Towards an Efficient Integrated Distance and Blended Learning Model: How to Minimize the Impact of COVID-19 on Education
subject: Distance learning
subject: COVID-19 Pandemic
subject: e-learning
subject: Perceptions
subject: Modeling
subject: Competency
description: As governments and international bodies worldwide sought to prevent the spread of Covid-19, underdeveloped countries have been particularly challenged as they have little or no technological models and frameworks in place and the literature offers little guidance. The current research applied a quantitative approach to researching educational practitioners’ perceptions of e-learning acceptance, using a sample of 4,024 educators and students from a range of Kuwaiti educational institutions. Findings indicate that respondents were slightly supportive of e-learning adoption, with a majority acknowledging its advantages. However, respondents also mention the need for development in the technological competencies required to operate the proposed e-learning programs and a range of challenges that may impact e-learning. Hence, the authors propose a distance and blended learning model (DBLM) to enhance the implementation, utilisation, and evaluation of e-learning within the Kuwaiti educational system. Also, an e-learning teacher capability maturity model (eTCMM) was proposed to foster educators’ competencies and enable their active use of e-learning platforms.
creator: Al-Hunaiyyan, Ahmed
creator: Alhajri, Rana
creator: Bimba, Andrew
source: International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 10 (2021); pp. 173-193
source: 1865-7923
publisher: International Association of Online Engineering (IAOE), Vienna, Austria
date: 2021-05-25
rights: Copyright (c) 2021 Ahmed Al-Hunaiyyan, Rana Alhajri, Andrew Bimba
format: application/pdf
language: eng
type: info:eu-repo/semantics/article
type: info:eu-repo/semantics/publishedVersion
type: Peer-reviewed Article

Fog Computing Based on Machine Learning: A Review
subject: Fog Computing
subject: Machine Learning
subject: IoT
subject: Optimization
description: Internet of Things (IoT) systems usually produce massive amounts of data, while the number of devices connected to the internet might reach billions by now. Sending all this data over the internet will overhead the cloud and consume bandwidth. Fog computing's (FC) promising technology can solve the issue of computing and networking bottlenecks in large-scale IoT applications. This technology complements the cloud computing by providing processing power and storage to the edge of the network. However, it still suffers from performance and security issues. Thus, machine learning (ML) attracts attention for enabling FC to settle its issues. Lately, there has been a growing trend in utilizing ML to improve FC applications, like resource management, security, lessen latency and power usage. Also, intelligent FC was studied to address issues in industry 4.0, bioinformatics, blockchain and vehicular communication system. Due to the ML vital role in the FC paradigm, this work will shed light on recent studies utilized ML in a FC environment. Background knowledge about ML and FC also presented. This paper categorized the surveyed studies into three groups according to the aim of ML implementation. These studies were thoroughly reviewed and compared using sum-up tables. The results showed that not all studies used the same performance metric except those worked on security issues. In conclusion, the simulations of proposed ML models are not sufficient due to the heterogeneous nature of the FC paradigm.
creator: Samann, Fady Esmat Fathel
creator: Abdulazeez, Adnan Mohsin
creator: Askar, Shavan
source: International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 12 (2021); pp. 21-46
source: 1865-7923
publisher: International Association of Online Engineering (IAOE), Vienna, Austria
date: 2021-06-18
rights: Copyright (c) 2021 Fady Esmat Fathel Samann, Adnan Mohsin Abdulazeez
format: application/pdf
language: eng
type: info:eu-repo/semantics/article
type: info:eu-repo/semantics/publishedVersion
type: Peer-reviewed Article

MODEL-Based Performance Quality Assessment for IoT Applications
subject: internet of things
subject: IoT
subject: prediction
subject: MBT
subject: quality assurance
subject: performance prediction.
description: The number of applications incorporating Internet of Things (IoT) concepts increases extraordinarily. This increase cannot continue without high-quality assurance. There are some difficulties in testing IoT applications; the system heterogeneity, test cost and time are taken to test the system, and the precision percentage of test results.A well-known and possibly the best solution to overcoming these difficulties is to model the system for evaluation purposes, known as model-based testing (MBT). This paper aims to design a model-based testing approach to assess IoT applications performance quality attributes. The ISO 25000 quality model is used as a standard for software quality assurance applications. IoTMaaS is used as a case study to implement the methodological approach. The possible test cases were generated using the ACTS combinatorial test generation tool. The performance metrics of each test case were monitored until the optimum test case was identified, with the shortest response time and the least amount of resources used. The proposed testing method appears to be successful, according to the results.
creator: Kh., Teeba Ismail
creator: Hamarash, Ibrahim I.
source: International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 12 (2021); pp. 4-20
source: 1865-7923
publisher: International Association of Online Engineering (IAOE), Vienna, Austria
date: 2021-06-18
rights: Copyright (c) 2021 Teeba Ismail Kh., Ibrahim I. Hamarash
format: application/pdf
language: eng
type: info:eu-repo/semantics/article
type: info:eu-repo/semantics/publishedVersion
type: Peer-reviewed Article

Design an Adaptive Mobile Scaffolding System According to Students’ Cognitive Style Simplicity vs Complexity for Enhancing Digital Well-Being
subject: adaptive mobile scaffold system (AMSS)
subject: Cognitive style simplicity vs complexity (CSSC)
subject: digital will-being (DWB)
description: The present study is aimed to design an adaptive mobile scaffolding System (AMSS) to provide educational scaffolding to students that is compatible with their cognitive style simplicity vs complexity (CSSC), and to measure the effectiveness of the model in enhancing students' digital well-being (DWB) in the Faculty of education, University of XXXX. Semi-experimental design of two groups was used: the first experimental group received unified mobile scaffold regardless of their cognitive styles. The second experimental group received mobile scaffold that was organized and directed to the students based on their characteristics related to their CSSC. Both experimental groups received mobile scaffold as a complementary component to the lectures delivered for the Technological Innovations in Education course in the General Diploma in Education. The study sample consisted of (71) students who met the requirements and they were randomized to two experimental groups. To examine the effectiveness of the AMSS, a DWB scale was developed. Kelly's scale of CSSC was used to identify students who fell within the scope of this style. The results were statistically analyzed using T-test to compare between the groups and to determine the significance of differences. The results showed the effectiveness of the proposed model of AMSS in developing the students’ DWB compared to the unified scaffold model.
creator: Alhalafawy, Waleed Salim
creator: Najmi, Ali Hassan
creator: Zaki, Marwa Zaki Tawfiq
creator: Alharthi, Majed Hamed
source: International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 13 (2021); pp. 108-127
source: 1865-7923
publisher: International Association of Online Engineering (IAOE), Vienna, Austria
date: 2021-07-13
rights: Copyright (c) 2021 waleed salim alhalafawy, Ali Hassan Najmi, Marwa Zaki Tawfiq Zaki, Majed hamed Alharthi
format: application/pdf
language: eng
type: info:eu-repo/semantics/article
type: info:eu-repo/semantics/publishedVersion
type: Peer-reviewed Article

Designing Cuckoo Based Pending Interest Table for CCN Networks
description: Content Centric Networking (CCN) is a modern architecture that got wide attention in the current researches as a substitutional for the current IP-based architecture. Many studies have been investigated on this novel architecture but only little of them focused on Pending Interest Table (PIT) which is very important component in every CCN router. PIT has fundamental role in packet processing in both upstream process (Interest packets) and downstream process (Data packets). PIT must be fast enough in order to not become an obstruction in the packet processing and also it must be big enough to save a lot of incoming information. In this paper, we suggest a new PIT design and implementation named CF-PIT for CCN router. Our PIT design depends on modifying and utilizing an approximate data structure called Cuckoo filter (CF). Cuckoo filter has ideal characteristics like: high insertion/query/deletion performance, acceptable storage demands and false positive probability which make it with our modification convenient for PIT implementation. The experimental results showed that our CF-PIT design has high performance in different side of views which make it very suitable to be implemented on CCN routers.
creator: Alhisnawi, Mohammad
creator: Abdulhassan, Aladdin
source: International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 07 (2021); pp. 140-153
source: 1865-7923
publisher: International Association of Online Engineering (IAOE), Vienna, Austria
date: 2021-04-09
rights: Copyright (c) 2021 Ahmed J. obaid
format: application/pdf
language: eng
type: info:eu-repo/semantics/article
type: info:eu-repo/semantics/publishedVersion
type: Peer-reviewed Article

Gamification Design Elements to Enhance Adolescent Motivation in Diagnosing Depression
subject: adolescent depression
subject: adolescent motivation
subject: gamification
subject: model development
subject: human-computer interaction
description: Depression is a critical public health problem, mainly when it affects young people (adolescents). This condition is most challenging to detect in this group because they tend to think about other people's negative assumptions. Adolescents with depressive symptoms refuse to seek professional help due to their stigma and their future if they were labeled as depressed teenagers. Depression is a severe mental issue that should be detected from an early stage so that the problem can be curbed and resolved immediately. Diagnosis should be carried out to assess mental health, followed by referral to professional help. This study aims to motivate adolescents to diagnose depression levels through gamification techniques. Fifty-three secondary students participated in a survey designed in this study to measure motivation enhancement factors. The result of this study was used to develop a depression diagnosis model. The proposed model applied a gamification design technique consisting of three main ideas: gamification elements, user types, and motivational elements. This model will serve as the foundation to develop a mobile application system that can benefit users, especially adolescents, in self-diagnosing depression.
creator: Jamaludin, Nurul Fasihah
creator: Tengku Wook, Tengku Siti Meriam
creator: Mat Noor, Siti Fadzilah
creator: Qamar, Faizan
source: International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 10 (2021); pp. 154-172
source: 1865-7923
publisher: International Association of Online Engineering (IAOE), Vienna, Austria
date: 2021-05-25
rights: Copyright (c) 2021 Nurul Fasihah Jamaludin, Tengku Siti Meriam Tengku Wook, Siti Fadzilah Mat Noor, Faizan Qamar
format: application/pdf
language: eng
type: info:eu-repo/semantics/article
type: info:eu-repo/semantics/publishedVersion
type: Peer-reviewed Article

Adoption of Mobile Learning: The Influence And Opportunities For Learning During The Covid-19 Pandemic
subject: Adoption of mobile learning
subject: covid pandemic 19
subject: online learning
subject: student inter-ests
description: Research It is designed using quantitative and qualitative approaches. The sampling technique used in this study was purposive sampling. The samples in this study were lecturers and students. Data collection techniques using questionnaires and interviews. Interviews were conducted by interviewing lecturers at several different campuses. The results of the interview show that mobile learning is the learning that students are most interested in because it can be accessed through their cellphones. Quantitative data analysis used the product-moment correlation test. The research subjects consisted of 110 students. The significance level of 0.001 (p <0.05) indicates that there is a significant influence between the adoption of mobile learning on student interest in learning during the Covid pandemic 19.
creator: Pebriantika, Leni
creator: Wibawa, Basuki
creator: Paristiowati, Maria
source: International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 05 (2021); pp. 222-230
source: 1865-7923
publisher: International Association of Online Engineering (IAOE), Vienna, Austria
date: 2021-03-16
rights: Copyright (c) 2021 Leni Pebriantika, Basuki Wibawa, Maria Paristiowati
format: application/pdf
language: eng
type: info:eu-repo/semantics/article
type: info:eu-repo/semantics/publishedVersion
type: Non-refereed Article

The Use of AR Technology to Overcome Online Shopping Phobia: A Systematic Literature Review
subject: Online Shopping
subject: Augmented Reality
subject: AR Technology
subject: Shopping Phobia
description: With every year’s start being a new beginning and a source of happiness, reigniting hopes and optimism around the world, the happiness and enjoyment of the year 2020 faded away quite earlier. It was not long into the year 2020 that the notorious COVID-19 hit the world. Millions of people died of it and billions of people got affected by it either directly or indirectly. With its impact on everybody, it drastically affected the business world as well; individuals lost their jobs and companies lost their businesses. However, companies learned to respond to the pandemic by converting their businesses to the online business model and the customers also shifted to online shopping. With this compelling shift, the customers still had the phobia of online shopping and tried to abstain from it as much as possible. To respond to this, a systematic review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was developed to offer a systematic and holistic literature review of the research regarding customer confidence in online shopping particularly by the use of Augmented Reality (AR) technology. The database of this review includes a set of 54 systemically selected state-of-the-art articles from Scopus database covering empirical and theory research conducted in different countries with different resource endowments. The results show that the use of AR technology can help customers in overcoming their shopping phobia and thus, it can be a source of enhanced online business for companies. Some possible opportunities for future research are also illustrated in this paper.
creator: Shah Kazmi, Syed Sibtain Ali
creator: Hassan, Muhammad
creator: Khawaj, Shahid Ali
creator: Falindah Padlee, Siti
source: International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 05 (2021); pp. 127-139
source: 1865-7923
publisher: International Association of Online Engineering (IAOE), Vienna, Austria
date: 2021-03-16
rights: Copyright (c) 2021 Syed Sibtain Ali Shah Kazmi, Muhammad Hassan, Shahid Ali Khawaj, Dr. Stit Falindah Padlee
format: application/pdf
language: eng
type: info:eu-repo/semantics/article
type: info:eu-repo/semantics/publishedVersion
type: Peer-reviewed Article

Predictive Analytic on Human Resource Department Data Based on Uncertain Numeric Features Classification
subject: Predictive Analytic
subject: Naïve Bayes
subject: Business Intelligence
subject: Human Resource
description: Business Intelligence is very popular and useful for a better understanding of business progress these days, and there are many different methods or tools being used in Business Intelligence. It uses combination of artificial intelligence, data mining, math, and statistic to gain better understanding and insight on the business process performance. As employees have an important role in business process, the desire to have a tool for classifying and predicting their wages are desirable. In this research, we tried to analyzed dataset from Human Resource Department, and this dataset can be used to analyst the data in order to draw a conclusion about whether any employees would prematurely leave the company, and then, a preventive action based on those parameters can be proposed. This is a kind of predictive analytic system which bases on Naïve Bayes, and it can predict whether an employee would leave or stay according to his or her characteristics. But the Naïve Bayes itself does not enough. So we develop a way to solve the problem using uncertain Numeric features classification on it. The accuracy of the result is depended on the amount and effectiveness of the training sets.
creator: Huda, Asrul
creator: Ardi, Noper
source: International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 08 (2021); pp. 172-181
source: 1865-7923
publisher: International Association of Online Engineering (IAOE), Vienna, Austria
date: 2021-04-23
rights: Copyright (c) 2021 Asrul Huda, Noper Ardi
format: application/pdf
language: eng
type: info:eu-repo/semantics/article
type: info:eu-repo/semantics/publishedVersion
type: Non-refereed Article

Augmented Reality Technology as a Complement on Graphic Design to Face Revolution Industry 4.0 Learning and Competence: The Development and Validity
subject: Augmented Reality
subject: Revolution Industry 4.0
subject: Graphic Design
subject: Validity
description: This study aims at developing the augmented reality application technology, a complementary learning on graphic design to face the skills and learning of the industrial revolution 4.0. This study uses a 4D (four-D) development method for the development of augmented reality application technology and uses a survey method for validity. This AR application will be validated by 12 experts, while the respondents used in filling out the needs analysis questionnaire at the define stage (four-D) are students and lecturers of Informatics Engineering Education, Padang State University. The results of this study indicate that on the analysis of the achievement of the learning process, it can be seen that there are still expectations and advantages in the achievement of the learning process desired by lecturers and students, where the learning process is still in the sufficient category and 80%, students need development of technology as complement reality to be used as learning media in the learning process. The validation test also shows that the augmented reality application technology is included in the valid category with an average value of V value of 0.933. So, it cannot be denied that the augmented reality application technology is valid to be used in the learning process.
creator: Huda, Asrul
creator: Azhar, Nelda
creator: Almasri, Almasri
creator: Wulansari, Rizky Ema
creator: Mubai, Akrimullah
creator: Sakti, Rizki Hardian
creator: Firdaus, Firdaus
creator: Hartanto, Suryo
source: International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 05 (2021); pp. 116-126
source: 1865-7923
publisher: International Association of Online Engineering (IAOE), Vienna, Austria
date: 2021-03-16
rights: Copyright (c) 2021 Asrul Huda, Nelda Azhar, Almasri Almasri, Rizky Ema Wulansari, Akrimullah Mubai, Rizki Hardian Sakti, Firdaus Firdaus, Suryo Hartanto
format: application/pdf
language: eng
type: info:eu-repo/semantics/article
type: info:eu-repo/semantics/publishedVersion
type: Peer-reviewed Article