Enhancing Algorithm and Programming Education through Collaborative Blended Learning: A Problem-Based Approach for First-Year Students
Автор: Ajcharee Pimpimool
Журнал: International Journal of Modern Education and Computer Science @ijmecs
Статья в выпуске: 4 vol.16, 2024 года.
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This research study aims to compare the learning achievements of first-year students in an algorithm and programming course before and after participating in cooperative blended learning activities focused on variables, expressions, and control commands. By utilizing problem-based learning methods, the researchers sought to meticulously analyze the profound impact of these activities on students’ academic advancement. The research tools deployed encompassed satisfaction questionnaires and achievement tests. The research cohort encompassed seven experienced specialists within higher education institutions, each endowed with a minimum of ten years of pedagogical experience, along with twenty-five participating students. Employing rigorous statistical analysis via T-tests, the study conclusively revealed a statistically noteworthy enhancement in student achievement post the program, underscoring the affirmative influence of cooperative blended learning activities. Moreover, the overall satisfaction level among learners engaging in the proposed learning activities was remarkably elevated, evident through an average satisfaction rating of 4.54 and a standard deviation of 0.73. These empirical insights succinctly underscore the demonstrable effectiveness of assimilating cooperative blended learning methods within algorithm and programming education, thereby accentuating the pivotal role of these pedagogical approaches in shaping contemporary educational practices.
Cooperative blended learning, Algorithm and programming education, Learning achievement, Problem-based learning, Learner satisfaction
Короткий адрес: https://sciup.org/15019177
IDR: 15019177 | DOI: 10.5815/ijmecs.2024.04.03
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