https://scidar.kg.ac.rs/handle/123456789/8214 2026-03-12T14:15:14Z https://scidar.kg.ac.rs/handle/123456789/23073 Title: Mathematical Modelling in the Computation of Volumes of Solids of Revolution Authors: Božić, Radoslav; Milenković, Aleksandar; Mitrović, Slađana Abstract: In this paper, the influence of the mathematical modelling approach in computer-supported collaborative learning (CSCL) on students’ knowledge of calculus contents, particularly the application of definite integral, is examined. The research was conducted with the final-grade students at the grammar school. Two groups of the students, the experimental and the control one, were observed. Both the groups learned in CSCL environment, while in the experimental group, mathematical modelling was applied. The work of the experimental group students during the whole mathematical modelling process was monitored and analyzed. Some examples of the students’ solutions are described. After the learning process of the integral contents, the students’ learning achievements were tested and compared. The results indicate that the use of mathematical modelling increases the students’ interest in solving the definite integral application problems. It is proved that the students who applied modelling process had better results than the students who did not. 2026-01-01T00:00:00Z https://scidar.kg.ac.rs/handle/123456789/23072 Title: Chatgpt 5.2 i finansijska matematika: analiza tačnosti i obrazovne vrednosti generisanih rešenja Authors: Vučićević, Nemanja; Svičević, Marina; Milenković, Aleksandar; Pavković, Miloš; Protić, Jelica Editors: Dumnić, Boris Abstract: U radu se ispituje uspešnost najnovije verzije velikog jezičkog modela ChatGPT 5.2 u rešavanju zadataka iz finansijske matematike na nivou visokoškolskog obrazovanja. Analiza je zasnovana na poređenju rešenja generisanih od strane modela i rezultata 40 studenata matematike i informatike na kolokvijumu koji obuhvata zadatke iz različitih oblasti finansijske matematike. Rešenja su vrednovana prema istoj bodovnoj skali i kriterijumima koji uključuju tačnost rezultata, matematičku korektnost postupka, jasnoću objašnjenja i obrazovnu vrednost. Dobijeni rezultati pokazuju da ChatGPT 5.2 u većini zadataka ostvaruje učinak uporediv sa studentskim postignućima, uz uočena ograničenja u pogledu formalne preciznosti i potpunosti rešenja. 2026-01-01T00:00:00Z https://scidar.kg.ac.rs/handle/123456789/23071 Title: Secondary school chemistry teachers’ attitudes toward developing entrepreneurial competencies in chemistry education Authors: Stašević, Filip; Dinčev, Emilija; Maksimovic, Aleksandra; Đurđević Nikolić, Jelena Abstract: Entrepreneurial competencies are increasingly recognized as important for everyone’s personal growth and future professional engagement. This study aims to provide a descriptive overview of secondary school chemistry teachers’ attitudes toward entrepreneurial competencies in chemistry education. In this exploratory quantitative research, data were collected from 132 chemistry teachers from Serbia via a structured online questionnaire comprising 21 items. Findings indicate that, although teachers demonstrate a substantial positive attitude toward the relevance and importance of entrepreneurial competencies, this understanding is not consistently reflected in classroom practice. Moreover, teachers reported limited acquisition of expertise regarding entrepreneurial competencies through initial teacher education and continuing professional development. These results highlight opportunities to enhance teacher preparation by explicitly integrating the development of entrepreneurial competencies into existing chemistry and pedagogical courses. The relatively small sample, combined with potential biases inherent in self-reported questionnaires, may limit the generalizability of the findings. Systematic and practical professional development initiatives could support teachers in linking instructional strategies with the cultivation of creativity, initiative, problem-solving, and other key entrepreneurial traits among students. 2026-01-01T00:00:00Z https://scidar.kg.ac.rs/handle/123456789/23048 Title: Classification of physics problems as a basis for the development of educational AI models Authors: Zivkovic, Milena; Zivkovic, Dubravka; Svičević, Marina; Milenković, Aleksandar; Vučićević, Nemanja Abstract: The integration of artificial intelligence (AI) into education has opened new possibilities for personalized learning, adaptive assessment, and intelligent content delivery (Tapalova & Zhiyenbayeva, 2022). However, the effectiveness of such systems largely depends on the availability of high-quality, well-structured datasets that reflect the complexity of real educational content. In the domain of science education, and particularly physics, problem-solving tasks represent a core component of learning and assessment (Küchemann et al., 2024). Despite their importance, these tasks are rarely prepared in formats suitable for machine learning applications. To address this gap, we propose a structured classification framework for physics problems at the elementary school level (Shamshin, 2024; de Souza et al., 2024). Our approach focuses on the systematic annotation and organization of tasks with pedagogically and cognitively relevant features, creating a dataset suitable for training and evaluating AI models in education. By classifying physics problems based on problem type, cognitive complexity, physical quantities, and other key attributes, this framework supports the development of intelligent educational systems capable of adaptive task recommendation, personalized learning, and formative assessment. The problems were processed and annotated according to relevant criteria, including problem type (conceptual, quantitative, mixed), cognitive complexity level according to revised Bloom’s taxonomy (Krathwohl, 2002), number of physical quantities and formulas, key concepts, and measurement units (Table 1). Problem complexity is determined by the number of reasoning steps required, from simple calculations (e.g., finding speed using 𝑣 = 𝑠/𝑡) to multi-concept problems (e.g., calculating acceleration while considering friction and inclined forces). For instance, determining a box's acceleration when pulled at an angle requires resolving forces, calculating friction, and applying Newton's laws - a 5-step analysis typical for 8th grade physics. The dataset covers key physics topics for grades 7 and 8, such as force and motion, oscillations, and optics. 2025-01-01T00:00:00Z