The Methodology for Using a Business Simulator with Elements of Machine Learning to Develop Personal Finance Management Skills

Antoniuk, Dmytro; Vakaliuk, Tetiana А.; Didkivskyi, Vladyslav; Vizghalov, Oleksandr; Олійник, Оксана Вікторівна; Yanchuk, Valentyn

doi:10.5220/0012061800003431

Cited by 8 publications

(2 citation statements)

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“…The empirical analysis of problem-solving methods using machine learning, particularly in sectors such as education, healthcare, and life safety, is a burgeoning area of research [3,4,10,[22][23][24][47][48][49]. This paper delves into the exploration of such methods, explicitly focusing on clustering and classification problems [13,36].…”

Section: Introductionmentioning

confidence: 99%

Empirical comparison of clustering and classification methods for detecting Internet addiction

Klochko,

Fedorets,

Klochko

2024

CTE Workshop Proc.

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Machine learning methods for clustering and classification are widely used in various domains. However, their performance and applicability may depend on the characteristics of the data and the problem. In this paper, we present an empirical comparison of several clustering and classification methods using WEKA, a free software for machine learning. We apply these methods to the data collected from surveys of students from different majors, aiming to detect the signs of Internet addiction (IA), a behavioural disorder caused by excessive Internet use. We use Expectation Maximization, Farthest First and K-Means for clustering, and AdaBoost, Bagging, Random Forest and Vote for classification. We evaluate the methods based on their accuracy, complexity and interpretability. We also describe the models developed by these methods and discuss their implications for identifying the respondents with IA symptoms and risk groups. The results show that these methods can be effectively used for clustering and classifying IA-related data. However, they have different strengths and limitations when choosing the best method for a specific task.

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Section: Introductionmentioning

confidence: 99%

Empirical comparison of clustering and classification methods for detecting Internet addiction

Klochko,

Fedorets,

Klochko

2024

CTE Workshop Proc.

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“…In return, the digitalization, building informational system, active applying ICT, artificial intelligence, etc. are significant stimulators (Chen et al, 2022;Volk et al, 2022;Skrynnyk et al, 2022;Antoniuk et al, 2022;Sadigov et al, 2022;Gladden et al, 2022;Sobczak, 2022;Košovská, 2022). ICT makes collaboration more easy, timely, optimal, cheaper, and effective.…”

Section: Introductionmentioning

confidence: 99%

Business – education collaboration in R&D investment: Analysis of development gaps and critical points using MAR-splines

Samoilikova¹,

Korpysa

Vasilyeva

et al. 2023

Journal of International Studies

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The purpose of the article is to determine development gaps and critical points in the system of business – education collaboration in R&D investment using MAR-splines. The study attempts to confirm hypotheses about the impact of business – education collaboration in R&D investment on the sustainable development, and, in turn, the influence of chosen factors on the level of cooperation of business and education in R&D investment taking into account development gaps and critical points. These factors include the values of gross domestic expenditure on R&D spent by the business enterprise sector and by the higher education sector, and the level of the informal economy. The study is based on the sample of the 10 countries leading the ranking of Sustainable Development Index for 2011-2018 (time limits are set due to the availability of all studied indicators in the statistical databases of the World Bank, UNDESA, OECD and WIPO). Critical points and knots are determined using MAR-splines and two-way median-spline plots in STATA software. It has been proven that the business – education collaboration in R&D investment contributes to increasing the level of sustainable development if the value of this indicator is in the range of critical points from 62.04 to 68.96 (1% growth increases the estimate of sustainable development by 0.7%). In turn, development gaps and critical points have also been found for factors influencing the level of business-education R&D collaboration.

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Simulator-mediated learning: enhancing accounting teaching-learning processes in higher education

Gaviria,

Arango,

Valencia-Arias

et al. 2024

Cogent Education

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The Methodology for Using a Business Simulator with Elements of Machine Learning to Develop Personal Finance Management Skills

Cited by 8 publications

References 0 publications

Empirical comparison of clustering and classification methods for detecting Internet addiction

Empirical comparison of clustering and classification methods for detecting Internet addiction

Business – education collaboration in R&D investment: Analysis of development gaps and critical points using MAR-splines

Simulator-mediated learning: enhancing accounting teaching-learning processes in higher education

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