Output is Dead, Long Live Process-Oriented Learning!
AI = Redundancy of Output-Oriented Education.
With AI capable of generating half decent writing, supporting research, and even creating works of art (depending on our definition of art), many ask what role human educators can play in the future.
I see this as a golden opportunity to refocus education entirely. Perhaps we should reverse the question: if AI is the answer, what was the question asked by education to begin with? The answer is complicated, but at least part of it has to do with decades of education being tailored around convenience for those who exercise it rather than optimal learning for those at the receiving end.
Hard words, perhaps, but output-oriented education was never principally concerned with processes. Now, however, AI is about to change that premise entirely.
The Radical Shift: Emphasizing Process over Product
Technologies have come and gone in education, but AI has already had a more radical influence on education than any other technology before: emphasis on the process of learning, rather than the end product, is the way forward for purpose-driven, human-led advances.
Summative assessments of what students produce at the end of a course will be of little or no interest for future learners and employees. Historically speaking, whether an essay, a mathematical proof, or a painting, the focus has been on evaluating the final output. Yet in the arts and sciences alike, the end product is largely meaningless without also understanding the processes that generated it.
When it comes to AI, for the time being most notably in the form of chatbots, the situation is largely the same. As AI evolves and becomes faster and still more capable of producing various types of content, educators are forced to reconsider the very substance of education and learning. This is no easy feat, but I believe part of the answer is to be found in cultivating the uniquely human skills of critical thinking and creativity.
Subjects like design, architecture, journalism, and the arts have always emphasised processes over product. Architects' sketches and models reveal their processes, and innovation labs obsess about design thinking. Scientists' notebooks show the twists and turns in their inquiry, favouring incremental adjustments along the way. These fields understand that forcing students to showcase finished products does not necessarily privilege those with the best ideas.
In future, all fields in higher education must adopt this process-focus. Courses should be redesigned with proces-oriented learning at the centre, with frequent opportunities for students to document, discuss, and reflect on their work. Assessments should evaluate not just the final project, paper or painting, but the iterative process that allowed students to refine their ideas. This approach allows students of all backgrounds to develop important metacognitive skills, and importantly, it will force students learn to think critically about how they think.
Some may argue this is an elitist view that privileges prestigious creative fields over practical disciplines like business or medicine. But process supersedes product even in technical fields like engineering and computer science. No one would trust a program or device that appeared fully formed without documentation of the iterative process behind it. Scratch work is essential for catching mistakes and testing assumptions in all areas.
I recently wrote about Problem Based Learning at Aalborg University, a pedagogical approach that arguably puts this institution at an advantage when it comes to rethinking curriculum and exam forms.
Challenges and Opportunities: Implementing Change in Education
For most institutions, recalibrating curricula around process over product for AI will not be easy. Institutions habituated to evaluating and ranking students based on final exams and term papers may resist. Industry insiders may argue that sacrificing output volume for deeper process focus leaves graduates unprepared for fast-paced corporate environments.
However, these arguments reflect short-term thinking. In the long run, process-focused learning is the only way to produce graduates capable of excelling in an AI-powered world. To stay ahead of algorithms and large language models, humans must go deeper, focusing less on what work looks like and more on the thinking that produced it.
Artificial intelligence requires a sweeping reevaluation of how we teach and assess student work. Rather than letting an obsolete model focused on standardized testing and credentialing die slowly, educators must be bold and proactively lead the way into a process-oriented future. Uncomfortable as this may very well be.
Implementing change of this magnitude is incredibly demanding. Policymakers must revise standards and testing regimes to prioritize ongoing demonstrations of process over high-stakes summative assessments. Accreditors should redefine quality indicators around the resources and opportunities institutions provide for meaningful, iterative practice. And individual educators must have the courage to fundamentally redesign curricula, assignments, and rubrics to direct their attention to process as much as product.
Curriculum redesign will most likely necessitate changes in institutional infrastructure as well. Traditional lecture halls and exams must give way to flexible studios and small group workspaces designed for active learning. Education budgets will need to prioritize funding for new types of equipment and technical support. And partnerships with industry must focus on providing real-world contexts and interactions, not just job credentials.
The jobs of tomorrow will require adaptability and problem solving. An education system designed around cultivating process, not products, can better equip students with these abilities to meaningfully shape the age of artificial intelligence, and their own personal and professional futures in it.
I honestly do believe it is possible to create an education system that develops thoughtful, creative, and engaged citizens who will thrive in an AI-powered world.
The students expect us to succeed. How’s that for motivation?
But it will be an uphill battle all the way.