Development of a Web-Based Aviation English Proficiency Test: Integrating Adaptive Algorithms and Dynamic Assessment for Enhanced Evaluation in Aviation Education

Aviation English proficiency is pivotal for aviation school students to ensure secure communication in global airspace per ICAO guidelines. Conventional methods are rigid, leading to inaccurate and time-consuming evaluations that hinder training efficacy. This research develops a web-based adaptive Aviation English proficiency test integrating adaptive algorithms like Item Response Theory and dynamic assessment to enhance aviation education outcomes. Using a mixed-methods framework with the ADDIE model and quantitative experimental approach, an explanatory sequential design with non-equivalent control group was employed, involving needs assessment, prototype development, validation, and implementation. The sample included 141 aviation school students. Data from pre/post-tests were analyzed via SPSS. The findings showed that i) the web-based test is valid and feasible as an assessment tool with a validation score of 89.5%; ii) student proficiency levels are significantly improved before and after using the adaptive system (paired t-test: mean rise from 72.6 to 91.4, t=-14.28, p=0.000 <0.05); iii) dynamic assessment positively impacts learning outcomes following implementation (32% uplift, ?=0.61, p<0.01); and iv) there is a significant difference between experimental and control groups in evaluation efficiency (independent t-test: 25% higher for experimental, t=10.52, p=0.000 <0.05). These affirm the test's efficacy, recommending broader adoption for refined aviation training.