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Difficulties in Learning and Teaching Programming at Lower Secondary Level in Mauritius

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  • Vinod Sharma Bhaugeerutty

Abstract

The rapid evolution of technology around the world has created a rapid growth and efficient learning environments. In Mauritius, for example, the government is investing huge amount of money in the educational sector with initiation of programming at an early stage. The ideology behind this push is to strengthen the link between the younger generation and the technological growth that will continue to have an ever-increasing impact on their lives and to fuel the pace of innovation. One of the core themes of this area is that of computer programming, which has now become a mandatory subject in early years’ education. As a result of this change, many challenges are being faced by educators and students; for example, educators require more training and students need appropriate tools that suit their level of learning. Therefore, this research aimed at exploring the difficulties in learning and teaching programming at lower secondary schools in Mauritius. Consequently, it can be interpreted from the research findings that an automated teaching and learning programming system that supports the right pedagogical aspects, example, assessment-driven learning with the inclusion of game-based learning, would make the learning process more successful and enjoyable for students in early years of education. Students with higher problem-solving abilities find programming easy and they can master programming with no or little difficulties regardless of the programming environment. On the contrary, students with lower problem-solving abilities find programming difficult to understand and are often unable to master it.

Suggested Citation

  • Vinod Sharma Bhaugeerutty, 2021. "Difficulties in Learning and Teaching Programming at Lower Secondary Level in Mauritius," Journal of Contemporary Research in Social Sciences, Learning Gate, vol. 3(3), pages 48-61.
  • Handle: RePEc:ajp:jocrss:v:3:y:2021:i:3:p:48-61:id:139
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    File URL: https://learning-gate.com/index.php/2641-0249/article/view/139/70
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    Cited by:

    1. HuiJae Park & JaMee Kim & WonGyu Lee, 2022. "Development of CNN-Based Data Crawler to Support Learning Block Programming," Mathematics, MDPI, vol. 10(13), pages 1-12, June.

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