California State University, Fullerton

Jen Dailo Chandler

Human Learning Advocate

From One-Size-Fits-All to Scaffolded Learning

For too many years, higher education has tried to be a one-size-fits-all model of learning. However, with the rising ubiquity of AI, higher education has an opportunity to offer scaffolded learning that finally recognizes that students bring varied prior experiences with AI tools, professional communications, workplace environments and life in general to campus. By leveraging AI, all of these can be at the forefront of individual learning. A scaffolded learning approach meets students where they are at and supports growth and learning over time rather than perfection on first attempts. 

In this way, innovation across higher education can center on human agency such that both faculty and students remain critical evaluators of AI-generated outputs, ensuring that as "the tool does more," the student's intellect does not do less.  As AI transforms higher education, institutions need to create best practices to animate the learner in all of these ways, rather than upstaging the learning with technology. Learning has always been an active effort, rather than a passive reception of information from a sole source of knowledge. To really leverage AI, higher education needs to use technology to expand student access to applied strategic learning and durable skill development for students with diverse educational, cultural and professional backgrounds and emphasize structured peer collaboration, iterative revision, reflective learning and multiple opportunities for students to strengthen critical thinking, communication and technology competency skills through practice and feedback. 

Building a Culture of Confident AI Adoption

Institutions need to encourage educators to experiment with new approaches to teaching while giving faculty a meaningful voice in how AI is introduced, integrated and supported across the institution. Regular implementation meetings, cross-disciplinary workshops and peer learning communities can help instructors share progress, troubleshoot challenges and align AI integration across different course levels. Equally important is close collaboration between information technology teams and academic affairs, recognizing that technology is no longer an add-on to teaching but an integral part of the learning environment.

"AI should meet students where they are and help them grow, not expect perfection from the start."

Building that culture also requires universities to rethink how they evaluate teaching and learning. Traditional assessment methods and instructor evaluation metrics must evolve to support innovation rather than discourage it. Faculty are more likely to embrace new pedagogical approaches when they know their institution values experimentation and provides sustained support.

At the same time, universities must prepare both faculty and students to use AI responsibly without compromising critical thinking, creativity or academic integrity. This begins by fostering curiosity and encouraging exploration so that educators and learners naturally develop confidence with emerging technologies. Institutions should invest in faculty-led curriculum redesign, ongoing professional development and peer mentorship from successful early adopters to ensure that effective practices can scale across campus. Collaboration with career services and industry professionals can further align AI instruction with evolving workplace expectations, helping students develop skills that remain relevant beyond the classroom.

Preparing Students for an AI-Driven Future

Over the next five years, AI will evolve from a disruptive novelty into a foundational "platform" that redefines the student experience by shifting the focus from passive information retrieval to active critical evaluation. Teaching will be transformed through a scaffolded developmental pathway wherein instructors facilitate a progression that involves and could be based on foundational AI literacy, to a complex, strategic integration of learning and technology within capstone experiences. Student success can be increasingly measured by the visibility of competencies, utilizing platforms for tracking and digital badging that allow learners to articulate their growth in a shared vocabulary recognized by industry practitioners. Ultimately, by embedding ethical AI use into authentic, workplace-inspired scenarios, higher education can successfully bridge the gap between academic theory and the evolving demands of contemporary professional practice.