Over the past few months, I have been exploring different pedagogical frameworks to guide teachers in making sense of AI integration in their practice. I’ve written about the SAMR model, which helps us think about how technology reshapes learning tasks; Bloom’s Taxonomy, a classic framework for structuring cognitive processes; and TPACK, which highlights the interplay between technological, pedagogical, and content knowledge in effective teaching.
In this post, I turn to Webb’s Depth of Knowledge (DOK), a framework centered on cognitive rigor and the varying levels of thinking students engage in. The goal is not to introduce something entirely new, these are models many educators already know well, but rather to revisit them through the lens of AI. By doing so, we can better understand how AI tools might be used to support, extend, and enrich learning at each level of complexity, while keeping pedagogy at the core.
In preparing this guide, I drew on a number of resources, including Nancy Boyles’ Reading, Writing, and Rigor (2018), Michael Martin’s Blending Instruction with Technology (2016), Karin Hess’s Depth of Knowledge Flip Chart (2013), the WebbAlign DOK Primer (2025), and curriculum studies such as Karuguti, Phillips, and Barr’s (2017) analysis of interprofessional education.
Note: I was not able to locate any peer-reviewed paper by Dr. Norman Webb that explains the Depth of Knowledge model. What exists are unpublished reports and technical monographs, while later educators and researchers have been the ones to expand on and formalize the framework in academic publications.
1. What is DOK
Depth of Knowledge (DOK) is a taxonomy of cognitive rigor developed by Norman Webb in the 1990s to differentiate levels of cognitive demand and describe how students engage with content (Martin, 2016). DOK is an evaluative tool for content analysis, a language system that helps educators distinguish among different levels of complexity in student engagement across tasks, questions, and assessments (WebbAlign, 2025).
The framework categorizes learning experiences according to the depth of thinking and mental effort they require, moving from simple recall to extended reasoning. Teachers and curriculum designers use DOK to align learning objectives with appropriate assessments, to ensure that instructional tasks match the rigor expected in academic standards, and to guide lesson planning, questioning, and evaluation practices that encourage deeper understanding and sustained problem-solving (Hess, 2013).
“Dr. Norman Webb originally developed the DOK language system for the purpose of evaluating the relationship between the complexity (often referred to as “cognitive complexity”) of academic standards and the complexity of corresponding assessment items.” (WebbAlign)
2. DOK’s Levels
The Depth of Knowledge framework is organized into four levels that reflect increasing complexity in how students think and work with content. Each level builds on the previous one, moving from simple recall to extended problem-solving and creation.
Level 1: Recall and Reproduction
Students remember and repeat basic information. These tasks are simple – students either know the facts or they don’t. There’s no need to change or analyze the information. Teachers might ask students to name vocabulary words, do basic math problems, or list important facts.
Level 2: Skills and Concepts
Students use information to make connections and decisions. They need to think through several steps and show they understand relationships between ideas. Tasks include comparing different concepts, organizing information into groups, explaining why something happens, or summarizing main points.
Level 3: Strategic Thinking and Reasoning
Students plan their approach and use evidence to solve complex problems. These tasks often have several correct answers, so students must explain their thinking and support their conclusions. Examples include examining what an author believes, working through challenging problems that require new approaches, or planning an experiment.
Level 4: Extended Thinking
Students work on demanding projects that take time and combine many skills. They gather information from different sources, apply what they know to new situations, and create original work. These might include research projects, essays that connect ideas across multiple texts, or developing solutions for real problems. Students often work together on these authentic, meaningful tasks.
4. Beneftis of DOK
The Depth of Knowledge framework offers multiple benefits for teaching and learning. It not only sharpens the focus on cognitive demand in classroom tasks but also provides clarity, alignment, and coherence across instruction, assessment, and curriculum design.
1. Supporting Deeper Learning
One of the main benefits of using Webb’s Depth of Knowledge (DOK) is its focus on the actual cognitive demand of tasks rather than just the verbs used in instructions. Unlike Bloom’s Taxonomy, which can sometimes be misapplied when teachers rely solely on action words, DOK emphasizes the level of reasoning and complexity required. This helps educators design lessons and assessments that move beyond rote recall to foster deeper understanding and meaningful engagement with content (Martin, 2016).
2. Clarity in Literacy Instruction
In the context of reading and writing, DOK provides teachers with a clearer pathway for structuring tasks across levels of rigor. It ensures that students progress from surface comprehension, such as recalling details, to higher-level literacy skills, such as analyzing an author’s purpose or synthesizing across multiple texts. This progression supports critical thinking and helps students apply their learning in authentic and complex ways (Boyles, 2018).
3. Improving Curriculum Alignment
DOK is also a powerful tool for evaluating whether curriculum, instruction, and assessment are aligned in terms of rigor. In a study of interprofessional education, DOK analysis revealed that while learning outcomes were set at high levels, the assessments often remained at lower levels. This misalignment limited students’ opportunities to demonstrate complex reasoning. Using DOK as an evaluative tool helps educators identify such gaps and redesign assessments to better reflect intended learning outcomes (Karuguti, Phillips, & Barr, 2017).
4. Enhancing Classroom Rigor and Progression
Practical tools like Hess’s Cognitive Rigor Matrices show how DOK can be applied to everyday instruction. Teachers can use it to scaffold tasks, ensuring that students move from basic skills, such as summarizing, to more demanding activities, such as analyzing or synthesizing information. This approach increases classroom rigor, supports authentic learning projects, and encourages students to sustain higher-order thinking across disciplines (Hess, 2013).
5. Promoting Systemic Coherence
At a broader level, DOK enhances coherence across education systems. It provides a shared language for teachers, curriculum developers, assessment designers, and policymakers to discuss the cognitive complexity of standards and tasks. This shared framework ensures that expectations are consistently understood and communicated, which in turn strengthens alignment between standards, instruction, and assessment (WebbAlign, 2025).
5. Bloom’s Taxonomy Vs DOK
Bloom’s Taxonomy and Webb’s Depth of Knowledge both provide useful ways of thinking about cognitive rigor, but they emphasize different aspects of learning. Bloom’s lays out a hierarchy of mental processes, moving from simple recall at the base to creation at the top, while Webb’s framework looks at the depth and complexity of a task, focusing on how students engage with content and what kind of reasoning is required (Martin, 2026).
I don’t suggest that one model is better than the other; rather, both offer valuable perspectives. Bloom’s helps teachers frame learning objectives and outcomes, while DOK guides the design of questions and tasks that stretch students’ thinking. Used together, they give educators complementary tools for planning lessons, designing assessments, and ensuring that students experience both a range of thinking skills and meaningful depth of understanding.
6. DOK and Literacy
Nancy Boyles (2018) introduces the Depth of Knowledge (DOK) framework as a way to strengthen literacy instruction by focusing on the cognitive demand required of students, not just the tasks themselves. She emphasizes that effective teaching in reading and writing moves beyond surface-level recall to deeper levels of comprehension, analysis, and synthesis.
The framework encourages teachers to design literacy experiences that progressively challenge students, helping them think critically, draw connections, and apply understanding in meaningful ways. Boyles highlights that using DOK in literacy provides clarity for teachers in aligning instruction with rigor and ensures students are prepared for complex thinking tasks in academic and real-world contexts.
7. DOK’s and AI
When paired with AI tools, the Depth of Knowledge framework offers teachers a practical way to see how technology can support learning at different levels of cognitive rigor. From quick recall to extended projects, AI can serve as a reference, a thinking partner, or a research assistant, always with teachers guiding students to use it critically and responsibly.
Level 1: Recall and Reproduction with AI
Teachers use AI to help students practice basic facts and information. AI tools can create flashcards, generate simple quiz questions, or provide instant feedback on vocabulary definitions. Students might use AI to check spelling, look up basic facts, or get quick answers to straightforward questions. At this level, AI serves as a digital textbook or reference tool that students consult for immediate information.
AI Tools:
- Quizlet: Generates flashcards and practice quizzes for quick recall.
- Wayground: Creates simple interactive drills and exercises.
- Grammarly: Checks spelling, grammar, and basic writing mechanics.
- QuizGPT: Builds auto-generated quizzes for fact-based review.
- Kahoot: Provides gamified quizzes for memorization practice.
Level 2: Skills and Concepts with AI
Teachers guide students to use AI for comparing ideas, organizing information, and explaining connections. Students might ask AI to help them categorize different concepts, create summaries of reading materials, or explain cause-and-effect relationships. AI becomes a thinking partner that helps students process information and see patterns. Teachers show students how to prompt AI effectively to get useful comparisons or explanations that deepen their understanding.
AI Tools:
- Notion AI: Organizes and summarizes notes into clear structures.
- ChatGPT: Compares ideas, explains connections, and provides summaries.
- Claude: Breaks down complex texts into simpler explanations.
- Gemini: Generates cause-effect explanations and highlights patterns.
- Latimer AI: Summarizes reading material into key points.
- Perplexity: Supplies contextual explanations with supporting evidence.
Level 3: Strategic Thinking and Reasoning with AI
Students collaborate with AI to tackle complex problems that require planning and evidence. They learn to ask AI thoughtful questions, evaluate the responses critically, and use AI-generated ideas as starting points for their own reasoning. Students might use AI to brainstorm different approaches to a problem, analyze multiple perspectives on an issue, or get feedback on their reasoning. Teachers emphasize that students must justify their thinking and not simply accept AI responses without question.
AI Tools
- NotebookLM: Analyzes documents and connects ideas across sources.
- ChatGPT: Brainstorms approaches, evaluates reasoning, and analyzes perspectives.
- Ideogram: Visualizes ideas and arguments for clearer reasoning.
- MirrorTalk: Engages in reflective dialogue to test reasoning.
- Claude: Assists with structuring arguments and exploring perspectives.
- Elicit: Extracts insights and evidence from research papers.
Level 4: Extended Thinking with AI
Students integrate AI throughout long-term, authentic projects while maintaining ownership of their work. They use AI as a research assistant, writing coach, or brainstorming partner across multiple stages of complex tasks. Students might collaborate with AI to develop research questions, analyze data from various sources, or refine their original ideas. Teachers help students understand how to use AI ethically while ensuring the final work reflects genuine learning and original thinking. The focus remains on students synthesizing, creating, and applying knowledge to real situations.
AI Tools:
- NotebookLM: Supports long-term projects with research and synthesis.
- Elicit: Collects and analyzes data from multiple academic sources.
- SciSpace: Simplifies and explains complex research papers.
- QuizGPT: Generates practice questions tailored to project content.
- Scholarlcy: Assists with academic writing and research support.
- Jenni: Acts as an AI writing partner for drafting and refining essays.
- DocAnalyzer: Analyzes lengthy documents and extracts insights for research.
Here the downloadable PDF version of Blending DOK with AI
References
- Boyles, N. (2018). Reading, writing, and rigor: Helping students achieve greater depth of knowledge in literacy. ASCD.
- Hess, K. K. (2013). Depth of knowledge flip chart: A guide for using Webb’s Depth of Knowledge with Common Core State Standards. Common Core Institute.
- Karuguti, W. M., Phillips, J., & Barr, H. (2017). Analysing the cognitive rigor of interprofessional curriculum using the Depth of Knowledge framework. Journal of Interprofessional Care, 31(4), 529–532. https://doi.org/10.1080/13561820.2017.1310718
- Martin, M. (2016). Blending instruction with technology: A blueprint for teachers to create unique, engaging, and effective learning experiences. Rowman & Littlefield.
- WebbAlign. (2025). Depth of Knowledge (DOK) primer. Wisconsin Center for Education Products and Services. https://www.webbalign.org/dok-primer
- Webb, N., Christopherson, S., & Morelan, B. (2023, March 27). An inside look at Webb’s Depth of Knowledge. Edutopia. https://www.edutopia.org/article/how-use-norman-webb-depth-of-knowledge/
