18, 1996).

    ERIC Educational Resources Information Center

    Cameron, Shona, Ed.

    This program for the 1996 Association for Learning Technology Conference summarizes the poster sessions, discussions, workshops, and software demonstrations, and provides abstracts of the 38 papers presented. Topics covered by the papers include: hand-held technology for mathematics; modeling global warming; computer-mediated communications; Java;…

  12. Sleep Promotes the Extraction of Grammatical Rules

    PubMed Central

    Nieuwenhuis, Ingrid L. C.; Folia, Vasiliki; Forkstam, Christian; Jensen, Ole; Petersson, Karl Magnus

    2013-01-01

    Grammar acquisition is a high level cognitive function that requires the extraction of complex rules. While it has been proposed that offline time might benefit this type of rule extraction, this remains to be tested. Here, we addressed this question using an artificial grammar learning paradigm. During a short-term memory cover task, eighty-one human participants were exposed to letter sequences generated according to an unknown artificial grammar. Following a time delay of 15 min, 12 h (wake or sleep) or 24 h, participants classified novel test sequences as Grammatical or Non-Grammatical. Previous behavioral and functional neuroimaging work has shown that classification can be guided by two distinct underlying processes: (1) the holistic abstraction of the underlying grammar rules and (2) the detection of sequence chunks that appear at varying frequencies during exposure. Here, we show that classification performance improved after sleep. Moreover, this improvement was due to an enhancement of rule abstraction, while the effect of chunk frequency was unaltered by sleep. These findings suggest that sleep plays a critical role in extracting complex structure from separate but related items during integrative memory processing. Our findings stress the importance of alternating periods of learning with sleep in settings in which complex information must be acquired. PMID:23755173

  13. The Art of Abstracting.

    ERIC Educational Resources Information Center

    Cremmins, Edward T.

    A three-stage analytical reading method for the composition of informative and indicative abstracts by authors and abstractors is presented in this monograph, along with background information on the abstracting process and a discussion of professional considerations in abstracting. An introduction to abstracts and abstracting precedes general…

  14. Learning from the Experience of Others: The Evolution of Faculty Tenure and Promotion Rules in Comprehensive Institutions

    ERIC Educational Resources Information Center

    Youn, Ted I. K.; Price, Tanya M.

    2009-01-01

    Organizational rules explain organizational stability and change. Using national surveys and fieldwork, we examine changes in tenure and promotion rules at comprehensive colleges and universities from 1969 to 2002. We find that increased rule founding and change arise from the increasingly rationalized environment, such as the academic…

  15. Innovation Abstracts, Volume XVII, 1995.

    ERIC Educational Resources Information Center

    Roueche, Suanne D., Ed.

    1995-01-01

    The abstracts in this volume describe innovative approaches to teaching and learning in the community college. Topics covered include: (1) the use of message mapping for speaking and writing instruction; (2) group projects and portfolios as evaluation tools; (3) helping students become strategic learners; (4) using writing assignments to ensure…

  16. Identifying users of traditional and Internet-based resources for meal ideas: An association rule learning approach.

    PubMed

    Doub, Allison E; Small, Meg L; Levin, Aron; LeVangie, Kristie; Brick, Timothy R

    2016-08-01

    Increasing home cooking while decreasing the consumption of food prepared away from home is a commonly recommended weight management strategy, however research on where individuals obtain ideas about meals to cook at home is limited. This study examined the characteristics of individuals who reported using traditional and Internet-based resources for meal ideas. 583 participants who were ≥50% responsible for household meal planning were recruited to approximate the 2014 United States Census distribution on sex, age, race/ethnicity, and household income. Participants reported demographic characteristics, home cooking frequency, and their use of 4 traditional resources for meal ideas (e.g., cookbooks), and 7 Internet-based resources for meal ideas (e.g., Pinterest) in an online survey. Independent samples t-tests compared home cooking frequency by resource use. Association rule learning identified those demographic characteristics that were significantly associated with resource use. Family and friends (71%), food community websites (45%), and cookbooks (41%) were the most common resources reported. Cookbook users reported preparing more meals at home per week (M = 9.65, SD = 5.28) compared to non-cookbook users (M = 8.11, SD = 4.93; t = -3.55, p < 0.001). Resource use was generally higher among parents and varied systematically with demographic characteristics. Findings suggest that home cooking interventions may benefit by modifying resources used by their target population.

  17. Motor Demands Constrain Cognitive Rule Structures

    PubMed Central

    Collins, Anne Gabrielle Eva; Frank, Michael Joshua

    2016-01-01

    Study of human executive function focuses on our ability to represent cognitive rules independently of stimulus or response modality. However, recent findings suggest that executive functions cannot be modularized separately from perceptual and motor systems, and that they instead scaffold on top of motor action selection. Here we investigate whether patterns of motor demands influence how participants choose to implement abstract rule structures. In a learning task that requires integrating two stimulus dimensions for determining appropriate responses, subjects typically structure the problem hierarchically, using one dimension to cue the task-set and the other to cue the response given the task-set. However, the choice of which dimension to use at each level can be arbitrary. We hypothesized that the specific structure subjects adopt would be constrained by the motor patterns afforded within each rule. Across four independent data-sets, we show that subjects create rule structures that afford motor clustering, preferring structures in which adjacent motor actions are valid within each task-set. In a fifth data-set using instructed rules, this bias was strong enough to counteract the well-known task switch-cost when instructions were incongruent with motor clustering. Computational simulations confirm that observed biases can be explained by leveraging overlap in cortical motor representations to improve outcome prediction and hence infer the structure to be learned. These results highlight the importance of sensorimotor constraints in abstract rule formation and shed light on why humans have strong biases to invent structure even when it does not exist. PMID:26966909

  18. Prefrontal Cortex Organization: Dissociating Effects of Temporal Abstraction, Relational Abstraction, and Integration with fMRI

    PubMed Central

    Nee, Derek Evan; Jahn, Andrew; Brown, Joshua W.

    2014-01-01

    The functions of the prefrontal cortex (PFC) underlie higher-level cognition. Varying proposals suggest that the PFC is organized along a rostral-caudal gradient of abstraction with more abstract representations/processes associated with more rostral areas. However, the operational definition of abstraction is unclear. Here, we contrasted 2 prominent theories of abstraction—temporal and relational—using fMRI. We further examined whether integrating abstract rules—a function common to each theory—recruited the PFC independently of other abstraction effects. While robust effects of relational abstraction were present in the PFC, temporal abstraction effects were absent. Instead, we found activations specific to the integration of relational rules in areas previously shown to be associated with temporal abstraction. We suggest that previous effects of temporal abstraction were due to confounds with integration demands. We propose an integration framework to understand the functions of the PFC that resolves discrepancies in prior data. PMID:23563962

  19. Evaluation of Machine Learning and Rules-Based Approaches for Predicting Antimicrobial Resistance Profiles in Gram-negative Bacilli from Whole Genome Sequence Data.

    PubMed

    Pesesky, Mitchell W; Hussain, Tahir; Wallace, Meghan; Patel, Sanket; Andleeb, Saadia; Burnham, Carey-Ann D; Dantas, Gautam

    2016-01-01

    The time-to-result for culture-based microorganism recovery and phenotypic antimicrobial susceptibility testing necessitates initial use of empiric (frequently broad-spectrum) antimicrobial therapy. If the empiric therapy is not optimal, this can lead to adverse patient outcomes and contribute to increasing antibiotic resistance in pathogens. New, more rapid technologies are emerging to meet this need. Many of these are based on identifying resistance genes, rather than directly assaying resistance phenotypes, and thus require interpretation to translate the genotype into treatment recommendations. These interpretations, like other parts of clinical diagnostic workflows, are likely to be increasingly automated in the future. We set out to evaluate the two major approaches that could be amenable to automation pipelines: rules-based methods and machine learning methods. The rules-based algorithm makes predictions based upon current, curated knowledge of Enterobacteriaceae resistance genes. The machine-learning algorithm predicts resistance and susceptibility based on a model built from a training set of variably resistant isolates. As our test set, we used whole genome sequence data from 78 clinical Enterobacteriaceae isolates, previously identified to represent a variety of phenotypes, from fully-susceptible to pan-resistant strains for the antibiotics tested. We tested three antibiotic resistance determinant databases for their utility in identifying the complete resistome for each isolate. The predictions of the rules-based and machine learning algorithms for these isolates were compared to results of phenotype-based diagnostics. The rules based and machine-learning predictions achieved agreement with standard-of-care phenotypic diagnostics of 89.0 and 90.3%, respectively, across twelve antibiotic agents from six major antibiotic classes. Several sources of disagreement between the algorithms were identified. Novel variants of known resistance factors and

  20. Evaluation of Machine Learning and Rules-Based Approaches for Predicting Antimicrobial Resistance Profiles in Gram-negative Bacilli from Whole Genome Sequence Data

    PubMed Central

    Pesesky, Mitchell W.; Hussain, Tahir; Wallace, Meghan; Patel, Sanket; Andleeb, Saadia; Burnham, Carey-Ann D.; Dantas, Gautam

    2016-01-01

    The time-to-result for culture-based microorganism recovery and phenotypic antimicrobial susceptibility testing necessitates initial use of empiric (frequently broad-spectrum) antimicrobial therapy. If the empiric therapy is not optimal, this can lead to adverse patient outcomes and contribute to increasing antibiotic resistance in pathogens. New, more rapid technologies are emerging to meet this need. Many of these are based on identifying resistance genes, rather than directly assaying resistance phenotypes, and thus require interpretation to translate the genotype into treatment recommendations. These interpretations, like other parts of clinical diagnostic workflows, are likely to be increasingly automated in the future. We set out to evaluate the two major approaches that could be amenable to automation pipelines: rules-based methods and machine learning methods. The rules-based algorithm makes predictions based upon current, curated knowledge of Enterobacteriaceae resistance genes. The machine-learning algorithm predicts resistance and susceptibility based on a model built from a training set of variably resistant isolates. As our test set, we used whole genome sequence data from 78 clinical Enterobacteriaceae isolates, previously identified to represent a variety of phenotypes, from fully-susceptible to pan-resistant strains for the antibiotics tested. We tested three antibiotic resistance determinant databases for their utility in identifying the complete resistome for each isolate. The predictions of the rules-based and machine learning algorithms for these isolates were compared to results of phenotype-based diagnostics. The rules based and machine-learning predictions achieved agreement with standard-of-care phenotypic diagnostics of 89.0 and 90.3%, respectively, across twelve antibiotic agents from six major antibiotic classes. Several sources of disagreement between the algorithms were identified. Novel variants of known resistance factors and

  1. Cognitive Control over Learning: Creating, Clustering, and Generalizing Task-Set Structure

    ERIC Educational Resources Information Center

    Collins, Anne G. E.; Frank, Michael J.

    2013-01-01

    Learning and executive functions such as task-switching share common neural substrates, notably prefrontal cortex and basal ganglia. Understanding how they interact requires studying how cognitive control facilitates learning but also how learning provides the (potentially hidden) structure, such as abstract rules or task-sets, needed for…

  2. Feature- versus rule-based generalization in rats, pigeons and humans.

    PubMed

    Maes, Elisa; De Filippo, Guido; Inkster, Angus B; Lea, Stephen E G; De Houwer, Jan; D'Hooge, Rudi; Beckers, Tom; Wills, Andy J

    2015-11-01

    Humans can spontaneously create rules that allow them to efficiently generalize what they have learned to novel situations. An enduring question is whether rule-based generalization is uniquely human or whether other animals can also abstract rules and apply them to novel situations. In recent years, there have been a number of high-profile claims that animals such as rats can learn rules. Most of those claims are quite weak because it is possible to demonstrate that simple associative systems (which do not learn rules) can account for the behavior in those tasks. Using a procedure that allows us to clearly distinguish feature-based from rule-based generalization (the Shanks-Darby procedure), we demonstrate that adult humans show rule-based generalization in this task, while generalization in rats and pigeons was based on featural overlap between stimuli. In brief, when learning that a stimulus made of two components ("AB") predicts a different outcome than its elements ("A" and "B"), people spontaneously abstract an opposites rule and apply it to new stimuli (e.g., knowing that "C" and "D" predict one outcome, they will predict that "CD" predicts the opposite outcome). Rats and pigeons show the reverse behavior-they generalize what they have learned, but on the basis of similarity (e.g., "CD" is similar to "C" and "D", so the same outcome is predicted for the compound stimulus as for the components). Genuinely rule-based behavior is observed in humans, but not in rats and pigeons, in the current procedure.

  3. Abstraction and Consolidation

    ERIC Educational Resources Information Center

    Monaghan, John; Ozmantar, Mehmet Fatih

    2004-01-01

    What is involved in consolidating a new mathematical abstraction? This paper examines the work of one student who was working on a task designed to consolidate two recently constructed absolute function abstractions. The study adopts an activity theoretic model of abstraction in context. Selected protocol data are presented. The initial state of…

  4. Abstraction and Consolidation

    ERIC Educational Resources Information Center

    Monaghan, John; Ozmantar, Mehmet Fatih

    2006-01-01

    The framework for this paper is a recently developed theory of abstraction in context. The paper reports on data collected from one student working on tasks concerned with absolute value functions. It examines the relationship between mathematical constructions and abstractions. It argues that an abstraction is a consolidated construction that can…

  5. Novel MRI-derived quantitative biomarker for cardiac function applied to classifying ischemic cardiomyopathy within a Bayesian rule learning framework

    NASA Astrophysics Data System (ADS)

    Menon, Prahlad G.; Morris, Lailonny; Staines, Mara; Lima, Joao; Lee, Daniel C.; Gopalakrishnan, Vanathi

    2014-03-01

    Characterization of regional left ventricular (LV) function may have application in prognosticating timely response and informing choice therapy in patients with ischemic cardiomyopathy. The purpose of this study is to characterize LV function through a systematic analysis of 4D (3D + time) endocardial motion over the cardiac cycle in an effort to define objective, clinically useful metrics of pathological remodeling and declining cardiac performance, using standard cardiac MRI data for two distinct patient cohorts accessed from CardiacAtlas.org: a) MESA - a cohort of asymptomatic patients; and b) DETERMINE - a cohort of symptomatic patients with a history of ischemic heart disease (IHD) or myocardial infarction. The LV endocardium was segmented and a signed phase-to-phase Hausdorff distance (HD) was computed at 3D uniformly spaced points tracked on segmented endocardial surface contours, over the cardiac cycle. An LV-averaged index of phase-to-phase endocardial displacement (P2PD) time-histories was computed at each tracked point, using the HD computed between consecutive cardiac phases. Average and standard deviation in P2PD over the cardiac cycle was used to prepare characteristic curves for the asymptomatic and IHD cohort. A novel biomarker of RMS error between mean patient-specific characteristic P2PD over the cardiac cycle for each individual patient and the cumulative P2PD characteristic of a cohort of asymptomatic patients was established as the RMS-P2PD marker. The novel RMS-P2PD marker was tested as a cardiac function based feature for automatic patient classification using a Bayesian Rule Learning (BRL) framework. The RMS-P2PD biomarker indices were significantly different for the symptomatic patient and asymptomatic control cohorts (p<0.001). BRL accurately classified 83.8% of patients correctly from the patient and control populations, with leave-one-out cross validation, using standard indices of LV ejection fraction (LV-EF) and LV end-systolic volume

  6. Collaboration rules.

    PubMed

    Evans, Philip; Wolf, Bob

    2005-01-01

    Corporate leaders seeking to boost growth, learning, and innovation may find the answer in a surprising place: the Linux open-source software community. Linux is developed by an essentially volunteer, self-organizing community of thousands of programmers. Most leaders would sell their grandmothers for workforces that collaborate as efficiently, frictionlessly, and creatively as the self-styled Linux hackers. But Linux is software, and software is hardly a model for mainstream business. The authors have, nonetheless, found surprising parallels between the anarchistic, caffeinated, hirsute world of Linux hackers and the disciplined, tea-sipping, clean-cut world of Toyota engineering. Specifically, Toyota and Linux operate by rules that blend the self-organizing advantages of markets with the low transaction costs of hierarchies. In place of markets' cash and contracts and hierarchies' authority are rules about how individuals and groups work together (with rigorous discipline); how they communicate (widely and with granularity); and how leaders guide them toward a common goal (through example). Those rules, augmented by simple communication technologies and a lack of legal barriers to sharing information, create rich common knowledge, the ability to organize teams modularly, extraordinary motivation, and high levels of trust, which radically lowers transaction costs. Low transaction costs, in turn, make it profitable for organizations to perform more and smaller transactions--and so increase the pace and flexibility typical of high-performance organizations. Once the system achieves critical mass, it feeds on itself. The larger the system, the more broadly shared the knowledge, language, and work style. The greater individuals' reputational capital, the louder the applause and the stronger the motivation. The success of Linux is evidence of the power of that virtuous circle. Toyota's success is evidence that it is also powerful in conventional companies.

  7. Changing the Rules: Making Space for Interactive Learning in the Galleries of the Detroit Institute of Arts

    ERIC Educational Resources Information Center

    Czajkowski, Jennifer Wild

    2011-01-01

    Three years after the Detroit Institute of Arts opened with all new, "visitor-centered" galleries, the museum's executive director of learning and interpretation shares the processes, successes, and lessons learned at an institution that embraced an array of hands-on learning models. The models are discussed as components of a…

  8. Bridging History of the Concept of Function with Learning of Mathematics: Students' Meta-Discursive Rules, Concept Formation and Historical Awareness

    NASA Astrophysics Data System (ADS)

    Kjeldsen, Tinne Hoff; Petersen, Pernille Hviid

    2013-08-01

    In this paper we present a matrix-organised implementation of an experimental course in the history of the concept of a function. The course was implemented in a Danish high school. One of the aims was to bridge history of mathematics with the teaching and learning of mathematics. The course was designed using the theoretical frameworks of a multiple perspective approach to history, Sfard's theory of thinking as communicating, and theories from mathematics education about concept image, concept definition and concept formation. It will be explained how history and extracts of original sources by Euler from 1748 and Dirichlet from 1837 were used to (1) reveal students' meta-discursive rules in mathematics and make them objects of students' reflections, (2) support students' learning of the concept of a function, and (3) develop students' historical awareness. The results show that it is possible to diagnose (some) of students' meta-discursive rules, that some of the students acted according to meta-discursive rules that coincide with Euler's from the 1700s, and that reading a part of a text by Dirichlet from 1837 created obstacles for the students that can be referenced to differences in meta-discursive rules. The experiment revealed that many of the students have a concept image that was in accordance with Euler's rather than with our modern concept definition and that they have process oriented thinking about functions. The students' historical awareness was developed through the course with respect to actors' influence on the formation of mathematical concepts and the notions of internal and external driving forces in the historical development of mathematics.

  9. Striatal degeneration impairs language learning: evidence from Huntington's disease.

    PubMed

    De Diego-Balaguer, R; Couette, M; Dolbeau, G; Dürr, A; Youssov, K; Bachoud-Lévi, A-C

    2008-11-01

    Although the role of the striatum in language processing is still largely unclear, a number of recent proposals have outlined its specific contribution. Different studies report evidence converging to a picture where the striatum may be involved in those aspects of rule-application requiring non-automatized behaviour. This is the main characteristic of the earliest phases of language acquisition that require the online detection of distant dependencies and the creation of syntactic categories by means of rule learning. Learning of sequences and categorization processes in non-language domains has been known to require striatal recruitment. Thus, we hypothesized that the striatum should play a prominent role in the extraction of rules in learning a language. We studied 13 pre-symptomatic gene-carriers and 22 early stage patients of Huntington's disease (pre-HD), both characterized by a progressive degeneration of the striatum and 21 late stage patients Huntington's disease (18 stage II, two stage III and one stage IV) where cortical degeneration accompanies striatal degeneration. When presented with a simplified artificial language where words and rules could be extracted, early stage Huntington's disease patients (stage I) were impaired in the learning test, demonstrating a greater impairment in rule than word learning compared to the 20 age- and education-matched controls. Huntington's disease patients at later stages were impaired both on word and rule learning. While spared in their overall performance, gene-carriers having learned a set of abstract artificial language rules were then impaired in the transfer of those rules to similar artificial language structures. The correlation analyses among several neuropsychological tests assessing executive function showed that rule learning correlated with tests requiring working memory and attentional control, while word learning correlated with a test involving episodic memory. These learning impairments significantly

  10. Students with Learning Disability in Math Are Left Behind in Multiplicative Reasoning? Number as Abstract Composite Unit Is a Likely "Culprit"

    ERIC Educational Resources Information Center

    Tzur, Ron; Xin, Yan Ping; Si, Luo; Kenney, Rachael; Guebert, Adam

    2010-01-01

    This study addressed the problem of why students with learning disabilities in mathematics too often fail to develop multiplicative and divisional concepts/operations. We conducted a constructivist teaching experiment with 12 students (nine 5th and three 4th graders). This report focuses on three students' conceptual progress, particularly on…

  11. Abstract and keywords.

    PubMed

    Peh, W C G; Ng, K H

    2008-09-01

    The abstract of a scientific paper represents a concise, accurate and factual mini-version of the paper contents. Abstract format may vary according to the individual journal. For original articles, a structured abstract usually consists of the following headings: aims (or objectives), materials and methods, results and conclusion. A few keywords that capture the main topics of the paper help indexing in the medical literature.

  12. Harmonious Triptychs: From Realism to Abstraction

    ERIC Educational Resources Information Center

    Horst, Carol

    2006-01-01

    The author of this article is continually trying to come up with interesting ways for beginning art students to put color theory into practice. This article describes a project that integrates new learning about color schemes with previously learned concepts such as observational contour drawing and abstraction and converting two-dimensional shape…

  13. Spatial abstraction for autonomous robot navigation.

    PubMed

    Epstein, Susan L; Aroor, Anoop; Evanusa, Matthew; Sklar, Elizabeth I; Parsons, Simon

    2015-09-01

    Optimal navigation for a simulated robot relies on a detailed map and explicit path planning, an approach problematic for real-world robots that are subject to noise and error. This paper reports on autonomous robots that rely on local spatial perception, learning, and commonsense rationales instead. Despite realistic actuator error, learned spatial abstractions form a model that supports effective travel.

  14. Technical Abstracts, 1988

    SciTech Connect

    Kotowski, M.

    1989-05-01

    This document is a compilation of the abstracts from unclassified documents published by Mechanical Engineering at Lawrence Livermore National Laboratory (LLNL) during the calendar year 1988. Many abstracts summarize work completed and published in report form. These are UCRL-90,000 and 100,000 series documents, which include the full text of articles to be published in journals and of papers to be presented at meetings, and UCID reports, which are informal documents. Not all UCIDs contain abstracts: short summaries were generated when abstracts were not included. Technical Abstracts also provides brief descriptions of those documents assigned to the MISC (miscellaneous) category. These are generally viewgraphs or photographs presented at meetings. The abstracts cover the broad range of technologies within Mechanical Engineering and are grouped by the principal author's division. An eighth category is devoted to abstracts presented at the CUBE symposium sponsored jointly by LLNL, Los Alamos National Laboratory, and Sandia Laboratories. Within these areas, abstracts are listed numerically. An author index and title index are provided at the back of the book for cross referencing. The publications listed may be obtained by contacting LLNL's TID library or the National Technical Information Service, US Department of Commerce, 5285 Port Royal Road, Springfield, VA 22161. Further information may be obtained by contacting the author directly or the persons listed in the introduction of each subject area.

  15. Paper Abstract Animals

    ERIC Educational Resources Information Center

    Sutley, Jane

    2010-01-01

    Abstraction is, in effect, a simplification and reduction of shapes with an absence of detail designed to comprise the essence of the more naturalistic images being depicted. Without even intending to, young children consistently create interesting, and sometimes beautiful, abstract compositions. A child's creations, moreover, will always seem to…

  16. Leadership Abstracts, Volume 10.

    ERIC Educational Resources Information Center

    Milliron, Mark D., Ed.

    1997-01-01

    The abstracts in this series provide brief discussions of issues related to leadership, administration, professional development, technology, and education in community colleges. Volume 10 for 1997 contains the following 12 abstracts: (1) "On Community College Renewal" (Nathan L. Hodges and Mark D. Milliron); (2) "The Community College Niche in a…

  17. Designing for Mathematical Abstraction

    ERIC Educational Resources Information Center

    Pratt, Dave; Noss, Richard

    2010-01-01

    Our focus is on the design of systems (pedagogical, technical, social) that encourage mathematical abstraction, a process we refer to as "designing for abstraction." In this paper, we draw on detailed design experiments from our research on children's understanding about chance and distribution to re-present this work as a case study in designing…

  18. Leadership Abstracts, 1996.

    ERIC Educational Resources Information Center

    Johnson, Larry, Ed.

    1996-01-01

    The abstracts in this series provide two-page discussions of issues related to leadership, administration, professional development, technology, and education in community colleges. Volume 9 for 1996 includes the following 12 abstracts: (1) "Tech-Prep + School-To-Work: Working Together To Foster Educational Reform," (Roderick F. Beaumont); (2)…

  19. Organizational Communication Abstracts--1975.

    ERIC Educational Resources Information Center

    Falcione, Raymond L.; And Others

    This document includes nearly 700 brief abstracts of works published in 1975 that are relevant to the field of organizational communication. The introduction presents a rationale for the project, a review of research methods developed by the authors for the preparation of abstracts, a statement of limitations as to the completeness of the coverage…

  20. Rules vs. analogy in English past tenses: a computational/experimental study.

    PubMed

    Albright, Adam; Hayes, Bruce

    2003-12-01

    Are morphological patterns learned in the form of rules? Some models deny this, attributing all morphology to analogical mechanisms. The dual mechanism model (Pinker, S., & Prince, A. (1998). On language and connectionism: analysis of a parallel distributed processing model of language acquisition. Cognition, 28, 73-193) posits that speakers do internalize rules, but that these rules are few and cover only regular processes; the remaining patterns are attributed to analogy. This article advocates a third approach, which uses multiple stochastic rules and no analogy. We propose a model that employs inductive learning to discover multiple rules, and assigns them confidence scores based on their performance in the lexicon. Our model is supported over the two alternatives by new "wug test" data on English past tenses, which show that participant ratings of novel pasts depend on the phonological shape of the stem, both for irregulars and, surprisingly, also for regulars. The latter observation cannot be explained under the dual mechanism approach, which derives all regulars with a single rule. To evaluate the alternative hypothesis that all morphology is analogical, we implemented a purely analogical model, which evaluates novel pasts based solely on their similarity to existing verbs. Tested against experimental data, this analogical model also failed in key respects: it could not locate patterns that require abstract structural characterizations, and it favored implausible responses based on single, highly similar exemplars. We conclude that speakers extend morphological patterns based on abstract structural properties, of a kind appropriately described with rules.

  1. The Influence of Ground Rules on Chinese Students' Learning of Critical Thinking in Group Work: A Cultural Perspective

    ERIC Educational Resources Information Center

    Fung, Dennis

    2014-01-01

    This article reports the results of a one-year longitudinal study examining a teaching intervention designed to enhance students' learning of critical thinking in Hong Kong. Seventy participating students (age 16-18) learned how to make reasoned arguments through a series of collaborative activities, including critical-thinking modelling tasks and…

  2. Playing by the Rules: Researching, Teaching and Learning Sexual Ethics with Young Men in the Australian National Rugby League

    ERIC Educational Resources Information Center

    Albury, Kath; Carmody, Moira; Evers, Clifton; Lumby, Catharine

    2011-01-01

    In 2004, the Australian National Rugby League (NRL) commissioned the Playing By The Rules research project in response to allegations of sexual assault by members of a professional rugby league team. This article offers an overview of the theoretical and methodological approaches adopted by the team, and the subsequent workplace education…

  3. Abstract Datatypes in PVS

    NASA Technical Reports Server (NTRS)

    Owre, Sam; Shankar, Natarajan

    1997-01-01

    PVS (Prototype Verification System) is a general-purpose environment for developing specifications and proofs. This document deals primarily with the abstract datatype mechanism in PVS which generates theories containing axioms and definitions for a class of recursive datatypes. The concepts underlying the abstract datatype mechanism are illustrated using ordered binary trees as an example. Binary trees are described by a PVS abstract datatype that is parametric in its value type. The type of ordered binary trees is then presented as a subtype of binary trees where the ordering relation is also taken as a parameter. We define the operations of inserting an element into, and searching for an element in an ordered binary tree; the bulk of the report is devoted to PVS proofs of some useful properties of these operations. These proofs illustrate various approaches to proving properties of abstract datatype operations. They also describe the built-in capabilities of the PVS proof checker for simplifying abstract datatype expressions.

  4. Object Classification via Planar Abstraction

    NASA Astrophysics Data System (ADS)

    Oesau, Sven; Lafarge, Florent; Alliez, Pierre

    2016-06-01

    We present a supervised machine learning approach for classification of objects from sampled point data. The main idea consists in first abstracting the input object into planar parts at several scales, then discriminate between the different classes of objects solely through features derived from these planar shapes. Abstracting into planar shapes provides a means to both reduce the computational complexity and improve robustness to defects inherent to the acquisition process. Measuring statistical properties and relationships between planar shapes offers invariance to scale and orientation. A random forest is then used for solving the multiclass classification problem. We demonstrate the potential of our approach on a set of indoor objects from the Princeton shape benchmark and on objects acquired from indoor scenes and compare the performance of our method with other point-based shape descriptors.

  5. ChemStable: a web server for rule-embedded naïve Bayesian learning approach to predict compound stability.

    PubMed

    Liu, Zhihong; Zheng, Minghao; Yan, Xin; Gu, Qiong; Gasteiger, Johann; Tijhuis, Johan; Maas, Peter; Li, Jiabo; Xu, Jun

    2014-09-01

    Predicting compound chemical stability is important because unstable compounds can lead to either false positive or to false negative conclusions in bioassays. Experimental data (COMDECOM) measured from DMSO/H2O solutions stored at 50 °C for 105 days were used to predicted stability by applying rule-embedded naïve Bayesian learning, based upon atom center fragment (ACF) features. To build the naïve Bayesian classifier, we derived ACF features from 9,746 compounds in the COMDECOM dataset. By recursively applying naïve Bayesian learning from the data set, each ACF is assigned with an expected stable probability (p(s)) and an unstable probability (p(uns)). 13,340 ACFs, together with their p(s) and p(uns) data, were stored in a knowledge base for use by the Bayesian classifier. For a given compound, its ACFs were derived from its structure connection table with the same protocol used to drive ACFs from the training data. Then, the Bayesian classifier assigned p(s) and p(uns) values to the compound ACFs by a structural pattern recognition algorithm, which was implemented in-house. Compound instability is calculated, with Bayes' theorem, based upon the p(s) and p(uns) values of the compound ACFs. We were able to achieve performance with an AUC value of 84% and a tenfold cross validation accuracy of 76.5%. To reduce false negatives, a rule-based approach has been embedded in the classifier. The rule-based module allows the program to improve its predictivity by expanding its compound instability knowledge base, thus further reducing the possibility of false negatives. To our knowledge, this is the first in silico prediction service for the prediction of the stabilities of organic compounds.

  6. ChemStable: a web server for rule-embedded naïve Bayesian learning approach to predict compound stability

    NASA Astrophysics Data System (ADS)

    Liu, Zhihong; Zheng, Minghao; Yan, Xin; Gu, Qiong; Gasteiger, Johann; Tijhuis, Johan; Maas, Peter; Li, Jiabo; Xu, Jun

    2014-09-01

    Predicting compound chemical stability is important because unstable compounds can lead to either false positive or to false negative conclusions in bioassays. Experimental data (COMDECOM) measured from DMSO/H2O solutions stored at 50 °C for 105 days were used to predicted stability by applying rule-embedded naïve Bayesian learning, based upon atom center fragment (ACF) features. To build the naïve Bayesian classifier, we derived ACF features from 9,746 compounds in the COMDECOM dataset. By recursively applying naïve Bayesian learning from the data set, each ACF is assigned with an expected stable probability ( p s ) and an unstable probability ( p uns ). 13,340 ACFs, together with their p s and p uns data, were stored in a knowledge base for use by the Bayesian classifier. For a given compound, its ACFs were derived from its structure connection table with the same protocol used to drive ACFs from the training data. Then, the Bayesian classifier assigned p s and p uns values to the compound ACFs by a structural pattern recognition algorithm, which was implemented in-house. Compound instability is calculated, with Bayes' theorem, based upon the p s and p uns values of the compound ACFs. We were able to achieve performance with an AUC value of 84 % and a tenfold cross validation accuracy of 76.5 %. To reduce false negatives, a rule-based approach has been embedded in the classifier. The rule-based module allows the program to improve its predictivity by expanding its compound instability knowledge base, thus further reducing the possibility of false negatives. To our knowledge, this is the first in silico prediction service for the prediction of the stabilities of organic compounds.

  7. Experience with abstract notation one

    NASA Technical Reports Server (NTRS)

    Harvey, James D.; Weaver, Alfred C.

    1990-01-01

    The development of computer science has produced a vast number of machine architectures, programming languages, and compiler technologies. The cross product of these three characteristics defines the spectrum of previous and present data representation methodologies. With regard to computer networks, the uniqueness of these methodologies presents an obstacle when disparate host environments are to be interconnected. Interoperability within a heterogeneous network relies upon the establishment of data representation commonality. The International Standards Organization (ISO) is currently developing the abstract syntax notation one standard (ASN.1) and the basic encoding rules standard (BER) that collectively address this problem. When used within the presentation layer of the open systems interconnection reference model, these two standards provide the data representation commonality required to facilitate interoperability. The details of a compiler that was built to automate the use of ASN.1 and BER are described. From this experience, insights into both standards are given and potential problems relating to this development effort are discussed.

  8. Automatic Abstraction in Planning

    NASA Technical Reports Server (NTRS)

    Christensen, J.

    1991-01-01

    Traditionally, abstraction in planning has been accomplished by either state abstraction or operator abstraction, neither of which has been fully automatic. We present a new method, predicate relaxation, for automatically performing state abstraction. PABLO, a nonlinear hierarchical planner, implements predicate relaxation. Theoretical, as well as empirical results are presented which demonstrate the potential advantages of using predicate relaxation in planning. We also present a new definition of hierarchical operators that allows us to guarantee a limited form of completeness. This new definition is shown to be, in some ways, more flexible than previous definitions of hierarchical operators. Finally, a Classical Truth Criterion is presented that is proven to be sound and complete for a planning formalism that is general enough to include most classical planning formalisms that are based on the STRIPS assumption.

  9. Searching Sociological Abstracts.

    ERIC Educational Resources Information Center

    Kerbel, Sandra Sandor

    1981-01-01

    Describes the scope, content, and retrieval characteristics of Sociological Abstracts, an online database of literature in the social sciences. Sample searches are displayed, and the strengths and weaknesses of the database are summarized. (FM)

  10. Conference Abstracts: AEDS '82.

    ERIC Educational Resources Information Center

    Journal of Computers in Mathematics and Science Teaching, 1982

    1982-01-01

    Abstracts from nine selected papers presented at the 1982 Association for Educational Data Systems (AEDS) conference are provided. Copies of conference proceedings may be obtained for fifteen dollars from the Association. (MP)

  11. Abstracts of SIG Sessions.

    ERIC Educational Resources Information Center

    Proceedings of the ASIS Annual Meeting, 1997

    1997-01-01

    Presents abstracts of SIG Sessions. Highlights include digital collections; information retrieval methods; public interest/fair use; classification and indexing; electronic publication; funding; globalization; information technology projects; interface design; networking in developing countries; metadata; multilingual databases; networked…

  12. Abstracts of contributed papers

    SciTech Connect

    Not Available

    1994-08-01

    This volume contains 571 abstracts of contributed papers to be presented during the Twelfth US National Congress of Applied Mechanics. Abstracts are arranged in the order in which they fall in the program -- the main sessions are listed chronologically in the Table of Contents. The Author Index is in alphabetical order and lists each paper number (matching the schedule in the Final Program) with its corresponding page number in the book.

  13. Paraphrasing for condensation in journal abstracting.

    PubMed

    Kittredge, Richard

    2002-08-01

    When authors of empirical science articles write abstracts, they employ a wide variety of distinct linguistic operations which interact to condense and rephrase a subset of sentences from the source text. An on-going comparison of biological and biomedical journal articles with their author-written abstracts is providing a basis for a more linguistically detailed model of abstract derivation using syntactic representations of selected source sentences. The description makes use of rich dictionary information to formulate paraphrasing rules of differing degrees of generality, including some which are sublanguage-specific, and others which appear valid in several languages when formulated using "lexical functions" to express important semantic relationships between lexical items. Some paraphrase operations may use both lexical functions and rhetorical relations between sentences to reformulate larger chunks of text in a concise abstract sentence. The descriptive framework is computable and utilizes existing linguistic resources.

  14. Metacognition and abstract reasoning.

    PubMed

    Markovits, Henry; Thompson, Valerie A; Brisson, Janie

    2015-05-01

    The nature of people's meta-representations of deductive reasoning is critical to understanding how people control their own reasoning processes. We conducted two studies to examine whether people have a metacognitive representation of abstract validity and whether familiarity alone acts as a separate metacognitive cue. In Study 1, participants were asked to make a series of (1) abstract conditional inferences, (2) concrete conditional inferences with premises having many potential alternative antecedents and thus specifically conducive to the production of responses consistent with conditional logic, or (3) concrete problems with premises having relatively few potential alternative antecedents. Participants gave confidence ratings after each inference. Results show that confidence ratings were positively correlated with logical performance on abstract problems and concrete problems with many potential alternatives, but not with concrete problems with content less conducive to normative responses. Confidence ratings were higher with few alternatives than for abstract content. Study 2 used a generation of contrary-to-fact alternatives task to improve levels of abstract logical performance. The resulting increase in logical performance was mirrored by increases in mean confidence ratings. Results provide evidence for a metacognitive representation based on logical validity, and show that familiarity acts as a separate metacognitive cue.

  15. The Rules of Evidence: Focus on Key Points to Develop the Best Strategy to Evaluate Professional Learning

    ERIC Educational Resources Information Center

    Guskey, Thomas R.

    2012-01-01

    Gathering evidence on the outcomes of any professional learning experience can be a challenging and complicated task. It involves consideration of a wide variety of perceptual and contextual issues, some obvious to education leaders and others not. Those who want to succeed in this process may find the following points helpful: (1) Always begin…

  16. The Efficacy of Explicit Grammar Instruction and Its Impact on L2 Rule-Learning: A Literature Review

    ERIC Educational Resources Information Center

    Gabriel, Raafat

    2009-01-01

    It is crucial that foreign language teachers know well what kinds of grammar teaching strategies best aid learning in the classroom in order to adjust their teaching toward a practical and successful approach. Much of the debate about how to help EFL learners achieve grammatical proficiency centers on the implicit versus explicit, or deductive…

  17. Rules of Engagement: The Joint Influence of Trainer Expressiveness and Trainee Experiential Learning Style on Engagement and Training Transfer

    ERIC Educational Resources Information Center

    Rangel, Bertha; Chung, Wonjoon; Harris, T. Brad; Carpenter, Nichelle C.; Chiaburu, Dan S.; Moore, Jenna L.

    2015-01-01

    We investigated the joint effect of trainer expressiveness and trainee experiential learning style on training transfer intentions. Extending prior research where trainer expressiveness has been established as a positive predictor of transfer, we show that trainer expressiveness is more impactful for trainees with high (vs. low) experiential…

  18. Functional Network Construction in Arabidopsis Using Rule-Based Machine Learning on Large-Scale Data Sets[C][W][OA

    PubMed Central

    Bassel, George W.; Glaab, Enrico; Marquez, Julietta; Holdsworth, Michael J.; Bacardit, Jaume

    2011-01-01

    The meta-analysis of large-scale postgenomics data sets within public databases promises to provide important novel biological knowledge. Statistical approaches including correlation analyses in coexpression studies of gene expression have emerged as tools to elucidate gene function using these data sets. Here, we present a powerful and novel alternative methodology to computationally identify functional relationships between genes from microarray data sets using rule-based machine learning. This approach, termed “coprediction,” is based on the collective ability of groups of genes co-occurring within rules to accurately predict the developmental outcome of a biological system. We demonstrate the utility of coprediction as a powerful analytical tool using publicly available microarray data generated exclusively from Arabidopsis thaliana seeds to compute a functional gene interaction network, termed Seed Co-Prediction Network (SCoPNet). SCoPNet predicts functional associations between genes acting in the same developmental and signal transduction pathways irrespective of the similarity in their respective gene expression patterns. Using SCoPNet, we identified four novel regulators of seed germination (ALTERED SEED GERMINATION5, 6, 7, and 8), and predicted interactions at the level of transcript abundance between these novel and previously described factors influencing Arabidopsis seed germination. An online Web tool to query SCoPNet has been developed as a community resource to dissect seed biology and is available at http://www.vseed.nottingham.ac.uk/. PMID:21896882

  19. Rule-Based Statistical Calculations on a Database Abstract.

    DTIC Science & Technology

    1983-06-01

    of chapter 6 has been submitted to the Second LBL Workshop on Statistical Database Management, 1913. Thanks to all referees for suggestions regarding...Boral, and David J. DeWitt,. A Framework fbr Research in Database Management for Statistical Analysis. In Pwceed;ngsx pages 69-78. ACM SIGMOD...E. Denning. A Security Model for the Statistical Database Problem. In Proceeding& Second LBL Workshop on Statistical Database Management, September

  20. Leadership Abstracts, 2001.

    ERIC Educational Resources Information Center

    Wilson, Cynthia, Ed.

    2001-01-01

    This is volume 14 of Leadership Abstracts, a newsletter published by the League for Innovation (California). Issue 1 of February 2001, "Developmental Education: A Policy Primer," discusses developmental programs in the community college. According to the article, community college trustees and presidents would serve their constituents well by…

  1. Abstract Film and Beyond.

    ERIC Educational Resources Information Center

    Le Grice, Malcolm

    A theoretical and historical account of the main preoccupations of makers of abstract films is presented in this book. The book's scope includes discussion of nonrepresentational forms as well as examination of experiments in the manipulation of time in films. The ten chapters discuss the following topics: art and cinematography, the first…

  2. Leadership Abstracts, 1993.

    ERIC Educational Resources Information Center

    Doucette, Don, Ed.

    1993-01-01

    This document includes 10 issues of Leadership Abstracts (volume 6, 1993), a newsletter published by the League for Innovation in the Community College (California). The featured articles are: (1) "Reinventing Government" by David T. Osborne; (2) "Community College Workforce Training Programs: Expanding the Mission to Meet Critical Needs" by…

  3. Leadership Abstracts, 1999.

    ERIC Educational Resources Information Center

    Leadership Abstracts, 1999

    1999-01-01

    This document contains five Leadership Abstracts publications published February-December 1999. The article, "Teaching the Teachers: Meeting the National Teacher Preparation Challenge," authored by George R. Boggs and Sadie Bragg, examines the community college role and makes recommendations and a call to action for teacher education.…

  4. Computers in Abstract Algebra

    ERIC Educational Resources Information Center

    Nwabueze, Kenneth K.

    2004-01-01

    The current emphasis on flexible modes of mathematics delivery involving new information and communication technology (ICT) at the university level is perhaps a reaction to the recent change in the objectives of education. Abstract algebra seems to be one area of mathematics virtually crying out for computer instructional support because of the…

  5. Reasoning abstractly about resources

    NASA Technical Reports Server (NTRS)

    Clement, B.; Barrett, A.

    2001-01-01

    r describes a way to schedule high level activities before distributing them across multiple rovers in order to coordinate the resultant use of shared resources regardless of how each rover decides how to perform its activities. We present an algorithm for summarizing the metric resource requirements of an abstract activity based n the resource usages of its potential refinements.

  6. Conference Abstracts: AEDS '84.

    ERIC Educational Resources Information Center

    Baird, William E.

    1985-01-01

    The Association of Educational Data Systems (AEDS) conference included 102 presentations. Abstracts of seven of these presentations are provided. Topic areas considered include LOGO, teaching probability through a computer game, writing effective computer assisted instructional materials, computer literacy, research on instructional…

  7. Leadership Abstracts, 2002.

    ERIC Educational Resources Information Center

    Wilson, Cynthia, Ed.; Milliron, Mark David, Ed.

    2002-01-01

    This 2002 volume of Leadership Abstracts contains issue numbers 1-12. Articles include: (1) "Skills Certification and Workforce Development: Partnering with Industry and Ourselves," by Jeffrey A. Cantor; (2) "Starting Again: The Brookhaven Success College," by Alice W. Villadsen; (3) "From Digital Divide to Digital Democracy," by Gerardo E. de los…

  8. Abstraction and art.

    PubMed Central

    Gortais, Bernard

    2003-01-01

    In a given social context, artistic creation comprises a set of processes, which relate to the activity of the artist and the activity of the spectator. Through these processes we see and understand that the world is vaster than it is said to be. Artistic processes are mediated experiences that open up the world. A successful work of art expresses a reality beyond actual reality: it suggests an unknown world using the means and the signs of the known world. Artistic practices incorporate the means of creation developed by science and technology and change forms as they change. Artists and the public follow different processes of abstraction at different levels, in the definition of the means of creation, of representation and of perception of a work of art. This paper examines how the processes of abstraction are used within the framework of the visual arts and abstract painting, which appeared during a period of growing importance for the processes of abstraction in science and technology, at the beginning of the twentieth century. The development of digital platforms and new man-machine interfaces allow multimedia creations. This is performed under the constraint of phases of multidisciplinary conceptualization using generic representation languages, which tend to abolish traditional frontiers between the arts: visual arts, drama, dance and music. PMID:12903659

  9. Annual Conference Abstracts

    ERIC Educational Resources Information Center

    Journal of Engineering Education, 1972

    1972-01-01

    Includes abstracts of papers presented at the 80th Annual Conference of the American Society for Engineering Education. The broad areas include aerospace, affiliate and associate member council, agricultural engineering, biomedical engineering, continuing engineering studies, chemical engineering, civil engineering, computers, cooperative…

  10. Abstracts of SIG Sessions.

    ERIC Educational Resources Information Center

    Proceedings of the ASIS Annual Meeting, 1994

    1994-01-01

    Includes abstracts of 18 special interest group (SIG) sessions. Highlights include natural language processing, information science and terminology science, classification, knowledge-intensive information systems, information value and ownership issues, economics and theories of information science, information retrieval interfaces, fuzzy thinking…

  11. RESEARCH ABSTRACTS, VOLUME VI.

    ERIC Educational Resources Information Center

    COLETTE, SISTER M.

    THIS SIXTH VOLUME OF RESEARCH ABSTRACTS PRESENTS REPORTS OF 35 RESEARCH STUDIES COMPLETED BY CANDIDATES FOR THE MASTER'S DEGREE AT THE CARDINAL STRITCH COLLEGE IN 1964. TWENTY-NINE STUDIES ARE CONCERNED WITH READING, AND SIX ARE CONCERNED WITH THE EDUCATION OF THE MENTALLY HANDICAPPED. OF THE READING STUDIES, FIVE PERTAIN TO THE JUNIOR HIGH LEVEL…

  12. Annual Conference Abstracts

    ERIC Educational Resources Information Center

    Engineering Education, 1976

    1976-01-01

    Presents the abstracts of 158 papers presented at the American Society for Engineering Education's annual conference at Knoxville, Tennessee, June 14-17, 1976. Included are engineering topics covering education, aerospace, agriculture, biomedicine, chemistry, computers, electricity, acoustics, environment, mechanics, and women. (SL)

  13. Making the Abstract Concrete

    ERIC Educational Resources Information Center

    Potter, Lee Ann

    2005-01-01

    President Ronald Reagan nominated a woman to serve on the United States Supreme Court. He did so through a single-page form letter, completed in part by hand and in part by typewriter, announcing Sandra Day O'Connor as his nominee. While the document serves as evidence of a historic event, it is also a tangible illustration of abstract concepts…

  14. Abstracts of SIG Sessions.

    ERIC Educational Resources Information Center

    Proceedings of the ASIS Annual Meeting, 1995

    1995-01-01

    Presents abstracts of 15 special interest group (SIG) sessions. Topics include navigation and information utilization in the Internet, natural language processing, automatic indexing, image indexing, classification, users' models of database searching, online public access catalogs, education for information professions, information services,…

  15. Seismic Consequence Abstraction

    SciTech Connect

    M. Gross

    2004-10-25

    The primary purpose of this model report is to develop abstractions for the response of engineered barrier system (EBS) components to seismic hazards at a geologic repository at Yucca Mountain, Nevada, and to define the methodology for using these abstractions in a seismic scenario class for the Total System Performance Assessment - License Application (TSPA-LA). A secondary purpose of this model report is to provide information for criticality studies related to seismic hazards. The seismic hazards addressed herein are vibratory ground motion, fault displacement, and rockfall due to ground motion. The EBS components are the drip shield, the waste package, and the fuel cladding. The requirements for development of the abstractions and the associated algorithms for the seismic scenario class are defined in ''Technical Work Plan For: Regulatory Integration Modeling of Drift Degradation, Waste Package and Drip Shield Vibratory Motion and Seismic Consequences'' (BSC 2004 [DIRS 171520]). The development of these abstractions will provide a more complete representation of flow into and transport from the EBS under disruptive events. The results from this development will also address portions of integrated subissue ENG2, Mechanical Disruption of Engineered Barriers, including the acceptance criteria for this subissue defined in Section 2.2.1.3.2.3 of the ''Yucca Mountain Review Plan, Final Report'' (NRC 2003 [DIRS 163274]).

  16. Abstraction through Game Play

    ERIC Educational Resources Information Center

    Avraamidou, Antri; Monaghan, John; Walker, Aisha

    2012-01-01

    This paper examines the computer game play of an 11-year-old boy. In the course of building a virtual house he developed and used, without assistance, an artefact and an accompanying strategy to ensure that his house was symmetric. We argue that the creation and use of this artefact-strategy is a mathematical abstraction. The discussion…

  17. EBS Radionuclide Transport Abstraction

    SciTech Connect

    R. Schreiner

    2001-06-27

    The purpose of this work is to develop the Engineered Barrier System (EBS) radionuclide transport abstraction model, as directed by a written development plan (CRWMS M&O 1999a). This abstraction is the conceptual model that will be used to determine the rate of release of radionuclides from the EBS to the unsaturated zone (UZ) in the total system performance assessment-license application (TSPA-LA). In particular, this model will be used to quantify the time-dependent radionuclide releases from a failed waste package (WP) and their subsequent transport through the EBS to the emplacement drift wall/UZ interface. The development of this conceptual model will allow Performance Assessment Operations (PAO) and its Engineered Barrier Performance Department to provide a more detailed and complete EBS flow and transport abstraction. The results from this conceptual model will allow PA0 to address portions of the key technical issues (KTIs) presented in three NRC Issue Resolution Status Reports (IRSRs): (1) the Evolution of the Near-Field Environment (ENFE), Revision 2 (NRC 1999a), (2) the Container Life and Source Term (CLST), Revision 2 (NRC 1999b), and (3) the Thermal Effects on Flow (TEF), Revision 1 (NRC 1998). The conceptual model for flow and transport in the EBS will be referred to as the ''EBS RT Abstraction'' in this analysis/modeling report (AMR). The scope of this abstraction and report is limited to flow and transport processes. More specifically, this AMR does not discuss elements of the TSPA-SR and TSPA-LA that relate to the EBS but are discussed in other AMRs. These elements include corrosion processes, radionuclide solubility limits, waste form dissolution rates and concentrations of colloidal particles that are generally represented as boundary conditions or input parameters for the EBS RT Abstraction. In effect, this AMR provides the algorithms for transporting radionuclides using the flow geometry and radionuclide concentrations determined by other

  18. Association Rules

    NASA Astrophysics Data System (ADS)

    Höppner, Frank

    Association rules are rules of the kind "70% of the customers who buy vine and cheese also buy grapes". While the traditional field of application is market basket analysis, association rule mining has been applied to various fields since then, which has led to a number of important modifications and extensions. We discuss the most frequently applied approach that is central to many extensions, the Apriori algorithm, and briefly review some applications to other data types, well-known problems of rule evaluation via support and confidence, and extensions of or alternatives to the standard framework.

  19. Artificial Intelligence Technical Paper Abstracts 1991

    DTIC Science & Technology

    1992-07-08

    Strategy Acquisition with Genetic Algorithms , John J. Grefenstene 28 [ ] AIC-91-014 Lamarckian Learning in Multi-agent Environments, John J...LEARNING Title: Is the Genetic Algorithm a Cooperative Leamner? Author(s): Helen G. Cobb E-mail Address: cobb@aic.nrl.navy.mil Citation: submitted to...the Second Workshop on Foundations of Genetic Algorithms (FOGA-92) Date: Forthcoming, 1992 AIC Report No.: AIC-91-001 Abstract This paper begins to

  20. Innovation Abstracts: Volume XI, Numbers 1-30.

    ERIC Educational Resources Information Center

    Roueche, Suanne D., Ed.

    1989-01-01

    This series of one- to two-page abstracts highlights a variety of innovative approaches to teaching and learning in the community college. Topics covered in the abstracts include: (1) cooperative planning for institutional excellence; (2) rewarding scholarship among community college faculty; (3) in-class debates as a learning strategy; (4)…

  1. The Acquisition of Abstract Words by Young Infants

    ERIC Educational Resources Information Center

    Bergelson, Elika; Swingley, Daniel

    2013-01-01

    Young infants' learning of words for abstract concepts like "all gone" and "eat," in contrast to their learning of more concrete words like "apple" and "shoe," may follow a relatively protracted developmental course. We examined whether infants know such abstract words. Parents named one of two events shown in side-by-side videos while their…

  2. Innovation Abstracts, Volume XIII, Numbers 1-30, 1991.

    ERIC Educational Resources Information Center

    Roueche, Suanne D., Ed.

    1991-01-01

    This series of one- to two-page abstracts highlights a variety of innovative approaches to teaching and learning in the community college. Topics covered in the abstracts include: (1) internationalizing the curriculum through focused interaction; (2) improving the small group approach to learning; (3) writing across the curriculum with early essay…

  3. Innovation Abstracts: Volume XII, Numbers 1-30, 1990.

    ERIC Educational Resources Information Center

    Roueche, Susanne D., Ed.

    1990-01-01

    This series of one- to two-page abstracts highlights a variety of innovative approaches to teaching and learning in the community college. Topics covered in the abstracts include: (1) academic partnerships pairing "high-risk" students with a concerned faculty member, counselor, or administrator; (2) teacher-to-teacher learning partnerships; (3)…

  4. 37 CFR 1.72 - Title and abstract.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2010-07-01 2010-07-01 false Title and abstract. 1.72 Section 1.72 Patents, Trademarks, and Copyrights UNITED STATES PATENT AND TRADEMARK OFFICE, DEPARTMENT OF COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES National Processing Provisions Specification § 1.72 Title and abstract. (a) The title of...

  5. 37 CFR 1.72 - Title and abstract.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2014-07-01 2014-07-01 false Title and abstract. 1.72 Section 1.72 Patents, Trademarks, and Copyrights UNITED STATES PATENT AND TRADEMARK OFFICE, DEPARTMENT OF COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES National Processing Provisions Specification § 1.72 Title and abstract. (a) The title of...

  6. 37 CFR 1.72 - Title and abstract.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2011-07-01 2011-07-01 false Title and abstract. 1.72 Section 1.72 Patents, Trademarks, and Copyrights UNITED STATES PATENT AND TRADEMARK OFFICE, DEPARTMENT OF COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES National Processing Provisions Specification § 1.72 Title and abstract. (a) The title of...

  7. 37 CFR 1.72 - Title and abstract.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2012-07-01 2012-07-01 false Title and abstract. 1.72 Section 1.72 Patents, Trademarks, and Copyrights UNITED STATES PATENT AND TRADEMARK OFFICE, DEPARTMENT OF COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES National Processing Provisions Specification § 1.72 Title and abstract. (a) The title of...

  8. Generalized Abstract Symbolic Summaries

    NASA Technical Reports Server (NTRS)

    Person, Suzette; Dwyer, Matthew B.

    2009-01-01

    Current techniques for validating and verifying program changes often consider the entire program, even for small changes, leading to enormous V&V costs over a program s lifetime. This is due, in large part, to the use of syntactic program techniques which are necessarily imprecise. Building on recent advances in symbolic execution of heap manipulating programs, in this paper, we develop techniques for performing abstract semantic differencing of program behaviors that offer the potential for improved precision.

  9. Abstraction Augmented Markov Models.

    PubMed

    Caragea, Cornelia; Silvescu, Adrian; Caragea, Doina; Honavar, Vasant

    2010-12-13

    High accuracy sequence classification often requires the use of higher order Markov models (MMs). However, the number of MM parameters increases exponentially with the range of direct dependencies between sequence elements, thereby increasing the risk of overfitting when the data set is limited in size. We present abstraction augmented Markov models (AAMMs) that effectively reduce the number of numeric parameters of k(th) order MMs by successively grouping strings of length k (i.e., k-grams) into abstraction hierarchies. We evaluate AAMMs on three protein subcellular localization prediction tasks. The results of our experiments show that abstraction makes it possible to construct predictive models that use significantly smaller number of features (by one to three orders of magnitude) as compared to MMs. AAMMs are competitive with and, in some cases, significantly outperform MMs. Moreover, the results show that AAMMs often perform significantly better than variable order Markov models, such as decomposed context tree weighting, prediction by partial match, and probabilistic suffix trees.

  10. Using Group Explorer in Teaching Abstract Algebra

    ERIC Educational Resources Information Center

    Schubert, Claus; Gfeller, Mary; Donohue, Christopher

    2013-01-01

    This study explores the use of Group Explorer in an undergraduate mathematics course in abstract algebra. The visual nature of Group Explorer in representing concepts in group theory is an attractive incentive to use this software in the classroom. However, little is known about students' perceptions on this technology in learning concepts in…

  11. Development of Abstract Grammatical Categorization in Infants

    ERIC Educational Resources Information Center

    Cyr, Marilyn; Shi, Rushen

    2013-01-01

    This study examined abstract syntactic categorization in infants, using the case of grammatical gender. Ninety-six French-learning 14-, 17-, 20-, and 30-month-olds completed the study. In a preferential looking procedure infants were tested on their generalized knowledge of grammatical gender involving pseudonouns and gender-marking determiners.…

  12. Cool Cats: Feline Fun with Abstract Art.

    ERIC Educational Resources Information Center

    Lambert, Phyllis Gilchrist

    2002-01-01

    Presents a lesson that teaches students about abstract art in a fun way. Explains that students draw cats, learn about the work of Pablo Picasso, and, in the style of Picasso, combine the parts of the cats (tail, legs, head, body) together in unconventional ways. (CMK)

  13. RCDPM 1992 Conference Book of Abstracts.

    ERIC Educational Resources Information Center

    1992

    This booklet contains 51 abstracts of papers presented at the 1992 conference for the Research Council for Diagnostic and Prescriptive Mathematics (RCDPM). Topics covered include: the use of expressive writing to enhance metacognition, adult assessment, cooperative learning assessment, visualization in problem solving, deaf students' beliefs about…

  14. Abstracts of Research Papers 1977 AAHPER Convention.

    ERIC Educational Resources Information Center

    Sage, George H., Ed.

    This volume of abstracts describes papers written on the following topics: (1) Strength Physiology; (2) Learning Disabilities (motor); (3) Physiology - General; (4) Work Capacity; (5) Measurement and Recreation; (6) Biomechanics; (7) Professional Preparation (physical education); (8) Muscle Performance; (9) Sociology of Sport; (10) History of…

  15. EBS Radionuclide Transport Abstraction

    SciTech Connect

    J. Prouty

    2006-07-14

    The purpose of this report is to develop and analyze the engineered barrier system (EBS) radionuclide transport abstraction model, consistent with Level I and Level II model validation, as identified in Technical Work Plan for: Near-Field Environment and Transport: Engineered Barrier System: Radionuclide Transport Abstraction Model Report Integration (BSC 2005 [DIRS 173617]). The EBS radionuclide transport abstraction (or EBS RT Abstraction) is the conceptual model used in the total system performance assessment (TSPA) to determine the rate of radionuclide releases from the EBS to the unsaturated zone (UZ). The EBS RT Abstraction conceptual model consists of two main components: a flow model and a transport model. Both models are developed mathematically from first principles in order to show explicitly what assumptions, simplifications, and approximations are incorporated into the models used in the TSPA. The flow model defines the pathways for water flow in the EBS and specifies how the flow rate is computed in each pathway. Input to this model includes the seepage flux into a drift. The seepage flux is potentially split by the drip shield, with some (or all) of the flux being diverted by the drip shield and some passing through breaches in the drip shield that might result from corrosion or seismic damage. The flux through drip shield breaches is potentially split by the waste package, with some (or all) of the flux being diverted by the waste package and some passing through waste package breaches that might result from corrosion or seismic damage. Neither the drip shield nor the waste package survives an igneous intrusion, so the flux splitting submodel is not used in the igneous scenario class. The flow model is validated in an independent model validation technical review. The drip shield and waste package flux splitting algorithms are developed and validated using experimental data. The transport model considers advective transport and diffusive transport

  16. Transfer, Abstraction, and Context

    ERIC Educational Resources Information Center

    Jones, Matthew G.

    2009-01-01

    The author responds to the recent work of Kaminski, Sloutsky, and Heckler (2008) and advances two major concerns about their research and its applicability to learning mathematics: a confounding variable that arises from the mathematical differences between the generic examples and concrete examples poses a threat to the construct validity of the…

  17. Innovation Abstracts, 2000.

    ERIC Educational Resources Information Center

    Roueche, Suanne D., Ed.

    2000-01-01

    This document is a series of short papers (47) on topics of interest to community college instructors and practitioners. The topics covered in the papers include: study and writing tips for students, teaching strategies and tips, descriptions of innovative programs, using technology in teaching and learning, interacting with students, and…

  18. State-of-the-art in design rules for drug delivery platforms: lessons learned from FDA-approved nanomedicines.

    PubMed

    Dawidczyk, Charlene M; Kim, Chloe; Park, Jea Ho; Russell, Luisa M; Lee, Kwan Hyi; Pomper, Martin G; Searson, Peter C

    2014-08-10

    The ability to efficiently deliver a drug to a tumor site is dependent on a wide range of physiologically imposed design constraints. Nanotechnology provides the possibility of creating delivery vehicles where these design constraints can be decoupled, allowing new approaches for reducing the unwanted side effects of systemic delivery, increasing targeting efficiency and efficacy. Here we review the design strategies of the two FDA-approved antibody-drug conjugates (Brentuximab vedotin and Trastuzumab emtansine) and the four FDA-approved nanoparticle-based drug delivery platforms (Doxil, DaunoXome, Marqibo, and Abraxane) in the context of the challenges associated with systemic targeted delivery of a drug to a solid tumor. The lessons learned from these nanomedicines provide an important insight into the key challenges associated with the development of new platforms for systemic delivery of anti-cancer drugs.

  19. Research Abstracts of 1980.

    DTIC Science & Technology

    1980-12-01

    ABSTRACTS OF 1980. 9 - DTIC ELECTEf ii S AN3O 1981j _NAVAL DISTRIBUTION SMT:MIT DENTAL RESEARCH Approved for PUbDiC T INSTITE iii~2 YA3 It81 Naval...Medical Research apd Development Command 30 £ Bethesda, Maryland ( *- i - NTIS - GRA&I DTIC TAB - Urrannouneed NAVAL DENTAL RESEARCH INSTITUTE...r1 w American Assoctat/ion for Dental Research, 58th Annual Session, Los Angeles, California, March 20-23, 1980. 1. AV6ERSON*, D. N., LANGELAND, K

  20. Research Abstracts of 1979.

    DTIC Science & Technology

    1979-12-01

    7 AD-AO82 309 NAVAL DENTAL RESEARCH INST GREAT LAKES IL F/6 6/9 RESCH ABTAT79 991 UNCLASSIFIED NORI-PR-79-11 NL ’NDRI-PR 79-11 December 1979...RESEARCH ABSTRACTS OF 1979 OTICSELZCreD MAR 2?718 S A NAVAL DENTAL RESEARCH INSTITUTE Naval Medical Research and Development Command Bethesda, Maryland...8G 3 23 O4ൌ p.,. ... ....-- - I -- - ’.... .I l l ---,, .. . = ., , ." .;’.- I 1 IV NAVAL DENTAL RESEARCH INSTITUTE NAVAL BASE, BLDG. I-H GREAT LAKES

  1. Using Group Explorer in teaching abstract algebra

    NASA Astrophysics Data System (ADS)

    Schubert, Claus; Gfeller, Mary; Donohue, Christopher

    2013-04-01

    This study explores the use of Group Explorer in an undergraduate mathematics course in abstract algebra. The visual nature of Group Explorer in representing concepts in group theory is an attractive incentive to use this software in the classroom. However, little is known about students' perceptions on this technology in learning concepts in abstract algebra. A total of 26 participants in an undergraduate course studying group theory were surveyed regarding their experiences using Group Explorer. Findings indicate that all participants believed that the software was beneficial to their learning and described their attitudes regarding the software in terms of using the technology and its helpfulness in learning concepts. A multiple regression analysis reveals that representational fluency of concepts with the software correlated significantly with participants' understanding of group concepts yet, participants' attitudes about Group Explorer and technology in general were not significant factors.

  2. EBS Radionuclide Transport Abstraction

    SciTech Connect

    J.D. Schreiber

    2005-08-25

    The purpose of this report is to develop and analyze the engineered barrier system (EBS) radionuclide transport abstraction model, consistent with Level I and Level II model validation, as identified in ''Technical Work Plan for: Near-Field Environment and Transport: Engineered Barrier System: Radionuclide Transport Abstraction Model Report Integration'' (BSC 2005 [DIRS 173617]). The EBS radionuclide transport abstraction (or EBS RT Abstraction) is the conceptual model used in the total system performance assessment for the license application (TSPA-LA) to determine the rate of radionuclide releases from the EBS to the unsaturated zone (UZ). The EBS RT Abstraction conceptual model consists of two main components: a flow model and a transport model. Both models are developed mathematically from first principles in order to show explicitly what assumptions, simplifications, and approximations are incorporated into the models used in the TSPA-LA. The flow model defines the pathways for water flow in the EBS and specifies how the flow rate is computed in each pathway. Input to this model includes the seepage flux into a drift. The seepage flux is potentially split by the drip shield, with some (or all) of the flux being diverted by the drip shield and some passing through breaches in the drip shield that might result from corrosion or seismic damage. The flux through drip shield breaches is potentially split by the waste package, with some (or all) of the flux being diverted by the waste package and some passing through waste package breaches that might result from corrosion or seismic damage. Neither the drip shield nor the waste package survives an igneous intrusion, so the flux splitting submodel is not used in the igneous scenario class. The flow model is validated in an independent model validation technical review. The drip shield and waste package flux splitting algorithms are developed and validated using experimental data. The transport model considers

  3. Binary translation using peephole translation rules

    DOEpatents

    Bansal, Sorav; Aiken, Alex

    2010-05-04

    An efficient binary translator uses peephole translation rules to directly translate executable code from one instruction set to another. In a preferred embodiment, the translation rules are generated using superoptimization techniques that enable the translator to automatically learn translation rules for translating code from the source to target instruction set architecture.

  4. Writing a successful research abstract.

    PubMed

    Bliss, Donna Z

    2012-01-01

    Writing and submitting a research abstract provides timely dissemination of the findings of a study and offers peer input for the subsequent development of a quality manuscript. Acceptance of abstracts is competitive. Understanding the expected content of an abstract, the abstract review process and tips for skillful writing will improve the chance of acceptance.

  5. Hamilton's rule.

    PubMed

    van Veelen, Matthijs; Allen, Benjamin; Hoffman, Moshe; Simon, Burton; Veller, Carl

    2017-02-07

    This paper reviews and addresses a variety of issues relating to inclusive fitness. The main question is: are there limits to the generality of inclusive fitness, and if so, what are the perimeters of the domain within which inclusive fitness works? This question is addressed using two well-known tools from evolutionary theory: the replicator dynamics, and adaptive dynamics. Both are combined with population structure. How generally Hamilton's rule applies depends on how costs and benefits are defined. We therefore consider costs and benefits following from Karlin and Matessi's (1983) "counterfactual method", and costs and benefits as defined by the "regression method" (Gardner et al., 2011). With the latter definition of costs and benefits, Hamilton's rule always indicates the direction of selection correctly, and with the former it does not. How these two definitions can meaningfully be interpreted is also discussed. We also consider cases where the qualitative claim that relatedness fosters cooperation holds, even if Hamilton's rule as a quantitative prediction does not. We furthermore find out what the relation is between Hamilton's rule and Fisher's Fundamental Theorem of Natural Selection. We also consider cancellation effects - which is the most important deepening of our understanding of when altruism is selected for. Finally we also explore the remarkable (im)possibilities for empirical testing with either definition of costs and benefits in Hamilton's rule.

  6. Adaptation and Extension of the Framework of Reducing Abstraction in the Case of Differential Equations

    ERIC Educational Resources Information Center

    Raychaudhuri, Debasree

    2014-01-01

    Although there is no consensus in regard to a unique meaning for abstraction, there is a recognition of the existence of several theories of abstraction, and that the ability to abstract is imperative to learning and doing meaningful mathematics. The theory of "reducing abstraction" maps the abstract nature of mathematics to the nature…

  7. Free-flying honeybees extrapolate relational size rules to sort successively visited artificial flowers in a realistic foraging situation.

    PubMed

    Howard, Scarlett R; Avarguès-Weber, Aurore; Garcia, Jair; Dyer, Adrian G

    2017-04-03

    Learning and applying relational concepts to solve novel tasks is considered an indicator of cognitive-like ability. It requires the abstraction of relational concepts to different objects independent to the physical nature of the individual objects. Recent research has revealed the honeybee's ability to rapidly learn and manipulate relations between visual stimuli such as 'same/different', 'above/below', or 'larger/smaller' despite having a miniature-sized brain. While honeybees can solve problems using rule-based relative size comparison, it remains unresolved as to whether bees can apply size rules when stimuli are encountered successively, which requires reliance on working memory for stimuli comparison. Additionally, the potential ability of bees to extrapolate acquired information to novel sizes beyond training sets remains to be investigated. We tested whether individual free-flying honeybees could learn 'larger/smaller' size rules when visual stimuli were presented successively, and whether such rules could then be extrapolated to novel stimulus sizes. Honeybees were individually trained to a set of four sizes such that individual elements might be correct, or incorrect, depending upon the alternative stimulus. In a learning test, bees preferred the correct size relation for their respective learning group. Bees were also able to successfully extrapolate the learnt relation during transfer tests by maintaining the correct size relationships when considering either two smaller, or two larger, novel stimulus sizes. This performance demonstrates that an insect operating in a complex environment has sufficient cognitive capacity to learn rules that can be abstracted to novel problems. We discuss the possible learning mechanisms which allow their success.

  8. Automated Supernova Discovery (Abstract)

    NASA Astrophysics Data System (ADS)

    Post, R. S.

    2015-12-01

    (Abstract only) We are developing a system of robotic telescopes for automatic recognition of Supernovas as well as other transient events in collaboration with the Puckett Supernova Search Team. At the SAS2014 meeting, the discovery program, SNARE, was first described. Since then, it has been continuously improved to handle searches under a wide variety of atmospheric conditions. Currently, two telescopes are used to build a reference library while searching for PSN with a partial library. Since data is taken every night without clouds, we must deal with varying atmospheric and high background illumination from the moon. Software is configured to identify a PSN, reshoot for verification with options to change the run plan to acquire photometric or spectrographic data. The telescopes are 24-inch CDK24, with Alta U230 cameras, one in CA and one in NM. Images and run plans are sent between sites so the CA telescope can search while photometry is done in NM. Our goal is to find bright PSNs with magnitude 17.5 or less which is the limit of our planned spectroscopy. We present results from our first automated PSN discoveries and plans for PSN data acquisition.

  9. Exoplanets and Multiverses (Abstract)

    NASA Astrophysics Data System (ADS)

    Trimble, V.

    2016-12-01

    (Abstract only) To the ancients, the Earth was the Universe, of a size to be crossed by a god in a day, by boat or chariot, and by humans in a lifetime. Thus an exoplanet would have been a multiverse. The ideas gradually separated over centuries, with gradual acceptance of a sun-centered solar system, the stars as suns likely to have their own planets, other galaxies beyond the Milky Way, and so forth. And whenever the community divided between "just one' of anything versus "many," the "manies" have won. Discoveries beginning in 1991 and 1995 have gradually led to a battalion or two of planets orbiting other stars, very few like our own little family, and to moderately serious consideration of even larger numbers of other universes, again very few like our own. I'm betting, however, on habitable (though not necessarily inhabited) exoplanets to be found, and habitable (though again not necessarily inhabited) universes. Only the former will yield pretty pictures.

  10. Stellar Presentations (Abstract)

    NASA Astrophysics Data System (ADS)

    Young, D.

    2015-12-01

    (Abstract only) The AAVSO is in the process of expanding its education, outreach and speakers bureau program. powerpoint presentations prepared for specific target audiences such as AAVSO members, educators, students, the general public, and Science Olympiad teams, coaches, event supervisors, and state directors will be available online for members to use. The presentations range from specific and general content relating to stellar evolution and variable stars to specific activities for a workshop environment. A presentation—even with a general topic—that works for high school students will not work for educators, Science Olympiad teams, or the general public. Each audience is unique and requires a different approach. The current environment necessitates presentations that are captivating for a younger generation that is embedded in a highly visual and sound-bite world of social media, twitter and U-Tube, and mobile devices. For educators, presentations and workshops for themselves and their students must support the Next Generation Science Standards (NGSS), the Common Core Content Standards, and the Science Technology, Engineering and Mathematics (STEM) initiative. Current best practices for developing relevant and engaging powerpoint presentations to deliver information to a variety of targeted audiences will be presented along with several examples.

  11. Linking Research to Policy, Practice, and Education: Lessons Learned, Tasks Ahead. Program Abstracts. Annual Scientific Meeting of the Gerontological Society of America (53rd, Washington, DC, November 17-21, 2000).

    ERIC Educational Resources Information Center

    Gerontologist, 2000

    2000-01-01

    This publication contains abstracts from the 53rd annual meeting of the Gerontological Society of America. The abstracts are arranged numerically by the session number in which they appear. Several abstracts are listed under each of the 388 sessions. Although the sessions are not limited to one topic, the dominant theme is education concerning all…

  12. Abstraction of Drift Seepage

    SciTech Connect

    J.T. Birkholzer

    2004-11-01

    This model report documents the abstraction of drift seepage, conducted to provide seepage-relevant parameters and their probability distributions for use in Total System Performance Assessment for License Application (TSPA-LA). Drift seepage refers to the flow of liquid water into waste emplacement drifts. Water that seeps into drifts may contact waste packages and potentially mobilize radionuclides, and may result in advective transport of radionuclides through breached waste packages [''Risk Information to Support Prioritization of Performance Assessment Models'' (BSC 2003 [DIRS 168796], Section 3.3.2)]. The unsaturated rock layers overlying and hosting the repository form a natural barrier that reduces the amount of water entering emplacement drifts by natural subsurface processes. For example, drift seepage is limited by the capillary barrier forming at the drift crown, which decreases or even eliminates water flow from the unsaturated fractured rock into the drift. During the first few hundred years after waste emplacement, when above-boiling rock temperatures will develop as a result of heat generated by the decay of the radioactive waste, vaporization of percolation water is an additional factor limiting seepage. Estimating the effectiveness of these natural barrier capabilities and predicting the amount of seepage into drifts is an important aspect of assessing the performance of the repository. The TSPA-LA therefore includes a seepage component that calculates the amount of seepage into drifts [''Total System Performance Assessment (TSPA) Model/Analysis for the License Application'' (BSC 2004 [DIRS 168504], Section 6.3.3.1)]. The TSPA-LA calculation is performed with a probabilistic approach that accounts for the spatial and temporal variability and inherent uncertainty of seepage-relevant properties and processes. Results are used for subsequent TSPA-LA components that may handle, for example, waste package corrosion or radionuclide transport.

  13. Attracting Girls into Physics (abstract)

    NASA Astrophysics Data System (ADS)

    Gadalla, Afaf

    2009-04-01

    A recent international study of women in physics showed that enrollment in physics and science is declining for both males and females and that women are severely underrepresented in careers requiring a strong physics background. The gender gap begins early in the pipeline, from the first grade. Girls are treated differently than boys at home and in society in ways that often hinder their chances for success. They have fewer freedoms, are discouraged from accessing resources or being adventurous, have far less exposure to problem solving, and are not encouraged to choose their lives. In order to motivate more girl students to study physics in the Assiut governorate of Egypt, the Assiut Alliance for the Women and Assiut Education District collaborated in renovating the education of physics in middle and secondary school classrooms. A program that helps in increasing the number of girls in science and physics has been designed in which informal groupings are organized at middle and secondary schools to involve girls in the training and experiences needed to attract and encourage girls to learn physics. During implementation of the program at some schools, girls, because they had not been trained in problem-solving as boys, appeared not to be as facile in abstracting the ideas of physics, and that was the primary reason for girls dropping out of science and physics. This could be overcome by holding a topical physics and technology summer school under the supervision of the Assiut Alliance for the Women.

  14. The Common Element Effect of Abstract-to-Abstract Mapping in Language Processing.

    PubMed

    Chen, Xuqian; Wang, Guixiang; Liang, Yuchan

    2016-01-01

    Since the 1990s, there has been much discussion about how concepts are learned and processed. Many researchers believe that the experienced bodily states (i.e., embodied experiences) should be an important factor that affects concepts' learning and use, and metaphorical mappings between abstract concepts, such as TIME and POWER, and concrete concepts, such as SPATIAL ORIENTATION, STRUCTURED EXPERIENCEs, etc., suggest the abstract-concrete concepts' connections. In most of the recent literature, we can find common elements (e.g., concrete concepts) shared by different abstract-concrete metaphorical expressions. Therefore, we assumed that mappings might also be found between two abstract concepts that share common elements, though they have no symbolic connections. In the present study, two lexical decision tasks were arranged and the priming effect between TIME and ABSTRACT ACTIONs was used as an index to test our hypothesis. Results showed a robust priming effect when a target verb and its prime belonged to the same duration type (TIME consistent condition). These findings suggest that mapping between concepts was affected by common elements. We propose a dynamic model in which mappings between concepts are influenced by common elements, including symbolic or embodied information. What kind of elements (linguistic or embodied) can be used would depend on how difficult it is for a concept to be learned or accessed.

  15. The Common Element Effect of Abstract-to-Abstract Mapping in Language Processing

    PubMed Central

    Chen, Xuqian; Wang, Guixiang; Liang, Yuchan

    2016-01-01

    Since the 1990s, there has been much discussion about how concepts are learned and processed. Many researchers believe that the experienced bodily states (i.e., embodied experiences) should be an important factor that affects concepts’ learning and use, and metaphorical mappings between abstract concepts, such as TIME and POWER, and concrete concepts, such as SPATIAL ORIENTATION, STRUCTURED EXPERIENCEs, etc., suggest the abstract-concrete concepts’ connections. In most of the recent literature, we can find common elements (e.g., concrete concepts) shared by different abstract-concrete metaphorical expressions. Therefore, we assumed that mappings might also be found between two abstract concepts that share common elements, though they have no symbolic connections. In the present study, two lexical decision tasks were arranged and the priming effect between TIME and ABSTRACT ACTIONs was used as an index to test our hypothesis. Results showed a robust priming effect when a target verb and its prime belonged to the same duration type (TIME consistent condition). These findings suggest that mapping between concepts was affected by common elements. We propose a dynamic model in which mappings between concepts are influenced by common elements, including symbolic or embodied information. What kind of elements (linguistic or embodied) can be used would depend on how difficult it is for a concept to be learned or accessed. PMID:27822192

  16. Levels of abstraction in orangutan (Pongo abelii) categorization.

    PubMed

    Vonk, Jennifer; MacDonald, Suzanne E

    2004-03-01

    Levels of abstraction have rarely been manipulated in studies of natural concept formation in nonhumans. Isolated examples have indicated that animals, relative to humans, may learn concepts at varying levels of abstraction with differential ease. The ability of 6 orangutans (Pongo abelii) of various ages to make natural concept discriminations at 3 levels of abstraction was therefore investigated. The orangutans were rewarded for selecting photos of orangutans instead of humans and other primates (concrete level), primates instead of other animals (intermediate level), and animals instead of nonanimals (abstract level) in a 2-choice touch screen procedure. The results suggest that, like a gorilla (Gorilla gorilla gorilla) tested previously (Vonk & MacDonald, 2002), orangutans can learn concepts at each level of abstraction, and unlike other nonhumans, most of these subjects rapidly learned the intermediate level discrimination.

  17. Abstracts of Review Articles and Educational Materials in Physiology

    ERIC Educational Resources Information Center

    Physiology Teacher, 1977

    1977-01-01

    Contained are 99 abstracts of review articles, texts, books, manuals, learning programs, and audiovisual material used in teaching physiology. Specific fields include cell physiology, circulation, comparative physiology, development and aging, endocrinology and metabolism, environmental and exercise physiology, gastrointestinal physiology, muscle…

  18. Learning to Learn about Uncertain Feedback

    ERIC Educational Resources Information Center

    Faraut, Mailys C. M.; Procyk, Emmanuel; Wilson, Charles R. E.

    2016-01-01

    Unexpected outcomes can reflect noise in the environment or a change in the current rules. We should ignore noise but shift strategy after rule changes. How we learn to do this is unclear, but one possibility is that it relies on learning to learn in uncertain environments. We propose that acquisition of latent task structure during learning to…

  19. Predicting Semantic Changes in Abstraction in Tutor Responses to Students

    ERIC Educational Resources Information Center

    Lipschultz, Michael; Litman, Diane; Katz, Sandra; Albacete, Patricia; Jordan, Pamela

    2014-01-01

    Post-problem reflective tutorial dialogues between human tutors and students are examined to predict when the tutor changed the level of abstraction from the student's preceding turn (i.e., used more general terms or more specific terms); such changes correlate with learning. Prior work examined lexical changes in abstraction. In this work, we…

  20. Knowledge Base Refinement by Monitoring Abstract Control Knowledge.

    ERIC Educational Resources Information Center

    Wilkins, D. C.; And Others

    Arguing that an explicit representation of the problem-solving method of an expert system shell as abstract control knowledge provides a powerful foundation for learning, this paper describes the abstract control knowledge of the Heracles expert system shell for heuristic classification problems, and describes how the Odysseus apprenticeship…

  1. Using abstract language signals power.

    PubMed

    Wakslak, Cheryl J; Smith, Pamela K; Han, Albert

    2014-07-01

    Power can be gained through appearances: People who exhibit behavioral signals of power are often treated in a way that allows them to actually achieve such power (Ridgeway, Berger, & Smith, 1985; Smith & Galinsky, 2010). In the current article, we examine power signals within interpersonal communication, exploring whether use of concrete versus abstract language is seen as a signal of power. Because power activates abstraction (e.g., Smith & Trope, 2006), perceivers may expect higher power individuals to speak more abstractly and therefore will infer that speakers who use more abstract language have a higher degree of power. Across a variety of contexts and conversational subjects in 7 experiments, participants perceived respondents as more powerful when they used more abstract language (vs. more concrete language). Abstract language use appears to affect perceived power because it seems to reflect both a willingness to judge and a general style of abstract thinking.

  2. Grounding Abstractness: Abstract Concepts and the Activation of the Mouth.

    PubMed

    Borghi, Anna M; Zarcone, Edoardo

    2016-01-01

    One key issue for theories of cognition is how abstract concepts, such as freedom, are represented. According to the WAT (Words As social Tools) proposal, abstract concepts activate both sensorimotor and linguistic/social information, and their acquisition modality involves the linguistic experience more than the acquisition of concrete concepts. We report an experiment in which participants were presented with abstract and concrete definitions followed by concrete and abstract target-words. When the definition and the word matched, participants were required to press a key, either with the hand or with the mouth. Response times and accuracy were recorded. As predicted, we found that abstract definitions and abstract words yielded slower responses and more errors compared to concrete definitions and concrete words. More crucially, there was an interaction between the target-words and the effector used to respond (hand, mouth). While responses with the mouth were overall slower, the advantage of the hand over the mouth responses was more marked with concrete than with abstract concepts. The results are in keeping with grounded and embodied theories of cognition and support the WAT proposal, according to which abstract concepts evoke linguistic-social information, hence activate the mouth. The mechanisms underlying the mouth activation with abstract concepts (re-enactment of acquisition experience, or re-explanation of the word meaning, possibly through inner talk) are discussed. To our knowledge this is the first behavioral study demonstrating with real words that the advantage of the hand over the mouth is more marked with concrete than with abstract concepts, likely because of the activation of linguistic information with abstract concepts.

  3. Grounding Abstractness: Abstract Concepts and the Activation of the Mouth

    PubMed Central

    Borghi, Anna M.; Zarcone, Edoardo

    2016-01-01

    One key issue for theories of cognition is how abstract concepts, such as freedom, are represented. According to the WAT (Words As social Tools) proposal, abstract concepts activate both sensorimotor and linguistic/social information, and their acquisition modality involves the linguistic experience more than the acquisition of concrete concepts. We report an experiment in which participants were presented with abstract and concrete definitions followed by concrete and abstract target-words. When the definition and the word matched, participants were required to press a key, either with the hand or with the mouth. Response times and accuracy were recorded. As predicted, we found that abstract definitions and abstract words yielded slower responses and more errors compared to concrete definitions and concrete words. More crucially, there was an interaction between the target-words and the effector used to respond (hand, mouth). While responses with the mouth were overall slower, the advantage of the hand over the mouth responses was more marked with concrete than with abstract concepts. The results are in keeping with grounded and embodied theories of cognition and support the WAT proposal, according to which abstract concepts evoke linguistic-social information, hence activate the mouth. The mechanisms underlying the mouth activation with abstract concepts (re-enactment of acquisition experience, or re-explanation of the word meaning, possibly through inner talk) are discussed. To our knowledge this is the first behavioral study demonstrating with real words that the advantage of the hand over the mouth is more marked with concrete than with abstract concepts, likely because of the activation of linguistic information with abstract concepts. PMID:27777563

  4. Mechanical Engineering Department technical abstracts

    SciTech Connect

    Denney, R.M.

    1982-07-01

    The Mechanical Engineering Department publishes listings of technical abstracts twice a year to inform readers of the broad range of technical activities in the Department, and to promote an exchange of ideas. Details of the work covered by an abstract may be obtained by contacting the author(s). Overall information about current activities of each of the Department's seven divisions precedes the technical abstracts.

  5. Innovation Abstracts, Volume VIII, Numbers 1-29.

    ERIC Educational Resources Information Center

    Roueche, Suanne D., Ed.

    1986-01-01

    This series of one- and two-page abstracts highlights a variety of innovative approaches to teaching and learning in the community college. Topics covered in the articles include: the use of "trigger films" in group learning situations; letter writing as a means of maintaining group cohesion in a nontraditional classroom; creative grading; the use…

  6. Rules for Optical Testing

    NASA Technical Reports Server (NTRS)

    Stahl, H. Philip

    2014-01-01

    Based on 30 years of optical testing experience, a lot of mistakes, a lot of learning and a lot of experience, I have defined seven guiding principles for optical testing - regardless of how small or how large the optical testing or metrology task: Fully Understand the Task, Develop an Error Budget, Continuous Metrology Coverage, Know where you are, Test like you fly, Independent Cross-Checks, Understand All Anomalies. These rules have been applied with great success to the inprocess optical testing and final specification compliance testing of the JWST mirrors.

  7. Are all abstracts created equal??

    PubMed

    Weinert, Clarann

    2010-05-01

    The preparation of a strong, convincing abstract is a necessary professional skill and prized art form for nurse scientists and clinical scholars. The power and the role of an abstract are often overlooked. Abstracts are used in a variety of scholarly forums including articles submitted for publication, research proposals, and responses to "calls for abstracts" for presentations at scientific conferences. The purpose of this article is to emphasize the highlights of the "art" rather than the "cookbook" details associated with preparing an abstract. Each of the critical stages of abstract development is explored-planning, drafting, reviewing, peer reviewing, editing, and packaging. Likewise, a few, hopefully helpful, hints on developing the six key elements-background, purpose, sample, methods, results, and implications-of the scientific abstract are given. Polishing, the essential skill of preparing an abstract, takes time and persistence and will pay off in the long run. The well-crafted abstract is an initial step in the process of getting research and scholarly pursuits noticed and accepted.

  8. An Integrated Planning Representation Using Macros, Abstractions, and Cases

    NASA Technical Reports Server (NTRS)

    Baltes, Jacky; MacDonald, Bruce

    1992-01-01

    Planning will be an essential part of future autonomous robots and integrated intelligent systems. This paper focuses on learning problem solving knowledge in planning systems. The system is based on a common representation for macros, abstractions, and cases. Therefore, it is able to exploit both classical and case based techniques. The general operators in a successful plan derivation would be assessed for their potential usefulness, and some stored. The feasibility of this approach was studied through the implementation of a learning system for abstraction. New macros are motivated by trying to improve the operatorset. One heuristic used to improve the operator set is generating operators with more general preconditions than existing ones. This heuristic leads naturally to abstraction hierarchies. This investigation showed promising results on the towers of Hanoi problem. The paper concludes by describing methods for learning other problem solving knowledge. This knowledge can be represented by allowing operators at different levels of abstraction in a refinement.

  9. Leadership Abstracts; Volume 4, 1991.

    ERIC Educational Resources Information Center

    Doucette, Don, Ed.

    1991-01-01

    "Leadership Abstracts" is published bimonthly and distributed to the chief executive officer of every two-year college in the United States and Canada. This document consists of the 15 one-page abstracts published in 1991. Addressing a variety of topics of interest to the community college administrators, this volume includes: (1) "Delivering the…

  10. Vague Language in Conference Abstracts

    ERIC Educational Resources Information Center

    Cutting, Joan

    2012-01-01

    This study examined abstracts for a British Association for Applied Linguistics conference and a Sociolinguistics Symposium, to define the genre of conference abstracts in terms of vague language, specifically universal general nouns (e.g. people) and research general nouns (e.g. results), and to discover if the language used reflected the level…

  11. Technical abstracts: Mechanical engineering, 1990

    SciTech Connect

    Broesius, J.Y.

    1991-03-01

    This document is a compilation of the published, unclassified abstracts produced by mechanical engineers at Lawrence Livermore National Laboratory (LLNL) during the calendar year 1990. Many abstracts summarize work completed and published in report form. These are UCRL-JC series documents, which include the full text of articles to be published in journals and of papers to be presented at meetings, and UCID reports, which are informal documents. Not all UCIDs contain abstracts: short summaries were generated when abstracts were not included. Technical Abstracts also provides descriptions of those documents assigned to the UCRL-MI (miscellaneous) category. These are generally viewgraphs or photographs presented at meetings. An author index is provided at the back of this volume for cross referencing.

  12. Abstracts

    NASA Astrophysics Data System (ADS)

    2012-09-01

    Measuring cosmological parameters with GRBs: status and perspectives New interpretation of the Amati relation The SED Machine - a dedicated transient spectrograph PTF10iue - evidence for an internal engine in a unique Type Ic SN Direct evidence for the collapsar model of long gamma-ray bursts On pair instability supernovae and gamma-ray bursts Pan-STARRS1 observations of ultraluminous SNe The influence of rotation on the critical neutrino luminosity in core-collapse supernovae General relativistic magnetospheres of slowly rotating and oscillating neutron stars Host galaxies of short GRBs GRB 100418A: a bridge between GRB-associated hypernovae and SNe Two super-luminous SNe at z ~ 1.5 from the SNLS Prospects for very-high-energy gamma-ray bursts with the Cherenkov Telescope Array The dynamics and radiation of relativistic flows from massive stars The search for light echoes from the supernova explosion of 1181 AD The proto-magnetar model for gamma-ray bursts Stellar black holes at the dawn of the universe MAXI J0158-744: the discovery of a supersoft X-ray transient Wide-band spectra of magnetar burst emission Dust formation and evolution in envelope-stripped core-collapse supernovae The host galaxies of dark gamma-ray bursts Keck observations of 150 GRB host galaxies Search for properties of GRBs at large redshift The early emission from SNe Spectral properties of SN shock breakout MAXI observation of GRBs and short X-ray transients A three-dimensional view of SN 1987A using light echo spectroscopy X-ray study of the southern extension of the SNR Puppis A All-sky survey of short X-ray transients by MAXI GSC Development of the CALET gamma-ray burst monitor (CGBM)

  13. Abstracts

    ERIC Educational Resources Information Center

    Parsegian, V. L., Ed.

    1972-01-01

    Includes summaries of six articles dealing with engineering education, population management, blood sampling, international pollution control, environmental quality index, and scientific phases in political science. (CC)

  14. A grounded theory of abstraction in artificial intelligence.

    PubMed

    Zucker, Jean-Daniel

    2003-07-29

    In artificial intelligence, abstraction is commonly used to account for the use of various levels of details in a given representation language or the ability to change from one level to another while preserving useful properties. Abstraction has been mainly studied in problem solving, theorem proving, knowledge representation (in particular for spatial and temporal reasoning) and machine learning. In such contexts, abstraction is defined as a mapping between formalisms that reduces the computational complexity of the task at stake. By analysing the notion of abstraction from an information quantity point of view, we pinpoint the differences and the complementary role of reformulation and abstraction in any representation change. We contribute to extending the existing semantic theories of abstraction to be grounded on perception, where the notion of information quantity is easier to characterize formally. In the author's view, abstraction is best represented using abstraction operators, as they provide semantics for classifying different abstractions and support the automation of representation changes. The usefulness of a grounded theory of abstraction in the cartography domain is illustrated. Finally, the importance of explicitly representing abstraction for designing more autonomous and adaptive systems is discussed.

  15. A grounded theory of abstraction in artificial intelligence.

    PubMed Central

    Zucker, Jean-Daniel

    2003-01-01

    In artificial intelligence, abstraction is commonly used to account for the use of various levels of details in a given representation language or the ability to change from one level to another while preserving useful properties. Abstraction has been mainly studied in problem solving, theorem proving, knowledge representation (in particular for spatial and temporal reasoning) and machine learning. In such contexts, abstraction is defined as a mapping between formalisms that reduces the computational complexity of the task at stake. By analysing the notion of abstraction from an information quantity point of view, we pinpoint the differences and the complementary role of reformulation and abstraction in any representation change. We contribute to extending the existing semantic theories of abstraction to be grounded on perception, where the notion of information quantity is easier to characterize formally. In the author's view, abstraction is best represented using abstraction operators, as they provide semantics for classifying different abstractions and support the automation of representation changes. The usefulness of a grounded theory of abstraction in the cartography domain is illustrated. Finally, the importance of explicitly representing abstraction for designing more autonomous and adaptive systems is discussed. PMID:12903672

  16. The effect of negative performance stereotypes on learning.

    PubMed

    Rydell, Robert J; Rydell, Michael T; Boucher, Kathryn L

    2010-12-01

    Stereotype threat (ST) research has focused exclusively on how negative group stereotypes reduce performance. The present work examines if pejorative stereotypes about women in math inhibit their ability to learn the mathematical rules and operations necessary to solve math problems. In Experiment 1, women experiencing ST had difficulty encoding math-related information into memory and, therefore, learned fewer mathematical rules and showed poorer math performance than did controls. In Experiment 2, women experiencing ST while learning modular arithmetic (MA) performed more poorly than did controls on easy MA problems; this effect was due to reduced learning of the mathematical operations underlying MA. In Experiment 3, ST reduced women's, but not men's, ability to learn abstract mathematical rules and to transfer these rules to a second, isomorphic task. This work provides the first evidence that negative stereotypes about women in math reduce their level of mathematical learning and demonstrates that reduced learning due to stereotype threat can lead to poorer performance in negatively stereotyped domains.

  17. Newborn infants perceive abstract numbers.

    PubMed

    Izard, Véronique; Sann, Coralie; Spelke, Elizabeth S; Streri, Arlette

    2009-06-23

    Although infants and animals respond to the approximate number of elements in visual, auditory, and tactile arrays, only human children and adults have been shown to possess abstract numerical representations that apply to entities of all kinds (e.g., 7 samurai, seas, or sins). Do abstract numerical concepts depend on language or culture, or do they form a part of humans' innate, core knowledge? Here we show that newborn infants spontaneously associate stationary, visual-spatial arrays of 4-18 objects with auditory sequences of events on the basis of number. Their performance provides evidence for abstract numerical representations at the start of postnatal experience.

  18. Ariel Database Rule System Project

    DTIC Science & Technology

    1992-01-14

    NOTES EL CT a Distribution unlimited UL 13. ABSTRACT (Mmmuum 200 we~ The Ariel project has culminated in several advancements in active database...4] Moez Chaabouni. A top-level discrimination network for database rule systems. Master’s thesis, Dept. of Computer Science and Eng., Wright State... Moez Chaabouni. The IBS-tree: A data structure for finding all intervals that overlap a point. Technical Report WSU-CS-90-11, Dept. of Computer

  19. Multistrategy learning: A case study

    SciTech Connect

    Domingos, P.

    1996-12-31

    Two of the most popular approaches to induction are instance-based learning (IBL) and rule generation. Their strengths and weaknesses are largely complementary. IBL methods are able to identify small details in the instance space, but have trouble with attributes that are relevant in some parts of the space but not others. Conversely, rule induction methods may overlook small exception regions, but are able to select different attributes in different parts of the instance space. The two methods have been unified in the RISE algorithm. RISE views instances as maximally specific rules, forms more general rules by gradually clustering instances of the same class, and classifies a test example by letting the nearest rule win. This approach potentially combines the advantages of rule induction and IBL, and has indeed been observed to be more accurate than each on a large number of bench-mark datasets. However, it is important to determine if this performance is indeed due to the hypothesized advantages, and to define the situations in which RISE`s bias will and will not be preferable to those of the individual approaches. This abstract reports experiments to this end in artificial domains.

  20. Learning.

    ERIC Educational Resources Information Center

    Glaser, Robert

    A report on learning psychology and its relationship to the study of school learning emphasizes the increasing interaction between theorists and educational practitioners, particularly in attempting to learn which variables influence the instructional process and to find an appropriate methodology to measure and evaluate learning. "Learning…

  1. Deficiencies in structured medical abstracts.

    PubMed

    Froom, P; Froom, J

    1993-07-01

    This study was carried out to determine if the content of structured abstracts conforms with recommendations of the Ad Hoc Working Group for the critical appraisal of the medical literature as adopted by the Annals of Internal Medicine. The study design was a survey. All articles published in Annals of Internal Medicine in 1991, excluding editorials, case-reports, literature reviews, decision analysis, studies in medical education, descriptive studies of clinical and basic phenomena, and papers lacking a structured abstract, were studied. Of a total of 150 articles, 20 were excluded. The abstract and text of each article were assessed for the presence of the following items; patient selection criteria, statements concerning extrapolation of findings, need for further study, and whether or not the information should be used now. Number of refusers, drop outs and reason(s) for drop outs were assessed for intervention and prospective cohort studies only. Deficiencies of assessed items were noted in both abstracts and texts. For abstracts, patient selection criteria, numbers of refusers, number of drop outs and reason(s) for drop outs were reported in 44.6% (58/130), 3.1% (4/130), 16.9% (14/83) and 2.4% (2/83) respectively. These items were reported more frequently in the texts 87.7% (114/130), 9.2% (12/130), 60.2% (50/83) and 37.3% (31/83) respectively (p < 0.05). Statements concerning extrapolation of findings, need for further study and use of information now were also more frequent in texts than abstracts (p < 0.0001). A large number of structured abstracts published in the Annals of Internal Medicine in 1991, lack information recommended by the Ad Hoc Working Group. Our findings should not be extrapolated to other journals requiring structured abstracts.

  2. Moral empiricism and the bias for act-based rules.

    PubMed

    Ayars, Alisabeth; Nichols, Shaun

    2017-01-31

    Previous studies on rule learning show a bias in favor of act-based rules, which prohibit intentionally producing an outcome but not merely allowing the outcome. Nichols, Kumar, Lopez, Ayars, and Chan (2016) found that exposure to a single sample violation in which an agent intentionally causes the outcome was sufficient for participants to infer that the rule was act-based. One explanation is that people have an innate bias to think rules are act-based. We suggest an alternative empiricist account: since most rules that people learn are act-based, people form an overhypothesis (Goodman, 1955) that rules are typically act-based. We report three studies that indicate that people can use information about violations to form overhypotheses about rules. In study 1, participants learned either three "consequence-based" rules that prohibited allowing an outcome or three "act-based" rules that prohibiting producing the outcome; in a subsequent learning task, we found that participants who had learned three consequence-based rules were more likely to think that the new rule prohibited allowing an outcome. In study 2, we presented participants with either 1 consequence-based rule or 3 consequence-based rules, and we found that those exposed to 3 such rules were more likely to think that a new rule was also consequence based. Thus, in both studies, it seems that learning 3 consequence-based rules generates an overhypothesis to expect new rules to be consequence-based. In a final study, we used a more subtle manipulation. We exposed participants to examples act-based or accident-based (strict liability) laws and then had them learn a novel rule. We found that participants who were exposed to the accident-based laws were more likely to think a new rule was accident-based. The fact that participants' bias for act-based rules can be shaped by evidence from other rules supports the idea that the bias for act-based rules might be acquired as an overhypothesis from the

  3. How Long Does It Take to Learn a Second Language?: Applying the "10,000-Hour Rule" as a Model for Fluency

    ERIC Educational Resources Information Center

    Eaton, Sarah Elaine

    2011-01-01

    This study applies the model of expertise developed by Ericsson et al (2007) to second and foreign language learning. Ericsson et al posits that in order to achieve expertise (as they define it) requires 10,000 or longer of "intense training". Applying this model to language learning, equating an expert level of competence with fluency, various…

  4. Abstract Context Representations in Primate Amygdala and Prefrontal Cortex.

    PubMed

    Saez, A; Rigotti, M; Ostojic, S; Fusi, S; Salzman, C D

    2015-08-19

    Neurons in prefrontal cortex (PFC) encode rules, goals, and other abstract information thought to underlie cognitive, emotional, and behavioral flexibility. Here we show that the amygdala, a brain area traditionally thought to mediate emotions, also encodes abstract information that could underlie this flexibility. Monkeys performed a task in which stimulus-reinforcement contingencies varied between two sets of associations, each defining a context. Reinforcement prediction required identifying a stimulus and knowing the current context. Behavioral evidence indicated that monkeys utilized this information to perform inference and adjust their behavior. Neural representations in both amygdala and PFC reflected the linked sets of associations implicitly defining each context, a process requiring a level of abstraction characteristic of cognitive operations. Surprisingly, when errors were made, the context signal weakened substantially in the amygdala. These data emphasize the importance of maintaining abstract cognitive information in the amygdala to support flexible behavior.

  5. Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons.

    PubMed

    Burbank, Kendra S

    2015-12-01

    The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be stacked to learn increasingly abstract representations. Several computational neuroscience models of sensory areas, including Olshausen & Field's Sparse Coding algorithm, can be seen as autoencoder variants, and autoencoders have seen extensive use in the machine learning community. Despite their power and versatility, autoencoders have been difficult to implement in a biologically realistic fashion. The challenges include their need to calculate differences between two neuronal activities and their requirement for learning rules which lead to identical changes at feedforward and feedback connections. Here, we study a biologically realistic network of integrate-and-fire neurons with anatomical connectivity and synaptic plasticity that closely matches that observed in cortical sensory areas. Our choice of synaptic plasticity rules is inspired by recent experimental and theoretical results suggesting that learning at feedback connections may have a different form from learning at feedforward connections, and our results depend critically on this novel choice of plasticity rules. Specifically, we propose that plasticity rules at feedforward versus feedback connections are temporally opposed versions of spike-timing dependent plasticity (STDP), leading to a symmetric combined rule we call Mirrored STDP (mSTDP). We show that with mSTDP, our network follows a learning rule that approximately minimizes an autoencoder loss function. When trained with whitened natural image patches, the learned synaptic weights resemble the receptive fields seen in V1. Our results use realistic synaptic plasticity rules to show that the powerful autoencoder learning algorithm could be within the reach of real biological networks.

  6. Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons

    PubMed Central

    Burbank, Kendra S.

    2015-01-01

    The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be stacked to learn increasingly abstract representations. Several computational neuroscience models of sensory areas, including Olshausen & Field’s Sparse Coding algorithm, can be seen as autoencoder variants, and autoencoders have seen extensive use in the machine learning community. Despite their power and versatility, autoencoders have been difficult to implement in a biologically realistic fashion. The challenges include their need to calculate differences between two neuronal activities and their requirement for learning rules which lead to identical changes at feedforward and feedback connections. Here, we study a biologically realistic network of integrate-and-fire neurons with anatomical connectivity and synaptic plasticity that closely matches that observed in cortical sensory areas. Our choice of synaptic plasticity rules is inspired by recent experimental and theoretical results suggesting that learning at feedback connections may have a different form from learning at feedforward connections, and our results depend critically on this novel choice of plasticity rules. Specifically, we propose that plasticity rules at feedforward versus feedback connections are temporally opposed versions of spike-timing dependent plasticity (STDP), leading to a symmetric combined rule we call Mirrored STDP (mSTDP). We show that with mSTDP, our network follows a learning rule that approximately minimizes an autoencoder loss function. When trained with whitened natural image patches, the learned synaptic weights resemble the receptive fields seen in V1. Our results use realistic synaptic plasticity rules to show that the powerful autoencoder learning algorithm could be within the reach of real biological networks. PMID:26633645

  7. Mechanical Engineering Department technical abstracts

    SciTech Connect

    Not Available

    1984-07-01

    The Mechanical Engineering Department publishes abstracts twice a year to inform readers of the broad range of technical activities in the Department, and to promote an exchange of ideas. Details of the work covered by an abstract may be obtained by contacting the author(s). General information about the current role and activities of each of the Department's seven divisions precedes the technical abstracts. Further information about a division's work may be obtained from the division leader, whose name is given at the end of each divisional summary. The Department's seven divisions are as follows: Nuclear Test Engineering Division, Nuclear Explosives Engineering Division, Weapons Engineering Division, Energy Systems Engineering Division, Engineering Sciences Division, Magnetic Fusion Engineering Division and Materials Fabrication Division.

  8. Meeting Abstracts - Annual Meeting 2016.

    PubMed

    2016-04-01

    The AMCP Abstracts program provides a forum through which authors can share their insights and outcomes of advanced managed care practice through publication in AMCP's Journal of Managed Care & Specialty Pharmacy (JMCP). Most of the reviewed and unreviewed abstracts are presented as posters so that interested AMCP meeting attendees can review findings and query authors. The Student/Resident/ Fellow poster presentation (unreviewed) is Wednesday, April 20, 2016, and the Professional poster presentation (reviewed) is Thursday, April 21. The Professional posters will also be displayed on Friday, April 22. The reviewed abstracts are published in the JMCP Meeting Abstracts supplement. The AMCP Managed Care & Specialty Pharmacy Annual Meeting 2016 in San Francisco, California, is expected to attract more than 3,500 managed care pharmacists and other health care professionals who manage and evaluate drug therapies, develop and manage networks, and work with medical managers and information specialists to improve the care of all individuals enrolled in managed care programs. Abstracts were submitted in the following categories: Research Report: describe completed original research on managed care pharmacy services or health care interventions. Examples include (but are not limited to) observational studies using administrative claims, reports of the impact of unique benefit design strategies, and analyses of the effects of innovative administrative or clinical programs. Economic Model: describe models that predict the effect of various benefit design or clinical decisions on a population. For example, an economic model could be used to predict the budget impact of a new pharmaceutical product on a health care system. Solving Problems in Managed Care: describe the specific steps taken to introduce a needed change, develop and implement a new system or program, plan and organize an administrative function, or solve other types of problems in managed care settings. These

  9. Metaphoric Images from Abstract Concepts.

    ERIC Educational Resources Information Center

    Vizmuller-Zocco, Jana

    1992-01-01

    Discusses children's use of metaphors to create meaning, using as an example the pragmatic and "scientific" ways in which preschool children explain thunder and lightning to themselves. Argues that children are being shortchanged by modern scientific notions of abstractness and that they should be encouraged to create their own explanations of…

  10. Carry Groups: Abstract Algebra Projects

    ERIC Educational Resources Information Center

    Miller, Cheryl Chute; Madore, Blair F.

    2004-01-01

    Carry Groups are a wonderful collection of groups to introduce in an undergraduate Abstract Algebra course. These groups are straightforward to define but have interesting structures for students to discover. We describe these groups and give examples of in-class group projects that were developed and used by Miller.

  11. ERGONOMICS ABSTRACTS 48347-48982.

    ERIC Educational Resources Information Center

    Ministry of Technology, London (England). Warren Spring Lab.

    IN THIS COLLECTION OF ERGONOMICS ABSTRACTS AND ANNOTATIONS THE FOLLOWING AREAS OF CONCERN ARE REPRESENTED--GENERAL REFERENCES, METHODS, FACILITIES, AND EQUIPMENT RELATING TO ERGONOMICS, SYSTEMS OF MAN AND MACHINES, VISUAL, AUDITORY, AND OTHER SENSORY INPUTS AND PROCESSES (INCLUDING SPEECH AND INTELLIGIBILITY), INPUT CHANNELS, BODY MEASUREMENTS,…

  12. Does "Social Work Abstracts" Work?

    ERIC Educational Resources Information Center

    Holden, Gary; Barker, Kathleen; Covert-Vail, Lucinda; Rosenberg, Gary; Cohen, Stephanie A.

    2008-01-01

    Objective: The current study seeks to provide estimates of the adequacy of journal coverage in the Social Work Abstracts (SWA) database. Method: A total of 23 journals listed in the Journal Citation Reports social work category during the 1997 to 2005 period were selected for study. Issue-level coverage estimates were obtained for SWA and…

  13. Typographic Settings for Structured Abstracts.

    ERIC Educational Resources Information Center

    Hartley, James

    2000-01-01

    Lists some of the major typographic variables involved in structured abstracts (containing sub-headings). Illustrates how typography can affect clarity by presenting seven examples that illustrate the effects of these typographic variables in practice. Concludes with a final example of an effective approach. (SR)

  14. Handedness Shapes Children's Abstract Concepts

    ERIC Educational Resources Information Center

    Casasanto, Daniel; Henetz, Tania

    2012-01-01

    Can children's handedness influence how they represent abstract concepts like "kindness" and "intelligence"? Here we show that from an early age, right-handers associate rightward space more strongly with positive ideas and leftward space with negative ideas, but the opposite is true for left-handers. In one experiment, children indicated where on…

  15. Chemical Abstracts' Document Delivery Service.

    ERIC Educational Resources Information Center

    Rollins, Stephen

    1984-01-01

    The Document Delivery Service offered by Chemical Abstracts is described in terms of the DIALORDER option on the Dialog information retrieval system, mail requests, and requests transmitted through OCLC's Interlibrary Loan system. Transmission costs, success rates, delivery rates, and other considerations in utilizing the service are included.…

  16. Physical Oceanography Program Science Abstracts.

    DTIC Science & Technology

    1986-04-01

    and turbulence . Present work in preparation for the OCEAN STORMS experiment ..- includes modelling of ocean reponse to realistic wind fields measured by...the Seasat scatterometer and modelling upper ocean turbulence and internal waves. 4 The principal investigator is also serving as coordinator for...and temperature variance are dissipated. We have been testing the applicability to oceanic turbulence of theoretical models , and rules derived from

  17. Using Monte Carlo Software to Teach Abstract Statistical Concepts: A Case Study

    ERIC Educational Resources Information Center

    Raffle, Holly; Brooks, Gordon P.

    2005-01-01

    Violations of assumptions, inflated Type I error rates, and robustness are important concepts for students to learn in an introductory statistics course. However, these abstract ideas can be difficult for students to understand. Monte Carlo simulation methods can provide a concrete way for students to learn abstract statistical concepts. This…

  18. Investigations in Science Education, Vol. 2, No. 3. Expanded Abstracts and Critical Analyses of Recent Research.

    ERIC Educational Resources Information Center

    Helgeson, Stanley L., Ed.; Blosser, Patricia E., Ed.

    This issue of Investigations in Science Education (ISE) provides analytical abstracts, prepared by science educators, of research reports in the areas of learning theories, concept learning, and teacher behaviors and attitudes. Each abstract includes bibliographical data, research design and procedure, purpose, research rationale, and an…

  19. Brain Research: Implications for the Education of Exceptional Children. Abstract XV: Research & Resources on Special Education.

    ERIC Educational Resources Information Center

    ERIC Clearinghouse on Handicapped and Gifted Children, Reston, VA.

    The one-page abstract summarizes "Brain Research: Implications for the Education of Exceptional Children," an ERIC Computer Search Reprint containing bibliographic information and abstracts of 115 documents. Citations are described in five sections: learning disabilities, autism, other learning handicaps, assessment techniques, and instructional…

  20. An Abstract Plan Preparation Language

    NASA Technical Reports Server (NTRS)

    Butler, Ricky W.; Munoz, Cesar A.

    2006-01-01

    This paper presents a new planning language that is more abstract than most existing planning languages such as the Planning Domain Definition Language (PDDL) or the New Domain Description Language (NDDL). The goal of this language is to simplify the formal analysis and specification of planning problems that are intended for safety-critical applications such as power management or automated rendezvous in future manned spacecraft. The new language has been named the Abstract Plan Preparation Language (APPL). A translator from APPL to NDDL has been developed in support of the Spacecraft Autonomy for Vehicles and Habitats Project (SAVH) sponsored by the Explorations Technology Development Program, which is seeking to mature autonomy technology for application to the new Crew Exploration Vehicle (CEV) that will replace the Space Shuttle.

  1. Abstraction Techniques for Parameterized Verification

    DTIC Science & Technology

    2006-11-01

    difference, consider an example frequently discussed in the history of science, namely the Ptolemaic system in which the planet earth is surrounded by...tend to imagine systems with the human observer in the center. While a Ptolemaic viewpoint is known to be wrong (or, more precisely, infeasible) in...physics, it naturally appears in the systems we construct. Consequently, the Ptolemaic viewpoint yields a natural abstraction principle for computer

  2. Cryogenic foam insulation: Abstracted publications

    NASA Technical Reports Server (NTRS)

    Williamson, F. R.

    1977-01-01

    A group of documents were chosen and abstracted which contain information on the properties of foam materials and on the use of foams as thermal insulation at cryogenic temperatures. The properties include thermal properties, mechanical properties, and compatibility properties with oxygen and other cryogenic fluids. Uses of foams include applications as thermal insulation for spacecraft propellant tanks, and for liquefied natural gas storage tanks and pipelines.

  3. Groundwater abstraction pollution risk assessment.

    PubMed

    Lytton, L; Howe, S; Sage, R; Greenaway, P

    2003-01-01

    A generic groundwater pollution risk assessment methodology has been developed to enable the evaluation and ranking of the potential risk of pollution to groundwater abstractions. The ranking can then be used to prioritise risk management or mitigation procedures in a robust and quantifiable framework and thus inform business investment decisions. The risk assessment consider the three components of the pollution transport model: source-pathway-receptor. For groundwater abstractions these correspond to land use (with associated pollutants and shallow subsurface characteristics), aquifer and the abstraction borehole. An hierarchical approach was chosen to allow the risk assessment to be successfully carried out with different quality data for different parts of the model. The 400-day groundwater protection zone defines the catchment boundary that form the spatial limit of the land use audit for each receptor. A risk score is obtained for each land use (potential pollution source) within the catchment. These scores are derived by considering the characteristics (such as load, persistence and toxicity) of all pollutants pertaining to each land use, their on-site management and the potential for the unsaturated subsurface to attenuate their effects in the event of a release. Risk scores are also applied to the aquifer characteristics (as pollutant pathway) and to the abstraction borehole (as pollutant receptor). Each risk score is accompanied by an uncertainty score which provides a guide to the confidence in the data used to compile the risk assessment. The application of the methodology has highlighted a number of problems in this type of work and results of initial case studies are being used to trial alternative scoring methods and a more simplified approach to accelerate the process of pollution risk assessment.

  4. The 5-Second Rule

    MedlinePlus

    ... What Happens in the Operating Room? The 5-Second Rule KidsHealth > For Kids > The 5-Second Rule Print A A A en español La ... it, he or she might have yelled, "5-second rule!" This so-called rule says food is ...

  5. Representations of Abstract Grammatical Feature Agreement in Young Children

    ERIC Educational Resources Information Center

    Melançon, Andréane; Shi, Rushen

    2015-01-01

    A fundamental question in language acquisition research is whether young children have abstract grammatical representations. We tested this question experimentally. French-learning 30-month-olds were first taught novel word-object pairs in the context of a gender-marked determiner (e.g., un[subscript MASC]ravole "a ravole"). Test trials…

  6. Functional Neuroanatomy of Contextual Acquisition of Concrete and Abstract Words

    ERIC Educational Resources Information Center

    Mestres-Misse, Anna; Munte, Thomas F.; Rodriguez-Fornells, Antoni

    2009-01-01

    The meaning of a novel word can be acquired by extracting it from linguistic context. Here we simulated word learning of new words associated to concrete and abstract concepts in a variant of the human simulation paradigm that provided linguistic context information in order to characterize the brain systems involved. Native speakers of Spanish…

  7. Non-Traditional Methods of Teaching Abstract Algebra

    ERIC Educational Resources Information Center

    Capaldi, Mindy

    2014-01-01

    This article reports on techniques of teaching abstract algebra which were developed to achieve multiple student objectives: reasoning and communication skills, deep content knowledge, student engagement, independence, and pride. The approach developed included a complementary combination of inquiry-based learning, individual (not group) homework…

  8. Development: Ages & Stages--How Abstract Thinking Develops

    ERIC Educational Resources Information Center

    Poole, Carla; Miller, Susan A.; Church, Ellen Booth

    2005-01-01

    Babies are active participants in their learning and need to explore a variety of objects. Nurturing relationships support these explorations. Objects are more clearly remembered and understood. Thus, one activity this article suggests doing with a 12-month-old to encourage abstract thinking, is talking about how squeezing the bottle of ketchup…

  9. Promoting Early Abstraction to Promote Early Literacy and Numeracy

    ERIC Educational Resources Information Center

    Pasnak, Robert; Kidd, Julie K.; Gadzichowski, Marinka K.; Gallington, Debbie A.; Saracina, Robin P.; Addison, Katherine T.

    2009-01-01

    A learning-set procedure was used to teach the oddity principle, insertions into series, and number conservation to 85 kindergarten children who did not grasp these abstractions. Control groups were given lessons in kindergarten literacy, numeracy, or art in sessions matched in timing and extent. The children who were taught the principles of…

  10. Bridging History of the Concept of Function with Learning of Mathematics: Students' Meta-Discursive Rules, Concept Formation and Historical Awareness

    ERIC Educational Resources Information Center

    Kjeldsen, Tinne Hoff; Petersen, Pernille Hviid

    2014-01-01

    In this paper we present a matrix-organised implementation of an experimental course in the history of the concept of a function. The course was implemented in a Danish high school. One of the aims was to bridge history of mathematics with the teaching and learning of mathematics. The course was designed using the theoretical frameworks of a…

  11. Learning the Rules of the Game: The Nature of Game and Classroom Supports When Using a Concept-Integrated Digital Physics Game in the Middle School Science Classroom

    ERIC Educational Resources Information Center

    Stewart, Phillip Michael, Jr.

    2013-01-01

    Games in science education is emerging as a popular topic of scholarly inquiry. The National Research Council recently published a report detailing a research agenda for games and science education entitled "Learning Science Through Computer Games and Simulations" (2011). The report recommends moving beyond typical proof-of-concept…

  12. From Abstract to Concrete Norms in Agent Institutions

    NASA Technical Reports Server (NTRS)

    Grossi, Davide; Dignum, Frank

    2004-01-01

    Norms specifying constraints over institutions are stated in such a form that allows them to regulate a wide range of situations over time without need for modification. To guarantee this stability, the formulation of norms need to abstract from a variety of concrete aspects, which are instead relevant for the actual operationalization of institutions. If agent institutions are to be built, which comply with a set of abstract requirements, how can those requirements be translated in more concrete constraints the impact of which can be described directly in the institution? In this work we make use of logical methods in order to provide a formal characterization of the translation rules that operate the connection between abstract and concrete norms. On the basis of this characterization, a comprehensive formalization of the notion of institution is also provided.

  13. Greenbook Abstract and Catalog--3.

    ERIC Educational Resources Information Center

    Coole, Walter A.

    This catalog is the third in a series extending and updating teaching materials previously disseminated through the ERIC system, including the "Greenbook System" of training materials for higher education professionals (ED 103 083 and 084), Open Classroom Documentation, a procedural manual for an autoinstructional learning laboratory at…

  14. Operating System Abstraction Layer (OSAL)

    NASA Technical Reports Server (NTRS)

    Yanchik, Nicholas J.

    2007-01-01

    This viewgraph presentation reviews the concept of the Operating System Abstraction Layer (OSAL) and its benefits. The OSAL is A small layer of software that allows programs to run on many different operating systems and hardware platforms It runs independent of the underlying OS & hardware and it is self-contained. The benefits of OSAL are that it removes dependencies from any one operating system, promotes portable, reusable flight software. It allows for Core Flight software (FSW) to be built for multiple processors and operating systems. The presentation discusses the functionality, the various OSAL releases, and describes the specifications.

  15. Learning the Rules of the Game: The Nature of Game and Classroom Supports When Using a Concept-Integrated Digital Physics Game in the Middle School Science Classroom

    NASA Astrophysics Data System (ADS)

    Stewart, Phillip Michael, Jr.

    Games in science education is emerging as a popular topic of scholarly inquiry. The National Research Council recently published a report detailing a research agenda for games and science education entitled Learning Science Through Computer Games and Simulations (2011). The report recommends moving beyond typical proof-of-concept studies into more exploratory and theoretically-based work to determine how best to integrate games into K-12 classrooms for learning , as well as how scaffolds from within the game and from outside the game (from peers and teachers) support the learning of applicable science. This study uses a mixed-methods, quasi-experimental design with an 8th grade class at an independent school in southern Connecticut to answer the following questions: 1. What is the nature of the supports for science content learning provided by the game, the peer, and the teacher, when the game is used in a classroom setting? 2. How do the learning gains in the peer support condition compare to the solo play condition, both qualitatively and quantitatively? The concept-integrated physics game SURGE (Scaffolding Understanding through Redesigning Games for Education) was selected for this study, as it was developed with an ear towards specific learning theories and prior work on student understandings of impulse, force, and vectors. Stimulated recall interviews and video observations served as the primary sources and major patterns emerged through the triangulation of data sources and qualitative analysis in the software QSR NVivo 9. The first pattern which emerged indicated that scaffolding from within the game and outside the game requires a pause in game action to be effective, unless that scaffolding is directly useful to the player in the moment of action. The second major pattern indicated that both amount and type of prior gaming experience has somewhat complex effects on both the uses of supports and learning outcomes. In general, a high correlation was found

  16. Abstraction of Seepage into Drifts

    SciTech Connect

    M.L. Wilson; C.K. Ho

    2000-09-26

    A total-system performance assessment (TSPA) for a potential nuclear-waste repository requires an estimate of the amount of water that might contact waste. This paper describes the model used for part of that estimation in a recent TSPA for the Yucca Mountain site. The discussion is limited to estimation of how much water might enter emplacement drifts; additional considerations related to flow within the drifts, and how much water might actually contact waste, are not addressed here. The unsaturated zone at Yucca Mountain is being considered for the potential repository, and a drift opening in unsaturated rock tends to act as a capillary barrier and divert much of the percolating water around it. For TSPA, the important questions regarding seepage are how many waste packages might be subjected to water flow and how much flow those packages might see. Because of heterogeneity of the rock and uncertainty about the future (how the climate will evolve, etc.), it is not possible to predict seepage amounts or locations with certainty. Thus, seepage is treated as a stochastic quantity in TSPA simulations, with the magnitude and spatial distribution of seepage sampled from uncertainty distributions. The distillation of the essential components of process modeling into a form suitable for use in TSPA simulations is referred to as abstraction. In the following sections, seepage process models and abstractions will be summarized and then some illustrative results are presented.

  17. Abstract art by shape classification.

    PubMed

    Song, Yi-Zhe; Pickup, David; Li, Chuan; Rosin, Paul; Hall, Peter

    2013-08-01

    This paper shows that classifying shapes is a tool useful in nonphotorealistic rendering (NPR) from photographs. Our classifier inputs regions from an image segmentation hierarchy and outputs the "best" fitting simple shape such as a circle, square, or triangle. Other approaches to NPR have recognized the benefits of segmentation, but none have classified the shape of segments. By doing so, we can create artwork of a more abstract nature, emulating the style of modern artists such as Matisse and other artists who favored shape simplification in their artwork. The classifier chooses the shape that "best" represents the region. Since the classifier is trained by a user, the "best shape" has a subjective quality that can over-ride measurements such as minimum error and more importantly captures user preferences. Once trained, the system is fully automatic, although simple user interaction is also possible to allow for differences in individual tastes. A gallery of results shows how this classifier contributes to NPR from images by producing abstract artwork.

  18. Discrimination theory of rule-governed behavior

    PubMed Central

    Cerutti, Daniel T.

    1989-01-01

    In rule-governed behavior, previously established elementary discriminations are combined in complex instructions and thus result in complex behavior. Discriminative combining and recombining of responses produce behavior with characteristics differing from those of behavior that is established through the effects of its direct consequences. For example, responding in instructed discrimination may be occasioned by discriminative stimuli that are temporally and situationally removed from the circumstances under which the discrimination is instructed. The present account illustrates properties of rule-governed behavior with examples from research in instructional control and imitation learning. Units of instructed behavior, circumstances controlling compliance with instructions, and rule-governed problem solving are considered. PMID:16812579

  19. Revisiting the syntactic abilities of non-human animals: natural vocalizations and artificial grammar learning.

    PubMed

    ten Cate, Carel; Okanoya, Kazuo

    2012-07-19

    The domain of syntax is seen as the core of the language faculty and as the most critical difference between animal vocalizations and language. We review evidence from spontaneously produced vocalizations as well as from perceptual experiments using artificial grammars to analyse animal syntactic abilities, i.e. abilities to produce and perceive patterns following abstract rules. Animal vocalizations consist of vocal units (elements) that are combined in a species-specific way to create higher order strings that in turn can be produced in different patterns. While these patterns differ between species, they have in common that they are no more complex than a probabilistic finite-state grammar. Experiments on the perception of artificial grammars confirm that animals can generalize and categorize vocal strings based on phonetic features. They also demonstrate that animals can learn about the co-occurrence of elements or learn simple 'rules' like attending to reduplications of units. However, these experiments do not provide strong evidence for an ability to detect abstract rules or rules beyond finite-state grammars. Nevertheless, considering the rather limited number of experiments and the difficulty to design experiments that unequivocally demonstrate more complex rule learning, the question of what animals are able to do remains open.

  20. Rule Breaking in the Child Care Centre: Tensions for Children and Teachers

    ERIC Educational Resources Information Center

    Brennan, Margaret

    2016-01-01

    Research suggests that young children transgress conventional rules in every culture and society. In this article, the argument is made that rule teaching and learning provide insight into how children learn to be part of a group. The research question addressed is, "Why do some children transgress the rules if their actions risk jeopardising…

  1. Does natural selection favour the Rescorla-Wagner rule?

    PubMed

    Trimmer, Pete C; McNamara, John M; Houston, Alasdair I; Marshall, James A R

    2012-06-07

    A fundamental question relating to animal behaviour is how animals learn; in particular, how they come to associate stimuli with rewards. Numerous empirical findings can be explained by assuming that animals use some mechanism similar to the Rescorla-Wagner learning rule, which is a relatively simple and highly general method of updating the associative strength between different stimuli. However, the Rescorla-Wagner rule is often not optimal, which raises the question of why a rule with such properties should have evolved. We consider the evolution of learning rules in a simple environment where there exists an optimal rule of similar complexity to the Rescorla-Wagner rule. We show that because the Rescorla-Wagner rule is less sensitive to changes in its parameters than the optimal rule, there is a wider range of parameter values over which the rule structure is initially viable. Consequently, the Rescorla-Wagner rule can be favoured by natural selection, ahead of other rules which are more accurate.

  2. A Proposed Multimedia Cone of Abstraction: Updating a Classic Instructional Design Theory

    ERIC Educational Resources Information Center

    Baukal, Charles E.; Ausburn, Floyd B.; Ausburn, Lynna J.

    2013-01-01

    Advanced multimedia techniques offer significant learning potential for students. Dale (1946, 1954, 1969) developed a Cone of Experience (CoE) which is a hierarchy of learning experiences ranging from direct participation to abstract symbolic expression. This paper updates the CoE for today's technology and learning context, specifically focused…

  3. Neural networks supporting switching, hypothesis testing, and rule application

    PubMed Central

    Liu, Zhiya; Braunlich, Kurt; Wehe, Hillary S.; Seger, Carol A.

    2015-01-01

    We identified dynamic changes in recruitment of neural connectivity networks across three phases of a flexible rule learning and set-shifting task similar to the Wisconsin Card Sort Task: switching, rule learning via hypothesis testing, and rule application. During fMRI scanning, subjects viewed pairs of stimuli that differed across four dimensions (letter, color, size, screen location), chose one stimulus, and received feedback. Subjects were informed that the correct choice was determined by a simple unidimensional rule, for example “choose the blue letter.” Once each rule had been learned and correctly applied for 4-7 trials, subjects were cued via either negative feedback or visual cues to switch to learning a new rule. Task performance was divided into three phases: Switching (first trial after receiving the switch cue), hypothesis testing (subsequent trials through the last error trial), and rule application (correct responding after the rule was learned). We used both univariate analysis to characterize activity occurring within specific regions of the brain, and a multivariate method, constrained principal component analysis for fMRI (fMRI-CPCA), to investigate how distributed regions coordinate to subserve different processes. As hypothesized, switching was subserved by a limbic network including the ventral striatum, thalamus, and parahippocampal gyrus, in conjunction with cortical salience network regions including the anterior cingulate and frontoinsular cortex. Activity in the ventral striatum was associated with switching regardless of how switching was cued; visually cued shifts were associated with additional visual cortical activity. After switching, as subjects moved into the hypothesis testing phase, a broad fronto-parietal-striatal network (associated with the cognitive control, dorsal attention, and salience networks) increased in activity. This network was sensitive to rule learning speed, with greater extended activity for the slowest

  4. Development of abstract mathematical reasoning: the case of algebra.

    PubMed

    Susac, Ana; Bubic, Andreja; Vrbanc, Andrija; Planinic, Maja

    2014-01-01

    Algebra typically represents the students' first encounter with abstract mathematical reasoning and it therefore causes significant difficulties for students who still reason concretely. The aim of the present study was to investigate the developmental trajectory of the students' ability to solve simple algebraic equations. 311 participants between the ages of 13 and 17 were given a computerized test of equation rearrangement. Equations consisted of an unknown and two other elements (numbers or letters), and the operations of multiplication/division. The obtained results showed that younger participants are less accurate and slower in solving equations with letters (symbols) than those with numbers. This difference disappeared for older participants (16-17 years), suggesting that they had reached an abstract reasoning level, at least for this simple task. A corresponding conclusion arises from the analysis of their strategies which suggests that younger participants mostly used concrete strategies such as inserting numbers, while older participants typically used more abstract, rule-based strategies. These results indicate that the development of algebraic thinking is a process which unfolds over a long period of time. In agreement with previous research, we can conclude that, on average, children at the age of 15-16 transition from using concrete to abstract strategies while solving the algebra problems addressed within the present study. A better understanding of the timing and speed of students' transition from concrete arithmetic reasoning to abstract algebraic reasoning might help in designing better curricula and teaching materials that would ease that transition.

  5. Development of abstract mathematical reasoning: the case of algebra

    PubMed Central

    Susac, Ana; Bubic, Andreja; Vrbanc, Andrija; Planinic, Maja

    2014-01-01

    Algebra typically represents the students’ first encounter with abstract mathematical reasoning and it therefore causes significant difficulties for students who still reason concretely. The aim of the present study was to investigate the developmental trajectory of the students’ ability to solve simple algebraic equations. 311 participants between the ages of 13 and 17 were given a computerized test of equation rearrangement. Equations consisted of an unknown and two other elements (numbers or letters), and the operations of multiplication/division. The obtained results showed that younger participants are less accurate and slower in solving equations with letters (symbols) than those with numbers. This difference disappeared for older participants (16–17 years), suggesting that they had reached an abstract reasoning level, at least for this simple task. A corresponding conclusion arises from the analysis of their strategies which suggests that younger participants mostly used concrete strategies such as inserting numbers, while older participants typically used more abstract, rule-based strategies. These results indicate that the development of algebraic thinking is a process which unfolds over a long period of time. In agreement with previous research, we can conclude that, on average, children at the age of 15–16 transition from using concrete to abstract strategies while solving the algebra problems addressed within the present study. A better understanding of the timing and speed of students’ transition from concrete arithmetic reasoning to abstract algebraic reasoning might help in designing better curricula and teaching materials that would ease that transition. PMID:25228874

  6. Phonological reduplication in sign language: Rules rule.

    PubMed

    Berent, Iris; Dupuis, Amanda; Brentari, Diane

    2014-01-01

    Productivity-the hallmark of linguistic competence-is typically attributed to algebraic rules that support broad generalizations. Past research on spoken language has documented such generalizations in both adults and infants. But whether algebraic rules form part of the linguistic competence of signers remains unknown. To address this question, here we gauge the generalization afforded by American Sign Language (ASL). As a case study, we examine reduplication (X→XX)-a rule that, inter alia, generates ASL nouns from verbs. If signers encode this rule, then they should freely extend it to novel syllables, including ones with features that are unattested in ASL. And since reduplicated disyllables are preferred in ASL, such a rule should favor novel reduplicated signs. Novel reduplicated signs should thus be preferred to nonreduplicative controls (in rating), and consequently, such stimuli should also be harder to classify as nonsigns (in the lexical decision task). The results of four experiments support this prediction. These findings suggest that the phonological knowledge of signers includes powerful algebraic rules. The convergence between these conclusions and previous evidence for phonological rules in spoken language suggests that the architecture of the phonological mind is partly amodal.

  7. Use of a geometric rule or absolute vectors: landmark use by Clark's nutcrackers (Nucifraga columbiana).

    PubMed

    Kelly, D M; Kippenbrock, S; Templeton, J; Kamil, A C

    2008-06-15

    Clark's nutcrackers (Nucifraga columbiana) were trained to search for a hidden goal located in the center of a four-landmark array. Upon completion of training, the nutcrackers were presented with tests that expanded the landmark array in the east-west direction, north-south direction and in both directions simultaneously. Although the birds learned to search accurately at the center of the landmark array during training, this search pattern did not transfer to the expansion tests. The nutcrackers searched at locations defined by absolute distance and/or direction relationships with landmarks in the training array. These results contrast with those from experiments with nutcrackers in which an abstract geometric rule was learned. This difference appears due to differences in the experimental paradigms used during training.

  8. 5-Second Rule

    MedlinePlus

    ... A Week of Healthy Breakfasts Shyness The 5-Second Rule KidsHealth > For Teens > The 5-Second Rule Print A A A Almost everyone has ... to eat it. Some people apply the "5-second rule" — that random saying about how food won' ...

  9. A Better Budget Rule

    ERIC Educational Resources Information Center

    Dothan, Michael; Thompson, Fred

    2009-01-01

    Debt limits, interest coverage ratios, one-off balanced budget requirements, pay-as-you-go rules, and tax and expenditure limits are among the most important fiscal rules for constraining intertemporal transfers. There is considerable evidence that the least costly and most effective of such rules are those that focus directly on the rate of…

  10. Two Rules for Communication

    ERIC Educational Resources Information Center

    Hamilton, Mark R.

    2005-01-01

    One of the most important and most difficult skills of academic leadership is communication. In this column, the author defines what he considers to be the two most important rules for communication. The first rule, which he terms the "Great American Rule," involves trusting that the person on the other end of the line or the fax or the e-mail is…

  11. Improving drivers' knowledge of road rules using digital games.

    PubMed

    Li, Qing; Tay, Richard

    2014-04-01

    Although a proficient knowledge of the road rules is important to safe driving, many drivers do not retain the knowledge acquired after they have obtained their licenses. Hence, more innovative and appealing methods are needed to improve drivers' knowledge of the road rules. This study examines the effect of game based learning on drivers' knowledge acquisition and retention. We find that playing an entertaining game that is designed to impart knowledge of the road rules not only improves players' knowledge but also helps them retain such knowledge. Hence, learning by gaming appears to be a promising learning approach for driver education.

  12. Rules on determining hearing appearances. Final rule.

    PubMed

    2013-05-21

    This final rule is another step in our continual efforts to handle workloads more effectively and efficiently. We are publishing final rules for portions of the rules we proposed in October 2007 that relate to persons, other than the claimant or any other party to the hearing, appearing by telephone. We are also clarifying that the administrative law judge (ALJ) will allow the claimant or any other party to a hearing to appear by telephone under certain circumstances when the claimant or other party requests to make his or her appearance in that manner. We expect that these final rules will make the hearings process more efficient and help us continue to reduce the hearings backlog. In addition, we made some minor editorial changes to our regulations that do not have any effect on the rights of claimants or any other parties.

  13. 1986 annual information meeting. Abstracts

    SciTech Connect

    Not Available

    1986-01-01

    Abstracts are presented for the following papers: Geohydrological Research at the Y-12 Plant (C.S. Haase); Ecological Impacts of Waste Disposal Operations in Bear Creek Valley Near the Y-12 Plant (J.M. Loar); Finite Element Simulation of Subsurface Contaminant Transport: Logistic Difficulties in Handling Large Field Problems (G.T. Yeh); Dynamic Compaction of a Radioactive Waste Burial Trench (B.P. Spalding); Comparative Evaluation of Potential Sites for a High-Level Radioactive Waste Repository (E.D. Smith); Changing Priorities in Environmental Assessment and Environmental Compliance (R.M. Reed); Ecology, Ecotoxicology, and Ecological Risk Assessment (L.W. Barnthouse); Theory and Practice in Uncertainty Analysis from Ten Years of Practice (R.H. Gardner); Modeling Landscape Effects of Forest Decline (V.H. Dale); Soil Nitrogen and the Global Carbon Cycle (W.M. Post); Maximizing Wood Energy Production in Short-Rotation Plantations: Effect of Initial Spacing and Rotation Length (L.L. Wright); and Ecological Communities and Processes in Woodland Streams Exhibit Both Direct and Indirect Effects of Acidification (J.W. Elwood).

  14. Ozone Conference II: Abstract Proceedings

    SciTech Connect

    1999-11-01

    Ozone Conference II: Pre- and Post-Harvest Applications Two Years After Gras, was held September 27-28, 1999 in Tulare, California. This conference, sponsored by EPRI's Agricultural Technology Alliance and Southern California Edison's AgTAC facility, was coordinated and organized by the on-site ATA-AgTAC Regional Center. Approximately 175 people attended the day-and-a-half conference at AgTAC. During the Conference twenty-two presentations were given on ozone food processing and agricultural applications. Included in the presentations were topics on: (1) Ozone fumigation; (2) Ozone generation techniques; (3) System and design applications; (4) Prewater treatment requirements; (5) Poultry water reuse; (6) Soil treatments with ozone gas; and (7) Post-harvest aqueous and gaseous ozone research results. A live videoconference between Tulare and Washington, D.C. was held to discuss the regulators' view from inside the beltway. Attendees participated in two Roundtable Question and Answer sessions and visited fifteen exhibits and demonstrations. The attendees included university and governmental researchers, regulators, consultants and industry experts, technology developers and providers, and corporate and individual end-users. This report is comprised of the Abstracts of each presentation, biographical sketches for each speaker and a registration/attendees list.

  15. SLAS Library Telescope Program (Abstract)

    NASA Astrophysics Data System (ADS)

    Small, J. S.

    2016-12-01

    (Abstract only) In the fall of 2014, I submitted to the members of the St. Louis Astronomical Society to take the $1,000 profit we had from a convention we had hosted and use it to purchase three telescopes to modify for a Library Telescope program that was invented by Mark Stowbridge and promoted by the New Hampshire Astronomical Society. I had met Mark at NEAF in 2012 when he was walking the floor demonstrating the telescope. We held meetings with three libraries, the St. Louis County Library system, the St. Louis Public Library system and an independent library in Kirkwood, Missouri. The response was overwhelming! SLCL responded with a request for ten telescopes and SLPL asked for five. We did our first build in October, 2014 and placed a total of eighteen telescopes. Since that time, SLAS has placed a total of eighty-eight telescopes in library systems around the St. Louis Metro area, expanding into neighboring counties and across the river in Illinois. In this talk, I will discuss how to approach this project and put it in place in your libraries!

  16. An abstract approach to music.

    SciTech Connect

    Kaper, H. G.; Tipei, S.

    1999-04-19

    In this article we have outlined a formal framework for an abstract approach to music and music composition. The model is formulated in terms of objects that have attributes, obey relationships, and are subject to certain well-defined operations. The motivation for this approach uses traditional terms and concepts of music theory, but the approach itself is formal and uses the language of mathematics. The universal object is an audio wave; partials, sounds, and compositions are special objects, which are placed in a hierarchical order based on time scales. The objects have both static and dynamic attributes. When we realize a composition, we assign values to each of its attributes: a (scalar) value to a static attribute, an envelope and a size to a dynamic attribute. A composition is then a trajectory in the space of aural events, and the complex audio wave is its formal representation. Sounds are fibers in the space of aural events, from which the composer weaves the trajectory of a composition. Each sound object in turn is made up of partials, which are the elementary building blocks of any music composition. The partials evolve on the fastest time scale in the hierarchy of partials, sounds, and compositions. The ideas outlined in this article are being implemented in a digital instrument for additive sound synthesis and in software for music composition. A demonstration of some preliminary results has been submitted by the authors for presentation at the conference.

  17. Handedness shapes children's abstract concepts.

    PubMed

    Casasanto, Daniel; Henetz, Tania

    2012-03-01

    Can children's handedness influence how they represent abstract concepts like kindness and intelligence? Here we show that from an early age, right-handers associate rightward space more strongly with positive ideas and leftward space with negative ideas, but the opposite is true for left-handers. In one experiment, children indicated where on a diagram a preferred toy and a dispreferred toy should go. Right-handers tended to assign the preferred toy to a box on the right and the dispreferred toy to a box on the left. Left-handers showed the opposite pattern. In a second experiment, children judged which of two cartoon animals looked smarter (or dumber) or nicer (or meaner). Right-handers attributed more positive qualities to animals on the right, but left-handers to animals on the left. These contrasting associations between space and valence cannot be explained by exposure to language or cultural conventions, which consistently link right with good. Rather, right- and left-handers implicitly associated positive valence more strongly with the side of space on which they can act more fluently with their dominant hands. Results support the body-specificity hypothesis (Casasanto, 2009), showing that children with different kinds of bodies think differently in corresponding ways.

  18. Mass Communication: Abstracts of Doctoral Dissertations Published in "Dissertation Abstracts International," January through June 1980 (Vol. 40 Nos. 7 through 12).

    ERIC Educational Resources Information Center

    ERIC Clearinghouse on Reading and Communication Skills, Urbana, IL.

    This collection of abstracts is part of a continuing series providing information on recent doctoral dissertations. The 55 titles deal with a variety of topics, including the following: (1) the prime time access rule; (2) media education; (3) magazine and children's advertising; (4) Irish national and Third World cinema; (5) international radio…

  19. Language Use, Language Ability, and Language Development: Abstracts of Doctoral Dissertations Published in "Dissertation Abstracts International," January through June 1982 (Vol. 42 Nos. 7 through 12).

    ERIC Educational Resources Information Center

    ERIC Clearinghouse on Reading and Communication Skills, Urbana, IL.

    This collection of abstracts is part of a continuing series providing information on recent doctoral dissertations. The 29 titles deal with a variety of topics, including the following: (1) aspects of the organization of redundancy rules in the lexicon; (2) the adult role in early child language acquisition; (3) semantic categorization,…

  20. Annotating user-defined abstractions for optimization

    SciTech Connect

    Quinlan, D; Schordan, M; Vuduc, R; Yi, Q

    2005-12-05

    This paper discusses the features of an annotation language that we believe to be essential for optimizing user-defined abstractions. These features should capture semantics of function, data, and object-oriented abstractions, express abstraction equivalence (e.g., a class represents an array abstraction), and permit extension of traditional compiler optimizations to user-defined abstractions. Our future work will include developing a comprehensive annotation language for describing the semantics of general object-oriented abstractions, as well as automatically verifying and inferring the annotated semantics.

  1. Abstraction and reformulation in artificial intelligence.

    PubMed Central

    Holte, Robert C.; Choueiry, Berthe Y.

    2003-01-01

    This paper contributes in two ways to the aims of this special issue on abstraction. The first is to show that there are compelling reasons motivating the use of abstraction in the purely computational realm of artificial intelligence. The second is to contribute to the overall discussion of the nature of abstraction by providing examples of the abstraction processes currently used in artificial intelligence. Although each type of abstraction is specific to a somewhat narrow context, it is hoped that collectively they illustrate the richness and variety of abstraction in its fullest sense. PMID:12903653

  2. Mean-field theory of meta-learning

    NASA Astrophysics Data System (ADS)

    Plewczynski, Dariusz

    2009-11-01

    We discuss here the mean-field theory for a cellular automata model of meta-learning. Meta-learning is the process of combining outcomes of individual learning procedures in order to determine the final decision with higher accuracy than any single learning method. Our method is constructed from an ensemble of interacting, learning agents that acquire and process incoming information using various types, or different versions, of machine learning algorithms. The abstract learning space, where all agents are located, is constructed here using a fully connected model that couples all agents with random strength values. The cellular automata network simulates the higher level integration of information acquired from the independent learning trials. The final classification of incoming input data is therefore defined as the stationary state of the meta-learning system using simple majority rule, yet the minority clusters that share the opposite classification outcome can be observed in the system. Therefore, the probability of selecting a proper class for a given input data, can be estimated even without the prior knowledge of its affiliation. The fuzzy logic can be easily introduced into the system, even if learning agents are built from simple binary classification machine learning algorithms by calculating the percentage of agreeing agents.

  3. From action to abstraction: Gesture as a mechanism of change

    PubMed Central

    Goldin-Meadow, Susan

    2015-01-01

    Piaget was a master at observing the routine behaviors children produce as they go from knowing less to knowing more about at a task, and making inferences not only about how the children understood the task at each point, but also about how they progressed from one point to the next. In this paper, I examine a routine behavior that Piaget overlooked—the spontaneous gestures speakers produce as they explain their solutions to a problem. These gestures are not mere hand waving. They reflect ideas that the speaker has about the problem, often ideas that are not found in that speaker’s talk. But gesture can do more than reflect ideas—it can also change them. In this sense, gesture behaves like any other action; both gesture and action on objects facilitate learning problems on which training was given. However, only gesture promotes transferring the knowledge gained to problems that require generalization. Gesture is, in fact, a special kind of action in that it represents the world rather than directly manipulating the world (gesture does not move objects around). The mechanisms by which gesture and action promote learning may therefore differ—gesture is able to highlight components of an action that promote abstract learning while leaving out details that could tie learning to a specific context. Because it is both an action and a representation, gesture can serve as a bridge between the two and thus be a powerful tool for learning abstract ideas. PMID:26692629

  4. From action to abstraction: Gesture as a mechanism of change.

    PubMed

    Goldin-Meadow, Susan

    2015-12-01

    Piaget was a master at observing the routine behaviors children produce as they go from knowing less to knowing more about at a task, and making inferences not only about how the children understood the task at each point, but also about how they progressed from one point to the next. In this paper, I examine a routine behavior that Piaget overlooked-the spontaneous gestures speakers produce as they explain their solutions to a problem. These gestures are not mere hand waving. They reflect ideas that the speaker has about the problem, often ideas that are not found in that speaker's talk. But gesture can do more than reflect ideas-it can also change them. In this sense, gesture behaves like any other action; both gesture and action on objects facilitate learning problems on which training was given. However, only gesture promotes transferring the knowledge gained to problems that require generalization. Gesture is, in fact, a special kind of action in that it represents the world rather than directly manipulating the world (gesture does not move objects around). The mechanisms by which gesture and action promote learning may therefore differ-gesture is able to highlight components of an action that promote abstract learning while leaving out details that could tie learning to a specific context. Because it is both an action and a representation, gesture can serve as a bridge between the two and thus be a powerful tool for learning abstract ideas.

  5. Core foundations of abstract geometry.

    PubMed

    Dillon, Moira R; Huang, Yi; Spelke, Elizabeth S

    2013-08-27

    Human adults from diverse cultures share intuitions about the points, lines, and figures of Euclidean geometry. Do children develop these intuitions by drawing on phylogenetically ancient and developmentally precocious geometric representations that guide their navigation and their analysis of object shape? In what way might these early-arising representations support later-developing Euclidean intuitions? To approach these questions, we investigated the relations among young children's use of geometry in tasks assessing: navigation; visual form analysis; and the interpretation of symbolic, purely geometric maps. Children's navigation depended on the distance and directional relations of the surface layout and predicted their use of a symbolic map with targets designated by surface distances. In contrast, children's analysis of visual forms depended on the size-invariant shape relations of objects and predicted their use of the same map but with targets designated by corner angles. Even though the two map tasks used identical instructions and map displays, children's performance on these tasks showed no evidence of integrated representations of distance and angle. Instead, young children flexibly recruited geometric representations of either navigable layouts or objects to interpret the same spatial symbols. These findings reveal a link between the early-arising geometric representations that humans share with diverse animals and the flexible geometric intuitions that give rise to human knowledge at its highest reaches. Although young children do not appear to integrate core geometric representations, children's use of the abstract geometry in spatial symbols such as maps may provide the earliest clues to the later construction of Euclidean geometry.

  6. Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule.

    PubMed

    Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin

    2015-11-01

    In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.

  7. Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule

    NASA Astrophysics Data System (ADS)

    Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin

    2015-11-01

    In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.

  8. Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule

    SciTech Connect

    Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin

    2015-11-15

    In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.

  9. The canonical forms of a lattice rule

    SciTech Connect

    Lyness, J.N.

    1992-12-31

    Much of the elementary theory of lattice rules may, be presented as an elegant application of classical results. These include Kronecker group representation theorem and the Hermite and Smith normal forms of integer matrices. The theory of the canonical form is a case in point. In this paper, some of this theory is treated in a constructive rather than abstract manner. A step-by-step approach that parallels the group theory is described, leading to an algorithm to obtain a canonical form of a rule of prime power order. The number of possible distinct canonical forms is derived, and this is used to determine the number of integration lattices having specified invariants.

  10. The canonical forms of a lattice rule

    SciTech Connect

    Lyness, J.N.

    1992-01-01

    Much of the elementary theory of lattice rules may, be presented as an elegant application of classical results. These include Kronecker group representation theorem and the Hermite and Smith normal forms of integer matrices. The theory of the canonical form is a case in point. In this paper, some of this theory is treated in a constructive rather than abstract manner. A step-by-step approach that parallels the group theory is described, leading to an algorithm to obtain a canonical form of a rule of prime power order. The number of possible distinct canonical forms is derived, and this is used to determine the number of integration lattices having specified invariants.

  11. Invented Rule with English Language Learners

    ERIC Educational Resources Information Center

    Boyer, Valerie E.; Martin, Kathryn Y.

    2012-01-01

    The purpose of this study was to utilize an invented rule with English language learners (ELLs) in a clinical setting to determine differences based on language and age of the children. The performance was correlated with teacher reports of strong and weak language learning. Using a within-participants design, ELLs of age three to five were taught…

  12. A Collaborative Educational Association Rule Mining Tool

    ERIC Educational Resources Information Center

    Garcia, Enrique; Romero, Cristobal; Ventura, Sebastian; de Castro, Carlos

    2011-01-01

    This paper describes a collaborative educational data mining tool based on association rule mining for the ongoing improvement of e-learning courses and allowing teachers with similar course profiles to share and score the discovered information. The mining tool is oriented to be used by non-expert instructors in data mining so its internal…

  13. Rules Urge New Style of Testing

    ERIC Educational Resources Information Center

    Gewertz, Catherine

    2010-01-01

    The author reports a federal competition that has opened for $350 million in federal money to design new ways of assessing what students learn. Rules for the contest make clear that the government wants to leave behind multiple-choice testing more often in favor of essays, multidisciplinary projects, and other more nuanced measures of achievement.…

  14. Another Look at the Rules of Differentiation

    ERIC Educational Resources Information Center

    Cupillari, Antonella

    2004-01-01

    It is an eye opening experience for students to find out that even a great mathematician like Leibniz made mistakes, forgot to check carefully his calculations, and was temporarily misled by user-friendly but incorrect formulas. From Leibniz's mishap with the derivation of the rules of differentiation students can learn the importance of spending…

  15. Indices To Measure Stability of Rule Application.

    ERIC Educational Resources Information Center

    Tatsuoka, Kikumi K.

    When learning is taking place, students test their hypotheses and evaluate them, and modify their current theories on the basis of new information. This phenomenon is known as "hypothesis testing view" or "theory changes." Many students change their rules to another while they are taking a test. This study introduced a new…

  16. Changing the Rules to Increase Discourse

    ERIC Educational Resources Information Center

    Brooks, Lisa A.; Dixon, Juli K.

    2013-01-01

    This article describes how one of the authors, second-grade teacher Lisa A. Brooks, challenged the raise-your-hand to-speak rule. Her desire to make this change was a result of experiences gained in a graduate class taught by the second author, Juli K. Dixon. Brooks had learned that it is possible to create a classroom community where students…

  17. When felids and hominins ruled at Olduvai Gorge: A machine learning analysis of the skeletal profiles of the non-anthropogenic Bed I sites

    NASA Astrophysics Data System (ADS)

    Arriaza, Mari Carmen; Domínguez-Rodrigo, Manuel

    2016-05-01

    In the past twenty years, skeletal part profiles, which are prone to equifinality, have not occupied a prominent role in the interpretation of early Pleistocene sites on Africa. Alternatively, taphonomic studies on bone surface modifications and bone breakage patterns, have provided heuristic interpretations of some of the best preserved archaeological record of this period; namely, the Olduvai Bed I sites. The most recent and comprehensive taphonomic study of these sites (Domínguez-Rodrigo et al., 2007a) showed that FLK Zinj was an anthropogenic assemblage in which hominins acquired carcasses via primary access. That study also showed that the other sites were palimpsests with minimal or no intervention by hominins. The FLK N, FLK NN and DK sequence seemed to be dominated by single-agent (mostly, felid) or multiple-agent (mostly, felid-hyenid) processes. The present study re-analyzes the Bed I sites focusing on skeletal part profiles. Machine learning methods, which incorporate complex algorithms, are powerful predictive and classification methods and have the potential to better extract information from skeletal part representation than past approaches. Here, multiple algorithms (via decision trees, neural networks, random forests and support vector machines) are combined to produce a solid interpretation of bone accumulation agency at the Olduvai Bed I sites. This new approach virtually coincides with previous taphonomic interpretations on a site by site basis and shows that felids were dominant accumulating agents over hyenas during Bed I times. The recent discovery of possibly a modern lion-accumulated assemblage at Olduvai Gorge (Arriaza et al., submitted) provides a very timely analog for this interpretation.

  18. Invented rule with English language learners.

    PubMed

    Boyer, Valerie E; Martin, Kathryn Y

    2012-07-01

    The purpose of this study was to utilize an invented rule with English language learners (ELLs) in a clinical setting to determine differences based on language and age of the children. The performance was correlated with teacher reports of strong and weak language learning. Using a within-participants design, ELLs of age three to five were taught to apply a nonsense morpheme to signal a semantic difference. The invented rule was taught and responses were elicited in both English and English with Spanish interpretation. No significant difference for language was identified. Effect sizes for age were large (English, eta = 0.389, and English + Spanish, eta = 0.430) with five-year-old participants more likely to apply the rule to novel stimuli regardless of language. The performance of the majority of the participants correlated with teacher reports. The invented rule may provide a mechanism for assessing processing independent of prior language knowledge.

  19. EDUCATIONAL MEDIA RESEARCH ABSTRACTING PROJECT. FINAL REPORT.

    ERIC Educational Resources Information Center

    HYER, ANNA L.

    THIS PROJECT PROVIDED ABSTRACTING COVERAGE OF 33 FINAL REPORTS OF U.S. OFFICE OF EDUCATION FINANCED RESEARCH PROJECTS IN EDUCATIONAL MEDIA. AN ABSTRACTOR, DR. WILLIAM ALLEN, WAS HIRED TO EVALUATE AND EDIT OR REWRITE ABSTRACTS SUBMITTED BY RESEARCHERS, AND TO PREPARE ABSTRACTS IF NECESSARY. TWO ANALYTICAL REVIEWS ON SELECTED AREAS OF MEDIA RESEARCH…

  20. Writing a Structured Abstract for the Thesis

    ERIC Educational Resources Information Center

    Hartley, James

    2010-01-01

    This article presents the author's suggestions on how to improve thesis abstracts. The author describes two books on writing abstracts: (1) "Creating Effective Conference Abstracts and Posters in Biomedicine: 500 tips for Success" (Fraser, Fuller & Hutber, 2009), a compendium of clear advice--a must book to have in one's hand as one prepares a…