Language Test

Language testing research focuses on developing accurate and equitable assessments of language proficiency, encompassing various modalities like speaking, writing, and reading comprehension. Current efforts concentrate on leveraging AI, particularly deep learning models such as BERT and wav2vec 2.0, to automate scoring and improve efficiency while mitigating biases and ensuring fairness. This research is crucial for enhancing the validity and reliability of language assessments across diverse populations and contexts, impacting fields like education, immigration, and professional certification.