Identifying Great Teachers Through Their Online Presence
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.
KeywordsE-recruitment systems Personality mining Personality traits Social web mining Recommendation systems Teacher evaluation
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