
The Rater Performance Categorization System (RPCS) for Intensive English Programs
Author(s) -
Alper Şahin
Publication year - 2021
Publication title -
shanlax international journal of education (online)
Language(s) - English
Resource type - Journals
ISSN - 2582-1334
DOI - 10.34293/education.v9i3.3986
Subject(s) - categorization , computer science , sample (material) , psychology , artificial intelligence , chromatography , chemistry
There are several student performance are assessed in Intensive English Programs (IEP) worldwide in each academic year. These student performances are mostly graded by human raters with a certain degree of error. However, the accuracy of these performance assessment is of utmost importance because they feed data into some high stakes decisions about the students and such performance assessments constitute a large number of students’ scores. Therefore, the accuracy of these performance assessments should be given priority by the IEPs. However, when the current rater performance monitors systems which can help the administrators of IEPs to monitor rater performance in performance assessment are away from practicality because they require the use of complex mathematical models and specialized software. A practical and easy to maintain rater performance categorization system is proposed in this paper and it was accompanied by a sample study Its benefits to the administrators of IEPs and their raters are also discussed besides its practical considerations.