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    基于画像技术的教师研修路径智能推荐研究

    Research on Intelligent Recommendation of Teacher Training Paths Based on Portrait Technology

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【作      者】:

胡小勇, 孙 硕, 穆 肃


【关 键 词 】:

教师画像; 教师专业发展; 多模态数据; 个性化研修; 智能推荐


【栏      目】:

学科建设与教师发展


【中文摘要】:

教师是教育的第一资源,研修是促进教师专业发展的重要方式。在大数据、数字画像等新技术赋能下,优化教师研修路径以提升教师发展质量变得尤为重要。文章构建了多模态数据和画像技术支持的教师研修路径智能推荐模型,包括数据伴随式采集分类与预处理、教师画像生成、研修路径算法三个模块,实现教师研修特征与优质研修资源的智能匹配。在教师研修路径动态优化方面,模型通过提供基于画像的个性化导研服务、基于知识图谱的资源关联推荐、基于群体智能的群体路径发现、基于目标导向的过程评价和基于研修行为的智能预警,满足教师的个性化研修需求,为发掘研修数据潜能、促进教师智能研修模式创新提供参考。


【英文摘要】:

Teachers are the primary resources of education, and training is an important way to promote teachers' professional development. Under the empowerment of new technologies such as big data and digital portraits, optimizing teacher training paths to improve the quality of teacher development has become particularly important. This paper constructs an intelligent recommendation model for teacher training paths supported by multimodal data and portrait technology, including three modules, namely, data accompanying collection, classification and preprocessing, teacher portraits generation, and training paths algorithm, so as to realize the intelligent matching of teacher training characteristics and high-quality training resources. In terms of dynamic optimization of teacher training paths, the model meets teachers' personalized training needs by providing personalized research guidance based on portraits, associated resource recommendation based on knowledge graphs, group path discovery based on group intelligence, process evaluations based on goal orientation and intelligent early-warning based on training behaviors, which provides reference for exploring the potential of training data and promoting the innovation of teachers' intelligent training model.

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