The Contribution of Self-Efficacy and Achievement Motivation on The SPIRIT Characters Building for The Students

This paper aimed to show how much Self-efficacy and Achievement Motivation contribute to the formation of SPIRIT character for the students in the post-covid-19 pandemic era when the education process is still ongoing with a combined method of online and offline learning. This research used quantitative methods and literature studies. The results of this research showed that self-efficacy and achievement motivation had not significance contribution to the SPIRIT characters building for the students. The other variables that are not discussed even have a much larger contribution. So it is interested to investigate this result. Even so, it does not mean that students do not need to pay attention to self-efficacy and achievement motivation, because even though they are small, they still need to be owned, so that the SPIRIT characters can be further developed in the post-covid-19 pandemic era. © 2022 ACM.

Utilizing Sentiment Analysis to Enhance the Quality of Online Learning

The COVID-19 pandemic spread worldwide in the year 2020 and became a global health emergency. This pandemic has brought awareness that social distancing and quarantine are ideal ways to protect people in the community from infection. Therefore, Saudi Arabia used online learning instead of stopping it completely to continue the education process. This paper proposes to use machine-learning algorithms for Arabic sentiment analysis to find out what students and teaching staff thought about online learning during the COVID-19 outbreak. During the pandemic, a real-world data set was gathered that included about 100,000 Arabic tweets related to online learning. The overall goal is to use sentiment analysis of tweets to find patterns that help improve the quality of online learning. The data set that was collected has three classes: 'Positive,' 'Negative,' and 'Neutral.' Crossvalidation is used to run the experiments ten times. Precision, recall, and F-measure was used to measure how well the algorithms worked. Classifiers, such as Support Vector Machines, K nearest neighbors, and Random Forest, were used to classify the dataset. Moreover, a detailed analysis and comparison of the results are made in this research. Finally, a visual examination of the data is made using the word cloud technique. © 2022 IEEE.

Possibilities and limitations of social media in education processes during the pandemic: The teachers perspective

The health emergency derived from the spread of COVID-19 led to the declaration of confinement for the protection of the population. During this temporary period, the educational centers of the Spanish state were forced to suspend face-to-face classes at all educational levels. To safeguard the teaching processes, educational centers and teachers relied on social media to continue their work. The objective of this study is to understand the possibilities and limitations of social media as the only means of communication in the educational and socialization processes of students from the perspective of teachers. The methodology used is based on the collection of data through a questionnaire distributed in the secondary education centers of the autonomous regions of the Basque Country and Navarra. The questionnaire was distributed electronically, respecting the anonymity of the teaching staff and the center in which they practice. The results reveal that the digital media the possibilities and limitations of these media in the teaching processes, showing that some of these are surmountable and others are not. © 2023 Copyright for this paper by its authors.

Toward an Effective Model for Evaluating Distance Education

Distance education has become popular due to their ability to provide learning from almost anywhere and anytime. COVID-19 forced educational institutions to urgently introduce distance education to ensure pedagogical continuity, so all stakeholders were invited to adapt to this new paradigm. In order to identify strengths and weaknesses, the research focuses on the need to create an effective mechanism for evaluating distance education. The aims of this research were to explore and evaluate the use of digital media in general and official platforms in particular in distance education practices. To this end, we have developed and validated a questionnaire before administering it to a sample of 431 teachers in Morocco. Teachers reported lower knowledge and skills in the didactic use of ICT in the distance education process. In addition, although age and educative experience of the teachers continue to modulate the level of instrumental skills. Therefore, resources (digital resources and infrastructure) and the teachers' ICT training present serious limitations, which require a training more focused on the distance educational paradigm and educational environments that allow teachers to create educational activities able to promote and facilitate the distance learning process © 2023, International Journal of Emerging Technologies in Learning.All Rights Reserved.

Triggers and Tweets: Implicit Aspect-Based Sentiment and Emotion Analysis of Community Chatter Relevant to Education Post-COVID-19

This research proposes a well-being analytical framework using social media chatter data. The proposed framework infers analytics and provides insights into the public’s well-being relevant to education throughout and post the COVID-19 pandemic through a comprehensive Emotion and Aspect-based Sentiment Analysis (ABSA). Moreover, this research aims to examine the variability in emotions of students, parents, and faculty toward the e-learning process over time and across different locations. The proposed framework curates Twitter chatter data relevant to the education sector, identifies tweets with the sentiment, and then identifies the exact emotion and emotional triggers associated with those feelings through implicit ABSA. The produced analytics are then factored by location and time to provide more comprehensive insights that aim to assist the decision-makers and personnel in the educational sector enhance and adapt the educational process during and following the pandemic and looking toward the future. The experimental results for emotion classification show that the Linear Support Vector Classifier (SVC) outperformed other classifiers in terms of overall accuracy, precision, recall, and F-measure of 91%. Moreover, the Logistic Regression classifier outperformed all other classifiers in terms of overall accuracy, recall, an F-measure of 81%, and precision of 83% for aspect classification. In online experiments using UAE COVID-19 education-related data, the analytics show high relevance with the public concerns around the education process that were reported during the experiment’s timeframe. © 2022 by the authors.

An Interactive Dashboard to Support Policymaking of Reopening School on Covid-19 Pandemic

In mid-April 2020, UNESCO monitored 191 countries and stated that around 1.723 trillion students in the world were affected by the policy of school from home. It is feared that school closures could hamper the provision of education services and could disrupt the education process which will affect the level of quality of education. There is still no creation of a computational model for the spread of covid as the main framework for schools reopening safely during the pandemic situation. Although there is already a framework from WHO and the government, there is no measuring tool that can evaluate the effect of reopening schools while the Covid-19 pandemic. For this reason, this research seeks to produce a model for the spread of Covid-19 as a basis for determining policies for safely reopening schools during the pandemic. In this research, we produced a recommendation to reopen face-to-face learning in the form of a dashboard. Recommendations are given by predicting the number of cases in each subdistrict using a predictive model. The prediction results are also combined with the factors that have been determined by the government to give recommendations. The allotment of recommendations process involves a critical factor analysis process where we identify which factors are dominant as a basis of a controllable pandemic. © 2022 IEEE.

Teacher's Assistant Application

With the start of the online teaching due to the COVID restrictions, the dynamics of the classes changed, and the Internet applications took a big swing in the education process. Before the COVID pandemic, teachers were forced to learn how to use web tools to deliver more productive teaching to pupils. But despite all the efforts of teachers and institutions to invest in quality online education, we are all witnesses that online instruction does not achieve the same effect as the teaching with a physical presence. We conducted several surveys in secondary and primary schools in the local area. The results lead to the conclusion that the attention of pupils and the quality of teaching is reduced compared to education with a physical presence. Teachers use paper notebooks, online teaching tools, online meeting scheduling tools, online assessment tools, and online homework tools from different sources. Surveys with teachers have also shown that they have difficulty dealing with inconsistent tools, paper records and most of the various software they use in their online teaching. This paper will examine the possibilities of the existing online applications for the above-mentioned teacher's needs. Following our survey results, we're creating an online tool that puts all the essential needs together, such as - keeping pupils' attention during classes, digitizing the teacher-led record section, quickly and easily assessing pupils, managing homeworks, working in groups on projects and automation of the previously listed processes. The main focus of this paper will be on our innovative application that will contribute to the work process of the teachers. © 2022 IEEE.

Distance Learning Transition at the University of Michigan during a COVID-19 Pandemic: Challenges and Solutions

In 2020, preschool teachers to college professors to workforce trainers are researching best practices for learning at distance in response to the COVID-19 school closings. Educators are faced with the unexpected challenge of delivering distance learning as the primary mode of instruction due to the Coronavirus pandemic. An outbreak of Covid-19 has dramatically impacted the way people live, work, and interact on a global level over the past few years. This article looks at the field of education and the radical changes it is experiencing due to the need to digitally transform education and training processes in record time with academics who lack the technical skills needed for online teaching. Moreover, we will discuss the challenges and solutions within the COVID-19 pandemic transition. Our study focused on the three campuses (Ann Arbor, Dearborn, and Flint) of the University of Michigan. The discussion and conclusion provide valuable insights into the digitalization of education. © 2022 IEEE.

Effect of Distance Teaching on Student's Course Evaluations

The COVID-19 pandemic has caused major changes in the learning and teaching process. One of the most common changes was migration to online lectures. This has changed how teaching practices are employed and demanded a rapid yet effective shift in traditional teaching methods. The unforeseen quick transition also presented a big challenge for students and teachers. Both needed to adapt to new tools, technologies, but also methods and partially a new mindset. The situation has a significant impact on the education process, particularly on students. At the University of Maribor, students fill out a survey each year to evaluate educators and their workload for all the courses they participated in that year. In this paper, we use this survey to investigate the impact of the COVID-19 pandemic on the study process. We investigated two aspects: the students' perceived effort required to finish their courses and their evaluation of educators. We used the student survey results from the study year 2017/2018 until the most recent one, for which data is available in 2020/2021. The results show no impact on the education process as the students' perceived effort and the educators' scores show a trend of improvement over the years. From the data analysis, we can conclude that in the year when COVID-19 started (2019/2020), the shift to distance learning slightly impacted the perception of students' effort, but later this trend returned to the pre-COVID-19 situation. © 2022 IEEE.

Anxiety Levels of Dental PhD and Specialty Program Students in Turkey About COVID-19 Pandemic Process

Objective: The aim of this study was to evaluate the anxiety levels about education, clinical practice and professional development of dental PhD and specialty program students in Turkey during pandemic process. Methods: In this study, a scale consisting of two parts was developed by researchers and an online survey portal was used to reach the participants. The first part included personal information of participants. In the second part, there were 5-point scale items with three sub-dimensions to determine the anxiety levels about COVID-19. Item pool was constructed with 23 scale items. For the construct validity, exploratory factor analysis and confirmatory factor analysis was conducted. After the exploratory factor analysis, 3 items exluded from the scale and it resulted in three-factor structure. According to the theoretical background, factors were called as "clinical practice process", "education process" and "professional development process". When the items related to the sub-dimensions were examined, it was seen that education process includes 8 items, clinical practice process includes 9 items and professional process includes 3 items. Then, this three-factor structure with 20 items by the way one factor model based on these three subfactors were tested through confirmatory factor analysis and higher order confirmatory factor analysis. After exploratory factor analysis and confirmatory factor analysis, it was concluded that there was enough evidence for the construct validity. For the reliability study Cronbach alfa coefficients and corrected item-total correlations was calculated. It was observed that the Cronbach alpha coefficients for the education process sub-dimension, the clinical practice process sub-dimension and the professional development process sub-dimension were 0.87, 0.86 and 0.70, respectively. The stratified Cronbach alpha coefficient calculated for the overall scale was 0.90. It was referred that the scores obtained from the sub-dimensions of the scale and by the way for general score were reliable. For the corrected item-total correlations, education process sub-dimension was in the range of 0.559-0.661, clinical practice sub-dimension was in the range of 0.407-0.812, and professional development process sub-dimension was in the range of 0.487-0.534. It was concluded that all items were sufficiently distinctive and served its purpose. Moreover the data based on the scale were analyzed with t-test and Kruskal Wallis H test. With the statistically significant results of Kruskal Wallis H test, Mann-Whitney U test were conducted as post hoc. Results: A total of 208 students (156 females, 52 males) participated. There was no significant difference among anxiety levels of the groups in terms of gender and department variables (p >0.05). However, there was statistically significant difference in terms of age and education year. The students with the ages in the interval of 22-24 had significantly lower anxiety levels regarding the clinical practice process (p <0.05). The anxiety levels of students with more than 4 years in education were significantly lower than other groups regarding education process (p <0.05). Younger students had lower anxiety levels about clinical practice process in PhD or specialty programs. Conclusion: Increase of the year in education leads reducement in the anxiety level about education process.

Optimizing Education Processes During the COVID-19 Pandemic Using the Technology Acceptance Model

The COVID-19 epidemic has become a significant global obstacle as it has impacted people's lives in various sectors, including social, economic, and education. To respond to the shock caused to education systems, massive efforts-such as conducting formal education through online classes-have been made. This study has employed Structural Equation Modeling (SEM) to examine this arena during the COVID-19 pandemic and has elaborated on how effectively the education system responded, especially through online lecturing. The Technology Acceptance Model (TAM) was implemented as this study's theoretical framework. Partial Least Squares Structural Equation Modeling was employed to measure and assess the proposed model. This study was conducted through a survey with 112 student participants in a postgraduate program between January and December 2021. The findings showed that (1) the TAM-based proposed variables have been successfully explained during the pandemic through factors predicting the use by an online class of postgraduate students, (2) significant effects were reported from perceived ease of use and perceived usefulness toward actual system use through behavioral intentions to use, (3) there were no significant results to show an indirect effect from perceived ease of use and perceived usefulness toward actual system use through behavioral intentions to use.

An Augmented Reality Framework for Eye Muscle Education

Due to the COVID-19 pandemic, the need for remote education is felt more than ever. New technologies such as Augmented Reality (AR) can improve students' training experiences and directly affect the learning process, especially in remote education. By using AR in medical education, we no longer need to worry about patient safety during the education process because AR helps students see inside the human body without needing to cut human flesh in the real world. In this paper, we present an augmented reality framework that has the ability to add a virtual eye muscle to a person's face in a single photo or a video. We go one step further to not just show the muscle of the eye but also customize it for each person by modeling the person's face with a 3D morphable model (3DMM). © 2022 IEEE.

Research on OBE Online Teaching Mode Combined with Expression Recognition—Taking Digital Image Processing Course as an Example

Although the engineering education has been widely developed in China, the training for engineers cannot completely satisfy the requirements from the society. The output-based education (OBE) designs education process according to the results of education so that students can have a certain level of ability when they graduate. However, influenced by the COVID-19 pandemic, plenty of offline practical activities have changed to online ones. Thus, the digital image processing course is taken as an example, and the online class video is taken as the test data for students to do practical experiments. Moreover, an algorithm extracting harr-like features to detect face and recognize expression is applied. The eyes are further extracted from the detected face images to calculate the ratio of width and height, and then the students’ studying state can be determined. The experimental results demonstrate that the algorithm can help teachers understand the students’ state and improve the teaching efficiency. Moreover, the OBE online teaching mode can improve the students’ practical ability. © 2021, Springer Nature Switzerland AG.

The Qualifications and Views of Instructors in the Distance Education System

A new process has been brought about due to the COVID-19 pandemic that has affected the world. Due to the COVID-19 pandemic, since the spring semester of the 2019–2020 academic year, all education and courses are provided through distance education. Therefore, since distance education is a new process for many, faculty members may encounter various problems. For this reason, determining the views of lecturers about the distance education process is important for the improvement and development of the distance education system. The aim of this study is to examine the views of the lecturers who teach through the distance education system and to make suggestions for the improvement of the system. The situation was determined using the qualitative research method. The research questions were prepared by the researchers. Their validity was ensured by taking experts’ opinions. For this purpose, interviews with semistructured questions were conducted with 28 instructors at Cyprus and Russian universities and the data obtained were evaluated by content analysis. The findings obtained as a result of the research are given in detail in the findings and results section. © 2021

A Hybrid Teaching Factory Model for Supporting the Educational Process in COVID-19 era.

The lockdown due to SARS-CoV-2 (COVID-19) pandemic forced both educators and students to swift and rely on digital technologies in order to ensure the successful completion of modules based on the official curriculum. Universities are still facing the challenging issue to offer high quality learning opportunities without risking participants' health. Towards that end, the current study presents a Hybrid Model under the Teaching Factory framework concept that has been successfully implemented and validated. In a hybrid laboratory case study, Engineering students guided remotely laboratory personnel towards a successful manufacture and assembly of a customized remote-control car. Benefits and boundaries of the current approach are discussed along with future perspectives.