IMPLEMENTATION OF INNOVATIVE OBJECT-ORIENTED TRAINING PRACTICES IN FIELD CLASSES FOR FORENSIC STUDENTS
УДК 378.1
Abstract
This article explores the concept of object-oriented learning and its application in an off-site criminology lesson designed for students at Sevastopol State University. The study is relevant due to the growing need for new pedagogical approaches that enhance students' ability to acquire knowledge and develop practical skills in criminology. The paper provides an overview of the principles of object-oriented learning, its historical development, and its advantages. It emphasizes the creation of situations and tasks that foster effective object-oriented learning, particularly through the use of artificial intelligence tools. The study's findings indicate that when students apply their acquired knowledge to situational tasks, they not only develop practical skills but also gain a deeper understanding of the subject matter. Moreover, incorporating artificial intelligence in the learning process enables the creation of simulations and virtual scenarios, which significantly enhance the realism of the educational experience. In conclusion, the research demonstrates that object-oriented learning, particularly when combined with artificial intelligence tools, is an effective strategy for teaching and fostering practical skill development in forensic science students.
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References
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Kayaoğlu M.N., Güçlütürk Y. Effects of metacognition on student success and satisfaction in an object-oriented programming course. Education and Information Technologies. 2017. No 22(5). P. 2251–2267.
Köse Ü., Gülbahar Y. A meta-analysis of computer-assisted scaffolded writing interventions for students with disabilities in K-12 settings. Computers & Education. 2015. Vol. 82(1). P. 33–43.
Patitsas E.C., Craig M., Easterbrook S., Henriques P. How programming instructors talk about novice errors: a taxonomy of novice error descriptions. ACM Transactions on Computing Education (TOCE). 2018. Vol. 18(3). P. 1–29.
Piwek P., Piwek L. Benefits and barriers to digital game-based learning in the classroom: An investigation of teachers' perceptions. Computers & Education. 2019. Vol. 141. P. 103617.
Radermacher A., Schümmer T. Learning analytics for student support in computer science education: A systematic literature review. ACM Transactions on Computing Education (TOCE). 2016. Vol. 16(4). P. 1–32.
Ruiz-Calleja A., Dennerlein S., Holocher-Ertl T. Cognitively activating instructional design in computer science education: A replication study. Computers & Education. 2019. Vol. 138. P. 46–58.
Velázquez-Iturbide J.-Á., Chimal-Eguía J.-C. Software engineering project grading techniques: An empirical study on student satisfaction and subjective quality. Computers & Education. 2017. Vol. 104. P. 30-40.
Villeneuve H., Reimann P., Bryant P., Hell T. Design features, student perceptions, and use patterns for different learning tasks in a computer-based formative assessment environment. Computers & Education. 2019. Vol. 128. P. 15–29.
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