AI and Big Data in Education: Managing Technological Risks

As educational technology evolves, bringing artificial intelligence and big data into the classroom offers incredible opportunities alongside significant responsibilities. Educators must navigate the complex landscape of student privacy, data consent, and algorithmic bias without sacrificing instructional quality. This text-only course equips you with the foundational knowledge to evaluate, select, and implement AI and data-driven tools safely and ethically. You will learn to move past the marketing hype and make evidence-based decisions that prioritize student well-being and actual learning outcomes. What you'll learn: Understand foundational AI and big data terminology and how these technologies function in educational settings; Evaluate educational tools using an outcome-focused framework rather than relying on industry hype; Navigate data privacy, consent, and security standards to protect sensitive student information; Identify and mitigate algorithmic bias and ethical concerns inherent in modern AI models; Establish clear, safe classroom guidelines for student interactions with generative AI tools; Analyze real-world scenarios to practice ethical decision-making regarding technology integration. The course starts with essential definitions and foundational concepts of educational technology risks before guiding you through privacy frameworks, ethical evaluation methods, and practical policy formulation. Through written explanations and analysis exercises, you will build a robust framework for secure technology integration. This course is designed for teachers, school administrators, and educational technology coordinators who are new to AI and want to establish safe practices. No prior technical or programming experience is required. Read through this comprehensive guide to confidently lead your classroom into the future of safe digital learning.