Akademik Veri Yönetim Sistemi
Australian Journal of Maritime and Ocean Affairs, cilt.16, sa.2, ss.205-220, 2024 (Scopus)
Measures were implemented between 2020 and 2022 to encourage people to stay at home in the context of the COVID-19 pandemic. One of these measures was the transition to remote and virtual education in many countries’ educational institutions. This study aims to predict the professional competencies of final-year undergraduate students selected from five maritime faculties in the spring semester of 2020-2021. To make this prediction, a survey was conducted with 52 inexperienced deck officers, and the data regarding their self-efficacy beliefs were collected. The officer's questionnaire answers were entered into the Orange data-mining program, and the decision tree learning algorithm was obtained to quantitatively evaluate the pupils’ professional competencies. The student's future professional performance was predicted thanks to the algorithm that was developed. As a result of the study, it has been determined that the most challenging competencies are Cargo Handling, Maritime English and Ship Handling. Furthermore, according to the decision tree learning algorithm, the distance education process has been determined to influence students’ future professional performance negatively. As a result of the study, a unique method application has been brought to the literature for evaluating self-efficacy belief levels. Finally, suggestions have been made regarding the deficiencies observed in education.