T14
Ethics, Equity & Responsible LE
Algorithmic fairness in adaptive systems; data privacy; equity in access; avoiding automation bias in assessment.
3 resources tagged with this topic
How to use this topic
Start with the resources below — they’re the practical methods, tools, and examples tagged to this area. Many can be adapted for resource-constrained and developing-country settings. When you need the underlying evidence and concept structure, switch the site lens to Researcher.
Concepts in this topic
AI Ethics & Responsible Use in Learning Evaluate
Builds on: AI & Foundation Models in Education
Ethics & Equity in Learning Engineering Evaluate
Resources
Reading List 3
Algorithmic Fairness in Education
Learning Engineering as an Ethical Framework
Van Campenhout frames learning engineering as an explicit ethical practice in adaptive instructional systems design and evaluation.