Bloom’s Taxonomy has long been regarded as the holy grail in leading students through a process of content mastery. The traditional journey begins with imparting information to learners and finds its apex in enabling learners to evaluate and assess knowledge claims. In theory, each step of the journey to mastery builds on prior steps.
Bloom’s model is dominant in education circles. Adherence to its features often goes unquestioned during the process of course design. The model also dates back to 1956, a time when information itself was not (literally) at the fingertips of every student. Decades later, in the age of the Internet, the meanings of the terms “information” and “knowledge” have changed dramatically. Students are drowning in information and learn early to evaluate and assess information sources. The Internet has ushered in an age of constant and reflexive information assessment. We live in a new age of sophistry . . . and cynicism.
It makes sense, then, to consider other, more recently developed, models for course design.
In 2005, Spencer Kagan questioned the legitimacy of the Bloom model and suggested a different system, one that aligns with neuroscience. Kagan offers instead a system of distinctions between three types of thought: understanding, transforming, and generating. Each of these three types is divided into several subtypes. Generally speaking, the category of understanding encompasses comprehension skills, transforming involves inductive and deductive logic skills, and generating involves research skills. Like Bloom’s taxonomy, it is a progressive system: students build on a foundation of understanding. At the same time, it offers a distinct alternative model for course design.
Workforce training can also provide interesting course design models for educators. Typically, employee “training” and higher education are viewed as divergent activities, but what Will Thalheimer calls “Training Maximizers” hold value for faculty in higher education. He offers a multi-step proposal for employee training programs that aims at “maximizing results”. Admittedly, “maximizing” is much more the language of business than of higher education. But beyond the lingo, his recommended system begins with credible content and engaging learning events. It continues with support for understanding, competent decision making, long-term remembering, and application. And it closes with support for perseverance in learning.
As a college educator, there is something undeniably attractive about Thalheimer’s model. As a more recent development, it’s built on the assumption that students arrive in the classroom pre-programmed with some evaluative skills, as the first step depends on content being “credible”.
More importantly, Thalheimer’s model places a clear emphasis on an important goal for modern educators: inspiring continuous learning. The speed of technological and scientific developments is accelerating, and the veracity of the content that college students learn in classrooms can be expected to change. Developing in students a lifelong love of learning is perhaps the most valuable contribution an educator can make.
Of course, there is still plenty of room for Bloom. And there’s room for faculty members to engage in lifelong learning, too.
For further reading:
Kagan, S. (2005) “Rethinking Thinking – Does Bloom’s Taxonomy Align with Brain Science?” Kagan Online. Retrieved from https://www.kaganonline.com/free_articles/dr_spencer_kagan/289/Rethinking-Thinking-Does-Bloom-s-Taxonomy-Align-with-Brain-Science
Thalheimer, W. (2015). “Training Maximizers” Work-Learning Research. Retrieved from https://www.worklearning.com/2015/04/08/training-maximizers/
Miriam Bowers-Abbott is the academic department leader for the Humanities at Mount Carmel College of Nursing. Her instructional duties have ranged from critical thinking, to composition, to ethics, in formats that include face-to-face, online, and everything in between. She’s a former TEDx speaker, a life-long learner, and a professional writer who used to hate everything about writing.