🎓 Problems Learning Analytics Addresses

In Higher Education

The Core Challenge

Traditional higher education operates on assumptions, traditions, and delayed feedback rather than real-time evidence about student learning.

Learning analytics promises to shift from: Assumption → Evidence | Delayed → Real-time | Invisible → Visible | Reactive → Proactive

12
Core Problems
3
Stakeholder Groups
∞
Implementation Challenges

📊 Organizing Framework: The Meta-Problem

All these problems share a common root: the challenge of teaching at scale while maintaining quality, personalization, and equity.

What Analytics Can Do

  • Make invisible patterns visible
  • Identify problems early
  • Enable scale and personalization
  • Provide evidence for decisions

What Analytics Can't Do

  • Replace pedagogical expertise
  • Capture joy, creativity, relationships
  • Automatically improve learning
  • Eliminate need for human connection

The Critical Question

When is analytics-rich design worthwhile (improves learning, supports students) vs. when does it become surveillance (monitors behavior, serves institution over learner)?