Cluster and Sentiment Analyses of YouTube Textual Feedback of Programming Language Learners to Enhance Learning in Programming
作者： Rex P. Bringula , John Noel Victorino , Marlene M. De Leon , Ma. Regina Estuar
DOI: 10.1007/978-3-030-32523-7_67
关键词: World Wide Web 、 Gratitude 、 Cluster (physics) 、 Sentiment analysis 、 Helpfulness 、 Content development 、 Computer science 、 Learning to program 、 Python (programming language)
摘要: This study intends to determine the clusters and sentiments of feedback YouTube users in learning program Python C++. Toward this goal, a total 2,583 on introductory video tutorials about C++ were collected. It is found that words “thanks” “thank” most frequently occurring word both videos – indicating appreciation helpfulness tutorials. The results k-means cluster analyses further disclosed groups are similar across two languages, i.e., confirmation, helpfulness, gratitude, recommendation. expressed positive towards tutorial videos. Implications teaching programming content development presented. Limitations also offered.
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