CiteULike: Tag instrumental

An "Instrumental Approach" to Study the Integration of a Computer Tool Into Mathematics Teaching: the Case of Spreadsheets

Mariam Haspekian — 2005-08-02T18:07:55-00:00

International Journal of Computers for Mathematical Learning, Vol. 10, No. 2. (January 2005), pp. 109-141.

Goal-directed instrumental action: contingency and incentive learning and their cortical substrates

Bernard Balleine — 2007-07-23T18:29:47-00:00

Neuropharmacology, Vol. 37, No. 4-5. (5 April 1998), pp. 407-419.

Instrumental behaviour is controlled by two systems: a stimulus-response habit mechanism and a goal-directed process that involves two forms of learning. The first is learning about the instrumental contingency between the response and reward, whereas the second consists of the acquisition of incentive value by the reward. Evidence for contingency learning comes from studies of reward devaluation and from demonstrations that instrumental performance is sensitive not only the probability of contiguous reward but also to the probability of unpaired rewards. The process of incentive learning is evident in the acquisition of control over performance by primary motivational states. Preliminary lesion studies of the rat suggest that the prelimibic area of prefrontal cortex plays a role in the contingency learning, whereas the incentive learning for food rewards involves the insular cortex.

The Predictors of Achievement and Dropout in Instrumental Tuition

Susan Hallam — 2008-07-28T19:22:32-00:00

Psychology of Music, Vol. 26, No. 2. (1 October 1998), pp. 116-132.

This study, using Carroll's (1963) model of learning as a framework, considers the relative importance of time spent practising in determining learning outcomes in instrumental tuition. Carroll's model states that degree of learning is a function of time spent learning, divided by time required for learning. One hundred and nine violin and viola pupils aged 6-16 years took part in the study. Multiple regression revealed that length of time learning (beta weight .78) and ability to understand instructions (.23) were the best predictors of level of achievement (R = .88), while the quality of achievement was best predicted by the teachers' rating of musical ability (5). Dropping out was best predicted by a range of ability and attitudinal measures. The findings are discussed in relation to the ways in which the quantity and quality of attainment may be determined by different presage and process factors and the importance of developing explanatory multivariate models in the field of instrumental tuition. 10.1177/0305735698262002

Self-regulating Learning Strategies in Instrumental Music Practice

Siw Nielsen — 2008-07-28T19:35:32-00:00

Music Education Research, Vol. 3, No. 2. (2001), pp. 155-167.

This paper reports on how two advanced conservatoire students self-regulated their use of learning strategies within practice sessions. The study capitalised on a naturally occurring activity, and the students were asked to give verbal reports both during and immediately after practice sessions as they prepared a complex piece for performance. The sessions were also videotaped. The findings indicated the students to have extensive self-regulatory skill that enabled them to optimise their learning and performances taking into account interpersonal, contextual and intrapersonal conditions. They sat specific goals, engaged in strategic planning, used self-instruction, task strategies and monitored themselves selectively at a detailed level. In addition, they evaluated themselves adopting criteria that they revised. The implication is that these advanced students demonstrated skilful self-regulatory learning. The complexity and the diversity of the cyclic self-regulation of learning strategies that these students engaged in during practice are demonstrated in a preliminary model .

The misbehavior of value and the discipline of the will.

P Dayan — 2007-11-16T14:12:57-00:00

Neural Netw, Vol. 19, No. 8. (October 2006), pp. 1153-1160.

Most reinforcement learning models of animal conditioning operate under the convenient, though fictive, assumption that Pavlovian conditioning concerns prediction learning whereas instrumental conditioning concerns action learning. However, it is only through Pavlovian responses that Pavlovian prediction learning is evident, and these responses can act against the instrumental interests of the subjects. This can be seen in both experimental and natural circumstances. In this paper we study the consequences of importing this competition into a reinforcement learning context, and demonstrate the resulting effects in an omission schedule and a maze navigation task. The misbehavior created by Pavlovian values can be quite debilitating; we discuss how it may be disciplined.

Reward, motivation, and reinforcement learning.

P Dayan — 2006-03-10T14:10:15-00:00

Neuron, Vol. 36, No. 2. (10 October 2002), pp. 285-298.

There is substantial evidence that dopamine is involved in reward learning and appetitive conditioning. However, the major reinforcement learning-based theoretical models of classical conditioning (crudely, prediction learning) are actually based on rules designed to explain instrumental conditioning (action learning). Extensive anatomical, pharmacological, and psychological data, particularly concerning the impact of motivational manipulations, show that these models are unreasonable. We review the data and consider the involvement of a rich collection of different neural systems in various aspects of these forms of conditioning. Dopamine plays a pivotal, but complicated, role.

Neuronal Transcriptome of Aplysia: Neuronal Compartments and Circuitry

Leonid Moroz — 2007-01-03T10:18:42-00:00

Cell, Vol. 127, No. 7. (29 December 2006), pp. 1453-1467.

SummaryMolecular analyses of Aplysia, a well-established model organism for cellular and systems neural science, have been seriously handicapped by a lack of adequate genomic information. By sequencing cDNA libraries from the central nervous system (CNS), we have identified over 175,000 expressed sequence tags (ESTs), of which 19,814 are unique neuronal gene products and represent 50%-70% of the total Aplysia neuronal transcriptome. We have characterized the transcriptome at three levels: (1) the central nervous system, (2) the elementary components of a simple behavior: the gill-withdrawal reflex--by analyzing sensory, motor, and serotonergic modulatory neurons, and (3) processes of individual neurons. In addition to increasing the amount of available gene sequences of Aplysia by two orders of magnitude, this collection represents the largest database available for any member of the Lophotrochozoa and therefore provides additional insights into evolutionary strategies used by this highly successful diversified lineage, one of the three proposed superclades of bilateral animals.

Inducing motor skill improvements with a declarative task

Rachel Brown — 2007-01-27T11:53:32-00:00

Nature Neuroscience, Vol. 10, No. 2. (21 January 2007), pp. 148-149.

Regulation of firing of dopaminergic neurons and control of goal-directed behaviors

Anthony Grace — 2007-04-04T14:05:09-00:00

Trends in Neurosciences, Vol. In Press, Corrected Proof

There are several brain regions that have been implicated in the control of motivated behavior and whose disruption leads to the pathophysiology observed in major psychiatric disorders. These systems include the ventral hippocampus, which is involved in context and focus on tasks, the amygdala, which mediates emotional behavior, and the prefrontal cortex, which modulates activity throughout the limbic system to enable behavioral flexibility. Each of these systems has overlapping projections to the nucleus accumbens, where these inputs are integrated under the modulatory influence of dopamine. Here, we provide a systems-oriented approach to interpreting the function of the dopamine system, its modulation of limbic-cortical interactions and how disruptions within this system might underlie the pathophysiology of schizophrenia and drug abuse.