Evaluating Preschoolers' Block Programming Using Complexity and Personality Traits

Programming learning at an early age effectively fosters logical thinking and self-centeredness, but an appropriate evaluation method for young learners has yet to be established. Herein we propose a new learning evaluation method that incorporates problem constructs and the complexity metrics used...

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Vydané v:Proceedings / Conference on Software Engineering Education & Training s. 1 - 5
Hlavní autori: Ono, Yui, Saito, Daisuke, Washizaki, Hironori
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 29.07.2024
Predmet:
Artificial intelligence
Block programming
Complexity
Complexity theory
Conferences
Correlation
Performance evaluation
Personality traits
Preschool programming education
Programming profession
Quality assessment
ISSN:2377-570X
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Shrnutí:Programming learning at an early age effectively fosters logical thinking and self-centeredness, but an appropriate evaluation method for young learners has yet to be established. Herein we propose a new learning evaluation method that incorporates problem constructs and the complexity metrics used in software engineering quality assessments. Specifically, we investigate the relationships between changes in block pro-gramming complexity, personality traits, and learning effects. Evaluation rubrics and log data assess complexity, while person-ality traits are based on Big-5. Then the learning effects of 34 kindergarten children participating in workshops are analyzed in terms of complexity and personality traits. After learning, first-time programmers tend to show a large increase in complexity. The correlation with the rubric score is \rho=0.43 , and the correlation with log data is \mathbf{r}s=0.92 . Furthermore, analysis using the Big-5 gives \rho=0.609 for the rate of increase in extraversion and complexity, indicating a strong relationship between learning effects and personality traits. In the future, this data will be used to build AI tools for automatic evaluations, feedback, and learning curriculum recommendations.
ISSN:2377-570X
DOI:10.1109/CSEET62301.2024.10663038