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Cluster and Sentiment Analyses of YouTube Textual Feedback of Programming Language Learners to Enhance Learning in Programming

  • Rex P. BringulaEmail author
  • John Noel Victorino
  • Marlene M. De Leon
  • Ma. Regina Estuar
Conference paper
  • 427 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1070)

Abstract

This study intends to determine the clusters and sentiments of feedback of YouTube users in learning to program in Python and C++. Toward this goal, a total of 2,583 feedback on introductory video tutorials about Python and C++ were collected. It is found that the words “thanks” and “thank” were the most frequently occurring word in both YouTube videos – indicating appreciation and helpfulness of the video tutorials. The results of k-means cluster analyses further disclosed that groups of feedback are similar across the two languages, i.e., confirmation, helpfulness, gratitude, and recommendation. YouTube users expressed positive sentiments towards the tutorial videos. Implications to teaching programming and YouTube video content development are presented. Limitations of the study are also offered.

Keywords

Learning Programming Sentiment analysis Videos YouTube 

Notes

Acknowledgment

The authors are indebted to the University of the East and Ateneo de Manila University for funding this study.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Rex P. Bringula
    • 1
    • 2
    Email author
  • John Noel Victorino
    • 2
  • Marlene M. De Leon
    • 2
  • Ma. Regina Estuar
    • 2
  1. 1.University of the EastManilaPhilippines
  2. 2.Ateneo de Manila UniversityManilaPhilippines

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