How to Learn Educational Technology

A structured path through Educational Technology — from first principles to confident mastery. Check off each milestone as you go.

Educational Technology Learning Roadmap

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Estimated: 23 weeks

Foundations of Learning Theory

2-3 weeks

Study core learning theories that underpin educational technology: behaviorism, cognitivism, constructivism, and connectivism. Understand how people learn, including cognitive load theory and multimedia learning principles.

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Instructional Design Fundamentals

2-3 weeks

Learn systematic instructional design models (ADDIE, SAM, backward design). Practice writing measurable learning objectives using Bloom's Taxonomy and aligning assessments to objectives.

Learning Management Systems & Authoring Tools

2-3 weeks

Gain hands-on experience with LMS platforms (Canvas, Moodle, Google Classroom) and content authoring tools (Articulate Storyline, Adobe Captivate, H5P). Learn SCORM and xAPI standards.

Online and Blended Learning Design

2-3 weeks

Design effective online and blended courses. Study synchronous and asynchronous strategies, flipped classrooms, community of inquiry framework, and student engagement techniques.

Accessibility, Equity, and UDL

1-2 weeks

Apply Universal Design for Learning principles. Learn accessibility standards (WCAG, Section 508), assistive technologies, and strategies for addressing the digital divide.

Assessment and Learning Analytics

2-3 weeks

Design effective formative and summative assessments for digital environments. Explore learning analytics tools, data visualization, early-alert systems, and evidence-based improvement cycles.

Emerging Technologies in Education

2-3 weeks

Explore adaptive learning platforms, AI-powered tutoring systems, virtual and augmented reality, gamification, and generative AI applications. Evaluate the SAMR model for technology integration.

Leadership, Ethics, and Implementation

2-3 weeks

Study change management for technology adoption, data privacy regulations (FERPA, COPPA, GDPR), ethical use of AI in education, digital citizenship, and program evaluation methods.

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