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Sentiment Analysis of Computer Science Students’ Attitudes Toward Programming Languages: An in-Depth Study

Authors: Isidro L. Duran; Imelda A. Duran;

Sentiment Analysis of Computer Science Students’ Attitudes Toward Programming Languages: An in-Depth Study

Abstract

This study investigates the sentiments of computer science students toward programming languages, focusing on Python, Java, and C, to explore factors influencing their learning experiences, motivation, and career aspirations. Data from forums, surveys, and social media platforms were analysed using sentiment analysis and thematic qualitative analysis. The findings reveal that students view programming as both challenging and rewarding. Python is valued for its role in data science, Java for enterprise solutions and Android development, and C for its foundational importance in programming. Students reported frustrations with syntax complexities, usability, and industry relevance despite these strengths. Despite these strengths, students reported frustrations with syntax complexities, usability, and industry relevance. The research highlights the need for adaptive teaching strategies that connect programming concepts to practical applications, foster resilience, and offer diverse learning opportunities. By bridging the gap between industrial expectations and academic preparation, these ideas hope to improve programming education and bring it into line with changing professional requirements.

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    1
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
gold