What to do when students aren’t learning

TL;DR: AI Support for Next-Step Learning

Core Idea

Learning is most effective in the zone of proximal development, where students can succeed with guidance but not yet independently. Instruction should target this zone, and AI can support teachers in identifying and acting on it.

The Five-Step Instructional Workflow

1. Determine What Students Can Do

Use formative assessments to identify current student understanding. This establishes the baseline for instruction.

2. Identify the Next Step for Learning

Analyze student responses to determine misconceptions, error patterns, and readiness. This defines what students are prepared to learn next.

3. Provide Scaffolding

Deliver targeted support that helps students move from current understanding to the next level, gradually increasing complexity.

4. Use Adaptive Practice

Align tasks and practice opportunities to individual student needs based on identified gaps and strengths.

5. Accelerate Feedback

Shorten the time between student work and instructional response to reinforce learning and correct misunderstandings quickly.

How AI Supports the First Two Critical Steps

Designing Formative Assessments

AI can rapidly generate targeted assessment questions aligned to specific skills, grade levels, and content areas. These are used to gather evidence of student understanding.

Analyzing Student Responses

AI processes student work to identify common errors, group misconceptions, and suggest likely causes. This helps teachers pinpoint where instruction is needed.

Identifying Student Groups and Needs

AI can categorize students based on error patterns, allowing teachers to target instruction to specific groups or individuals.

Extending Insight into Student Thinking

Beyond identifying errors, AI can infer likely student reasoning and misconceptions. This provides deeper insight into how students are thinking, enabling more precise instructional decisions.

Key Principle

Effective instruction depends on accurately identifying where students are and what they are ready to learn next. AI supports this process by making assessment design, analysis, and interpretation faster and more precise, but teacher judgment remains essential in deciding how to respond.