1 Jordan High School, Katy, Texas, United States.
2 West Forsyth High School, Cumming, Georgia, United States.
3 Irvington High School, Fremont, California, United States.
4 Jordan High School, Katy, Texas, United States.
5 Acellus High School, Cumming, Georgia, United States.
6 Jordan High School, Katy, Texas, United States.
Research Article
World Journal of Advanced Research and Reviews, 2024, 24(01), 877-882
Received on 22 August 2024; revised on 05 October 2024; accepted on 08 October 2024
This recent growth in early education in coding evidences the rising need for the computing-thinking-skills development in children. Though most of the programming curricula are based upon syntax and other basic concepts of coding, computational thinking encompasses broader cognitive skills, such as problem-solving, abstraction, and logical reasoning. This research therefore intends to fill a gap in research and will investigate the ways pre-coding games employ logical puzzles as an enhancement in developing computational thinking skills in children aged 7-10 years and how these affect the acquisition of programming knowledge. In all, there will be two groups assigned: one will be exposed to logical-oriented puzzle training, Group A, and the other will be a control group, Group B, which receives only regular standard lessons in programming introduction. Pre- and post-measures of computational thinking and basic programming skills will be obtained from the participants. The machine learning algorithms, such as Random Forest for prediction in terms of improvement in subject performance in computational thinking and K-Means clustering to identify patterns in their development of skills, will be implemented in their pure or integrated forms to analyze data. Logistic Regression will be executed in order to model the odds of improved performance in programming given an intervention of exposure to puzzles. The research study will, therefore, apply these algorithms in comparing the performance of the two groups and reveal the aspects of computational thinking to which the greatest influence in a positive way through puzzle activities is exerted. It is expected that children exposed to logical puzzles may show significant improvements in both computational thinking and programming skills. These findings should be useful to educators in their effort to show how logical puzzles can be integrated into the curricula of early coding education to build foundational skills and thereby contribute to a refinement of best practices in STEM education.
Random Forest; Machine Learning; Children; Logical puzzles
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Nishant Gadde, Avaneesh Mohapatra, Karan Mody, Siddhardh Manukonda, Navnit Vijay and Rayan Idris. Enhancing computational thinking in children through logical puzzles: A machine learning approach for early coding education. World Journal of Advanced Research and Reviews, 2024, 24(1), 877-882. Article DOI: https://doi.org/10.30574/wjarr.2024.24.1.3024