Research on Intelligent Evaluation of College English Teaching Effectiveness under Intelligent Big Data Technology

Abstract

Under the wave of digital transformation, intelligent big data technology deeply penetrates the entire process of higher education teaching, reconstructing the English teaching mode, teaching management logic, and teaching evaluation system in universities. The traditional evaluation of English teaching effectiveness in universities often relies on subjective manual scoring, one-dimensional assessment of final exam transcripts, and qualitative description of classroom performance. There are prominent problems such as one-sided evaluation dimensions, scattered data sources, lagging evaluation results, strong subjective interference, lack of dynamic tracking and accurate attribution, which are difficult to adapt to the development needs of personalized English teaching, hierarchical education, and precise quality improvement in universities in the new era. Intelligent big data technology, with its core advantages of massive data collection, multi-dimensional data mining, deep learning modeling, real-time dynamic analysis, and trend intelligent prediction, can comprehensively integrate the full scenario behavioral data of pre class preview, classroom teaching, post class consolidation, online learning, offline training, exam evaluation, and teacher-student interaction in college English teaching, and build a multi index, multi-level, and full cycle intelligent evaluation system for English teaching effectiveness.