可视化编程环境下视频学习如何促进新手NLP问题解决

How to Use Video Learning to Improve Novices’ NLP Problem Solving in the Visual Programming Environment

本研究聚焦可视化编程环境下新手进行NLP问题解决的探索过程,对学习行为进行分析以揭示视频学习对NLP问题解决的支持作用。结果表明,视频学习平台中回看视频、自我报告等行为对新手问题解决具有明显的提示和纠错作用,学习者在可视化编程环境下的问题解决面临模块参数编辑、变量应用的主要困难。研究还发现了新手无目的地探索和反复尝试行为在学习中的有效性,如何转变学习观念,找到学习者自由探索与教学支持干预的平衡点,是面向“做中学”的人工智能教育中设计和搭建有效脚手架的关键。

This study examines how novices solve NLP problems in an online visual programming environment. Using learning analytics,it is possible to see how online video tutorials could assist novices in NLP problem-solving. Behaviors associated with video learning,like wise rewatching videos and reporting one’s own progress in an online forum, have a significant influence on finding inspiring solutions and rectifying mistakes. When learning visual programming, learner’s most challenging attempts are modifying parameters in blocks and manipulating variables. A key consideration in the development of educational scaffolds for artificial intelligence could be how much leeway learners are given for unrestricted exploration while yet providing them with adequate instructional support.