Kris S. Chesky, University of North Texas, University of Texas at Arlington

The following assertions have been made with regard to musical performance and talent:

These and other statements with a similar thrust were made more than fifty years ago (Seashore, 1938). The search for objective means of talent prediction and assessment preceded these comments and has continued to be both a topic of interest and controversy (e.g., Humphreys, 1993; Schmidt & Zdzinski, 1993). In more recent years, the related issues of health and injury in the performing arts have received increasing attention (e.g., Pascarelli and Bishop, 1994).

Neither practitioners nor researchers in various arenas relevant to music can be overheard saying, "What we need is a good, comprehensive systems performance theory ...". It is argued, however, that this could be part of the answer to general problems disguised in different forms that pertain to systems, tasks, their interface, and the concept of "performance"--and perhaps, in part, why Seashore's dreams are yet to be fulfilled. This paper summarizes the Elemental Resource Model (ERM) for human performance (e.g., Kondraske, 1987; 1995a), and measurement/assessment technology (e.g., Kondraske, 1990; 1995b; Vasta and Kondraske, 1994) for reducing this model to practice, and applications in the music field. Research efforts that motivated these items originated in the field of rehabilition. However, the approach and tools were intended to apply in any context in which "a human" and "a task" are present. At issue conceptually is a cause-and-effect, quantitative understanding of the interface of the human system to the task executed. Detailed treatments are beyond the present scope and readers are encouraged to consult the cited literature.

The concept of "performance" pervades nearly all aspects of life, especially decision-making processes that involve human and artificial systems. Yet, it is not well understood theoretically and techniques for its modeling and measurement in all fields have been ad hoc at best. Although a considerable body of material known as general systems theory exists, the concept of performance has not been incorporated in it nor has performance been addressed in a general sense elsewhere. Most knowledge that does exist about performance and its quantitative treatment has evolved within specific applications, where generalizations can easily be elusive. Performance is multi-faceted, pertaining to how well a given system executes an intended function and the various factors that contribute to this. It differs from "behavior" in that "the best of something" is implied.

General Systems Performance Theory (GSPT) was developed in response to these observations (e.g., Kondraske, 1987; 1995a). Its broad objectives are to: (a) provide a common conceptual basis for defining and measuring all aspects of any system's performance; (b) provide a common conceptual basis for the analysis of any task in a manner that facilitates system-task interface assessments and decision-making; and (c) identify cause-and-effect principles that explain what occurs when any given system is used to accomplish any given task. Some of the more striking features of GSPT include the consistent use of a resource construct to model all aspects of a system's performance (i.e., performance capacities) and the nonlinear, threshold effect associated with resource economic mathematics. In addition, no distinction is made as to whether a given performance resource is derived from a human or artificial system; both types can be incorporated into models and analyses.

The ERM (Figures 1 and 2) is derived by applying the concept of monadology and GSPT to the human system. Monadology dates back to 384 B.C. and is essentially the idea of using the combination of a finite set of "basic elements" to describe a great deal of complexity; vis a vis chemistry, alphabets, genetic building blocks, etc. The concept is thus well accepted as being vital to systematic human system descriptions from certain perspectives (e.g., chemical, genetic, etc.). Success with the previous use of monadology, whether intentional or unwitting (i.e., discovered to be at play after a given taxonomy has emerged), compels its serious a priori consideration in pursuits of solutions to other problems.

Figure 1. The ERM contains multiple hierarchical levels. Performance resources at the "basic element level" are finite in number, as dictated by finite sets of human subsystems and their respective dimensions of performance. At higher levels, new "systems" (collectively resulting in a near-infinite number of higher level elements) are readily created by reconfiguration of basic element level systems GSPT is applied in the same way at any level.

Looking Toward the Human The entire human (lower part of Figure 2) is modeled as a pool of elemental performance resources grouped into four different domains: (a) life sustaining, (b) environmental interface (containing sensory and sensorimotor subsystems), (c) central processing, and (d) information. Within the first three domains, physical subsystems referred to as functional units are identified (see horizontal aspect of grids) through application of fairly rigorous criteria. GSPT is applied to each, yielding a set of dimensions of performance. A single Basic Element of Performance (BEP) is defined by specifying: (a) the basic functional unit and (b) one of its dimensions of performance. The information domain is substantially different. Whereas the first three represent physical systems and their intangible performance resources, the information domain simply represents "information". Thus, memory functional units are located within the central processing domain, while the contents of memory (e.g., motor programs and associated reference information acquired through training or experience) are partitioned into the information domain. As illustrated, information is grouped but within each group there are many specific information sets. The overall approach permits even the most abstract items such as motivation and "gentleness" to be considered with the same framework as strength and speed.

Looking Toward the Task The mid-portion of Figure 2 suggests the representation of any given task in terms of the unique set of demands (RDij(t)) imposed on the pool of BEPs and information resources; that is, this is the elemental level of task representation. Shadings imply the representation of demands in terms of amount. The upper portion of the figure defines hierarchical mapping options (see also Figure 1).

Figure 2. Schematic diagram of the Elemental Resource Model (ERM) for human performance. Three hierarchical levels are shown: (a) basic element level, (b) generic intermediate level, and (c) high level. In the major portion of this figure, the basic element level is emphasized. Considering the human-task interface, success in a given task (which includes achievement of a given level of performance in a given type of task) requires that the inequality RA „ RD is satisfied for each BEP involved. In other words, the human system must have "enough" of each performance resource. The threshold nature of the mathematics that describes this interface is particularly noteworthy.

Our group has developed a diverse array of measurement instruments over the past 15 years to measure hundreds of difference performance capacities at different hierarchical levels of the ERM (Kondraske, 1990). These efforts actually preceded the ERM and were revised beginning in 1986 to conform with constructs of GSPT and the ERM. Most devices are third generation or later and have been studied and applied in many different field contexts (e.g., rehabilitation, sports, surgeon performance, to study aging, to determine side effects of new drugs, etc.). Technology transfer was achieved in 1988 and the latest generation of tools (microprocessor-based modules running in a PC environment under Microsoft Windows; Table 1) is commerically available (Human Performance Measurement, Inc.; P.O. Box 1996, Arlington, TX 76004-1996).

Additional measurement instruments are in various stages of development within the university environment, as efforts continue to provide the broadest possible coverage of performance capacities. However, a large effort has been directed in recent years to software tools to assist researchers and practitioners formulate prediction models and make assessments of performance capacities (e.g., Vasta and Kondraske, 1994).

The ERM offers a number of application flexibilities (e.g. "in whole" or "in part", "conceptually" or "rigorously", with "low tech" or sophisticated "high tech" tools, and to define performance measures or to develop predictive models). Refer to references for examples. It also provides the motivation to consider coordinated, collaborative developments that allows complex problems to be addressed rigorously and systematically. The ready availability of the technology required facilities research that is distributed across various sites, yet "standardized" in terms of terminology and metrics. In music, a wide range of issues can potentially benefit (Figure 3).

Figure 3. The Elemental Resource Model and tools for measurement and analysis of musician performance capacities at different hierarchical levels offer the potential to systematically address many different issues with a common approach.

The ERM is one, relatively young attempt at organizing and dealing with the complexity of some major aspects of human performance. There is no known alternative that attempts to accomplish the same goals. Is it good enough? For what purposes? Is a completely different approach or merely refinement required? The process of revision is central to the natural course of the history of ideas. Science has been concerned with "significant differences". Perhaps equal time is required to identify "significant similarites" across fields and/or problems to enhance commonality in approaches where warranted and increase the potential for long-term progress.