Development, Validation and Testing of the Bayesian Network of Educational Institutions Financing

Lytvynenko, Volodymyr; Савіна, Наталія; Voronenko, Mariia; Doroschuk, Nadia; Smailova, Saule; Boskin, Oleg; Кравченко, Т К

doi:10.1109/idaacs.2019.8924307

Cited by 8 publications

(5 citation statements)

References 11 publications

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“…BN, which is widely used in a variety of fields, has been used in a small number of studies in the field of education (Almond et al, 2015;Culbertson, 2016;Reichenberg, 2018). However, BN is more advantageous than other methods with its ability to model students in the field of education (Levy, 2016;Lytvynenko et al, 2019;Sinharay, 2006) and to evaluate the model quickly (Kenekayoro, 2018;Kustitskaya et al, 2020;Millán et al, 2013;Nguyen & Do, 2009). Essential improvements in the education system are vital to enhance students' success.…”

Section: Discussionmentioning

confidence: 99%

Examining the factors affecting students' science success with Bayesian networks

KARABOĞA,

DEMİR

2023

International Journal of Assessment Tools in Education

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Bayesian Networks (BNs) are probabilistic graphical statistical models that have been widely used in many fields over the last decade. This method, which can also be used for educational data mining (EDM) purposes, is a fairly new method in education literature. This study models students' science success using the BN approach. Science is one of the core areas in the PISA exam. To this end, we used the data set including the most successful 25% and the least successful 25% students from Turkey based on their scores from Program for International Student Assessment (PISA) survey. We also made the feature selection to determine the most effective variables on success. The accuracy value of the BN model created with the variables determined by the feature selection is 86.2%. We classified effective variables on success into three categories; individual, family-related and school-related. Based on the analysis, we found that family-related variables are very effective in science success, and gender is not a discriminant variable in this success. In addition, this is the first study in the literature on the evaluation of complex data made with the BN model. In this respect, it serves as a guide in the evaluation of international exams and in the use of the data obtained.

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Section: Discussionmentioning

confidence: 99%

Examining the factors affecting students' science success with Bayesian networks

KARABOĞA,

DEMİR

2023

International Journal of Assessment Tools in Education

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“…The authors' related works are referenced as [84][85][86]. In their article titled "The recognition of speech defects using convolutional neural network" [124], Olha Pronina and Olena Piatykop (figure 11) present a solution to improve the recognition efficiency of speech defects in children by utilizing convolutional neural network models to process spectrogram-based sound data.…”

Section: Articles Overview 21 Digital Transformation Of Educationmentioning

confidence: 99%

ACNS Conference on Cloud and Immersive Technologies in Education: Report

et al. 2023

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This article serves as an introduction to a collection of selected papers presented at the ACNS Conference on Cloud and Immersive Technologies in Education (CITEd 2022), which took place in Kyiv, Ukraine, on December 21-22, 2022. The collection provides valuable insights into the latest advancements in cloud and immersive technologies in the field of education. The introductory text offers an overview of the conference events and provides concise summaries of the selected papers, offering a glimpse into the diverse topics and research areas covered. These selected papers reflect the cutting-edge research and innovative approaches showcased at CITEd 2022, making them a valuable resource for educators, researchers, and practitioners interested in exploring the potential of cloud and immersive technologies in education.

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“…At the macro-economic level, the movement of material, financial and information resources can be viewed in terms of the interrelationships between individual industries and sectors of the economy using the logistics infrastructure and its components. In a structured sense, these movements constitute separate material flows (Savina, 2019). The general concept of material flow implies the following: -The movement of a certain amount of material goods, economic and information products; -restrictions on movement, not only in terms of quantity, but also in terms of space and time, are called a "flow channel"; -the need to correlate these characteristics with specific time intervals to quantify the flow.…”

Section: The Importance Of Financial Flows In Educationmentioning

confidence: 99%

“…Indeed, the formation and analysis of financial flows require significant analytical calculations. These calculations involve estimating and discounting future payments to their present value, determining the discount rate, aggregating flows, calculating indicators such as NPV (Net Present Value) and IRR (Internal Rate of Return), and other aspects of financial analysis (Savina, 2019).…”

Section: The Importance Of Financial Flows In Educationmentioning

confidence: 99%

The Role of Financial Flows in Crisis Management in the Education Sector

Mykhailova,

Savina

2023

GBDEJ

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In the dynamic landscape of education, characterised by an information-driven society and the ever-increasing threat of crises, this paper delves into the vital role of financial flows in crisis management in the education sector. The purpose of this study is to clarify the importance of financial resource allocation by demonstrating its transformative impact on the resilience of educational institutions in times of crisis. The research highlights the important purpose of this study: to assess the strategic use of financial flows, explore their adaptability, and evaluate the joint efforts of educational institutions and governments to mitigate the effects of the crisis. Methodology. To achieve its objectives, the study adopts a multifaceted approach. It draws on a variety of sources, including case studies, policy analysis and financial data, to develop a comprehensive understanding of the role of financial flows in crisis management. A qualitative methodology is used to analyse the strategic allocation of financial resources, assess their dynamic nature and examine the effectiveness of joint efforts. The analysis is based on both primary and secondary data sources, providing a solid basis for the research. Results. The conclusions of this study are multifaceted and reflect the complex interrelationship of financial flows in crisis management in the education sector. First, the study reveals the key role of financial flows as a mechanism for ensuring the sustainability of educational institutions. The case studies show that institutions that proactively allocate funds to infrastructure, technology and student support are better prepared to effectively deal with unexpected disruptions. Second, the study identifies the importance of strategic resource allocation in times of crisis. By assessing risks and implementing crisis response plans, educational institutions can prioritise financial support and resource allocation, ensuring that critical needs are met quickly. Third, the study highlights the importance of collaborative efforts between educational institutions and governments. Public-private partnerships, government grants and support policies are becoming important components of crisis management that contribute to a coordinated response to crisis situations. Thus, this study highlights the integral role of financial flows in crisis management in the education sector. It emphasises their transformative potential by highlighting strategic allocation, adaptability and collaboration as key elements of resilience. By adopting these principles, education institutions and governments can effectively mitigate the impact of crises while upholding the fundamental right to education for all in the face of adversity.

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Development, Validation and Testing of the Bayesian Network of Educational Institutions Financing

Cited by 8 publications

References 11 publications

Examining the factors affecting students' science success with Bayesian networks

Examining the factors affecting students' science success with Bayesian networks

ACNS Conference on Cloud and Immersive Technologies in Education: Report

The Role of Financial Flows in Crisis Management in the Education Sector

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