Cross-Dimensional Drivers

CCR designed the 4-Dimensional Competency Framework to help answer the question “what should students learn?” The acceleration of artificial intelligence, and the ways in which it disrupts life and work, now elevates the question of “why should students learn?” to the forefront. 

Triangle pointing from left to right. Inside the triangle, the word "Motivation" reads from top to bottom on the left indicating that the other concepts move through it. To the right, the words "Identity," "Agency," and "Purpose" step up from each other.

Cross-dimensional drivers, introduced in Education for the Age of AI, are CCR’s answer to this question.

In a world in which AI can demonstrate aspects of knowledge, skills, character, and meta-learning, it is vital that students better harness and develop their motivation, identity, agency, and purpose. With these drivers, teachable across all disciplines and through all competencies, students can continuously grapple with the inevitable changes they will face throughout their lifetimes. They serve as vehicles for personalizing learning experiences, which can make them more meaningful to students.

The following table showcases CCR’s actionable definitions and related constructs synthesized from learning sciences research:

CCR Term CCR Definition Associated Terms and Constructs
Motivation Why you take action Drive, incentive, self-determination, inspiration
Identity Who you are in the world and in your relationships Belonging, self-concept, personhood
Agency Your capacity to take action Growth Mindset, autonomy, self-efficacy, empowerment, intentionality
Purpose Your sense of significance Passions, interests, intentions, ambition

 

Personalization

By tailoring approaches to teaching and learning to address student’s individual needs, preferences, and rhythms, educators can meet students where they are at. Most importantly, students are not homogenous; they come with varied backgrounds, abilities, and learning needs. Traditional “one-size-fits-all” instructional methods insufficiently address the various backgrounds, abilities, and learning strategies of all students, and fail to engage all students equally, often leading to underachievement. In addition to the performance advantages of such educational practices, personalization can contribute to developing deeper connections to learning. When education resonates with a student’s interests and aspirations, it can ignite passion and intrinsic motivation, leading to more profound, lasting understanding and a greater likelihood of long-term success.

Of course, personalizing education is a time- and resource-intensive initiative for schools and educators. Education for the Age of AI showcases some of the latest strategies for leveraging new technology tools to help facilitate this work and indicates directions in which the field can explore integrating these crucial drivers into modern education.