Muallif: Khodjieva Zumrad

Chop etilgan yil: 2026

Nashriyot: SamDCHTI

Chop etilgan shahar: Samarqand

Khodjieva Zumrad AI-based technologies in assessing English language skills// “Madaniyatlararo muloqotni rivojlantiruvchi omillar: yechimlar, ananalar va innovatsiyalar” mavzusidagi xalqaro ilmiy-amaliy anjumani materiallari. – Samarqand: SamDChTI, 2026. 59-61 B.

Assessment plays a crucial role in language learning as it measures learners’ progress, informs instruction, and supports decision-making in educational systems. Traditional assessment methods, such as paper-based tests and teacher-led evaluations, often face challenges related to subjectivity, time consumption, and limited feedback. With the advancement of artificial intelligence, new opportunities have emerged to improve the assessment of English language skills. AI-based technologies enable automated, data-driven, and personalized assessment processes, aligning with modern educational demands for efficiency, accuracy, and learner-centered approaches. In addition, AI is not only transforming how assessment is conducted but also how assessment tasks themselves are designed and generated. Automated Essay Scoring systems use natural language processing (NLP) and machine learning algorithms to evaluate written texts. Tools such as e-rater (ETS) analyze grammar, vocabulary, coherence, and organization. These systems provide instant feedback, ensure consistency in scoring, and reduce teacher workload, although they may have limitations in evaluating creativity and deeper meaning. AI-powered speech recognition technologies assess pronunciation, fluency, and intonation. Widely used in modern proficiency tests, these systems analyze spoken responses in real time and provide objective scoring aligned with proficiency levels such as those defined by CEFR. Computer Adaptive Testing (CAT) adjusts question difficulty based on learner responses. AI lgorithms estimate proficiency levels efficiently, offering personalized assessment experiences, reducing testing time, and increasing measurement precision. AI-based platforms provide continuous assessment through interaction, tracking learner performance, offering formative feedback, and adapting tasks to individual needs. This supports the concept of assessment as an ongoing learning process.