There is no denying that the COVID-19 pandemic resulted in significant stress worldwide and impacted practically every aspect of human activity. The impacts of this deadly virus on education are not seen as gaining much-needed focus from the scientific research community. The majority of educational institutions globally switched to online instruction during the COVID-19 pandemic. However, there were considerable differences in the technical readiness of various nations. In this regard, the study’s attempt to provide a way forward for how the educational sector ought to manage the challenges brought on by COVID-19 issues in support of online educational activities. Since some of the consequences that resulted have an impact on the educational sector, the answers presumably also should have included innovations that would improve scientific research to lessen its effects. Particularly, it appears there is still much that has to be done about the impact of the COVID-19 pandemic on the educational sector. Hence, this perspective review study aims to explore the potential relationship between the COVID-19 pandemic and the educational sector while suggesting a way forward.

The study’s purpose is to investigate the relationship effect of innovation on online organizational learning applications and employees’ engagement in the Jordanian public sector. Quantities and descriptive analytical approach were used, and the population was covered (10) Jordanian public departments in Amman capital. Convenience method was used, which covered all departments’ managers and assistances in the Jordanian public services department’s headquarters, with (284) employee. Electronic survey set used. The SPSS-V20 and AMOS-V24 were used for hypotheses statistical analysis testing. The study found a significant impact of online organizational learning applications in its dimensions (Zoom, Teams, Goto Meeting, and Google Meet) on employee’s engagement, and a significant relationship of innovation between online organizational learning applications and employee’s engagement in Jordanian public services departments. The study contributions show that employees are willing to engage with their occupied work to achieve work goals, and to control over of how they undertake the employees career development, empowerment, communication skills, and work completion competences. The study implications for organizations management to conduct more future studies concerning online organizational learning applications by other dimensions as well as social media and other digital workshop and training in different organizations environments.

The digital era has ushered in significant advancements in Generative Artificial Intelligence (GAI), particularly through Generative Models and Large Language Models (LLMs) like ChatGPT, revolutionizing educational paradigms. This research, set against the backdrop of Society 5.0 and aimed at sustainable educational practices, utilizes qualitative analysis to explore the impact of Generative AI in various learning environments. It highlights the potential of LLMs to offer personalized learning experiences, democratize education, and enhance global educational outcomes. The study finds that Generative AI revitalizes learning methodologies and supports educational systems’ sustainability by catering to diverse learning needs and breaking down access barriers. In conclusion, the paper discusses the future educational strategies influenced by Generative AI, emphasizing the need for alignment with Society 5.0’s principles to foster adaptable and sustainable educational inclusion.

This study aims to explore the relationship between classroom anxiety and self-efficacy among Chinese Korean language learners and the impact of these variables on learning outcomes. Utilizing a quantitative research approach, the study conducted a questionnaire survey with 300 learners to assess their levels of Korean language learning classroom anxiety and self-efficacy. The questionnaire comprised two parts: one for assessing learning anxiety and the other for self-efficacy. Data were analyzed using descriptive statistical analysis, Pearson correlation coefficients, and multiple regression analysis. The results indicate a significant negative correlation between classroom anxiety and self-efficacy. That is, higher levels of classroom anxiety in Korean language learners correspond to lower levels of self-efficacy. Additionally, self-efficacy played a partial mediating role between classroom anxiety and learning outcomes. The study also found that teaching strategies offering positive feedback and encouragement can effectively reduce learners’ classroom anxiety and enhance their self-efficacy, thereby improving learning outcomes. This research is significant for understanding the psychological characteristics of Chinese Korean language learners and their impact on the learning process. The findings underscore the need to focus on learners’ psychological states in language teaching and provide strategies for teachers on how to improve teaching effectiveness by alleviating classroom anxiety and enhancing self-efficacy.

The progress of a country can be directly related to the education level of its countrymen. Over a time period, the internet has become a game changer for the world of disseminating education. From 2000 onwards, the scale of online courses has increased manyfold. The main reason for this growth in online learning can be attributed to the flexibility in course delivery and scheduling. Through this study, the authors analyzed the challenges in adopting Online degree programs in higher education in management in India. The authors used Focus Group discussions, semi-structured interviews, and in-depth interviews to collect the data from the various stakeholders. Thematic analysis was used to analyze the responses. Considering the challenges and constraints in India, the authors proposed a sustainable model for implementation. Based on the viewpoints of the different stakeholders, the authors find that online degrees can be instrumental in bringing inclusivity in higher education. There are obvious constraints like a lack of IT infrastructure, the inexperience of faculty in online pedagogy, and the need for more expertise in the administration of online programs by existing universities. However, using SWAYAM as a platform can overcome most of these constraints, as it reduces the burden on individual universities. Hence, the authors proposed models where SWAYAM (technology platform) and Universities (academic partners) can come together to provide a sustainable education model.

Creating a crop type map is a dominant yet complicated model to produce. This study aims to determine the best model to identify the wheat crop in the Haridwar district, Uttarakhand, India, by presenting a novel approach using machine learning techniques for time series data derived from the Sentinel-2 satellite spanned from mid-November to April. The proposed methodology combines the Normalized Difference Vegetation Index (NDVI), satellite bands like red, green, blue, and NIR, feature extraction, and classification algorithms to capture crop growth's temporal dynamics effectively. Three models, Random Forest, Convolutional Neural Networks, and Support Vector Machine, were compared to obtain the start of season (SOS). It is validated and evaluated using the performance metrics. Further, Random Forest stood out as the best model statistically and spatially for phenology parameter extraction with the least RMSE value at 19 days. CNN and Random Forest models were used to classify wheat crops by combining SOS, blue, green, red, NIR bands, and NDVI. Random Forest produces a more accurate wheat map with an accuracy of 69% and 0.5 MeanIoU. It was observed that CNN is not able to distinguish between wheat and other crops. The result revealed that incorporating the Sentinel-2 satellite data bearing a high spatial and temporal resolution with supervised machine-learning models and crop phenology metrics can empower the crop type classification process.