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HomeLanguagesSpanishAutomated Scoring for AAPPL Spanish PW

Automated Scoring for AAPPL Spanish PW

ACTFL and LTI introduce groundbreaking system for presentational writing component AAPPL

In September 2023, ACTFL and Language Testing International (LTI) launched an automated scoring system for the ACTFL Assessment of Performance toward Proficiency in Languages (AAPPL) Spanish presentational writing (PW) component.

The AAPPL PW component evaluates the spontaneous writing abilities of learners in grades 5–12, without access to revisions or editing tools. It serves as a crucial measurement of written language performance, guiding goal setting, curriculum development, and instruction. The automated scoring system, also known as machine scoring, has been implemented for Spanish PW tests in conjunction with human raters. This integration of machine scoring alongside human raters means that all Spanish PW tests will receive a machine score combined with those provided by certified human raters to produce a final score.

In addition, the rating process will be more streamlined by identifying tests that require additional human ratings. The machine scoring system assesses the AAPPL PW responses based on several parameters, as described in the ACTFL Performance Descriptors, including functions, context/content, text type, and comprehensibility. LTI’s machine scoring system has undergone rigorous training using rating data from ACTFL-certified AAPPL raters.

Extensive research, conducted by Dr. Erik Voss of Teachers College, Columbia University, has validated the accuracy of machine scoring compared to human raters over multiple years of administration. This innovation represents the culmination of nearly ten years of dedicated research and development and is a significant advancement in language-assessment rating systems that will enhance the accuracy and efficiency of the AAPPL evaluation process.

ACTFL and LTI remain committed to maintaining currency and relevance in language testing and contributing to the advancement of research in non-English second-language machine scoring procedures.

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