Microlearning has become increasingly popular not only in education sector but also in corporate sector in recent years. However, its definition and didactics conceptualization, integration into instruction design, and effects on learning outcomes remain largely underexplored in terms of synthesized findings. Consequently, challenges persist in clarifying microlearning definition, and didactics, and designing effective microlearning instruction to yield improved learning outcomes. To address these gaps, we analyzed 40 relevant studies following PRISMA guidelines. Based on the findings, we maintain that microlearning is an instructional approach that delivers targeted, action-oriented, bite-sized content to achieve specific objectives within a short period, typically within a few seconds or minutes. The most important findings from the reviewed studies indicate that microlearning has positive impact on learning outcomes. The key learning outcomes identified, categorized according to Bloom's Taxonomy, include cognitive (knowledge acquisition, retention, improvement, recall, transfer, and application as well as critical thinking, problem-solving, professional, feedback and self-regulation skills, core competencies such as digital and pedagogical competence, and performance like test performance), behavioural (presentation skills development, task or work performance, higher completion rates, behavioural patterns, engagement, and collaboration), and affective (positive perceptions and attitudes, increased motivation, satisfaction, and improved self-efficacy). Based on Andragogy in Practice Model, Bloom's Taxonomy, and Sweller's CLT, we proposed a novel microlearning instructional design framework consisting of three integral components—differences consisting of individual, situational, and subject differences; guiding principles including specific-objective, bite-sized content, appropriate timeframe, interactive and engaging content, personalization, and selecting appropriate delivery medium and mode; and learning outcomes (cognitive, behavioural and affective). The proposed framework aims to integrate microlearning into instruction to improve learning outcomes. Educators, instruction designers, and policymakers can use the framework to design microlearning instruction to improve learning outcomes.

Microlearning, characterized by its concise and targeted learning content, has emerged as a dynamic pedagogical approach. However, its effectiveness on learning outcomes is subject to mixed research findings, and there’s limited understanding of the underlying factors influencing these outcomes. To address this gap, we collected both quantitative and qualitative data from life-long learners who were taking micro credentials modules hosted on Canvas. This study identified and categorized specific content and learner-level factors into contextual (media richness), behavioral (interaction and engagement), cognitive (comprehensiveness) and affective (motivation, self-concept, and satisfaction), affecting learning outcomes drawing from multiple theories such as the Expectancy-Disconfirmation, constructivism, Self-determination, Situation(al) Awareness, Cognitive Multimedia Learning, and Andragogy. The study introduced a novel framework to investigate factors affecting microlearning outcomes. We utilized SmartPLS v4 for quantitative analysis and ATLAS.ti v24 for qualitative analysis. Quantitative findings revealed significant influence of media richness on interactivity, engagement, satisfaction, and comprehension. Interactivity significantly influenced engagement, and engagement, in turn, shaped learner satisfaction and self-concept. Additionally, comprehension significantly affected both learning outcomes and satisfaction. However, interactivity, engagement, and satisfaction did not significantly affect learning outcomes, suggesting areas for improvement in microlearning module design. Qualitative analysis identified specific challenges like limited peer interaction, pace of instruction, and comprehension difficulties with complex content. However, it also highlighted positive aspects such as flexibility and accessibility. This research provides valuable implications for curriculum designers, tools developers and educators to developed personalized microlearning.

Personalized learning involves tailoring learning experiences to individual learners' needs, preferences, and progress. However, ensuring personalized learning remains a challenging task. Artificial intelligence (AI) usage can be an opportunity to enhance personalized learning. This chapter explores AI role in enhancing personalized learning in medical education. The chapter covers content development, AI-assisted tutoring, adaptive case-based learning, automated assessments, immediate feedback, and clinical decision-making in personalized medical education. It further discusses AI in conducting literature reviews and knowledge synthesis in medical education. Moreover, it provides insights into AI risks and ethical considerations in medical education, including potential bias, data privacy, accuracy and reliability challenges, and over-reliance on this technology. It emphasizes the need to promote AI literacy among medical learners, offering insights into effective AI-assisted personalized learning in medical education.

Artificial Intelligence (AI) is rapidly transforming education, yet many institutions lack a comprehensive framework to integrate AI effectively. This paper develops an AI Education Competency Framework to guide the integration of AI in educational settings through a systematic literature review. Methodologically, a rigorous systematic literature review (SLR) was conducted following PRISMA guidelines, ensuring methodological rigor and empirical grounding. Key databases (e.g., Google Scholar, IEEE Xplore, SpringerLink) were searched for studies on AI frameworks in education, yielding 21 relevant sources. The analysis resulted in a novel framework which is built on four pillars—Foundation, Integration, Innovation, and AI Citizenship, encompassing fundamental AI knowledge, curricular and administrative integration, AI-driven innovation in pedagogy, and ethical AI use. The proposed framework informed by findings from these studies, addressing gaps such as the lack of unified approaches that combine technical, pedagogical, and ethical dimensions. The framework provides a holistic strategy for AI integration in education, including for open and distance education contexts, bridging theoretical and practical aspects. In discussion, we highlight the framework’s contributions in filling identified gaps, its potential implementation challenges, and recommendations for educators and policymakers. The study concludes that the AI Education Competency Framework offers significant contributions by aligning AI advancements with educational competencies, ensuring stakeholders are prepared to navigate AI’s complexities responsibly and effectively.

Twenty-first century skills refer to a broad set of skills that are critically important in the educational system to meet the complex and rapid changes around the world. Of particular concern in the context of Afghanistan is the failure to produce graduates with the essential competencies necessary for success in the workplace. In education, incorporating these skills is important to meet the current and future demands of society. This study investigates Afghan lecturers’ and students’ perceptions toward the implementation of 21st century skills in EFL classrooms. Quantitative approach was used, whereby data were collected through questionnaires from 197 participants at three public universities in Afghanistan. The Statistical Package for Social Science (SPSS) version 25 was used for descriptive and inferential analyses. The findings revealed that all of the eight 21st century skills were implemented to some degree in the EFL classrooms. In addition, the level of implementation varied between key skills, subcategories, and specific practices listed within each domain whereby none of the skills were fully and consistently incorporated into the classroom. The findings of this study will provide EFL lecturers and students, educationists, and curriculum developers with insights into implementing 21st century skills at tertiary level education.