Search

The rapid advancement of technology and innovation is also impacting education across different levels. The rise of Artificial Intelligence (AI) is beginning to transform education in various areas, from course materials to assessment systems. This requires educators to reconsider how they evaluate students' knowledge. It is crucial to understand if and to what extent assignments can be completed using AI tools. This study explores two hypotheses about the risks of using code-based 3D modeling software in education and the potential for students to delegate their work to AI when completing assignments. We selected two tasks that students were able to successfully complete independently and provided the same amount of information (both textual and image) to AI in order to generate the necessary code. We tested the widely used ChatGPT and Gemini AI bots to assess their current performance in generating code based on text prompts or image-based information for the two models. Our findings indicate that students are not yet able to entirely delegate their work to these AI tools. [ABSTRACT FROM AUTHOR]

Almost every component of the information society is influenced by elements built on communication technology. Learning also tends to be related to the dynamic usage of computers. Nowadays, a number of applications (online or offline) are also available that engage large groups of potential users and simultaneously provide a virtual environment to facilitate learning. This study introduces the self-developed interactive blind map teaching-examining e-learning system of the University of Debrecen. Results of testing the system with a control group are also presented. Both experimental and control groups of students were required to sita test of topographic knowledge following a semester of study. The pass mark for the test was 80%. The experimental group used the new digital environment to study, while the control group prepared for their exam using paper maps in the traditional way. The key research questions addressed by the study were to determine whether exam results obtained by the group using the "digital" method better than those of the control's; and if there were a difference between the exam performances of the two groups, was this statistically significant and, therefore, likely to occur in other similar scenarios?

Because of the increased demand for information, the scientific community have published their results on the Internet over the last 20 years, adapting to society requirements. Due to the development of web-based spatial information soil systems, access to data on various themes and of varying quality has become substantially easier. The focus of our paper is to demonstrate a freely accessible and usable web-based soil database and soil information system (Soil Information and Soil Classifier System), which is suitable for geovisualization uploaded soil data and for determining reference soil groups (RSGs) in accordance with the World Reference Base of Soil Resources (WRB; RSG). In order to achieve this, we algorithmized the diagnostic soil classification process of the WRB, then we created decision trees to correspond input soil data to the WRB system. In order to facilitate geovisualization of the spatial data, the Keyhole Markup Language file format supported by Google API was applied.

In our study, by investigating reambulated soil profiles from the Nagy-Sárrét region in Hungary, we attempt to determine the extent of changes which have occurred due to effects which impacted the landscape in terms of the soil chemistry properties of soil profiles exposed during the Kreybig soil survey more than 70 years ago. Based on the results, in the areas used as grassland, we observed a decrease in pH and an increase in the humus content of the topsoil. The increased CaCO3 following the chemical improvement of the soil which was used as cropland is still characteristic of the area. During the past decades, the investigated soils have been affected by significant changes with regard to water management, which have also modified the investigated parameters. We have classified the reambulated soil profiles among the Solonetz, Vertisol, and Gleysol reference groups based on the World Reference Base of Soil Resources (WRB) diagnostic system.

In our study, we tested the existing and freely accessible soil databases covering a smaller geographical region surveyed and classified according to the Hungarian classification in order to approximate the WRB soil reference groups (RSG). We tested the results and applicability of approximation for the RSG with three different methods on 12 soil profiles. First, RSGs were assigned to Hungarian soil taxa based on results of previous correlation studies, secondly, a freely accessible online database of ISRIC was applied furthermore, and an automated reclassification developed and programmed by us was used, which takes the original soil data as input.