The instructional routines in this playbook offer repeatable, lesson-embedded structures for using AI to support literacy instruction within the HMH platform. Each routine aligns to a specific instructional need and clarifies when a particular instructional move is appropriate and how AI can support that move within the flow of instruction. Across routines, AI serves as a planning and design partner by helping teachers surface patterns in student work, anticipate instructional barriers, and generate supports aligned to the lesson’s purpose and text. Instructional decisions remain grounded in teacher judgment, with AI responding to teacher-defined intent and producing outputs that teachers review, refine, and implement.
AI-Enabled Instructional Routines
Select a link below to go directly to an instructional routine.
The Role of AI Across Instructional Routines
AI plays a supportive and bounded role across all routines. Its primary value is in helping teachers move from evidence to action more efficiently and with greater precision.
Within routines, AI is used to:
Surface patterns in student responses, performance, or access needs Generate draft instructional supports aligned to a specific lesson purpose Assist with designing lesson-embedded routines that are brief, targeted, and intentional AI outputs are always mediated by teacher review. Teachers refine prompts, revise generated activities, and make final instructional decisions to ensure alignment with students, texts, and instructional goals.
Design Structure Shared Across All Routines
The Value Add of Technology on Teaching Framework
The instructional routines are grounded in the to ensure technology use stays focused on supporting real instructional work. The routines are designed so technology supports your instructional judgment at key moments, such as anticipating where students may struggle, noticing patterns in their responses, and planning targeted instructional supports. Across these routines, AI helps you plan with greater clarity, respond more effectively to student thinking, and maintain alignment to the lesson’s purpose as instruction unfolds. AI is used selectively and intentionally to support thoughtful instructional moves that keep expectations high and instruction coherent, without introducing new demands or disrupting the flow of daily teaching. Value of Grounding in the VATT Framework
Elevates human work by keeping professional judgment and lesson purpose at the center of AI use. Strengthens instructional impact by surfacing patterns in student thinking to support responsive instruction. Increases educator capacity by streamlining routine planning and data-related work. Expands instructional possibilities, such as timely feedback and improved access, while preserving rigor and productive struggle.