Under the background of educational transformation in the 21st century, the promotion of deep learning has been paid more and more attention, among which high-quality teaching interaction is considered as the key to enhance students' deep learning. Smart classroom environment provides support for interactive teaching and deep learning. In this paper, a variety of technology-supported teaching interaction strategies are implemented in the smart classroom based on cloud. With the help of multimodal data analysis techniques, including data collection, correlation analysis, variance analysis, covariance analysis, regression analysis, etc., the interaction between teaching interaction and deep learning is discussed, and it is found that: (1) Different levels of teaching interaction have a significant impact on deep learning. The level of deep learning, curriculum knowledge and thinking in the high-level group of teaching interaction is significantly higher than that in the low-level group of teaching interaction; (2) The three deep cognitive processing behaviors of "application", "analysis" and "evaluation" have significant predictive power for deep learning. "Application" and "analysis" behaviors can significantly predict learners' deep learning level, while "application" and "evaluation" behaviors can significantly predict learners' curriculum knowledge level and thinking level.
Key words
multimodal data /
instructional interaction /
cognitive processing behavior /
deep learning
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