Resource
AI Infused Assignment Playbook
The AI Infused Assignment Playbook is a practical guide from Sarah Lewis (Barry University, social work) for instructors who want to integrate generative AI with intention rather than bolting it onto existing assignments. It pairs a pedagogical foundation — learning goals, critical thinking, student agency, transparency, and appropriate boundaries for AI use — with adaptable assignment templates, design frameworks, prompts, examples and implementation guidance that instructors can use across disciplines. The goal is explicitly not to prescribe one approach to AI but to help educators design learning experiences in which AI use is purposeful, transparent, and aligned with what students are expected to learn and demonstrate.
What you can do with it
The playbook is organized around a thesis in Chapter 1 that learning is network construction, not information accumulation — the offloading question at the center of AI literacy debate — so the real question is whether AI supports or bypasses that network-building work. Every assignment is built from five formative design principles: structured prompts, not vague AI use (students identify their purpose, relevant concepts, current understanding and the specific help they seek before they are allowed to prompt); critical evaluation of AI outputs (students document what they accept, modify and reject, and justify it); documentation and transparency (prompts, AI-response excerpts, decision logs and rationales make use assessable); metacognitive reflection; and knowledge verification via short closed-note checks.
Chapter 3 ships a fully worked sample assignment (AI-Enhanced Iterative Writing) plus sixteen condensed template entries — AI Dialogue Reflection, AI Literature Review Assistant, AI Bias Detection, AI Study Partner Reflection, AI-Assisted Self-Assessment, AI Debate Partner, AI Client Simulation, AI Scenario Testing, AI-Facilitated Group Project, Peer Review with AI Comparison, Professional AI Use Policy Development, and a Transparent AI Integration Portfolio. Appendix A provides an AI–Human Collaboration Log for capturing the process. Faculty can take single assignments à la carte or adopt a cluster as an AI-infused spine for a whole course.
Who it is for
Instructors across disciplines, especially in higher education and professional programs (the author writes from social work, and nursing/healthcare are named as parallel contexts), plus faculty developers and those preparing accreditation evidence. It assumes students are already using AI and that the responsible response is to bring that use into the open, structure it, and teach students to use AI well rather than hope they avoid it.
Notes and caveats
This is a practical guide, not an empirical study; its claims about student AI use rest on cited external sources (BestColleges, Campbell, Digital Education Council, Flaherty) rather than new data. The "network construction" framework and the "illusion of understanding" framing are drawn from the wider literature (Wigmore et al.; Williamson et al.) and are presented as pedagogical rationale, not tested outcomes of the playbook itself. The assignments are authored templates — none is reported with effect sizes, so they should be treated as designs to adapt and evaluate locally. Published 2026-10-07, v1, on Zenodo under CC BY 4.0; free to download without an account. As of ingestion the record shows only ~35 views and ~14 downloads, so it has seen little external use or peer review yet.
Connected Concepts
Connected Resources
- The Pedagogical PromptbookAn open-access book of evaluated prompts for evidence-based teaching and instructional design practices, each chapter publishing the prompt, its development process and its evaluation results.
- Student Guide to AIA free three-edition student guide to artificial intelligence from Elon University, AAC&U and The Princeton Review, whose 2026 edition builds ten human capacities with teacher-ready learning modules and an anonymous self-assessment.
- Process FeedbackA free, process-based alternative to AI detection: it records how a piece of writing was produced and turns that into a report for a conversation about learning rather than a verdict.
- The ID ToolboxMore than fifty free single-purpose browser utilities for instructional designers: scoping, estimation, caption and translation tooling, readability and consistency checks.