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Machine Learning for modelling and identification of Educational Robotics activities

机译：机器学习，用于建模和识别教育机器人活动

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Educational Robotics (ER) is a powerful tool to help students learn school subjects, robotics, and developing cognitive skills and soft skills. Assessing the learning outcomes of ER activities requires the identification of the model that underly the process. Machine learning can be useful to identify such models and to interpret data. This paper aims to present a system that could help integrating Educational Data Mining and Learning Analytics techniques into the open-ended learning environment that characterizes the constructionist approach of ER. Both supervised and unsupervised learning methods could be applied to extract meaningful information. Students’ approaches to learning as well as a prediction of their final performance could inform teachers’ decision and facilitate the implementation of effective ER activities in formal and non-formal education. First results show good premises for a future broader implementation, but more research is needed to face all the open issues.
机译：教育机器人（ER）是一个强大的工具，可以帮助学生学习学校学习学科，机器人和开发认知技能和软技能。评估ER活动的学习结果需要识别该过程的模型。机器学习可用于识别此类模型并解释数据。本文旨在提出一个系统，可以帮助将教育数据挖掘和学习分析技术集成到特征ER的建筑师方法的开放式学习环境中。可以应用监督和无监督的学习方法来提取有意义的信息。学生的学习方法以及预测最终表现可以为教师的决定提供信息，并促进在正式和非正规教育中实施有效的ER活动。第一个结果显示未来更广泛实施的良好场所，但需要更多的研究来面对所有开放问题。

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