E-Learning and Blended Learning Methodologies Used in Universities During and After COVID-19

Ghazal, Ghadeer; Alian, Marwah; Alkhawaldeh, Eslam

doi:10.3991/ijim.v16i18.32721

Cited by 4 publications

(5 citation statements)

References 18 publications

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“…(Rodríguez-Galván et al, 2022) The feedback provided by the teacher exhibited a noticeable improvement with a heightened degree of positivity and recognition for the efforts put in by students. (Ghazal et al, 2022) Different e-learning platforms were used in universities, such as Microsoft Teams, Moodle, and Google Classrooms. The three learning types included in the study are face-to-face, blended, and online learning.…”

Section: Charting the Datamentioning

confidence: 99%

Revolutionizing Education: Navigating the New Landscape Post-COVID-19: A Scoping Review

Nang,

Maat,

Mahmud

2024

INT J EDUC METHODOL

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<p style="text-align:justify">Education systems worldwide have been significantly disrupted due to the COVID-19 pandemic, creating an immediate need for a revamp of conventional teaching and learning techniques. To explore how this has affected the educational landscape, a scoping review was conducted. This scoping review aimed to examine the changes that occurred in the education field and to explore how it has transformed the educational landscape review. Using Arksey and O'Malley's methodology, 51 articles were selected for analysis from two leading databases: Scopus and Web of Science. All chosen articles were then subjected to thematic analysis. Three main aspects impacted by this global event were uncovered, which are technological advancements and digital transformation, changes in pedagogy and teaching methods, and mental health and well-being issues. This scoping review provides valuable insights into one of the most critical sectors affected by COVID-19, which can assist with planning future strategies for similar crises.</p>

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Section: Charting the Datamentioning

confidence: 99%

Revolutionizing Education: Navigating the New Landscape Post-COVID-19: A Scoping Review

Nang,

Maat,

Mahmud

2024

INT J EDUC METHODOL

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“…Relevant research related to the impact of the influence of software in online learning in higher education during the covid-19 pandemic, there is a good and significant influence between the variable of the effectiveness of the use of technology and information with the variable of online learning during covid-19 (Ghazal et al, 2022;Ma et al, 2019;Pu et al, 2018). This is because the use of technology is appropriate and has been applied by users as a source of knowledge (Golding-Day et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

The Impact of Using Online Learning Software During the Covid-19 Pandemic in Higher Education

Natalie,

Mahendika,

Salong

et al. 2024

J. Int. Lingua Tech

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The occurrence of covid-19 has a major effect on the smooth running of education, one of which is in higher education. So that lecturers and students need supporting media in the smooth learning process, such as the use of software. The use of software can make it easier for students to carry out the online learning process. This study aims to reveal the effect of using software on students in carrying out the distance learning process. In conducting this research, researchers used quantitative research methods with observations made in the form of distributing questionnaires to students to see the effect of software as a supporting medium in the learning process. The results of this study are that learning media using software is very helpful and has a good impact on students in the learning process during the covid-19 pandemic. The conclusion of this study is that fluency in the world of education during the co-19 pandemic is very limited, because students cannot integrate directly with lecturers in the learning process, therefore students and lecturers need media that can be used as supporting tools such as software for the smooth discussion and learning process, teaching in higher education. The limitation in this study is that researchers did not get accurate data in data collection. Therefore, it is hoped that future researchers will also conduct the same research in order to maintain relevant data results in analyzing the use of software in the learning process in higher education. This study also recommends that future researchers make this topic an ongoing discussion to obtain relevant and very effective research results so that this research can become a benchmark in the influence of using software as a learning medium during the covid-19 pandemic, so as to create a learning process based on supporting science and technology.

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“…The pandemic caused by COVID-19 resulted in outbreaks and lockdowns around the world. Since its emergence in the end of 2019, the pandemic affected people's lives in different fields, such as social life, psychological, learning and teaching, healthcare, and finance [1] [47]. During this phase, people used social media platforms, such as Twitter and Facebook, to express their feelings and opinions about the current situation, thereby encouraging researchers to investigate people's feelings among these social platforms through sentiment analysis studies [2].…”

Section: Introductionmentioning

confidence: 99%

Sentiment Analysis for People’s Opinions about COVID-19 Using LSTM and CNN Models

Al-Khazaleh

Alian

Biltawi³

et al. 2023

Int. J. Onl. Eng.

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The emergence of social media platforms, which contributed in activating the patterns of connection between individuals, leads to the availability of a huge amount of content such as text, images, and videos. Twitter is one of the most popular platforms of social media that encourage researchers to investigate people’s feelings and opinions among through sentiment analysis studies that elicited the interest of researchers in natural language processing field. Many techniques related to machine learning and deep learning models could be used to improve the efficiency and performance of sentiment analysis, especially in complex classification problems. In this paper, different models of long short-term memory recurrent neural network are used for the sentiment classification task. The input text was represented as vectors using Arabic pre-trained word embedding (Aravec). Experiments were conducted using different dimensions of Aravec on 15779 tweets about COVID-19 collected and labeled as positive and negative. The experimental results show an accuracy value of 98%.

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E-Learning and Blended Learning Methodologies Used in Universities During and After COVID-19

Cited by 4 publications

References 18 publications

Revolutionizing Education: Navigating the New Landscape Post-COVID-19: A Scoping Review

Revolutionizing Education: Navigating the New Landscape Post-COVID-19: A Scoping Review

The Impact of Using Online Learning Software During the Covid-19 Pandemic in Higher Education

Sentiment Analysis for People’s Opinions about COVID-19 Using LSTM and CNN Models

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