Precise Evaluation of Foreign Language Learning in Intelligent Environment

The reform of intelligent teaching model based on artificial intelligence continues to deepen. The reform of teaching model and the application of advanced teaching approaches have greatly improved the efficiency of foreign language teaching, facilitating students to form self-learning awareness and habits. However, as the main subject of language learning, most test-based assessments can only evaluate the achievement of learning goals, and there is a lack of tracking to learning process, learning needs, emotional attitudes, and other factors, and the application of evaluation results is insufficient. This study explores a precise evaluation model for foreign language learning, by enriching the dimensions of foreign language teaching evaluation, establishing dynamic learning files, building a precise evaluation system, and formulating a foreign language learning behavior evaluation scale. It seeks to explore the pathways for serving precise foreign language teaching and meeting individualized learning needs.