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From Traditional to Transformative: The Evolution of Pedagogy in Modern Education

Pedagogy—the art and science of teaching—has undergone profound change over the past century. The shift from teacher-centred instruction to learner-centred approaches marks a critical chapter in the evolution of pedagogy . Today, teaching is no longer just about transferring knowledge; it is about cultivating critical thinking, creativity, and collaboration in dynamic and inclusive learning environments. This post explores how pedagogy has evolved, compares traditional and modern methods, and highlights the transformative practices redefining 21st-century education. The Role of Case Studies in Academic Research: Best Practices 1. Traditional Pedagogy: A Foundation Rooted in Authority and Rote Learning In traditional classrooms, the teacher is the central figure of authority, and learning is a linear, structured process. The focus is on content mastery, memorisation, and standardised assessment. Characteristics of traditional pedagogy: Teacher-centred instruction Passive student roles E...
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Urgent Need for Addressing Bias in AI-Powered Assessment Tools

Addressing bias in AI-powered assessment tools is one of the most urgent challenges in educational technology today. While artificial intelligence has brought efficiency, scale, and speed to student assessment, it has also raised valid concerns about fairness, equity, and discrimination. As more institutions adopt AI to evaluate written work, analyse performance, and deliver feedback, ensuring that these tools operate without bias is not optional—it’s essential. Bias in AI systems often stems from the data used to train them. If training datasets are skewed towards a specific demographic—such as students from certain geographic regions, language backgrounds, or academic levels—the algorithm may unintentionally favour those groups. The result? An uneven learning experience where assessments do not reflect true student ability, and grading may be inaccurate or discriminatory. How to Use Case Studies to Showcase Your Expertise Why Addressing Bias in AI-Powered Assessment Tools Matters Ed...
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Using AI to Identify At-Risk Students Early: A Powerful Tool for Timely Intervention

Using AI to identify at-risk students is one of the most promising advances in education today. As institutions aim to increase student success, retention, and graduation rates, artificial intelligence is emerging as a critical ally in spotting early signs of struggle— before students fail or drop out . By analyzing learning behaviors, engagement patterns, and performance metrics, AI enables educators to intervene proactively and provide tailored support when it matters most . Inside the CAIBS Course: What You’ll Learn in the Certified AI Business Strategist Program What Makes a Student At-Risk? At-risk students are those who are likely to: Fail a course Drop out of a program Experience academic or emotional burnout Miss critical milestones for graduation Traditionally, these risks were only discovered after students underperformed. With AI, educators can detect red flags in real time , allowing for data-informed, early intervention . How AI Detects At-Risk Students AI tools integrate...
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