Personalized Learning
What Is Personalized Learning?
An educational model that tailors instruction, content, and pace to the individual needs, strengths, and interests of each learner. AI-powered personalized learning systems can analyze student data to recommend resources, adjust difficulty levels, and provide targeted feedback.
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Related Terms in Teaching & Learning
Gamification
The application of game design elements such as points, badges, leaderboards, and challenges in non-game educational contexts to increase student motivation and engagement. AI-enhanced gamification can dynamically adjust difficulty and rewards based on individual student behavior and progress.
Microlearning
An educational approach that delivers content in small, focused units designed to be consumed in short time periods, typically 5-10 minutes. AI can optimize microlearning by determining the ideal sequence, spacing, and content of these bite-sized lessons based on learner performance data.
Blended Learning
An instructional approach that combines traditional face-to-face classroom teaching with online digital activities and resources. AI tools enhance blended learning by providing personalized online components that complement in-person instruction and adapt to each student's needs.
Flipped Classroom
A pedagogical model where students engage with instructional content (such as video lectures) at home and use classroom time for active learning, discussion, and practice. AI supports the flipped classroom by generating pre-class materials, creating adaptive quizzes, and identifying topics students struggle with before class.
Competency-Based Education
An educational approach where students progress by demonstrating mastery of specific skills or competencies rather than spending a fixed amount of time on each topic. AI-powered competency-based systems can continuously assess student mastery and unlock new content when readiness is demonstrated.
Formative Assessment
Ongoing assessments conducted during instruction to monitor student learning and provide feedback that guides teaching adjustments. AI enhances formative assessment by enabling real-time automated feedback, adaptive quizzing, and instant analysis of student responses to identify knowledge gaps.