学生如何学习编程?:研究理论与实践与学习分析

Proceedings of the 27th ACM Conference on on Innovation and Technology in Computer Science Education Vol. 2 Pub Date : 2022-07-07 DOI:10.1145/3502717.3532110

Julie M. Smith

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引用次数: 1

摘要

本论文将使用Blackbox数据集来探索哪些学生行为最有可能导致学习编程概念，从而产生一个学生学习模型，该模型将被分析以确定它支持哪些学习理论和模型。最后，探讨机器学习是否可以用于预测学生的学习。

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How Do Students Learn to Program?: Investigating Theory and Practice with Learning Analytics

This dissertation will use the Blackbox data set to explore which student behaviors are most likely to lead to learning a programming concept, resulting in a model of student learning which will be analyzed to determine which learning theories and models it supports. Finally, whether machine learning can be used to predict student learning will be explored.

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来源期刊

Proceedings of the 27th ACM Conference on on Innovation and Technology in Computer Science Education Vol. 2

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