Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal International Journal of Economics Studies International Journal of Technology and Modeling
Mensah, Kofi
Unknown Affiliation
Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Analysis of Factors Affecting Economic Growth in Developing Countries Mensah, Kofi
International Journal of Economics Studies Vol. 1 No. 1 (2024): International Journal of Economics Studies
Publisher : Raudhah Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Economic growth in developing countries is often influenced by a variety of complex and interrelated factors. This study aims to analyze the main factors that affect economic growth in developing countries. The research issue focuses on how variables such as foreign investment, education, infrastructure, and government policies affect economic growth. To achieve this goal, this study uses a qualitative method that involves literature study and secondary data analysis from economic reports, academic journals, and policy documents. Data is collected from trusted sources covering a wide range of developing countries. The analysis was carried out with a thematic approach to identify patterns and relationships between these factors. The results of the study show that foreign direct investment, improving the quality of education, and infrastructure development have a significant impact on economic growth. In addition, government policies that support innovation and economic reform have also been proven to contribute to better economic growth. However, the results of the study also reveal that challenges such as political instability and corruption can hinder the potential for economic growth despite the presence of positive factors. These findings provide important insights for policymakers in developing countries to design effective strategies to spur sustainable economic growth.
Applying AI Models to Analyze Student Learning Interests Through Digital Interaction Patterns Agyemang, Akosua; Mensah, Kofi; Owusu, Esi
International Journal of Technology and Modeling Vol. 2 No. 3 (2023)
Publisher : Etunas Sukses Sistem

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63876/ijtm.v2i3.142

Abstract

In the digital era, students increasingly engage with learning platforms that generate vast amounts of interaction data. This study explores the application of Artificial Intelligence (AI) models to analyze students' learning interests based on their digital interaction patterns. By leveraging machine learning algorithms and behavioral analytics, we identify correlations between user activities—such as clickstreams, time spent on content, and interaction frequencies—and subject preferences. The study utilizes a dataset from an online learning management system and applies classification and clustering techniques to detect interest trends among students. Results show that AI models can effectively predict individual learning preferences and offer insights to personalize educational content. These findings highlight the potential of integrating AI-driven analytics in education to enhance learner engagement and optimize teaching strategies.
Co-Authors Agyemang, Akosua Owusu, Esi