It’s not just what you know, it’s who you know: Testing a model of the relative importance of social networks to academic performance

Applying three mathematical modeling techniques, this study proposes and tests the fit of an academic performance model, and then estimates the relative importance of four performance predictors: academic ability, performance goal orientation, educational technology use, and social network density. Drawing on social network theory, findings from this study show that social network density is a statistically important and unique predictor of academic performance, suggesting that “who you know” matters in large classroom settings. However, this study also indicates that academic ability is the most dominant factor in the explanation of academic performance. Practical and theoretical implications for enhancing academic performance through social networks are discussed.

人工神经网络在临床应用中的伦理思考

现代临床医学中的海量信息具有非线性特质,人工神经网络的自我学习、记忆和归纳功能,刚好适应了医学的新发展,在医学领域有良好的应用前景。事实上,人工神经网络临床应用的理论研究成果丰富,但商业应用并不多见。本文探讨人工神经网络在临床应用中可能引发的社会伦理争议,对其临床适用范围进行初步的论述。     

Theorising Interventions as Events in Systems

Conventional thinking about preventive interventions focuses over simplistically on the “package” of activities and/or their educational messages. An alternative is to focus on the dynamic properties of the context into which the intervention is introduced. Schools, communities and worksites can be thought of as complex ecological systems. They can be theorised on three dimensions: (1) their constituent activity settings (e.g., clubs, festivals, assemblies, classrooms); (2) the social networks that connect the people and the settings; and (3) time. An intervention may then be seen as a critical event in the history of a system, leading to the evolution of new structures of interaction and new shared meanings. Interventions impact on evolving networks of person-time-place interaction, changing relationships, displacing existing activities and redistributing and transforming resources. This alternative view has significant implications for how interventions should be evaluated and how they could be made more effective. We explore this idea, drawing on social network analysis and complex systems theory.     

Social network composition and attitude strength: Exploring the dynamics within newly formed social networks

Recent evidence suggests that people who are embedded within attitudinally congruent social networks have stronger attitudes than those embedded in attitudinally diverse networks. The current research examines the causal processes responsible for this relation. Two studies capitalized on naturally occurring experiments whereby college students are quasi-randomly assigned to social contexts containing varying levels of attitudinal diversity. Replicating past research, individuals in attitudinally diverse social networks exhibited less resistance to attitude change and less attitude stability than those in more attitudinally congruent networks. Although there was evidence of attitude projection and selective network construction, neither of these processes could account for the relation between social network composition and attitude strength. These findings corroborate and extend previous results, reinforcing the notion that the social context in which people are embedded has important implications for the durability of their attitudes.     

Similarity and rules United: similarity- and rule-based processing in a single neural network

A central controversy in cognitive science concerns the roles of rules versus similarity. To gain some leverage on this problem, we propose that rule- versus similarity-based processes can be characterized as extremes in a multidimensional space that is composed of at least two dimensions: the number of features (Pothos, 2005) and the physical presence of features. The transition of similarity- to rule-based processing is conceptualized as a transition in this space. To illustrate this, we show how a neural network model uses input features (and in this sense produces similarity-based responses) when it has a low learning rate or in the early phases of training, but it switches to using self-generated, more abstract features (and in this sense produces rule-based responses) when it has a higher learning rate or is in the later phases of training. Relations with categorization and the psychology of learning are pointed out.     

Competitively Contingent Rewards and Intrinsic Motivation: Can Losers Remain Motivated?

We explored the effects on intrinsic motivation and ego-involved persistence of winning versus losing a competitively contingent reward and, for losers, the additional effects of receiving either positive performance feedback or performance-contingent rewards. Winners were more intrinsically motivated than losers. Losers given an explicit normative standard who received positive feedback for meeting the standard were more intrinsically motivated than losers who did not receive the additional standard and feedback. Losers who received a performance-contingent reward for reaching the same explicit standard displayed less intrinsic motivation behaviorally assessed than did losers who got positive feedback, but the two groups did not differ on self-reported enjoyment. Effects on enjoyment were mediated by perceived competence, but effects on free-choice behavior were not. People who lost the competition showed more ego-involved persistence than people who won or did not compete.     

Understanding Cognition Through Large-Scale Cortical Networks

An emerging body of evidence from a number of fields is beginning to reveal general neural principles underlying cognition. The characteristic adaptability of cognitive function is seen to derive from large-scale networks in the cerebral cortex that are able to repeatedly change the state of coordination among their constituent areas on a subsecond time scale. Experimental and theoretical studies suggest that large-scale network dynamics operate in a metastable regime in which the interdependence of cortical areas is balanced between integrating and segregating activities. Cortical areas, through their coordination dynamics, are thought to rapidly resolve a large number of mutually imposed constraints, leading to consistent local states and a globally coherent state of cognition.     

Connecting the Many Levels and Facets of Cognitive Aging

Basic cognitive mechanisms, such as the abilities to briefly maintain, focus, and process information, decline with age. Related fields of cognitive aging research have been advancing rapidly, but mostly independently, at the biological, information processing, and behavioral levels. To facilitate integration, this article reviews research on cognitive aging at the different levels, and describes a recent integrative theory postulating that aging-related deficiencies in neurotransmission cause increased noise in information processing and less distinctive cortical representation, which in turn lead to cognitive deficits. Aging-related attenuation of catecholaminergic modulation can be modeled by lowering a neural network parameter to reduce the signal-to-noise ratio of information processing. The performance of such models is consistent with benchmark phenomena observed in humans, ranging from age differences in learning rate, asymptotic performance, and interference susceptibility to intra- and interindividual variability and ability dedifferentiation. Although the details of the conjectured sequence of effects linking neuromodulation to cognitive aging deficits await further empirical validation, cross-level theorizing of the kind illustrated here could foster the coevolution of related fields through cross-level data synthesis and hypothesis testing.     

Instrumental Values – Strong and Weak

What does it mean that an object has instrumental value? While some writers seem to think it means that the object bears a value, and that instrumental value accordingly is a kind of value, other writers seem to think that the object is not a value bearer but is only what is conducive to something of value. Contrary to what is the general view among philosophers of value, I argue that if instrumental value is a kind of value, then it is a kind of extrinsic final value.     

La motivation et son ancrage utilitaire/désirable dans l’évaluation

Motivation has an important place among the personal characteristics that professional assessors take in account. A first study shows that different professionals do not choose the same criteria to assess motivation and also shows that normative factors affect their judgement. Then a series of studies focuses on the valorization of intrinsic motivation and on the anchoring in utility / desirability of this attribution of value. It appears that, compared with extrinsically motivated applicants, intrinsically motivated applicants are rather described by judges with desirable traits than with utility traits. This result is found as well with professionals and non professional respondents. So it seems that the valorization of intrinsic motivation would be more anchored in desirability than in utility, which is a difference with the norm of internality that is clearly anchored in utility.