TDNet Discover

The purpose of this quantitative secondary data analysis was to examine patterns of cooccurrence among low-scoring subdomains on the Educational Interpreter Performance Assessment (EIPA). Educational interpreters play a critical role in providing equitable access to instruction for d/Deaf and hard-of-hearing (DHH) students in K–12 settings, yet limited research has examined whether weaknesses across specific EIPA subdomains systematically co-occur among interpreters scoring below benchmark levels. Grounded in cognitive load theory and Gile’s Effort Model of Interpreting, the study analyzed aggregated EIPA performance data from 15 comprehensive score bands below the 4.0 benchmark using descriptive statistics, correlation structures, and frequency analyses. The analysis explored whether weaknesses across EIPA subdomains occurred independently or demonstrated patterned relationships across performance levels. Results indicated that weaknesses did not occur independently but instead clustered consistently across score bands. Three primary clusters emerged: (a) discourse management and global message comprehension, (b) sign-to-voice expressive precision, and (c) voice-to-sign morphosyntactic production. Subdomains such as discourse mapping, fingerspelling and numbers, non-manual behaviors, and verb directionality appeared repeatedly among the lowestperforming areas, supporting rejection of the null hypothesis. These findings suggest that cognitive load and simultaneous processing demands may depress related interpreting skills concurrently, contributing to patterned weaknesses among interpreters scoring below the benchmark level. The results offer implications for interpreter education, targeted skill development, and assessment practices. Future research should examine individual-level EIPA data and explore how interpreter preparation programs may address cognitive load during interpreter training