基于深度学习的课堂交互行为数据搜索方法

Search method for classroom interaction behavior data based on deep learning

课堂交互行为数据具有复杂性和多样性,包括师生交互、生生交互以及人机交互等多种形式,这会导致搜索结果无法全面反映课堂交互行为的实际情况,为此文章研究了基于深度学习的搜索方法。该研究通过预处理确保数据的准确性,融合多源数据捕捉多样性,计算交互密度揭示课堂结构动态,提取核心关键词反映交互特征。试验显示该方法实现了高效数据搜索,其数据覆盖度高,能有效提取关键词相关交互数据,提升了课堂交互行为数据搜索的准确性和全面性。

Classroom interaction behavior data is complex and diverse,including teacher-student interaction,student interaction and human-computer interaction,this will lead to search results cannot fully reflect the actual situation of classroom interaction behavior.Therefore,this paper studies the search method based on deep learning.This study ensures the accuracy of the data through preprocessing,integrates multi-source data to capture the diversity,calculates the interaction density to reveal the dynamics of the classroom structure,and extracts the core keywords to reflect the interaction features.The experiment shows that this method realizes efficient data search,with high data coverage,can effectively extract keyword related interaction data,and improves the accuracy and comprehensiveness of classroom interaction behavior data search.