Theories of Critical Thinking - Kyle Kilgore

 In today’s classrooms, meaningful learning goes far beyond memorizing facts, it requires deep engagement, collaboration, and the ability to think critically about information. Fullan and Langworthy’s (2014) theory of Deep Learning emphasizes student-driven exploration through real-world tasks that use technology as a tool for discovery and creation. For students, this means moving from passive learning to active problem-solving, research, and digital content creation. As a result, students develop stronger digital literacy skills and become more confident, independent learners. For classmates and peers, this approach encourages teamwork and digital collaboration, making learning more interactive and socially engaging.

Teachers and coworkers are also deeply affected by how learning is structured. Bloom’s Taxonomy (as explained by Huitt, 2011) provides a valuable framework for designing instruction that moves students through levels of thinking, from remembering and understanding to applying, analyzing, and creating. When educators plan with these cognitive stages in mind, especially in tech-integrated environments, it helps coworkers and peers better support one another in pushing students toward higher-level digital skills. Whether you're a teacher developing rubrics with colleagues or a student giving peer feedback in a project, Bloom’s model creates a shared understanding of learning expectations that enhances digital fluency for everyone involved.

However, adopting technology and new instructional strategies doesn’t happen at the same pace for everyone. Rogers’ (1963) Diffusion of Innovations theory explains how change spreads within a community or organization, and why some embrace new tools while others resist. Among your coworkers or classmates, you’ll likely notice the five adopter types: innovators who try new tech first, early adopters who recognize value early, the early and late majority who follow once it’s proven effective, and laggards who are slow to change. Recognizing where individuals fall in this adoption curve helps create realistic expectations and allows for targeted support. For example, tech-savvy students might lead group work using digital platforms, while others need guided practice to build confidence. Teachers might introduce tools in phases to help colleagues feel supported rather than overwhelmed.

Together, these theories help explain how technology and digital literacy can be successfully integrated into teaching and learning. When we aim for deep learning, use Bloom’s Taxonomy to guide instruction, and understand how innovation spreads, we create a more inclusive, collaborative, and effective environment. This benefits everyone, students become engaged creators, classmates grow as digital thinkers, and coworkers build shared practices that keep pace with the demands of a digital age.

Fullan, M., & Langworthy, M. (2014). A rich seam: How new pedagogies find deep learning. Pearson. 

Hobbs, R. (2011). Empowering learners with digital and media literacy. Knowledge Quest, 39(5), 12–17.

Huitt, W. (2011). Bloom et al.'s taxonomy of the cognitive domain. Educational Psychology Interactive. Valdosta State University. http://www.edpsycinteractive.org/topics/cognition/bloom.html

Kuhn, M. S. (2008). Connecting depth and balance in class. Learning & Leading with Technology, 36(1), 18–21.

Rogers, E. M. (1963). The adoption process II. Journal of Cooperative Extension, 1(2), 69–75.