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

• Published in: 2024 IEEE/ACIS 22nd International Conference on Software Engineering Research, Management and Applications (SERA) pp. 295 - 299
• Main Authors: Nakao, Motoi, Oomachi, Yuhei
• Format: Conference Proceeding
• Language: English
• Published: IEEE 30.05.2024
• Subjects: Education; elemental school; Employment; Information age; Learning analytics; Motivation and achievement scale; Problem-solving; Programing education; Questionnaire; Self-efficacy scale; Shape; Software; Surveys
• ISSN: 2770-8209
• DOI: 10.1109/SERA61261.2024.10685574

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.