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1.
International Journal of Emerging Technologies in Learning (Online) ; 17(20):4-19, 2022.
Article in English | ProQuest Central | ID: covidwho-2099974

ABSTRACT

This study contributes to the existing literature on online learning during COVID-19 pandemic in higher education by investigating the relationships between the cognitive variables and students' adoption of online learning. Based on Technology Acceptance Model (TAM), some hypotheses we formulated to test the links between TAM constructs and online learning anxiety as an antecedent. This study adopted structural equation modeling (SEM) to scrutinize technology adoption for a sample of 569 students in Oman. The results indicated that attitude towards online learning is a strong predictor of technology adoption during COVID-19 pandemic. Furthermore, both the perceived usefulness of online learning and perceived ease of online use yielded a significant contribution of attitude. Besides, online learning anxiety affected both the perceived usefulness and perceived ease of online use negatively where perceived ease of use is predicted largely while perceived usefulness is predicted modestly. In the light of the previous findings, some recommendations and implications are provided.

2.
TELKOMNIKA ; 20(6):1248-1255, 2022.
Article in English | ProQuest Central | ID: covidwho-2080976

ABSTRACT

This research aimed to evaluate the performance of the A Lite BERT (ALBERT), efficiently learning an encoder that classifies token replacements accurately (ELECTRA) and a robust optimized BERT pretraining approach (RoBERTa) models to support the development of the Indonesian language question and answer system model. The two problems above, namely sorting candidate documents and validating answers have been handled by several methods such as the application of long-short term memory-recurrent neural network (LSTM-RNN) [12], template convolutional recurrent neural network (T-CRNN) [13], CNN-BiLSTM [14], dynamic co-attention networks (DCN) [15]. [...]section 4 presents the conclusion of the paper. Based on the proposed method in Figure 1, the article about coronavirus disease 2019 (COVID'19) news (we got it from crawling results on Indonesian Wikipedia, Jakarta News, Okezone, Antara, Kumparan, Tribune, and Open Super-large Crawled ALMAnaCH coRpus (OSCAR)) which is the input data for our study in preprocessing and converting the format to be used as input data for our study as a knowledge base system.

3.
i-Manager's Journal on Information Technology ; 11(1):35-47, 2022.
Article in English | ProQuest Central | ID: covidwho-2056928

ABSTRACT

The Internet has changed everyone's life. Social networks may have only been initiated with the help of the Internet. Today's generation is using the internet, which means social media like Snap-chat, Twitter, Facebook, etc., is increasing. Hence, the purpose of this paper is to understand the positive and negative outcomes of social media. In addition, this paper discusses the current situation, the previous situation, and the situation where people do not have social networks. Finally, the influence of social networks on different stages of a person's life is described.

4.
International Journal of Emerging Technologies in Learning (Online) ; 17(18):118-135, 2022.
Article in English | ProQuest Central | ID: covidwho-2055560

ABSTRACT

There have been many studies on technology-supported learning based on cognitive theory in the literature. However, little is known about GeoGebra-assisted social cognitive learning in supporting students' reasoning abilities for online learning during the COVID-19 pandemic. This study aims to examine and analyze the differences in the improvement of students' mathematical reasoning abilities who follow GeoGebra-assisted social cognitive learning (Geo-SCL) and GeoGebra-assisted problem-based learning (Geo-PBL). This study used a quantitative method with a quasi-experimental nonequivalent pre-test post-test control-group design. The sample consisted of 70 students from XI SMA Negeri 8 in Bandung, Indonesia. Before and after therapy, research data were collected using a mathematical reasoning test consisting of 5 essay questions. Paired sample t-test analysis and independent t-test were used to answer the research hypothesis. The results of the study concluded that students who studied with Geo-SCL obtained a higher increase in mathematical reasoning abilities than students who studied with Geo-PBL, with the criteria for improving abilities in both classes being in the moderate category. Research findings related to the application of Geo-SCL can be an alternative learning model in online learning situations.

5.
Contemporary Educational Technology ; 14(3), 2022.
Article in English | ProQuest Central | ID: covidwho-2040646

ABSTRACT

The subject of the study is the psychological difficulties of adopting distance education technologies by university students. The materials of exploratory research obtained on a sample of students from several universities of the Sakha Republic (Yakutia) are presented. The study involved respondents aged 19 to 22 (N = 86), 39% of whom were males. In the research, the unstructured interview method was used, during which we asked students to share in detail about their user experience, describing not only the learning process itself but the whole learning context in general. Considering the results using the TAM model, it can be assumed that students are not satisfied with any of the components. Distance learning technologies are not perceived by students as easy to use, and there is a low assessment of the perceived usefulness of these technologies. The attitude towards technology is also rather negative. From the point of view of student acceptance of technology, it can be said that distance learning causes some difficulties associated with cognitive, and emotional aspects, as well as interaction in a virtual environment, and the learning process. Learning creates anxiety and dissatisfaction with the learning process itself.

6.
Contemporary Educational Technology ; 14(3), 2022.
Article in English | ProQuest Central | ID: covidwho-2040644

ABSTRACT

The COVID-19 outbreak has wreaked havoc on educational systems on a scale never seen before in history. The closure of schools and other institutions of learning has impacted 94% of the world’s student population. Even school closures, such as those that occur during the summer, have a significant effect on children’s academic ability. The word “learning loss” refers to any loss of information and abilities, whether specific or generic. By Fall 2020, extended absences from school will have a detrimental effect on student achievement. Learning loss is commonly addressed when schools close for extended periods of time during the summer, natural catastrophes, or epidemics. Even brief school closures might result in significant loss of learning. Due to the global nature of the COVID-19 epidemic, special attention was devoted to learning losses. During the pandemic, learning loss occurs as a result of kids studying at home due to school closures. School closures do not have to result in an equal loss of learning for all students. The variables that contribute to learning loss include “change in teaching methods”, “opportunities to reach education”, “less time for learning”, and “emotional factors”. Reduced instructional time–provided by teachers in accordance with the national curriculum–is likely to result in loss of learning. Due to the disparate scales used in the studies, it is hard to compare the magnitudes of learning losses. However, based on the data from the studies, it is reasonable to assume that these nations are investigating learning losses and that they exist. As a result, there is convincing evidence that students lose more information during lockdown than they do over the course of a normal school year. The elements causing learning losses differ according to context. With the reopening of schools, it is important to establish the actual magnitude of learning losses and to implement remedial measures in order to avoid the emergence of medium- and long-term educational difficulties.

7.
Contemporary Educational Technology ; 14(3), 2022.
Article in English | ProQuest Central | ID: covidwho-2040643

ABSTRACT

The use of educational computer games in the context of the coronavirus pandemic is becoming increasingly popular in the educational process when studying a variety of disciplines. And if practical steps have been taken in this direction in technical, pedagogical, and some other sciences, then there is a doctrinal and practical gap in the teaching of legal disciplines that needs to be filled. The purpose of the study is to argue the prospects for the use of educational computer games at law faculties, which makes it possible to more effectively assess students’ knowledge, as well as increase their motivation to actively participate in the educational process. In the course of the study, methodology involved the theoretical and practical experience of developing educational computer games in various academic disciplines was summarized, the scientific literature and the existing practice of their use were analyzed, and the possible effect of introducing educational computer games into the educational process at law faculties after the development and implementation of such games in practice, including the first-generation educational computer game developed by the authors, was modeled. The research findings indicate formulation of a doctrinal concept of the use of educational computer games, identifies three of their generations, and shows the features of the development and application of each of them, including the author’s experience in developing a training computer game by right of the first generation. The authors analyzed the technical problems associated with the development of educational computer games and suggested ways to solve them. The authors’ proposals can be used by universities in any country to interact with game design studios to develop educational games.

8.
IEEE Technology & Society Magazine ; 41(3):58-70, 2022.
Article in English | ProQuest Central | ID: covidwho-2037841

ABSTRACT

Amid the COVID-19 pandemic, governments around the world have been facing an increased spread of disinformation on social media by foreign and domestic actors. The COVID-19 pandemic has highlighted the challenges of online disinformation facing governments and societies globally, including Canada. Indeed, disinformation is increasingly being framed by supranational institutions and states as a threat to democracy, prompting legislative and policy interventions [1] . However, much of the scholarly work thus far on disinformation has focused on social media content that is publicly available and open to the wider public. This article, on the other hand, aims to shed light on disinformation encountered through private messaging platforms (e.g., WhatsApp, Facebook Messenger, WeChat, and so on).

9.
i-Manager's Journal on Information Technology ; 11(1):1-9, 2022.
Article in English | ProQuest Central | ID: covidwho-2030577

ABSTRACT

The coronavirus (COVID-19) pandemic is causing a worldwide health catastrophe, so according to the World Health Organization (WHO), wearing masks in public is an effective safety method. The COVID-19 pandemic has forced governments around the world to impose quarantines to prevent transmission of the virus. According to reports, wearing masks in public does reduce the threat of transmission of the virus. An efficient and cost-effective way to use Artificial Intelligence (AI) to create a secure environment in a manufacturing environment. A hybrid model for using a deep and classic face mask detection device will be proposed. The face mask detection dataset includes the mask, and without mask photos, it uses the Open-Source Computer Vision Library (OpenCV) to detect faces in real-time from the stay circulation through the webcam. It uses the dataset to build a computer vision COVID-19 face mask detector using Python, OpenCV, TensorFlow, and Keras. Using computer vision and deep learning, the goal is to understand whether a character in a picture or video stream is wearing a mask or not using computer vision and deep learning.

10.
The International Journal of Technologies in Learning ; 30(1):1-16, 2022.
Article in English | ProQuest Central | ID: covidwho-2030482

ABSTRACT

Online distance learning became a lifeline for many universities and schools worldwide during the COVID-19 lockdown. However, developing countries have had several obstacles to transform education into online learning. This study presents an investigation of the transformation from traditional learning (face-to-face learning) to online learning at Imam Abdulrahman bin Faisal University (IAFU). This paper aims to study the online learning structure which has been adopted by the College of Education at IAFU during the COVID-19 pandemic. There is a need to investigate the online distance learning transformation phase to provide a better understanding of the adopted framework, applications which are in use, and challenges. A quantitative approach was adopted as the research methodology, with data via two online questionnaires. There were ninety-seven responses from the faculty and 250 responses from students. This research addressed the gap in knowledge on online learning for higher education in Saudi Arabia. The study showed growing interest among both the faculty and students in completing their learning online. About eighty percent of the responses preferred to use Zoom software as the main software platform for online learning. The results include reports of several challenges which students faced such as: poor internet connections and accessibility;the need to have a personal computer;lack of online support;and lack of online learning skills and awareness. The study’s results include significant differences between students regarding whether they had experience with e-learning.

11.
The International Journal of Technologies in Learning ; 29(2):45-55, 2022.
Article in English | ProQuest Central | ID: covidwho-2030481

ABSTRACT

The COVID-19 pandemic forced educational institutions to expand virtual learning options, with many providing more synchronous online courses using video conferencing technology. This case study explores the student experience in a newly synchronous online course using live remote sessions and compares their perceptions of learning in that environment with traditional in-person and asynchronous online courses. Learning more about the student experience in classrooms of various modalities is important as institutions continue to expand virtual learning options in higher education and workforce training. Students responded to an online survey, and responses were summarized and described categorically and descriptively. Albeit limited to a single course, the overall student response rated their experience in a synchronous online course at or below a traditional classroom learning experience. The live sessions did not adequately address the common shortfalls that often come with asynchronous online learning, including building a sense of community and connectedness with the instructor and fellow classmates. Due to the unprecedented times, the synchronous online modality was the only option provided to students for this class. Virtual learning opportunities are essential to meet the diverse needs of students in higher education, but synchronous online learning is not an automatic substitution for an in-person experience;students should be provided multiple modalities to choose the classroom environment that best fits their learning style.

12.
The International Journal of Technologies in Learning ; 29(1):79-93, 2022.
Article in English | ProQuest Central | ID: covidwho-2030480

ABSTRACT

In 2020, the COVID-19 pandemic presented many higher education institutions with a sudden challenge to shift from either face-to-face and/or blended instruction to remote teaching in order to save the academic year. This article examines preservice teachers’ experiences of a redesigned blended-learning year course on work-integrated learning (WIL). The article uses the Technological Pedagogical Content Knowledge (TPACK) framework within a blended-learning environment to examine the responses of 414 preservice teachers in their first year of study to a survey completed at the end of the course. Descriptive statistics were used together with course content analysis to generate the findings, which suggested that the majority (above 80%) of the preservice teachers remained active during the shift to remote teaching, and about 93.3% responded positively to the course redesign by actively accessing the course on the online platform at least once a week. The survey results also showed that only 10.4% of the preservice teachers did not experience one or another form of challenge in learning through remote teaching during this time. The results build a case for how other practitioners and instructional designers could redesign courses with the consideration of context and learning challenges. The article concludes with the argument for the design of blended courses for future needs to focus more closely on each aspect of the mode of delivery so as to ensure effective design that can withstand emergency situations, such as those we have seen during COVID-19.

13.
TELKOMNIKA ; 20(5):971-978, 2022.
Article in English | ProQuest Central | ID: covidwho-2025608

ABSTRACT

Latent Dirichlet allocation (LDA) is an important probabilistic generative model and has usually used in many domains such as text mining, retrieving information, or natural language processing domains. The posterior inference is the important problem in deciding the quality of the LDA model, but it is usually non-deterministic polynomial (NP)-hard and often intractable, especially in the worst case. For individual texts, some proposed methods such as variational Bayesian (VB), collapsed variational Bayesian (CVB), collapsed Gibb's sampling (CGS), and online maximum a posteriori estimation (OPE) to avoid solving this problem directly, but they usually do not have any guarantee of convergence rate or quality of learned models excepting variants of OPE. Based on OPE and using the Bernoulli distribution combined, we design an algorithm namely general online maximum a posteriori estimation using two stochastic bounds (GOPE2) for solving the posterior inference problem in LDA model. It also is the NP-hard non-convex optimization problem. Via proof of theory and experimental results on the large datasets, we realize that GOPE2 is performed to develop the efficient method for learning topic models from big text collections especially massive/streaming texts, and more efficient than previous methods.

14.
International Journal of Emerging Technologies in Learning (Online) ; 17(16):269-288, 2022.
Article in English | ProQuest Central | ID: covidwho-2024445

ABSTRACT

The unexpected prolonged expansion of the Covid-19 pandemic has urged nu-merous educational institutions worldwide, including Vietnam, to offer online courses. Identifying factors that impact student satisfaction and academic achievement, hence, becomes crucial in online learning environments. The current study examines the impact of students' self-regulated learning and Internet self-efficacy on these two learning outcomes in an online environment. The proposed research model consists of two exogenous variables including students' Internet self-efficacy and self-regulated learning, and two endogenous variables, namely students' satisfaction and academic achievement. 710 students from four universi-ties in Vietnam voluntarily participated in this study by completing an online sur-vey questionnaire. The data analysis was performed by Partial Least Square Structural Equation Modeling (PLS-SEM). The results indicated that Internet self-efficacy, goal setting, and help-seeking have direct positive effects on both student satisfaction and academic achievement. Self-evaluation positively affected student satisfaction while it did not have an impact on student academic achieve-ment. Elaboration, environment structuring, and task strategies did not have a sta-tistically significant relationship with student satisfaction as well as their academic achievement. Students' satisfaction has a direct positive impact on their academic achievement. Pedagogical implications and limitations of the study are also deduced.

15.
International Journal of Emerging Technologies in Learning (Online) ; 17(16):243-268, 2022.
Article in English | ProQuest Central | ID: covidwho-2024444

ABSTRACT

In the previous ten years, there has been an astounding expansion in the study and application of e-learning frameworks. The recent literature and e-learning ideas were investigated in this study, with e-learning research's different parameters being précised. E-learning processes' associated services, technology, as well as stakeholders, are the three principal aspects of e-learning systems. A typology of services comprising e-learning models is presented in a framework, with stakeholders, technology, and learning approaches being included. Accordingly, the aforementioned aspects are considered through a detailed literature review, with e-learning frameworks' relationship with the different classified stakeholder groups also clarified. Finally, ways to resolve the foremost challenges identified through the literature review are posed, with our e-learning system also presented. Furthermore, the proposed answer may direct and facilitate the appropriate appraisal of learners, educators, and educational facilities by decision-makers, drawing on data provided through live interaction.

16.
International Journal of Emerging Technologies in Learning (Online) ; 17(16):167-193, 2022.
Article in English | ProQuest Central | ID: covidwho-2024443

ABSTRACT

With the pandemic, there was an urgent transition to online education. In this process, challenges were experienced while benefiting from the opportunities of online education. This research aims to identify the existing literature on online education in higher education institutions during the pandemic and to highlight the opportunities and challenges reported in research in this process. The study was carried out as a systematic literature review. The results show that maintaining social distance and increased confidence in the effectiveness of e-learning are the main opportunities. The lack of practice, especially in medical applications, limited ICT resources, and pedagogical deficiencies in online environments are shown as challenges of online education during the pandemic. It is thought that this study will make significant contributions to the online education process post-pandemic. The results from this study reinforce previous study findings and identify research that will make the online learning process more effective. Based on the results obtained, suggestions are given for future online learning studies.

17.
Applied System Innovation ; 5(4):86, 2022.
Article in English | ProQuest Central | ID: covidwho-2023109

ABSTRACT

Additive manufacturing (AM) technologies are growing more and more in the manufacturing industry;the increase in world energy consumption encourages the quantification and optimization of energy use in additive manufacturing processes. Orientation of the part to be printed is very important for reducing energy consumption. Our work focuses on defining the most appropriate direction for minimizing energy consumption. In this paper, twelve machine learning (ML) algorithms are applied to model energy consumption in the fused deposition modelling (FDM) process using a database of the FDM 3D printing of isovolumetric mechanical components. The adequate predicted model was selected using four performance criteria: mean absolute error (MAE), root mean squared error (RMSE), R-squared (R2), and explained variance score (EVS). It was clearly seen that the Gaussian process regressor (GPR) model estimates the energy consumption in FDM process with high accuracy: R2 > 99%, EVS > 99%, MAE < 3.89, and RMSE < 5.8.

18.
Applied System Innovation ; 5(4):73, 2022.
Article in English | ProQuest Central | ID: covidwho-2023108

ABSTRACT

Using technology to prevent cyber-attacks has allowed organisations to somewhat automate cyber security. Despite solutions to aid organisations, many are susceptible to phishing and spam emails which can make an unwanted impact if not mitigated. Traits that make organisations susceptible to phishing and spam emails include a lack of awareness around the identification of malicious emails, explicit trust, and the lack of basic security controls. For any organisation, phishing and spam emails can be received and the consequences of an attack could result in disruption. This research investigated the threat of phishing and spam and developed a detection solution to address this challenge. Deep learning and natural language processing are two techniques that have been employed in related research, which has illustrated improvements in the detection of phishing. Therefore, this research contributes by developing Phish Responder, a solution that uses a hybrid machine learning approach combining natural language processing to detect phishing and spam emails. To ensure its efficiency, Phish Responder was subjected to an experiment in which it has achieved an average accuracy of 99% with the LSTM model for text-based datasets. Furthermore, Phish Responder has presented an average accuracy of 94% with the MLP model for numerical-based datasets. Phish Responder was evaluated by comparing it with other solutions and through an independent t-test which demonstrated that the numerical-based technique is statistically significantly better than existing approaches.

19.
Advances in Technology Innovation ; 7(4):295-302, 2022.
Article in English | ProQuest Central | ID: covidwho-2012858

ABSTRACT

Limited studies have been conducted on low-aluminum and rich-iron-calcium fly ash (LARICFA)-based geopolymer concrete with increased strength. This study aims to investigate the mechanical characteristics of LARICFA-based geopolymer concrete, including its compressive strength, split tensile strength, and ultimate moment. The steps of this study include material preparation and testing, concrete mix design and casting, specimen curing and testing, and the analysis of testing results. Furthermore, the specimen tests consist of the bending, compressive, and split tensile strength tests. The results show that the average compressive strength and the ultimate moment of the geopolymer concrete are 38.20 MPa and 22.90 kN·m, respectively, while the average ratio between the split tensile and compressive strengths is around 0.09. Therefore, the fly ash-based geopolymer concrete can be used in structural components.

20.
TEM Journal ; 11(2):779-790, 2022.
Article in English | ProQuest Central | ID: covidwho-2012817
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