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

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.

[1]  Elsje Scott,et al.  The Fear Factor: How It Affects Students Learning to Program in a Tertiary Environment , 2010 .

[2]  Tapio Salakoski,et al.  What about a simple language? Analyzing the difficulties in learning to program , 2006, Comput. Sci. Educ..

[3]  Janet Rountree,et al.  Learning and Teaching Programming: A Review and Discussion , 2003, Comput. Sci. Educ..

[4]  Roy D. Pea,et al.  Comparing Simple and Advanced Video Tools as Supports for Complex Collaborative Design Processes , 2010 .

[5]  David Perkins,et al.  Fragile knowledge and neglected strategies in novice programmers , 1985 .

[6]  Raja Maznah Raja Hussain,et al.  Empowering learners as the owners of feedback while YouTube-ing , 2009, Interact. Technol. Smart Educ..

[7]  Mark Pendergast,et al.  Teaching Introductory Programming to IS Students: Java Problems and Pitfalls , 2006, J. Inf. Technol. Educ..

[8]  Paul Roe,et al.  Learning to Program: Going Pair-Shaped , 2007 .

[9]  G. Kocabay,et al.  Learning electrocardiogram on YouTube: how useful is it? , 2014, Journal of electrocardiology.

[10]  Rex Perez Bringula,et al.  "Why computing students are not using e-resources?": Evidence from the University of the East , 2014, WCCCE.

[11]  D. Lahner,et al.  Medical information on the Internet: Quality assessment of lumbar puncture and neuroaxial block techniques on YouTube , 2012, Clinical Neurology and Neurosurgery.

[12]  Rex Perez Bringula,et al.  Push and Pull of Institutional Image Indicators and Computing Degree Programs Viewed Through the Lens of Shifters and Transferee , 2016 .

[13]  Dorothy DeWitt,et al.  The Potential of Youtube for Teaching and Learning in the Performing Arts , 2013 .

[14]  Ainin Sulaiman,et al.  Social media as a complementary learning tool for teaching and learning: The case of youtube , 2018 .

[15]  Mark R. Lehto,et al.  User acceptance of YouTube for procedural learning: An extension of the Technology Acceptance Model , 2013, Comput. Educ..

[16]  Rex Perez Bringula,et al.  Influence of usage of e-books, online educational materials, and other programming books and students' profiles on adoption of printed programming textbooks , 2017, Program.

[17]  Martin C. Carlisle,et al.  Using You Tube to enhance student class preparation in an introductory Java course , 2010, SIGCSE.

[18]  V. S. Wong,et al.  The presentation of seizures and epilepsy in YouTube videos , 2013, Epilepsy & Behavior.