Amalgamating Bloom’s Taxonomy and Artificial Intelligence to Face the Challenges of Online EFL Learning Amid Post-COVID-19 In Saudi Arabia

Abstract

During the coronavirus pandemic, remote learning offered instructors numerous potential opportunities to implement online applications for the success of students’ language proficiency. Despite this, there has been a rise in the number of challenges that afflicted EFL Saudi instructors and their learners from attaining sustainable development. The core purpose of this work was to explore these complexities and provide suggestions on how Saudi EFL instructors could adapt while maintaining learners’ cognitive and psychological well-being. Furthermore, it questioned the extent to which artificial intelligence (AI) and Bloom’s digital taxonomy (BDT) played an innovative role in improving Saudi educational quality and effectiveness. To this end, a qualitative study design was embraced, consisting of a meta-analysis of the most recent studies conducted on the topic of study. The findings indicated that despite having gained access to platforms and apps led by technology, EFL instructors faced numerous challenges such as inadequate training, incompetence, restricted accessibility, poor web infrastructure, modest technological assistance, low motivation, and attention to deficit learners. Thus, AI and BDT may help bridge the gaps and overcome some of the pandemic's challenges. This study provided recommendations for curriculum designers, developers, and policymakers, on the challenges of e-learning systems and how to address them during the pandemic and afterward.