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Post-COVID-19 Education for a Sustainable Future: Challenges, Emerging Technologies and Trends

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Education and Approaches".

Deadline for manuscript submissions: closed (15 June 2022) | Viewed by 66952

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Dr. Sébastien Jacques

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Guest Editor

College of Engineering, University of Tours, CEDEX 1, 37020 Tours, France
Interests: smart energy management systems; machine learning; attractiveness of higher education
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Abdeldjalil OUAHABI

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Guest Editor

iBrain UMR 1253, University of Tours, 37000 Tours, France
Interests: signal and image processing; machine/deep learning; medical imaging; attractiveness of higher education
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The COVID-19 pandemic, which the world has been experiencing in full force since late 2019, has significant health, economic, financial, social, cultural, environmental, political, and also educational implications. The pandemic has also challenged the suitability, viability and sustainability of university operating models, practices and systems. If they are to survive and thrive after the pandemic, universities must reassess and adapt their strategies. It is important to seize the moment to be innovative, proactive and adapt to a post-COVID-19 world; higher education must rethink its future and take steps to do so.

This Special Issue aims to provide concrete answers to today’s major challenges to accelerate education towards a sustainable future. The first challenge concerns the training of education professionals in digital culture. The “teacher factor” appears to be one of the most important factors for the success of students, who must be able to adapt throughout their lives to a constantly changing environment. The second challenge is the success of all, regardless of social origin. The third challenge concerns digital inclusion, which is expressed in terms of hardware (access to equipment and especially to networks), usage (use of tools and acquisition of good practices) and understanding (proper use of the systems used and familiarization with artificial intelligence), which is necessary for mastering usage and for the need to upgrade equipment.

“Post-COVID-19 Education for a Sustainable Future: Challenges, Emerging Technologies and Trends” will be an opportunity to both support active and engaged education, and build the post-COVID-19 educational world.

Dr. Sébastien Jacques
Prof. Dr. Abdeldjalil OUAHABI
Guest Editors

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Keywords

educational practices with information and communications technology (ICT)
online learning
digital teaching
sustainability strategy
machine/deep learning
augmented reality technology
face recognition

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Published Papers (13 papers)

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Editorial

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4 pages, 199 KiB

Open AccessEditorial

Post-COVID-19 Education for a Sustainable Future: Challenges, Emerging Technologies and Trends

by Sébastien Jacques, Abdeldjalil Ouahabi and Zoe Kanetaki

Sustainability 2023, 15(8), 6487; https://doi.org/10.3390/su15086487 - 11 Apr 2023

Cited by 17 | Viewed by 1784

Abstract

The COVID-19 pandemic, which has been destabilizing the world since the end of 2019, has significant repercussions on not only health but also the economy, finances, society, politics, the environments, culture and education [...] Full article

(This article belongs to the Special Issue Post-COVID-19 Education for a Sustainable Future: Challenges, Emerging Technologies and Trends)

Research

Jump to: Editorial

25 pages, 1285 KiB

Open AccessArticle

Use of Latent Dirichlet Allocation and Structural Equation Modeling in Determining the Factors for Continuance Intention of Knowledge Payment Platform

by Heng Xu, Menglu Zhang, Jun Zeng, Huihui Hao, Hao-Chiang Koong Lin and Mengyun Xiao

Sustainability 2022, 14(15), 8992; https://doi.org/10.3390/su14158992 - 22 Jul 2022

Cited by 5 | Viewed by 2914

Abstract

Knowledge payment is a new type of E-learning that has developed in the era of social media. With the influence of the COVID-19 epidemic, the knowledge payment market is developing rapidly. Exploring the influencing factors of users’ continuance intention is beneficial for the sustainable development of knowledge payment platforms. Our study took “Himalayan FM” as an example and included two studies: Study 1 used latent dirichlet allocation (LDA) to explore the main factors affecting the users’ willingness to continue use, through mining user comment data on the knowledge payment platform; Study 2 constructed the conceptual model by integrating the technology acceptance model (TAM) and IS success model (IS) and carried out empirical analysis by SPSS and AMOS using the data that were collected through the questionnaire. The results show that: (1) perceived usefulness, user satisfaction, and spokesperson identity have a direct positive impact on users’ willingness to continuous use, while perceived cost has a direct negative impact on users’ willingness to continue use; (2) perceived ease of use, content quality, and system quality of knowledge payment platforms impacted user satisfaction directly, then affected users’ willingness to continue use indirectly; (3) users’ perceived enjoyment, membership experience, auditory experience, and other factors also directly impacted user satisfaction, affecting users’ willingness to continue use indirectly. This study effectively expands the factors influencing knowledge payment users’ willingness to continue use and provides a useful reference for the sustainable development of knowledge payment platforms. Full article

(This article belongs to the Special Issue Post-COVID-19 Education for a Sustainable Future: Challenges, Emerging Technologies and Trends)

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13 pages, 503 KiB

Open AccessArticle

Sustaining Teaching with Technology after the Quarantine: Evidence from Chinese EFL Teachers’ Technological, Pedagogical and Content Knowledge

by Fang Huang, Jiafu Qi and Ailin Xie

Sustainability 2022, 14(14), 8774; https://doi.org/10.3390/su14148774 - 18 Jul 2022

Cited by 15 | Viewed by 2574

Abstract

Given that little is known about English teachers’ technological, pedagogical and content knowledge (TPACK), this study examined teachers’ TPACK of using interactive whiteboards (IWBs) by contextualizing the research in the Chinese EFL context. Surveys and multi-case interviews were conducted among secondary school EFL teachers. The results revealed that Chinese EFL teachers generally perceived themselves to be competent in TPACK, with content knowledge achieving the highest value (5.545) and technological knowledge having the lowest value (5.147). In addition, teachers with higher professional titles perceived themselves as having lower TPACK. Barriers to using IWBs in English teaching include a lack of using efficacy regarding IWBs, traditional teaching beliefs, insufficient technical support and training, defects in IWBs for English teaching and time constraints. This study enriched technology adoption literature and informed policymakers and educational institutions of the necessity to provide specialized training to improve teachers’ TPACK and take measures to reduce teachers’ non-teaching-related tasks to ensure sustainable technology adoption in English teaching. Full article

(This article belongs to the Special Issue Post-COVID-19 Education for a Sustainable Future: Challenges, Emerging Technologies and Trends)

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23 pages, 1192 KiB

Open AccessArticle

Factors Influencing Parents’ Intention on Primary School Students’ Choices of Online Learning during and after the COVID-19 Pandemic in China

by Cunqi Han, Liqun Liu and Siyu Chen

Sustainability 2022, 14(14), 8269; https://doi.org/10.3390/su14148269 - 6 Jul 2022

Cited by 9 | Viewed by 3503

Abstract

Since the COVID-19 outbreak, online learning has become the norm. Primary school students require parental assistance and supervision due to their lack of digital media capabilities and safety concerns. This study uses the mixed research method to process and analyze the interview data of 10 primary school parents and 564 questionnaire data using topic coding and partial least squares structural equation model (PLS-SEM) to explore the factors influencing primary school parents’ choice of online learning and the mechanism of these factors on choice intention. The results show that online learning continuity and learning attitude development risk are two new variables affecting parents’ cognition of online learning. They have a significant positive impact on performance evaluation and risk perception. Perceived ease of use, performance evaluation, and perceived cost affect parents’ assessment of their children’s satisfaction with online learning during the pandemic. Parents’ satisfaction with online learning positively affects their intention to choose online learning. The results of this study can provide a reference for education departments and schools on how to carry out online teaching with higher quality in case of emergencies. Full article

(This article belongs to the Special Issue Post-COVID-19 Education for a Sustainable Future: Challenges, Emerging Technologies and Trends)

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16 pages, 1992 KiB

Open AccessArticle

Learning Performance Prediction-Based Personalized Feedback in Online Learning via Machine Learning

by Xizhe Wang, Linjie Zhang and Tao He

Sustainability 2022, 14(13), 7654; https://doi.org/10.3390/su14137654 - 23 Jun 2022

Cited by 17 | Viewed by 3351

Abstract

Online learning has become a vital option for ensuring daily instruction in response to the emergence of the COVID-19 epidemic. However, different from conventional massive online learning, inadequate available data bring challenges for instructors to identify underachieving students in school-based online learning, which may obstruct timely guidance and impede learning performance. Exploring small-sample-supported learning performance prediction and personalized feedback methods is an urgent need to mitigate these shortcomings. Consequently, considering the problem of insufficient data, this study proposes a machine learning model for learning performance prediction with additional pre-training and fine-tuning phases, and constructs a personalized feedback generation method to improve the online learning effect. With a quasi-experiment involving 62 participants (33 in experimental group and 29 in control group), the validity of the prediction model and personalized feedback generation, and the impact of the personalized feedback on learning performance and cognitive load, were evaluated. The results revealed that the proposed model reached a relatively high level of accuracy compared to the baseline models. Additionally, the students who learned with personalized feedback performed significantly better in terms of learning performance and showed a lower cognitive load. Full article

(This article belongs to the Special Issue Post-COVID-19 Education for a Sustainable Future: Challenges, Emerging Technologies and Trends)

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17 pages, 1429 KiB

Open AccessArticle

Constructing a Digital Competence Evaluation Framework for In-Service Teachers’ Online Teaching

by Lin Tang, Jianjun Gu and Jinlei Xu

Sustainability 2022, 14(9), 5268; https://doi.org/10.3390/su14095268 - 27 Apr 2022

Cited by 7 | Viewed by 2734

Abstract

The focus on online teaching and teachers’ digital competence (DC) has reached a new level following the emergence of COVID-19 and its dramatic influence on the educational industry, requiring teachers to be equipped with DC. However, there is no consensus on the measuring framework of teachers’ DC. Therefore, this study aimed to construct a reliable self-evaluation framework for in-service teachers’ DC during online teaching. The data of 1342 teachers with online teaching experience were obtained. The methods of data analysis included exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and item analysis. Results demonstrated that the constructed evaluation framework performed consistently with the collected data. CFA also confirmed a good model fitting of the relevant 10 factors of the teachers’ DC framework. Therefore, in the teachers’ DC evaluation framework, the constructs interacting with each other consist of technical knowledge (TK, four items), learner knowledge (LK, three items), pedagogical knowledge (PK, three items), ethical knowledge (EK, three items), learner technical knowledge (LTK, four items), learner pedagogical knowledge (LPK, four items), learner ethical knowledge (LEK, four items), technical pedagogical knowledge (TPK, three items), technical ethical knowledge (TEK, four items), and pedagogical ethical knowledge (PEK, three items), but in total the scale comprises 35 items. It can be an effective instrument to support in-service teachers’ DC measurement for their online teaching. Full article

(This article belongs to the Special Issue Post-COVID-19 Education for a Sustainable Future: Challenges, Emerging Technologies and Trends)

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24 pages, 3516 KiB

Open AccessArticle

Grade Prediction Modeling in Hybrid Learning Environments for Sustainable Engineering Education

by Zoe Kanetaki, Constantinos Stergiou, Georgios Bekas, Sébastien Jacques, Christos Troussas, Cleo Sgouropoulou and Abdeldjalil Ouahabi

Sustainability 2022, 14(9), 5205; https://doi.org/10.3390/su14095205 - 26 Apr 2022

Cited by 40 | Viewed by 3403

Abstract

Since mid-March 2020, due to the COVID-19 pandemic, higher education has been facing a very uncertain situation, despite the hasty implementation of information and communication technologies for distance and online learning. Hybrid learning, i.e., the mixing of distance and face-to-face learning, seems to be the rule in most universities today. In order to build a post-COVID-19 university education, i.e., one that is increasingly digital and sustainable, it is essential to learn from these years of health crisis. In this context, this paper aims to identify and quantify the main factors affecting mechanical engineering student performance in order to build a generalized linear autoregressive (GLAR) model. This model, which is distinguished by its simplicity and ease of implementation, is responsible for predicting student grades in online learning situations in hybrid environments. The thirty or so variables identified by a previously tested model in 2020–2021, in which distance learning was the exclusive mode of learning, were evaluated in blended learning spaces. Given the low predictive power of the original model, about ten new factors, specific to blended learning, were then identified and tested. The refined version of the GLAR model predicts student grades to within ±1 with a success rate of 63.70%, making it 28.08% more accurate than the model originally created in 2020–2021. Special attention was also given to students whose grade predictions were underestimated and who failed. The methodology presented is applicable to all aspects of the academic process, including students, instructors, and decisionmakers. Full article

(This article belongs to the Special Issue Post-COVID-19 Education for a Sustainable Future: Challenges, Emerging Technologies and Trends)

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14 pages, 4921 KiB

Open AccessArticle

Research on Open Practice Teaching of Off-Campus Art Appreciation Based on ICT

by Baoqing Song, Bingyang He, Zehua Wang, Ruichong Lin, Jinrui Yang, Runxian Zhou and Yunji Cai

Sustainability 2022, 14(7), 4274; https://doi.org/10.3390/su14074274 - 4 Apr 2022

Cited by 6 | Viewed by 2947

Abstract

Art appreciation is an effective way to promote artistic literacy and is also an important component of aesthetic education in school. With the help of information and communication technology, the authors organized open practice teaching for students to learn art appreciation outside school. During the COVID-19 epidemic, local art appreciation education could not be carried out in the city where the authors’ school is located. With the support of mobile positioning technology and information platforms, students were able to carry out 32 art appreciation activities in their hometowns during this period. Through the mobile positioning information submitted by students, feedback questionnaires, after-view data, and other data, learning achievements were identified. A correlation analysis of the data submitted by the students on the information platform confirmed that satisfaction with the art appreciation activity directly affected their interest in art. The correlation reached 0.78. Satisfaction was strongly correlated with psychological expectations (0.67) and art information obtained in the early stage (0.61). The authors propose that using information and communication technology to carry out art appreciation education outside the school is the way to promote the sustainable development of aesthetic education in school. Full article

(This article belongs to the Special Issue Post-COVID-19 Education for a Sustainable Future: Challenges, Emerging Technologies and Trends)

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24 pages, 1705 KiB

Open AccessArticle

Development of Blockchain Learning Game-Themed Education Program Targeting Elementary Students Based on ASSURE Model

by Eunsun Choi, Youngmi Choi and Namje Park

Sustainability 2022, 14(7), 3771; https://doi.org/10.3390/su14073771 - 23 Mar 2022

Cited by 12 | Viewed by 4220

Abstract

The blockchain education program based on the ASSURE model proposed in this article is of value because it can be applied in blended learning during the COVID-19 pandemic, using learning games to facilitate self-directed learning. We developed the education program in accordance with the six steps of the education design process of the ASSURE model. Firstly, we assessed learners to identify digital literacy issues of South Korean elementary students and jobs desired by them. Secondly, the objective of blockchain education was defined as improving awareness of and attention to blockchain technology by elementary students. Thirdly, gamification applied lessons were used as a teaching method, with educational media and data developed as worksheets and materials that can be used both online and offline. Fourthly, the educational contents and teaching aids were tested to evaluate the developed learning materials. Fifthly, the learning games were designed to offer rewards. Last, we designed the program to teach the principles of consensus mechanisms, private blockchain, and public blockchain. Education experts’ feedback was analyzed using technical statistics and LDA-based topic modeling to assess and modify the program. The education program design approach incorporating gamification elements was effective but needed expansion in coverage to include level-based teaching elements. Full article

(This article belongs to the Special Issue Post-COVID-19 Education for a Sustainable Future: Challenges, Emerging Technologies and Trends)

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28 pages, 3046 KiB

Open AccessArticle

Online Education in the COVID-19 Pandemic—Premise for Economic Competitiveness Growth?

by Florența-Diana Tănase, Suzana Demyen, Venera-Cristina Manciu and Adrian-Costinel Tănase

Sustainability 2022, 14(6), 3503; https://doi.org/10.3390/su14063503 - 16 Mar 2022

Cited by 5 | Viewed by 2503

Abstract

In today’s context, marked by globalization and a growing recognition of interdependencies, there is a permanent change in the world’s economic big picture. In this ever-changing environment, competitiveness is the key factor when it comes to passing the test of requirements on all levels. Obviously, competitiveness, in turn, is conditioned by several elements, one of which being the quality of the workforce. The current situation, strongly influenced by the presence of the SARS-CoV-2 virus, imposes new rules of conduct, and organizations must be inventive if they wish to survive in this period. As a basic pillar of competitiveness, education cannot and should not lag behind, as the transfer of knowledge must continue with or without COVID-19. The questions arise: Can online education train the younger generations and provide them with the skills they need in order to adapt to the labor market? Will 2020 be a reference year for a paradigm shift in education? In order to answer these questions, the present paper includes an extensive survey conducted in Romania among two samples of respondents, one made of 173 university professors and the other consisting of 732 students. The results presented in the paper indicate a high level of adaptation to the new teaching methods, among professors (84.4%) as well as among students (58.7%), with a high number of professors (51.4%) considering that online education can become an important factor in the development of society and in the enhancement of economic competitiveness (60.7%). Full article

(This article belongs to the Special Issue Post-COVID-19 Education for a Sustainable Future: Challenges, Emerging Technologies and Trends)

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13 pages, 2232 KiB

Open AccessArticle

Learning Analytics for Diagnosing Cognitive Load in E-Learning Using Bayesian Network Analysis

by Younyoung Choi and Jigeun Kim

Sustainability 2021, 13(18), 10149; https://doi.org/10.3390/su131810149 - 10 Sep 2021

Cited by 7 | Viewed by 2793

Abstract

A learner’s cognitive load is highly associated with their academic achievement within learning systems. Diagnostic information about a learner’s cognitive load is useful for achieving optimal learning, by enabling the learner to manage and control their cognitive load in the e-learning environment. However, little empirical research has been conducted to obtain diagnostic information about the cognitive load in e-learning systems. The purpose of this study was to analyze a personalized diagnostic evaluation for a learner’s cognitive load in an e-learning system, using the Bayesian Network (BN) as a learning analytic method. Data from 700 learners were collected from Cyber University. A learner’s cognitive load level was measured in terms of three components: extraneous cognitive load, intrinsic cognitive load, and germane cognitive load. The BN was built by representing the relationship among the extraneous cognitive load, intrinsic cognitive load, germane cognitive load, and academic achievement. The conditional and marginal probabilities in the BN were estimated. This study found that the BN provided diagnostic information about a learner’s level of cognitive load in the e-learning system. In addition, the BN predicted the learner’s academic achievement in terms of their different cognitive load patterns. This study’s results imply that diagnostic information related to cognitive load helps learners to improve academic achievement by managing and controlling their cognitive loads in the e-learning environment. In addition, instructional designers are able to offer more appropriately customized instructional methods by considering learners’ cognitive loads in online learning. Full article

(This article belongs to the Special Issue Post-COVID-19 Education for a Sustainable Future: Challenges, Emerging Technologies and Trends)

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12 pages, 699 KiB

Open AccessArticle

Responses to COVID-19 in Higher Education: Students’ Learning Experience Using Microsoft Teams versus Social Network Sites

by Abu Elnasr E. Sobaih, Amany E. Salem, Ahmed M. Hasanein and Ahmed E. Abu Elnasr

Sustainability 2021, 13(18), 10036; https://doi.org/10.3390/su131810036 - 8 Sep 2021

Cited by 48 | Viewed by 10216

Abstract

The long-lasting impact of COVID-19 forced governments to continue with distance learning. Due to the absence of a formal digital learning management system (DLMS), public universities in many countries adopted social network sites (SNSs), e.g., Facebook and WhatsApp, and/or digital communication platforms, e.g., Microsoft (MS) Teams and Zoom for teaching and learning. This research investigates students’ learning experiences and responses to course/s incorporating SNSs and MS Teams as a sole distance learning platform during COVID-19. An online, pre-tested, questionnaire was used, directed at bachelor students in public institutions in Egypt, offering tourism and hotel programs, who received their courses using both SNSs and MS Teams. The results showed that the usage of both SNSs and MS Teams helped students to access information and learning resources, have good impact on their knowledge construction and critical refection, and report overall positive learning experience. The results of paired-samples t-test showed statistically significant differences between students’ experiences of course/s incorporating SNSs and MS Teams. However, students recorded limited support by their educators and peers and low participation in course activities that adopted MS Teams. They also reported poor assessment and feedback with course/s that incorporated SNSs. Hence, several implications for scholars, policymakers, and educators were presented for achieving better learning experience and to cope with the pandemic or similar crises, especially in universities with poor infrastructure, including unavailability of DLMS. Full article

(This article belongs to the Special Issue Post-COVID-19 Education for a Sustainable Future: Challenges, Emerging Technologies and Trends)

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15 pages, 1042 KiB

Open AccessArticle

School Students’ Perception and Challenges towards Online Classes during COVID-19 Pandemic in India: An Econometric Analysis

by Mohammed Arshad Khan, Tuba Kamal, Asheref Illiyan and Mohd Asif

Sustainability 2021, 13(9), 4786; https://doi.org/10.3390/su13094786 - 24 Apr 2021

Cited by 51 | Viewed by 19331

Abstract

Due to the COVID-19 pandemic, the worldwide education system has been severely affected, following the shutdown of schools and colleges/universities since March 2020 in order to prevent the spread of the virus. Conventional classrooms shifted to online classrooms which profoundly impacted teachers’ and students’ closed interaction, making a paradigm shift in the teaching-learning process, inter alia. Against such a backdrop, it is relevant to analyze the perception of students and the challenges of online classes during this ongoing COVID-19 outbreak. The present study is based on a quantitative and sample survey approach. The respondent sample of 385 secondary school students from grades 8 to 12 in Delhi have been collected through a Google Form Questionnaire. The study was conducted in the months of January and February 2021. Statistical techniques, such as Descriptive Statistics, Chi-Square Test, Factor Analysis, Reliability Test and Logistic Regression, were used for analyzing the data. The Logistic Regression result shows that the quality of Internet, prior knowledge of ICT, family income, mother’s education and the number of rooms are positively impacting online classes. The findings of the study revealed that, on average, students have positive perceptions towards online classes during the pandemic to maintain their academic growth. Nonetheless, they experienced several challenges in online classes. Thus, the outcome of this research study will encourage policy makers and educational institutes to handle online classes in a better way, by adopting the latest techniques of online classes and by training teachers and students continuously so that the teaching–learning process becomes more enjoyable and effective during this ongoing pandemic. The government must take certain remedial measures to overcome the challenges in online classes and reduce the digital divide so that no students will be left out. Full article

(This article belongs to the Special Issue Post-COVID-19 Education for a Sustainable Future: Challenges, Emerging Technologies and Trends)

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