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Identifying Great Teachers Through Their Online Presence

机译:通过他们的在线表现识别伟大的教师

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Evaluating candidate teachers is a very tricky task, as there are a lot of criteria -objective and not-that are important for identifying a good teacher. The teacher's efficiency depends on the academic qualifications and experience, on teacher's personality, even the students of the class and how well teaching and learning dynamically 'grows'. In this work we propose a novel approach for teacher online evaluation. We implemented a prototype system which extracts values for a set of objective criteria from the teachers' LinkedIn profile, and infers personality characteristics using linguistic analysis on their Facebook and Twitter posts. Machine learning algorithms were used to solve the final ranking problem.
机译:评估候选人教师是一个非常棘手的任务,因为有很多标准 - 标准而不是 - 这对于识别好老师来说很重要。教师的效率取决于学术资格和经验,对教师的个性,甚至是班级的学生以及教学和学习如何动态地“生长”。在这项工作中,我们提出了一种新的教师在线评估方法。我们实现了一个原型系统,它从教师LinkedIn配置文件中提取了一组客观标准的值,并且在他们的Facebook和Twitter帖子上使用语言分析使用了Infers个性特征。机器学习算法用于解决最终排名问题。

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