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Observation and Evaluation for Individual Student Using Learning Analytics of Software Programing and Functional Questionnaire | IEEE Conference Publication | IEEE Xplore

Observation and Evaluation for Individual Student Using Learning Analytics of Software Programing and Functional Questionnaire


Abstract:

This study assessed the impact of programming education on self-efficacy and motivation among elementary school students using learning analytics and functional questionn...Show More

Abstract:

This study assessed the impact of programming education on self-efficacy and motivation among elementary school students using learning analytics and functional questionnaire surveys. By analyzing the behavioral patterns for elemental school students in programming tasks related to basic geometric shapes through learning analytics, we identified the frequency of Run/Execute operations as a differentiating factor between students who completed all tasks and those who did not. Furthermore, employing a uniquely designed questionnaire allowed us to extract clear differences in motivation and achievement scales, as well as self-efficacy scales, between students who improved their learning outcomes and those who did not. The integration of learning analytics and functional questionnaires into elementary programming education emerged as a crucial tool for understanding and enhancing students' learning experiences, indicating the significance of adaptive educational strategies in the digital age.
Date of Conference: 30 May 2024 - 01 June 2024
Date Added to IEEE Xplore: 26 September 2024
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Conference Location: Honolulu, HI, USA

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