Periodica Polytechnica (Budapest University of Technology and Economics)
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Volunteer Teachers’ Intrinsic Motivation in Myanmar’s IDP Camps through the Lens of Self-Determination Theory
No full textIn the areas of Myanmar impacted by conflict, numerous volunteer teachers are significantly contributing to the ongoing education of displaced children. They operate in regions with significant security issues but receive only minimal educational assistance. This research investigates the reasons behind the motivation of these volunteer teachers. The sample for the study includes seven volunteer teachers operating in Internally Displaced Persons (IDPs) camps in the Sagaing and Karenni Regions. Using Ryan and Deci’s (2017) Self-Determination Theory (SDT) as a framework, the study investigates three fundamental psychological needs of intrinsic motivation – autonomy, competence, and relatedness. And the study also find out the impact of these basic needs on teachers’ resilience and dedication.
In this research, researchers conducted semi-structured interviews and obtained qualitative data, which were analysed through thematic analysis. According to the data, the research shows that volunteer teachers in these targeted areas adjusted their lessons to adapt to students’ emotional state, security conditions, and the limitations of the learning environment. Moreover, teachers in these areas participated in peer learning groups and built close relationships with students and the community.
These approaches helped teachers remain motivated and keep teaching under challenging conditions.
The findings from this study suggest that Self-Determination Theory (SDT) is a valuable instrument for understanding teacher motivation in crisis settings. The study also highlights the need for policies to provide structured professional support for teachers.
A key implication for future development in this study is to design teacher training programs that strengthen professional skills and equip teachers to navigate the challenges of crisis contexts. Such support may involve mentoring programs, accessing teaching materials, and ongoing professional development. All these supports are essential for sustaining teachers’ motivation and professional development
Hálózatban a tudás: A BOBCATSSS konferencia múltja és jelene
No full textThe BOBCATSSS organization hosts an annual symposium coordinated by students from various European universities specializing in library and information science (LIS). Since its establishment in 1993, this conference has become an important platform for students, practitioners, and scholars to share their research, engage in discussions about current challenges, and examine emerging trends within the LIS field. Its distinctive student-led character ensures the integration of fresh insights and creative approaches that mirror the dynamic and evolving nature of the discipline. Each year, a different university across Europe organizes the event, fostering intercultural exchange and strengthening the international dimension of LIS education and research. BOBCATSSS covers a wide array of topics, including digital libraries, information literacy, knowledge management, and the effects of new technologies on information services. By serving as an interdisciplinary venue, the conference supports the generation of novel ideas and the development of professional networks, thus playing a significant role in advancing the field of library and information science.A BOBCATSSS nemzetközi konferencia egy évente megrendezett esemény, amelyet különböző európai egyetemek könyvtár- és információtudományi hallgatói koordinálnak, elősegítve az együttműködést és a tudásmegosztást a könyvtár- és információtudomány (LIS) területén. 1993-as indulásuk óta a BOBCATSSS konferenciák jelentős platformként szolgálnak hallgatók, szakemberek és akadémikusok számára, hogy bemutassák kutatásaikat, megvitassák a kortárs kérdéseket, illetve feltérképezzék a tudományterület legújabb trendjeit. A konferencia különleges, hallgatóközpontú jellege biztosítja a friss nézőpontok és az innovatív megközelítések megjelenését, tükrözve a szakterület dinamikus és folyamatosan változó természetét. Minden évben más és más európai egyetem ad otthont az eseménynek, ezáltal támogatva a nemzetközi mobilitást és a kulturális információcserét, valamint erősítvea könyvtár- és információtudományi oktatás, illetve kutatás nemzetközi dimenzióját. A BOBCATSSS konferenciák fő témái sokszínűek, számos területet lefednek, interdiszciplináris fórumként elősegítik az új ötletek kialakulását és a szakmai hálózatok kiépülését, ezáltal jelentősen hozzájárulva a könyvtár- és információtudomány fejlődéséhez
Hallgatói tanulási mintázatok vizsgálata a felsőoktatási szakképzésben
No full textIndependent and effective learning plays a crucial role in higher education. In this context, it is essential to explore the methods and tools that enhance learning outcomes. The first step in optimizing the learning process is identifying individual learning styles, as awareness of these can help students apply the techniques most effective for them. The aim of our study was to explore the learning characteristics of students enrolled in short-cycle higher education programmes in Hungary (n = 1628). Data collection was carried out through a questionnaire-based survey conducted in 23 Hungarian higher education institutions, involving both full-time and part-time students across all fields of study. Our research focused on identifying the learning methods and tools commonly used by students and how these contribute to learning efficiency. The data were analyzed by field of study, and a range of statistical methods were used to test our hypotheses. Overall, our research contributes to a deeper understanding of the learning characteristics of students in higher education vocational training. Our findings highlight that commitment to independent learning and intrinsic motivational factors—such as a thirst for knowledge, curiosity, and career goals—play a decisive role in the learning process. At the same time, external obligations and deficiencies in learning organization present significant challenges for students. Through a cluster-based analysis of learning strategies, we were able to identify distinct patterns that reflect the diverse learning pathways students follow. Our study provides valuable insights into the learning strategies of a student population that has received limited attention in Hungarian educational research since the transformation of short-cycle higher education programmes.A felsőoktatásban kiemelt jelentősége van az önálló, hatékony tanulásnak. Ennek kapcsán érdemes feltárni azokat a módszereket és eszközöket, amelyek a tanulás eredményességét növelik. A tanulási folyamat optimalizálásának első lépése a tanulási stílusok azonosítása, hiszen ezek ismerete elősegíti, hogy a tanulók a számukra leghatékonyabb technikákat alkalmazzák. Kutatásunk célja az volt, hogy a felsőoktatási szakképzésben tanuló hallgatók tanulási sajátosságait feltárjuk (n = 1628 fő). Az adatfelvétel kérdőíves módszerrel zajlott, amelyet Magyarország 23 felsőoktatási intézményében végeztünk, a felsőoktatási szakképzés nappali és levelező tagozatán tanulók körében, valamennyi képzési területet lefedve. Vizsgálatunkban arra kerestük a választ, hogy mely tanulási módszerek és eszközök használata jellemző a hallgatók körében, és ezek miként járulnak hozzá a tanulási hatékonysághoz. Az adatokat képzési területek szerint elemeztük, hipotéziseink vizsgálatához pedig többféle statisztikai eljárást alkalmaztunk. Összességében kutatásunk hozzájárul a felsőoktatási szakképzésben tanuló hallgatók tanulási jellemzőinek mélyebb megértéséhez. Eredményeink rámutattak arra, hogy az önálló tanulás iránti elköteleződés, valamint a belső motivációs tényezők – mint a tudásvágy, érdeklődés és karriercélok – meghatározó szerepet játszanak a tanulási folyamatban. Ugyanakkor a tanulást nehezítő körülmények, különösen a külső kötelezettségek és a tanulásszervezési hiányosságok, komoly kihívásokat jelenthetnek a hallgatók számára. A tanulási stratégiák klaszteralapú vizsgálata révén azonosítani tudtuk azokat a mintázatokat, amelyek mentén a hallgatók eltérő tanulási utakat járnak be. Kutatásunk segítségével egy olyan hallgatói csoport tanulási stratégiáiban kaphatunk betekintés, mely témával a felsőoktatási szakképzés átalakulását követően a hazai kutatók kevésbé foglalkoztak.
 
Enhancement of Sulfate Resistance in Dune Sand Mortars through Polypropylene Fiber Incorporation
Get PDFThis study investigates the impact of different polypropylene fiber (PPF) dosages (0.1% and 0.15%) and lengths (12 mm and 18 mm) on dune mortar (DM) modified with river sand (RS) at a replacement ratio of 50%. The main objective is to evaluate the durability of this fiber-reinforced mortar in a sulfate-rich environment. Compressive strength was assessed at 28, 60, and 180 days, along with mass loss and strength degradation analyses. Microstructural characteristics were examined by scanning electron microscopy (SEM) and energy dispersive X-ray analysis (EDX). while porosity (P) and sorptivity tests were performed to evaluate permeability. The results reveal that PPF reinforcement significantly enhances sulfate resistance, reducing deterioration rates in mass and compressive strength by up to 46% and 40.87%, respectively. Additionally, water absorption and sorptivity coefficient (S) decreased to 83.91% and 86.36%, respectively, compared with the control. The synergy between modified sand content and PPF reinforcement demonstrates potential for improving sulfate durability, making it a viable solution for concrete applications in aggressive environments
Consumption of Historical Space: Spatial Transformation of Safranbolu Historical Bazaar
Get PDFUnder the influence of the consumer culture that dominates the relationship between cultural heritage and tourism, competing cities have begun to resemble each other and their identities have been damaged. It is thought that the Safranbolu Historical Bazaar is an example of the process described due to its constant marketing by the tourism industry and the danger of its unique culture being commodified and collapsing. In this study, it is aimed to first examine and reveal the threats to the sustainability of cultural heritage through the relations established by the space with the concepts of production-consumption and tourism, and then to create a framework that will ensure the sustainable development of the transformation that the space undergoes throughout the production process in historical cities. Based on this, the study aims to contribute to the development of alternative conservation approaches for the Historical Bazaar by producing information that will strengthen and transfer the unique value of the space. The study was designed with qualitative research methods and multiple data collection tools were used together. Observations and in-depth interviews were conducted in order to reveal spatial practices. As a result of the evaluations in the Historical Bazaar, it was seen that the transformation of the city was shaped around a heritage discourse that emphasised consumption, and suggestions were presented to contribute to the sustainability of cultural heritage
Study of the Design of a Drum Separator Using Halbach Array Magnets for the Removal of Fine Iron Particles
Get PDFThe aim of this paper is to study the possibility of use of the Halbach array magnets in the design of a magnetic drum separator and to address their performance and efficiency in removing fine iron particles transported by conveyor belt. Such a study is based on the estimation and comparison between the particle capture efficiencies of two configurations of the drum separator, one designed by using conventional arrangement of magnets and other based on the use of Halbach array magnets. To check the capture efficiency, we computed the particle trajectory. For this, we solved numerically the magnetic and particle dynamic governing equations by coupling the finite element (FE) and Runge-Kutta (RK4) methods. The obtained results show that the Halbach configuration can give better capture performance
Analysis of Slope Stability Based on Four Machine Learning Models: An Example of 188 Slopes
Get PDFTo achieve rapid and precise prediction of slope stability, we propose an intelligent assessment method utilizing machine learning techniques. This approach aims to enhance the precision of slope stability evaluations, facilitating more effective and timely decision-making in geotechnical engineering. By analyzing 188 slope cases from domestic and international sources, we have identified six key feature variables to evaluate the Factor of Safety (FOS) for slope stability assessment. The dataset was established for evaluating slope stability, and to ensure robustness, it was divided into training and testing set using a 5-fold cross-validation approach. Four slope stability prediction models- GBM, SVM, XGB, and RF- were developed using machine learning algorithms. The accuracy of the models in predicting FOS for slopes was assessed using metrics such as MAE, MSE, RMSE, and R2. The best-performing machine learning model, along with the finite element model developed using GeoStudio, was applied to engineering examples to compare their feasibility and efficiency. The research findings demonstrates that the GBM model has a minimal error between the predicted and actual slope FOS, highlighting its high accuracy. The model shows a strong correlation between predicted and actual FOS, indicating its superior performance relative to other models. GBM model and the finite element model align well with the actual field conditions. However, the GBM model stands out due to its higher accuracy and faster computational efficiency. Therefore, the GBM model offers a high degree of fit between the predicted FOS and the actual values, making it well-suited for evaluating slope stability
Exploring the Potential of Machine Learning in Predicting Soil California Bearing Ratio Values
Get PDFAccurately predicting the California Bearing Ratio (CBR) of soil is vital for civil engineering projects as it determines soil strength and stability, crucial for designing safe and durable infrastructure. Conventional methods for calculating CBR values are both expensive and time-consuming, prompting the need for more efficient approaches. This study explores the use of advanced machine learning (ML) techniques to improve workflow and productivity in CBR prediction. Specifically, the Improved Arithmetic Optimization Algorithm (IAOA) and the Bonobo Optimization Algorithm (SBOA) are applied to enhance the Stochastic Gradient Boosting Regression (SGBR) model for predicting CBR values. The SGBR model, known for its ability to handle complex datasets and nonlinear interactions, is optimized to improve predictive accuracy. Performance metrics such as the coefficient of determination (R2), n10-index, and Root Mean Squared Error (RMSE) are used to assess the model's performance. After training, testing, and validation with relevant data, the optimized SGIA model (SGBR enhanced by IAOA) achieves impressive results, including an n10-index of 1.000, a root mean square error of 0.161, and an R2 value of 0.981. These metrics demonstrate the SGIA model's capability to accurately forecast CBR values, offering a reliable, cost-effective alternative to traditional methods for soil evaluation in engineering applications
Metamodel-based Optimization of Anisotropic Rotor Axial Flux Permanent Magnet Synchronous Motors
Get PDFAxial flux motors have some significant advantages over radial flux motors in high torque-density applications. However, the optimization of axial flux permanent magnet synchronous motors is a challenging task; the analysis usually requires 3D finite element analysis or the application of the 2D multi-slice method. In this paper a novel single-surrogate multi-slice method (SS-MSM) is proposed for modeling anisotropic rotor axial flux permanent magnet motors. However, the general methodology can be applied to other axial flux motors as well. A model calibration methodology has been described where the SS-MSM parameters have been determined using a 2D finite element approach as a reference. The SS-MSM was found to be suitable for a fast and reasonably accurate approximation of the motor performance. Based on the described analysis method, an efficient optimization approach is proposed