Developing a domain theory defining and exemplifying a learning theory of progressive attainments

This article defines the concept of Domain Theory, or, when educational measurement is the goal, one might call it a "Learning Theory of Progressive Attainments in X Domain". The concept of Domain Theory is first shown to be rooted in validity theory, then the concept of domain theory is expanded to amplify its necessary but long neglected connection to design research disciplines. The development of a local learning theory of progressive attainments in the domain of Fluent Oral Reading is presented as an illustration. Such a theory is local to a defined domain of application, having well delineated boundaries. It depends on measures having a deep and valid connection to constructs, and the constructs back to the items or tasks at pertinent levels of the measurement scale. Thus instrument development and theory development, which occur in tandem, depend on establishing construct validity in a deep and thoroughgoing manner.     

The recovery of the density scale using a stochastic quasi-realization of additive conjoint measurement

This paper attempts to illuminate some of the practical limitations that the Rasch model (and by extension, Item Response Theory models) may have by focusing on the recovery of the density scale. Five simulation trials were conducted: the first four to recover the density scale with different deviations from the assumptions implicit in the use of the Rasch model and the fifth trial with an almost ideal data set. Results demonstrate that when error distributions are insufficient the results may be ordinal at best, and when error distributions are non-symmetrical, the positions of items may be biased with respect to the positions of persons. Results also confirm that errors of estimation, and test and sample information functions are sample dependent.     

Quantification of feature space changes with experience during electromyogram pattern recognition control

Pattern recognition of the electromyogram (EMG) has been demonstrated in the laboratory to be a successful alternative to conventional control methods for myoelectric prostheses. Pattern recognition control is dependent upon both machine and user learning; the user learns to generate distinct classes of muscle activity while the machine learns to interpret them. With experience, users may learn to generate distinct classes by reducing intraclass variability or by increasing interclass distance. The goal of this study was to identify which of these strategies best explained differences in EMG patterns between subjects with and without experience using pattern recognition control. We compared classification errors of novice nonamputee subjects with experienced nonamputee subjects. We found that after brief exposure to the control method, classification error in novices was reduced, although not to the level of experienced subjects. While the level of intraclass variability in novices was similar to that of the experienced subjects, they did not achieve the same level of interclass distance. These differences can be used to guide the development of much needed rehabilitation methods to train subjects to use pattern recognition devices. In particular we recommend training protocols that emphasize increasing the interclass distance.     

Management team learning orientation and business unit performance.

Although research has suggested that teams can differ in the extent to which they encourage proactive learning and competence development among their members (a team learning orientation), the performance consequences of these differences are not well understood. Drawing from research on goal orientation and team learning, this article suggests that, although a team learning orientation can encourage adaptive behaviors that lead to improved performance, it is also possible for teams to compromise performance in the near term by overemphasizing learning, particularly when they have been performing well. A test of this proposition in a sample of business unit management teams provides strong support. The results confirm that an appropriate emphasis on learning can have positive consequences for team effectiveness. (PsycINFO Database Record (c) 2010 APA, all rights reserved)