Surprise and change: Variations in the strength of present and absent cues in causal learning

It is said that “absence makes the heart grow fonder.” But, when and why does an absent event become salient to the heart or to the brain? An absent event may become salient when its nonoccurrence is surprising. Van Hamme and Wasserman (1994) found that a nonpresented but expected stimulus can actually change its associative status—and in the opposite direction from a presented stimulus. Associative models like that of Rescorla and Wagner (1972) focus only on presented cues; so, they cannot explain this result. However, absent cues can be permitted to change their value by assigning different learning parameters to present and absent cues. Van Hamme and Wasserman revised the Rescorla-Wagner model so that the α parameter is positive for present cues, but negative for absent cues; now, changes in the associative strength of absent cues move in the opposite direction as presented ones. This revised Rescorla-Wagner model can thus explain such otherwise vexing empirical findings as backward blocking, recovery from overshadowing, and backward conditioned inhibition. Moreover, the revised model predicts new effects. For example, explicit information about the absence of nonpresented cues should increase their salience (that is, their negative α value should be larger), leading to stronger associative changes than when no explicit mention is made of cue absence. Support for this prediction is detailed in a new causal judgment experiment in which participants rated the effectiveness of different foods’ triggering a patient’s allergic reaction. Overall, these and other findings encourage us to view human causal learning from an associative perspective.     

Response rate is not an effective mediator of learned stimulus equivalence in pigeons

We explored response rate as a possible mediator of learned stimulus equivalence. Five pigeons were trained to discriminate four clip art pictures presented during a 10-sec discrete-trial fixed interval (FI) schedule: two paired with a one-pellet reinforcer, which supported a low rate of responding, and two paired with a nine-pellet reinforcer, which supported a high rate of responding. After subjects associated one stimulus from each of these pairs with a discriminative choice response, researchers presented two new clip art stimuli during a 10-sec FI: one trained with a differential reinforcement of low rate schedule (DRL) after the FI and the other trained with a differential reinforcement of high rate schedule (DRH) after the FI. Each of the stimuli that were withheld during choice training was later shown to see if the choice responses would transfer to these stimuli. The results suggest that response rate alone does not mediate learned stimulus equivalence.     

The Long Decay Model of One-Dimensional Projectile Motion

This article introduces a research study on student model formation and development in introductory mechanics. As a point of entry, I present a detailed analysis of the Long Decay Model of one-dimensional projectile motion. This model has been articulated by Galileo (in De Motu) and by contemporary students. Implications for instruction are discussed.

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Auswertung von elektromyographischen Signalen zur Steuerung von Exoskeletten

Zusammenfassung  Diese Arbeit stellt ein Modell und ein System zur Steuerung von Exoskeletten mit Hilfe von elektrischen Signalen vor, die an den Muskeln des Benutzers gemessen werden. Anhand dieser Signale wird der eigene Drehmomentbeitrag des Benutzer zur gewünschten Bewegung abgesch?tzt, und ein einstellbarer Faktor bestimmt das vom Exoskelett hinzugefügte Drehmoment in Bezug auf den Beitrag des Benutzers. Die Signale werden durch ein komplexes biomechanisches Modell ausgewertet. CR subject classification  J.3 ; J.7 ; I.6.5     

Retrieving and classifying instances of source code plagiarism

Automatic detection of source code plagiarism is an important research field for both the commercial software industry and within the research community. Existing methods of plagiarism detection primarily involve exhaustive pairwise document comparison, which does not scale well for large software collections. To achieve scalability, we approach the problem from an information retrieval (IR) perspective. We retrieve a ranked list of candidate documents in response to a pseudo-query representation constructed from each source code document in the collection. The challenge in source code document retrieval is that the standard bag-of-words (BoW) representation model for such documents is likely to result in many false positives being retrieved, because of the use of identical programming language specific constructs and keywords. To address this problem, we make use of an abstract syntax tree (AST) representation of the source code documents. While the IR approach is efficient, it is essentially unsupervised in nature. To further improve its effectiveness, we apply a supervised classifier (pre-trained with features extracted from sample plagiarized source code pairs) on the top ranked retrieved documents. We report experiments on the SOCO-2014 dataset comprising 12K Java source files with almost 1M lines of code. Our experiments confirm that the AST based approach produces significantly better retrieval effectiveness than a standard BoW representation, i.e., the AST based approach is able to identify a higher number of plagiarized source code documents at top ranks in response to a query source code document. The supervised classifier, trained on features extracted from sample plagiarized source code pairs, is shown to effectively filter and thus further improve the ranked list of retrieved candidate plagiarized documents.     

The effect of network size on intra-network knowledge processes

This paper addresses a neglected topic in the knowledge management literature: how the size of a network of actors affects the nature of intra-network social relations and knowledge processes. It makes a theoretical contribution to developing understanding in this area drawing on a range of literatures including practice-based perspectives on knowledge, the literature on the embeddedness of social relations, and relevant knowledge management literature. The central focus of this paper is on the relationship between network size, network density, and how these variables affect intra-network knowledge processes. It suggests that as network size increases network density is likely to decrease (as it becomes problematic for the actors in such networks to retain strong ties with a significant proportion of the network's members), which it will be suggested has significant ramifications for intra-network knowledge processes. This paper concludes by reflecting on the implications of the ideas developed for network-based forms of organizing, and innovation processes.     

Contents Volume 7 2001

Volume Contents

Contents Volume 7 2001     

Community College Counseling: Why Are Research Outcomes So Elusive?

This article focuses on counseling research in the community college context. The article suggests the need for a robust community college knowledge base, describes some limitations of the current community college literature, and suggests a framework for more effective work in this area. The authors’ own experiences and selected examples of published studies are used as illustrations of the hurdles encountered and solutions available when examining counseling theories, practices, and outcomes in 2‐year settings.