Although supported or competitive community employment has become a near universal expectation for public education, it continues to be an elusive goal for many individuals with disabilities (Brady & Rosenberg, 2002a; Rogan, Callahan, Griffin, & Hammis, 2007). After completing years of training and preparation, many students with disabilities exit school programs only to become unemployed or under-employed as adults, or are only able to gain access to sheltered employment or "work experience" programs (Hurlbutt & Chalmers, 2004; Mank, Cioffi, & Yovanoff, 1998; McDermott, Martin, & Butkus, 1999; Murphy, Rogan, Handley, Kincaid, & Royce-Davis, 2002).
For community employment to become a reliable post-school outcome, many individuals with disabilities require explicit, meaningful employment and transition planning. Employment preparation must target improvement of work performance in future employees, as well as the design and delivery of work supports (Brady & Rosenberg, 2002a; Rogan, Banks, & Howard, 2000. In addition, employment assessment systems need to target these two separate, but related dimensions. Where most employment evaluations certainly assess employees' work performance, few assess employees' performance given the types and levels of support provided (Brady, Rosenberg, & Frain, 2008).
In addition to including these two employment dimensions (performance and support needs), transition and employment evaluations also need to consider the data sources for the assessments. In school programs, external sources of data include the perceptions of teachers and job coaches; the perceptions of students themselves are another data source. In supported community employment, data sources include the perceptions of work supervisors and the employees. Data from the external sources (teachers, job coaches, work supervisors) are frequently used to make employment decisions about hiring, promotions, raises, and retention (Hamilton & Shumate, 2005). In contrast, many job planning and placement decisions gain validity only when students or adult employees themselves provide a self-determined voice (Brady et al., 2008; Wehman, 2006). For example, interventions such as self-monitoring and covert coaching promote job skills, placement selections, or changes in support and are highly dependent on the perceptions and willingness to participate of the people targeted for these interventions (Martin et al., 2003; Menchetti & Garcia, 2003; Olney & Salomone, 1992; Rogan et al., 2000).
To provide relevant and successful employment and transition plans for individuals with disabilities, assessments should include four dimensions. The first dimension includes students' and adult employees' work productivity (i.e., whether or not these individuals' productivity matches the productivity of others without disabilities). In practice, this dimension typically is assessed by reviewing employer and supervisor evaluations (Hamilton & Shumate, 2005. The second dimension includes assessments for supported employment that incorporate input on the type and level of support needed to establish any particular level of performance (Rogan et al., 2000). The third dimension of an employment assessment includes the teacher's or supervisor's perception of the person's performance and support needs supervisors' perceptions are critical to the day-to-day operation of the enterprise. Finally, the fourth dimension of an employment assessment that promotes learning and performance must include the individual's self-determined perspectives of one's own performance and support needs (Agran & Hughes, 2008; Brady et al., 2008).
Employment assessments that incorporate these four dimensions provide valuable data for transition and employment plans because decisions are made on potential job roles, work placements, performance interventions, and models of employment support. Data collected on these dimensions could reveal, for example, that a student's work performance on an assembly task is not sufficient to enter most community employment settings, but that restructuring a complex job into a series of simple tasks would improve that performance. …