International Journal of Education and Management Engineering (IJEME)

IJEME Vol. 11, No. 6, Dec. 2021

Cover page and Table of Contents: PDF (size: 606KB)

Table Of Contents

REGULAR PAPERS

Design Online Learning System for Kampus Merdeka: A Case Study Web Programming Course

By Budi Harijanto Meyti Eka Apriyani Elok Nur Hamdana

DOI: https://doi.org/10.5815/ijeme.2021.06.01, Pub. Date: 8 Dec. 2021

Distance learning is an online-based learning model with an open model or a combination of face-to-face learning models. Currently, the term "Independence Campus" implies that students are given the option of attending lectures on campus or off campus according to their talents and interests, one of which does not leave the nature of online lectures. Currently, the learning model that can provide one of these facilities is the Massive Online Open Course (MOOC). This online learning can provide access anywhere and anytime by integrating technology into the learning process that can help improve the ability to understand the material. In this study, it will be measured how learning design using MOOC for "Kampus Merdeka" can affect the implementation of lectures, especially for the Web Programming Design course. A trial will be conducted to be able to see the effect of the implementation of the use of MOOC on the users of this MOOC. The choice of case studies for this course is because this course can provide practical learning activities that require an understanding of a strong theoretical basis so that it can be implemented in practicum. The result of learning web programming with the online learning design method using MOOC, which is useful for students is that they can practice source code directly through MOOC. In this study, the effect of using online learning design with MOOC which was attended by 30 people showed that an average of 78.2% was interested in joining MOOC online classes. This interest is because MOOC can provide self-development models such as material in the syllabus, learning videos and the ability to do practicals

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E-Government in Pakistan – Implementation and Challenges

By Uzair Ahmed Siddiqui Waqas Mehmood

DOI: https://doi.org/10.5815/ijeme.2021.06.02, Pub. Date: 8 Dec. 2021

Today, the explosion of information and ever-improving digital connectivity has revolutionized the way business is performed, how organizations work, how the simplest of everyday chores are supposed to be done. A new world order has emerged; with newer, disruptive innovative ideas being incepted at a pace more than anyone could’ve ever imagined only a few decades ago.

Public organizations; just like private ones, had to re-invent themselves in order to sustain and keep up with the increasing expectations of digital and effective public service delivery; From conventional government to E-Government.

Implementation of e-Government solutions and strategies has become the topmost prerequisite of good governance in today’s globalized world, yet it remains a challenge in most of the developing countries including Pakistan. Despite countless efforts of the federal and provincial government in trying to go paperless, there remains a gap between the government and citizens, in the context of service delivery and between government employees and administration in the context of effective business process transformations. This paper aims to:

•Study different models and indexes devised by scholars and organizations worldwide

•Current implementations and the reasons behind their success or failure; based on interviews with people engaged in implementations of different digital solutions.

•Study key contrasts in current and proposed business processes and their implications

•Study key contrasts between ICT implementation strategies adopted by different counties

•Identify recommendations and options for the government including institutional and cultural reforms for effective business transformation and service delivery

•Engage with the people directly involved with the current and previous implementations of e-government applications in the country to provide the crux of all the challenges faced in different parts of the country.

•Act as a roadmap for future ICT implementations in the country.

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Behavioral Changes of Children Intelligence for the Extreme Affection of Parents

By Prodipto Bishnu Angon Sujit Mondal Chandona Rani Das Mintu Kumar Bishnu

DOI: https://doi.org/10.5815/ijeme.2021.06.03, Pub. Date: 8 Dec. 2021

A nation's most valuable resource is its children. In the future, a nation will be controlled in the same way that a kid will develop. The majority of parent’s lack expertise about how to help their children develop a positive outlook. We concluded in our study by analyzing the association between parental excessive affection and the development of children's intelligence. Through the use of a questionnaire, information was gathered from 531 families. Whereas 43 percent of parents show excessive affection to their children, while 45 percent lavish proper affection. On the other hand, in our study, 48 percent of the children had an IQ score of less than 49. We have identified the alterations in their child's brain as a result of their parents' blind affection and have also identified remedies to the problem. We analyzed it so that the growth of children's intelligence is not hampered by their parents' excessive affection and that the parents and children enjoy a close relationship with their parents.

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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.

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Bangla News Headline Categorization

By Amran Hossain Niraj Chaudhary Zahid Hasan Rifad B M Mainul Hossain

DOI: https://doi.org/10.5815/ijeme.2021.06.05, Pub. Date: 8 Dec. 2021

News categorization from various newspapers is important as readers want to read the news by category. But, the readers face difficulty if the news from different categories is presented without any order. This study aims to determine the category of news from online Bangla newspapers. In this context Bangla news headlines data, along with its categories, were collected from various online newspapers through scrapping. Eight categories of news are considered for this work and the headlines of the news are used for categorization. The input data is modeled by the LSTM and GRU neural networks, and the predicted category is compared with the actual category. For LSTM model, the result gives an accuracy of 82.74% and GRU model, The result gives an accuracy of 87.48%. GRU accuracy is higher than LSTM.

Because, GRU training performance is faster than that of LSTM. In GRU 64 units used and in LSTM 128 units used for this research. For this reason, it also suggests that the GRU model gives better results than that of LSTM. 

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