International Journal of Education and Management Engineering (IJEME)

ISSN: 2305-3623 (Print)

ISSN: 2305-8463 (Online)

DOI: https://doi.org/10.5815/ijeme

Website: https://www.mecs-press.org/ijeme

Published By: MECS Press

Frequency: 6 issues per year

Number(s) Available: 82

(IJEME) in Google Scholar Citations / h5-index

IJEME is committed to bridge the theory and practice of education and management engineering. From innovative ideas to specific algorithms and full system implementations, IJEME publishes original, peer-reviewed, and high quality articles in the areas of education and management engineering. IJEME is a well-indexed scholarly journal and is indispensable reading and references for people working at the cutting edge of education and management engineering applications.

 

IJEME has been abstracted or indexed by several world class databases: Google Scholar, Microsoft Academic Search, Baidu Wenku, Open Access Articles, Scirus, CNKI, CrossRef, JournalTOCs, etc..

Latest Issue
Most Viewed
Most Downloaded

IJEME Vol. 15, No. 1, Feb. 2025

REGULAR PAPERS

Analysis of Human Behavior and Interests Based on Text Data

By Irada Alakbarova

DOI: https://doi.org/10.5815/ijeme.2025.01.01, Pub. Date: 8 Feb. 2025

Information technology has revolutionized data collection and analysis, offering unprecedented opportunities to study human behavior. Various information registers, the internet of things, and electronic demographic platforms that collect and analyze user data from various online sources provide a unique opportunity to predict human behavior using machine learning methods. This study applies machine learning to analyze textual data derived from diverse sources: demographic data, scientific articles, employee documents, and social media content. The primary goal is to identify a person's area of interest and predict their behavior. We propose using Support Vector Machines (SVM) as a robust and versatile machine learning algorithm for text data analysis. SVM's ability to handle diverse data types makes it well-suited for analyzing complex human behavior patterns. By classifying documents into relevant topics, SVM can help assess how employee behavior aligns with organizational goals and performance metrics. This research aims to contribute to human behavior analysis by demonstrating the effectiveness of machine learning techniques, particularly SVM, in extracting meaningful insights from textual data.

[...] Read more.
Identifying Patterns and Trends in Campus Placement Data Using Machine Learning

By Raghavendra C K Smaran N. G. Spandana A. P. Vijay D. Vishruth M. V.

DOI: https://doi.org/10.5815/ijeme.2025.01.02, Pub. Date: 8 Feb. 2025

This research delves into the utilization of machine learning algorithms to address the urgent challenge of assisting students in navigating a highly competitive job market. Recognizing the limitations of conventional methods in delivering effective guidance for securing job opportunities, there is a growing imperative to integrate advanced technology. Our model using Machine Learning (ML) algorithms offers customized solutions and emphasizes the algorithms that exhibit the highest effectiveness within this context. In the contemporary employment, achieving success extends beyond mere academic credentials, necessitating a holistic grasp of industry trends and in-demand skills. Through the application of machine learning, a fresh approach is presented, encompassing the gathering, and preprocessing of diverse data that encompasses skill proficiencies. This data forms the bedrock upon which ML algorithms operate, predicting and enhancing students’ likelihood of securing favorable job placements. The proposed work focuses on the careful selection of suitable machine learning algorithms, with special attention given to classification techniques such as Linear Regression, Random Forest, Decision Tree Classifier, K-nearest neighbors Classifier, and ensembled models. By meticulous evaluation and Ensemble Technique, these algorithms unearth intricate patterns within the data, deciphering the multifaceted factors influencing job placement outcomes. By deconstructing the performance of each algorithm, the report provides valuable insights into their strengths and potential synergies.

[...] Read more.
A Multi-factor Based Sleep Quality Prediction System Using Machine Learning

By Hossain Ahmad Maruf Mahfuzul H. Chowdhury

DOI: https://doi.org/10.5815/ijeme.2025.01.03, Pub. Date: 8 Feb. 2025

Sleep is a critical biological process required for physical recovery, cognitive function, emotional regulation, and sound health. Conventional techniques for evaluating the quality of sleep are usually costly and intrusive, especially when they use sleep clinics and advanced sensors. Instead of using several factors to predict sleep quality, the majority of earlier studies only employed one factor and a short dataset. Their results were less accurate since they did not apply machine learning to look into the cause of poor sleep quality. This paper initiates a machine-learning (ML) based method for assessing and predicting sleep quality using a larger dataset and the Pittsburgh Sleep Quality Index (PSQI). To find the best machine learning model for predicting sleep quality, the proposed system tests eight classifiers. The results show that the Cat Boost classifier outperforms other models, with an accuracy value of 90.1%, precision value of 87%, recall value of 88%, and f1-score value of 87%. The proposed prediction model also outperformed previous works in terms of accuracy, precision, and recall by 12%, 8%, and 11%, respectively. This paper also describes a web application with features such as personalized sleep quality prediction, result checking, improvement suggestions, and doctor consultation services. According to the review results, up to 65 percent of users agreed that the proposed sleep quality assistance web application features were appropriate and necessary.

[...] Read more.
Artificial Intelligence in Security and Privacy: A Study on AI's Role in Cybersecurity and Data Protection

By Mahmoud Mohamed Khaled Alosman

DOI: https://doi.org/10.5815/ijeme.2025.01.04, Pub. Date: 8 Feb. 2025

The increase in value of security and privacy is compounded by the rapid advancements in the digital landscape sprouting new problems in information security. This research explores the use of artificial intelligence (AI) to enhance cybersecurity and to strengthen data protection. This research aims to first assess and critically evaluate the potential of applying AI methods to improve predicting, mitigating, and resolving cyber threats while addressing important ethical issues. Specifically, it wants to determine AI’s advantages compared to traditional cybersecurity ways and the plausible technological risks and ethical implications associated with its use. We show that AI tools, especially machine learning and deep learning, can greatly aid the threat detection and response automation. The rise of AI, however, brings forth new vulnerabilities and necessitates stronger ethical frameworks to preclude their misuse. This study offers a balanced view of potential with AI and hazards. The results emphasize the importance of AI in securing both the cybersecurity and data protection portfolio, and urge strongly for ethical standards to be met and the research to be continued in order to mitigate risks and promote responsible AI integration.

[...] Read more.
Enhanced Credit Card Fraud Detection Using iForest Classifier of Ensemble Learning with Automated Hyperparameter Tuning

By Kakelli Anil Kumar Akanksha Dhar Ishita Chauhan

DOI: https://doi.org/10.5815/ijeme.2025.01.05, Pub. Date: 8 Feb. 2025

Recent technological advancements have fueled a notable increase in credit card usage, consequently amplifying the prevalence of credit card fraud in both offline and online transactions. Although measures such as PIN codes, embedded chips, and supplementary keys like tokens have enhanced credit card security, financial institutions are compelled to bolster their usage controls and deploy real-time monitoring systems to promptly identify and mitigate suspicious activities. This study explores the utilization of ensemble methods, incorporating the k-nearest neighbors (KNN), Random Forest (RF), and Logistic Regression (LR) models, along with the Isolation Forest (iForest) algorithm, to enhance the efficacy of credit card fraud detection. Additionally, automated parameter optimization using GridSearchCV is employed to fine-tune the iForest model parameters. By integrating multiple classifiers into an ensemble approach and automating parameter tuning for the iForest model, our research aims to provide a robust solution capable of adapting to varying datasets and improving fraud detection accuracy. Through empirical analysis and comparison of individual models with the ensemble approach, we underscore the significance of ensemble learning and parameter optimization in enhancing fraud detection capabilities, thereby contributing to the advancement of financial security measures in the realm of credit card transactions.

[...] Read more.
Push Management Platform Based on Wechat Small Program and Cloud Development

By Yan Wu Fang Wang Yanying Zou Huaijin Zhang Bingsheng Chen Mengshan Li

DOI: https://doi.org/10.5815/ijeme.2020.01.03, Pub. Date: 8 Feb. 2020

On the Wechat platform, the current article push is mainly completed by the Wechat Public Account, but it is not perfect in the aspects of user information collection, user service, data storage and management. With economic development and progress of the times, people seek development in spiritual and cultural aspects. This program "One Thing One Story" uses Wechat Web Developer Tools as the medium and Wechat Small Program and Cloud Development as the platform. The purpose of push management platform is "use at any time". Small program cloud development has a relatively complete cloud background. It does not need to rebuild the server in the development cycle. Through the relevant interface, small program development can be started and time cost can be reduced. Using JavaScript, CSS style, JSON database and other technologies, we can realize user data collection, article push, push classification management, push data storage, user praise collection and other functions. This program is applied to article pushing, cultural dissemination and other aspects. Through the platform of Wechat applet, the dream of "accessible" can be realized. 

[...] Read more.
A Study on Malware and Malware Detection Techniques

By Rabia Tahir

DOI: https://doi.org/10.5815/ijeme.2018.02.03, Pub. Date: 8 Mar. 2018

The impact of malicious software are getting worse day by day. Malicious software or malwares are programs that are created to harm, interrupt or damage computers, networks and other resources associated with it. Malwares are transferred in computers without the knowledge of its owner. Mostly the medium used to spread malwares are networks and portable devices. Malwares are always been a threat to digital world but with a rapid increase in the use of internet, the impacts of the malwares become severe and cannot be ignored. A lot of malware detectors have been created, the effectiveness of these detectors depend upon the techniques being used. Although researchers are developing latest technologies for the timely detection of malwares but still malware creators always stay one step ahead. In this paper, a detailed review of malwares types are provided, malware analysis and detection techniques are studied and compared. Furthermore, malware obfuscation techniques have also been presented.

[...] Read more.
Stressors and Stress-Coping Mechanisms of Academic Scholars in HEIs: A Basis for Stress Management Plan Formulation

By Ruth G. Luciano Mickel John Salvatierra

DOI: https://doi.org/10.5815/ijeme.2022.03.01, Pub. Date: 8 Jun. 2022

This study aims to describe the stress coping mechanism of the academic scholars from the College of Education (COEd) in one of the private higher education institutions in Cabanatuan City, Philippines. This is an action research that focuses on the assessment of the academic scholars’ stressors and their correlates. It involves systematic observations and data collection that enables the researchers to reflect, decide and develop a training plan for stress management. The findings show that monthly family income and economic-related stressors were highly correlated. This further explains that students with high family income are less likely to experience frequent stress. In contrary, students who belong to low-income families are more prone to experience frequent stress. In other words, students who belong to poor families are more vulnerable to stress. Likewise, monthly family income and physiological responses to stress had high interdependence, which means that students with higher socio-economic status are less likely to experience severe anxiety, while students belonging to low-income families tend to experience severe anxiety. The results of this quantitative analysis served as basis in designing or preparing the stress management plan for these students. 

[...] Read more.
Medicine Management System: Its Design and Development

By Ruth G. Luciano Rhoel Anthony G. Torres Edward B. Gomez Hardly Joy D. Nacino Rodmark D. Ramirez

DOI: https://doi.org/10.5815/ijeme.2023.03.02, Pub. Date: 8 Jun. 2023

The researchers conducted this study with the main purpose of helping the residents of the municipality to expedite the process of obtaining free medicine. In the current setup, an individual who needs to avail of free medicine from the barangay or municipal health center personally visits the place to request maintenance medicine. This motivated the researchers to make a research study focusing on converting the manual requisition system to something that people can access quickly and comfortably without necessarily going out of their households, especially during these challenging times – the pandemic. The researchers called it a “Medicine Management System”. The researchers aimed to speed up the requisition of medicine using this online system. The patients or qualified recipients need not consume time lining up to request medicine from the municipal health center. This system can be accessed over the internet anytime and anywhere. Users must register and upload a legit doctor’s prescription. Researchers have created this system using HTML for the system interface, XAMPP for maintaining database records, and PHP for other system functionalities.

[...] Read more.
An Internet of Thing based Agribot (IOT- Agribot) for Precision Agriculture and Farm Monitoring

By Kakelli Anil Kumar Aju. D.

DOI: https://doi.org/10.5815/ijeme.2020.04.04, Pub. Date: 8 Aug. 2020

Developing nations like India have a huge potential for agricultural business and better cultivation. Because of the large size of cultivation land, improper water supply systems and lack of technology-based agricultural practices, there is a huge gap among expected and actual quantity and quality of agricultural products. Hence there is a need for significant revival in agribusiness using emerging technologies. The article proposes an intelligent water framework device called Agribot designed for the agricultural industry to minimize the water wastage and a better supply of cultivating materials using the Internet of Things (IoT). Our proposed IOT- Agribot will energize the water framework, improve the cost-effective water usage and reduce the labor force to achieve precision agriculture. The proposed IOT- Agribot has performed well for variable weather conditions, soli type, moisture content and crops.

[...] Read more.
Classroom Management Strategies and Academic Performance of Junior High School Students

By Maxwell Kontor Owusu Bakari Yusuf Dramanu Mark Owusu Amponsah

DOI: https://doi.org/10.5815/ijeme.2021.06.04, Pub. Date: 8 Dec. 2021

The study examined the influence of classroom management strategies of Junior High School teachers on the academic performance of students in the Ashanti Akim North District. The descriptive survey design was used for the study. One hypothesis and two research questions were developed to guide the study. Multistage sampling technique was used to select 48 teachers and 297 year two students to respond to the Behaviour and Instructional Management Scale (BIMS). Test scores in English Language, Integrated Science, Mathematics and Social Studies were used to measure students’ academic performance. The statistical tools used to analyse the data collected were means, standard deviation, Pearson’s Product Moment Correlation Coefficient (PPMCC) and Multiple Regression. The findings revealed that both students and teachers identified good relationship and reinforcement as the mostly used classroom management strategies. It was found that a significant positive relationship existed between reinforcement and antecedent as classroom management schemes and students’ academic performance. However, good relationship and punishment as classroom management strategies did not have a positive relationship with the academic performance of students. It is recommended that teachers should use reinforcement and antecedent strategies frequently in their classrooms since they play a dual role of managing behaviour and predicting the academic performance of students. Good relationship as a classroom management strategy should be cautiously used because it could potentially be misinterpreted or abused and can lead to low academic performance. Using punishment as a classroom management strategy should be avoided as its use hinders academic performance of students.

[...] Read more.
The Effectiveness of the TaRL Approach on Moroccan Pupils’ Mathematics, Arabic, and French Reading Competencies

By Abdessamad Binaoui Mohammed Moubtassime Latifa Belfakir

DOI: https://doi.org/10.5815/ijeme.2023.03.01, Pub. Date: 8 Jun. 2023

Teaching at the Right Level (henceforth, TaRL) is a new trending remedial educational approach being piloted in many countries. It basically matches pedagogical content to pupils’ educational needs through various adapted activities after segmentation of pupils’ depending on their actual difficulties and needs. In this respect, Morocco has been piloting this relatively new approach during the beginning of the school year 2022-23. Therefore, this study aimed at measuring the effectiveness of the TaRL approach on Moroccan pupils’ mathematics, Arabic, and French reading competencies. An experimental study took place involving 106 pupils from 4th grade to 6th grade during a one-month remedial course (half an hour per day, one subject per day) based on TaRL guidelines. After carefully examining the data through the Wilcoxon Signed Ranks Test by comparing the baseline and endline results in all three subjects. The results showed statistically high improvements with large effect sizes in the levels of the three subjects suggesting that TaRL was effective in raising the levels of numeracy and literacy and may be, safely, further adopted throughout Moroccan primary schools.

[...] Read more.
A Critical Review by Teachers on the Online Teaching-Learning during the COVID-19

By Malik Mubasher Hassan Tabasum Mirza Mirza Waseem Hussain

DOI: https://doi.org/10.5815/ijeme.2020.05.03, Pub. Date: 8 Oct. 2020

The world has witnessed a sudden change in the teaching-learning processes due to the ongoing pandemic of COVID-19. The worldwide compulsive lockdown for ensuring the preventive measures to stop the spread of this infection has equally affected education sector as other business sectors. As all of us know that quality education is the only long-term rescue for all the challenges and therefore, the need to find out the alternative solution to the traditional classroom teaching-learning is the concern of all stakeholders and the only option found is online mode of teaching-learning, which was somehow already available and had attracted an intense attention during this period. The aim of the paper is to study the teacher’s perspective in India about this mode of learning, challenges and issues faced by them in migration to online platform, experience about online tools/platforms used for instructional delivery and their suggestions to improve the process for effective teaching. This study will help in gaining insight towards the possible improvements in the ongoing mode of online teaching and in future situations also. The results obtained based on sample collection through web based questionnaire clearly gives some information, which could be an eye opener for enhancing the implementation of the online teaching-learning among the learners especially teachers, who can further help in implementation of the large. Although, the online mode was already in place and was utilized in blended form to a substantial level in the developed countries, but in developing countries like India, where teachers are not familiar with online platforms/tools, lack of knowledge and skills to handle the online ICT infrastructure in a challenging situation. The results also give an impression about the need of professional development with special focus on digital literacy skills and awareness among the teacher community about the merits of online platforms for the teaching-learning process.

[...] Read more.
The Digital Literacy in Teachers of the Schools of Rajouri (J&K)-India: Teachers Perspective

By M Mubasher Hassan Tabasum Mirza

DOI: https://doi.org/10.5815/ijeme.2021.01.04, Pub. Date: 8 Feb. 2021

The present age is the age of information. The globalization has affected every sphere of the life including education. In spite of availability of ICT infrastructure in schools, their potential is underutilized because of digital incompetence of the teachers.  New digital technologies are acting as a catalyst towards improvement of learning outcome and enhancing quality of education, but only introduction of such technologies in schools for producing change and innovation is not enough, it requires digitally competent teachers to facilitate the use of ICT in education. These teachers will act as facilitators and mentors to students to lead them towards problem solving and innovation to meet the new challenges of globalization. Teachers must be able to create learning environments which are student centric and foster creativity, Meta cognition, meta-literacy, collaboration and communication in learners. Mere superficial use of ICT in teaching will not yield the required learning outcome, but the integration of ICT in pedagogy is important to enhance teaching, learning process. This can be done only when teachers are competent enough to use ICT tools and facilitate ICT integrated education. In this paper, we tried to assess the teacher’s perspective about the ICT and investigate the factors responsible for resistance of teachers in using ICT in schools and suggestive measures for successful integration of ICT in the teaching process by the teachers of Rajouri district (J&K, India). The ICT skills are very important for teachers to support alternative modes of teaching, learning, i.e. e-learning, mobile learning in the present outbreak of pandemic disease caused by Coronavirus-COVID19. 

[...] Read more.
Development of a Prediction Model on Demographic Indicators based on Machine Learning Methods: Azerbaijan Example

By Makrufa Sh. Hajirahimova Aybeniz S. Aliyeva

DOI: https://doi.org/10.5815/ijeme.2023.02.01, Pub. Date: 8 Apr. 2023

The accuracy of population forecasts is one of the most important calculations in demography statistics. However, traditional demographic methods used in population projections are tend to produce biased results. The need for accurate prediction of future behavior in a number of areas require the application of reliable and efficient methods. Recently, machine learning (ML) models have emerged as a serious competitor to classical statistical models in the forecasting community. In this study, the performance and capacity of the four different ML models such as Random forest (RF), Decision tree (DT), Linear regression (LR) and K-nearest neighbors (KNN) to the prediction of population has been examined. The aim of the study is to find the best performing regression model among these machine learning algorithms for forecasting of population. The data were collected from the State Statistical Committee of the Republic of Azerbaijan website were used for the analysis. We used five metrics such as mean absolute percentage error (MAPE), mean absolute error (MAE), root mean squared error (RMSE), mean square error (MSE) and R-squared to compare the predictive ability of the models. As the result of the analysis, it has been known that the all ML models showed high results with correlation coefficient of 0.985 - 0.996. Also the KNN and RF prediction models showed the lowest root mean square deviation, means square error and mean absolute error values compared to other models. By effectively using the advantage of the ML algorithms, the forecast of population growth the near future can be observed objectively, and it can provide an objective reference to the strategic planning in the public and private sectors, particularly in education, health and social areas.

[...] Read more.
Push Management Platform Based on Wechat Small Program and Cloud Development

By Yan Wu Fang Wang Yanying Zou Huaijin Zhang Bingsheng Chen Mengshan Li

DOI: https://doi.org/10.5815/ijeme.2020.01.03, Pub. Date: 8 Feb. 2020

On the Wechat platform, the current article push is mainly completed by the Wechat Public Account, but it is not perfect in the aspects of user information collection, user service, data storage and management. With economic development and progress of the times, people seek development in spiritual and cultural aspects. This program "One Thing One Story" uses Wechat Web Developer Tools as the medium and Wechat Small Program and Cloud Development as the platform. The purpose of push management platform is "use at any time". Small program cloud development has a relatively complete cloud background. It does not need to rebuild the server in the development cycle. Through the relevant interface, small program development can be started and time cost can be reduced. Using JavaScript, CSS style, JSON database and other technologies, we can realize user data collection, article push, push classification management, push data storage, user praise collection and other functions. This program is applied to article pushing, cultural dissemination and other aspects. Through the platform of Wechat applet, the dream of "accessible" can be realized. 

[...] Read more.
Medicine Management System: Its Design and Development

By Ruth G. Luciano Rhoel Anthony G. Torres Edward B. Gomez Hardly Joy D. Nacino Rodmark D. Ramirez

DOI: https://doi.org/10.5815/ijeme.2023.03.02, Pub. Date: 8 Jun. 2023

The researchers conducted this study with the main purpose of helping the residents of the municipality to expedite the process of obtaining free medicine. In the current setup, an individual who needs to avail of free medicine from the barangay or municipal health center personally visits the place to request maintenance medicine. This motivated the researchers to make a research study focusing on converting the manual requisition system to something that people can access quickly and comfortably without necessarily going out of their households, especially during these challenging times – the pandemic. The researchers called it a “Medicine Management System”. The researchers aimed to speed up the requisition of medicine using this online system. The patients or qualified recipients need not consume time lining up to request medicine from the municipal health center. This system can be accessed over the internet anytime and anywhere. Users must register and upload a legit doctor’s prescription. Researchers have created this system using HTML for the system interface, XAMPP for maintaining database records, and PHP for other system functionalities.

[...] Read more.
A Study on Malware and Malware Detection Techniques

By Rabia Tahir

DOI: https://doi.org/10.5815/ijeme.2018.02.03, Pub. Date: 8 Mar. 2018

The impact of malicious software are getting worse day by day. Malicious software or malwares are programs that are created to harm, interrupt or damage computers, networks and other resources associated with it. Malwares are transferred in computers without the knowledge of its owner. Mostly the medium used to spread malwares are networks and portable devices. Malwares are always been a threat to digital world but with a rapid increase in the use of internet, the impacts of the malwares become severe and cannot be ignored. A lot of malware detectors have been created, the effectiveness of these detectors depend upon the techniques being used. Although researchers are developing latest technologies for the timely detection of malwares but still malware creators always stay one step ahead. In this paper, a detailed review of malwares types are provided, malware analysis and detection techniques are studied and compared. Furthermore, malware obfuscation techniques have also been presented.

[...] Read more.
An Internet of Thing based Agribot (IOT- Agribot) for Precision Agriculture and Farm Monitoring

By Kakelli Anil Kumar Aju. D.

DOI: https://doi.org/10.5815/ijeme.2020.04.04, Pub. Date: 8 Aug. 2020

Developing nations like India have a huge potential for agricultural business and better cultivation. Because of the large size of cultivation land, improper water supply systems and lack of technology-based agricultural practices, there is a huge gap among expected and actual quantity and quality of agricultural products. Hence there is a need for significant revival in agribusiness using emerging technologies. The article proposes an intelligent water framework device called Agribot designed for the agricultural industry to minimize the water wastage and a better supply of cultivating materials using the Internet of Things (IoT). Our proposed IOT- Agribot will energize the water framework, improve the cost-effective water usage and reduce the labor force to achieve precision agriculture. The proposed IOT- Agribot has performed well for variable weather conditions, soli type, moisture content and crops.

[...] Read more.
Development of a Prediction Model on Demographic Indicators based on Machine Learning Methods: Azerbaijan Example

By Makrufa Sh. Hajirahimova Aybeniz S. Aliyeva

DOI: https://doi.org/10.5815/ijeme.2023.02.01, Pub. Date: 8 Apr. 2023

The accuracy of population forecasts is one of the most important calculations in demography statistics. However, traditional demographic methods used in population projections are tend to produce biased results. The need for accurate prediction of future behavior in a number of areas require the application of reliable and efficient methods. Recently, machine learning (ML) models have emerged as a serious competitor to classical statistical models in the forecasting community. In this study, the performance and capacity of the four different ML models such as Random forest (RF), Decision tree (DT), Linear regression (LR) and K-nearest neighbors (KNN) to the prediction of population has been examined. The aim of the study is to find the best performing regression model among these machine learning algorithms for forecasting of population. The data were collected from the State Statistical Committee of the Republic of Azerbaijan website were used for the analysis. We used five metrics such as mean absolute percentage error (MAPE), mean absolute error (MAE), root mean squared error (RMSE), mean square error (MSE) and R-squared to compare the predictive ability of the models. As the result of the analysis, it has been known that the all ML models showed high results with correlation coefficient of 0.985 - 0.996. Also the KNN and RF prediction models showed the lowest root mean square deviation, means square error and mean absolute error values compared to other models. By effectively using the advantage of the ML algorithms, the forecast of population growth the near future can be observed objectively, and it can provide an objective reference to the strategic planning in the public and private sectors, particularly in education, health and social areas.

[...] Read more.
The Effectiveness of the TaRL Approach on Moroccan Pupils’ Mathematics, Arabic, and French Reading Competencies

By Abdessamad Binaoui Mohammed Moubtassime Latifa Belfakir

DOI: https://doi.org/10.5815/ijeme.2023.03.01, Pub. Date: 8 Jun. 2023

Teaching at the Right Level (henceforth, TaRL) is a new trending remedial educational approach being piloted in many countries. It basically matches pedagogical content to pupils’ educational needs through various adapted activities after segmentation of pupils’ depending on their actual difficulties and needs. In this respect, Morocco has been piloting this relatively new approach during the beginning of the school year 2022-23. Therefore, this study aimed at measuring the effectiveness of the TaRL approach on Moroccan pupils’ mathematics, Arabic, and French reading competencies. An experimental study took place involving 106 pupils from 4th grade to 6th grade during a one-month remedial course (half an hour per day, one subject per day) based on TaRL guidelines. After carefully examining the data through the Wilcoxon Signed Ranks Test by comparing the baseline and endline results in all three subjects. The results showed statistically high improvements with large effect sizes in the levels of the three subjects suggesting that TaRL was effective in raising the levels of numeracy and literacy and may be, safely, further adopted throughout Moroccan primary schools.

[...] Read more.
Classroom Management Strategies and Academic Performance of Junior High School Students

By Maxwell Kontor Owusu Bakari Yusuf Dramanu Mark Owusu Amponsah

DOI: https://doi.org/10.5815/ijeme.2021.06.04, Pub. Date: 8 Dec. 2021

The study examined the influence of classroom management strategies of Junior High School teachers on the academic performance of students in the Ashanti Akim North District. The descriptive survey design was used for the study. One hypothesis and two research questions were developed to guide the study. Multistage sampling technique was used to select 48 teachers and 297 year two students to respond to the Behaviour and Instructional Management Scale (BIMS). Test scores in English Language, Integrated Science, Mathematics and Social Studies were used to measure students’ academic performance. The statistical tools used to analyse the data collected were means, standard deviation, Pearson’s Product Moment Correlation Coefficient (PPMCC) and Multiple Regression. The findings revealed that both students and teachers identified good relationship and reinforcement as the mostly used classroom management strategies. It was found that a significant positive relationship existed between reinforcement and antecedent as classroom management schemes and students’ academic performance. However, good relationship and punishment as classroom management strategies did not have a positive relationship with the academic performance of students. It is recommended that teachers should use reinforcement and antecedent strategies frequently in their classrooms since they play a dual role of managing behaviour and predicting the academic performance of students. Good relationship as a classroom management strategy should be cautiously used because it could potentially be misinterpreted or abused and can lead to low academic performance. Using punishment as a classroom management strategy should be avoided as its use hinders academic performance of students.

[...] Read more.
Stressors and Stress-Coping Mechanisms of Academic Scholars in HEIs: A Basis for Stress Management Plan Formulation

By Ruth G. Luciano Mickel John Salvatierra

DOI: https://doi.org/10.5815/ijeme.2022.03.01, Pub. Date: 8 Jun. 2022

This study aims to describe the stress coping mechanism of the academic scholars from the College of Education (COEd) in one of the private higher education institutions in Cabanatuan City, Philippines. This is an action research that focuses on the assessment of the academic scholars’ stressors and their correlates. It involves systematic observations and data collection that enables the researchers to reflect, decide and develop a training plan for stress management. The findings show that monthly family income and economic-related stressors were highly correlated. This further explains that students with high family income are less likely to experience frequent stress. In contrary, students who belong to low-income families are more prone to experience frequent stress. In other words, students who belong to poor families are more vulnerable to stress. Likewise, monthly family income and physiological responses to stress had high interdependence, which means that students with higher socio-economic status are less likely to experience severe anxiety, while students belonging to low-income families tend to experience severe anxiety. The results of this quantitative analysis served as basis in designing or preparing the stress management plan for these students. 

[...] Read more.
The Digital Literacy in Teachers of the Schools of Rajouri (J&K)-India: Teachers Perspective

By M Mubasher Hassan Tabasum Mirza

DOI: https://doi.org/10.5815/ijeme.2021.01.04, Pub. Date: 8 Feb. 2021

The present age is the age of information. The globalization has affected every sphere of the life including education. In spite of availability of ICT infrastructure in schools, their potential is underutilized because of digital incompetence of the teachers.  New digital technologies are acting as a catalyst towards improvement of learning outcome and enhancing quality of education, but only introduction of such technologies in schools for producing change and innovation is not enough, it requires digitally competent teachers to facilitate the use of ICT in education. These teachers will act as facilitators and mentors to students to lead them towards problem solving and innovation to meet the new challenges of globalization. Teachers must be able to create learning environments which are student centric and foster creativity, Meta cognition, meta-literacy, collaboration and communication in learners. Mere superficial use of ICT in teaching will not yield the required learning outcome, but the integration of ICT in pedagogy is important to enhance teaching, learning process. This can be done only when teachers are competent enough to use ICT tools and facilitate ICT integrated education. In this paper, we tried to assess the teacher’s perspective about the ICT and investigate the factors responsible for resistance of teachers in using ICT in schools and suggestive measures for successful integration of ICT in the teaching process by the teachers of Rajouri district (J&K, India). The ICT skills are very important for teachers to support alternative modes of teaching, learning, i.e. e-learning, mobile learning in the present outbreak of pandemic disease caused by Coronavirus-COVID19. 

[...] Read more.
An Empirical Study on Make-or-buy Decision Making

By Monika Arora Anand Kumar

DOI: https://doi.org/10.5815/ijeme.2022.01.03, Pub. Date: 8 Feb. 2022

Every enterprise will be based on the other enterprise to manufacture, product items/parts, for make or buy. The make-buy decision is based on the assessment whether it should be manufactured or buy it from an outside supplier to produce a component internally or to buy it from the outside. It depends on cost and profitability. The cost for both the alternatives may be calculated and the alternative with less cost is to be chosen. The aim of any enterprise is to improve its performance that is measured in terms of profitability. There is some research that has been carried out to make the decision based on profitability of the enterprise for make or buy decision.  The strategy is based on cost, flexibility and responsiveness of work to be carried out. However, some of the research is required to maintain the relationship between profitability and make or buy decision.

The reports of this paper attempt made on how buying decision influences the performances of an enterprise. The different sectors were chosen for the study such as Manufacturing, Automobile, Food, Textile and Hospitality. The focus of the study was based on three theories such as operational control, performance management and decision. The paper reveals the current trends and make or buy decision of the components and its relationship in taking decisions. It also discusses the two techniques break even analysis and economic analysis for decision making in make or buy decision. The study discusses the advantage of outsourcing and discusses the four theories in the study for make and buys decision

[...] Read more.