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The outbreak of COVID-19 forced billions of learners to stay at home in order to receive online education. The aim of the study is to construct an online sustainable educational model to facilitate this learning approach. This study included 53 peer-reviewed articles for the review study following the selection process of the Preferred Reporting Items for Systematic Review and Meta-analysis Protocol (PRISMA-P) and the clustering techniques of VOSviewer. It is concluded that the model consists of online educational platforms, online assessment systems, social media, and digital literacy. With these features, online education could be sustained. However, challenges should also be addressed to sustain online education during the pandemic. Designers, scientists, and teachers should make every effort to increase learning engagement, enhance learning supervision, formulate adequate emergency programs, minimize educational inequalities, solve technical issues, and formulate systematic learning management and organization. The sustainable online educational model may be updated and perfected by including more practical features in the future.

In this COVID-19 pandemic, learners across the world are encouraged to stay at home receiving online education, which has nearly caused various learning outcomes. It is thus necessary to analyze online learning outcomes, as well as their gender differences to provide constructive references for learners, teachers, and technology developers. This study obtained reliable data from various databases using searching techniques. The study also selected the research articles based on inclusion and exclusion criteria. After analyzing the forest and funnel plots drawn via Review Manager 5.3, the study arrived at the conclusion that online learning outcomes were significantly higher than the traditional learning outcomes with a large effect size (d = 1.24), while the gender differences in learning outcomes were not significant with a small effect size (d = -0.03). In the future, experts could make every effort to develop advanced emotion detection applications via interdisciplinary cooperation to improve online learning outcomes.

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Social media applications such as Facebook have received wide attention in their use in education. However, it is still hard to arrive at a conclusion regarding whether a Facebook-assisted approach is effective in education and whether there are any significant gender differences in the learning outcomes. Based on rigid inclusion criteria, this study included 21 peer-reviewed high-quality journal articles. Through a meta-analysis using Reviewer Manager 5.3, the authors concluded that a Facebook-assisted approach could obtain significantly higher learning outcomes than the non-Facebook-assisted one with a medium effect size (d = 0.42) and that females could achieve significantly better learning outcomes than males with a very small effect size (d = -0.21) in the Facebook-assisted education. Future research could examine the effect of educational use of other social media applications, as well as in sociological, psychological, or educational dimensions.

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The new decade has been witnessing the wide acceptance of artificial intelligence (AI) in education, followed by serious concerns about its ethics. This study examined the essence and principles of AI ethics used in education, as well as the bibliometric analysis of AI ethics for educational purposes. The clustering techniques of VOSviewer (n = 880) led the author to reveal the top 10 authors, sources, organizations, and countries in the research of AI ethics in education. The analysis of clustering solution through CitNetExplorer (n = 841) concluded that the essence of AI ethics for educational purposes included deontology, utilitarianism, and virtue, while the principles of AI ethics in education included transparency, justice, fairness, equity, non-maleficence, responsibility, and privacy. Future research could consider the influence of AI interpretability on AI ethics in education because the ability to interpret the AI decisions could help judge whether the decision is consistent with ethical criteria.

Classcraft has become an attractive gamification choice that turns classes into motivating and joyful role-playing experiences. Based on the content analysis and meta-analysis, this study aims to investigate the efficiency of Classcraft in terms of optimal gamification learning experiences associated with learning achievement and motivation. After the identification, screening, eligibility, and inclusion processes, we have found that learning achievement and motivation are significant factors conducive to optimal gamification learning. The meta-analysis based on STATA 15 has demonstrated that gamification platforms including Classcraft can similarly enhance learning achievement (d = 0.621, z = 5.846, 95% CI [0.413, 0.829]) and motivation (d = 0.608, z = 6.167, 95% CI [0.415, 0801]), suggesting that gamification platforms including Classcraft can create optimal learning experiences. Another content analysis has revealed that Classcraft involving gamified reward mechanics, interactive settings, and collaborative tasks can fulfil the conditions of optimal gamification learning experiences. The main conclusion is that Classcraft can efficiently create optimal gamification learning processes that can positively influence learning achievement and motivation. We have also discussed the potential reasons for the positive effects of gamification on learning achievement and motivation. Game implementation can reflect learners’ preference for well-being based on continuity, interaction, and openness.