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Reimagining Education Through Generative Learning

Schools need to be redesigned to prepare students for professional trajectories we can’t currently imagine. As the former provost and dean of faculty at the Philadelphia University and the dean of Parsons School of Design, I’ve seen firsthand the urgent need to abandon the Industrial-Age approach to higher education that dominates today. Studies of siloed individual subjects assessed by antiquated systems and given value by an increasingly irrelevant system of credits are no longer productive. The process of learning needs to be reframed to keep up with today’s employment landscape.

The professional world confronting graduates today is remarkably dynamic due in part to interconnected global economies that are continually restructuring. As new vocations rapidly emerge, crest and die, our very concept of what a professional practice means and promises is profoundly challenged.

Redesigning Design Education

To shore up their campuses against the tsunami of change surging their way, schools around the world are experimenting with new methods for learning. One interesting development taking hold is the unbundling of monolithic degrees (terminal degrees like the bachelors, masters and doctoral degrees in the United States) in order to certify and describe learning in deeper and more textured ways. These changes are also opening up learning opportunities to a wider set of students outside of those currently enrolled at the institutions or within specific departments. Purdue has been a leader in building a robust badging infrastructure and using it to create a richer, more descriptive approach to documenting learning in areas as diverse as nanotechnology and intercultural learning. UC Davis has also been a pioneer—its best known badging system is in sustainable agriculture and encompasses a wide range of learning modalities. MOOC platforms like Harvard and MIT’s edX are also building substantial badging capabilities.

 Rather than pursuing requisite classes toward a traditional bachelor or master degree, “microcredentialing” and badging are creating new opportunities for learners to master specific skills and technical abilities, methods of inquiry and approaches to problem solving and technical abilities in fields that are relevant to their broad goals. While the aim of micro- or “stackable” credentials is sometimes to add up to a degree, the structure allows the learner, hiring manager, graduate school selection committee or colleagues to embrace the story of everything that a learner has achieved. From problem-solving abilities to professional practices across fields, critical thinking to software competency, anything can be a badge or microcredential as long as it can be rigorously assessed. The magic and potential is in how we use this information to enhance learning.

Generative Design

Even though I work for a 3D design company, I am by no means a technological determinist. I know driving change requires creative people working with technology. That said, I’m optimistic about the continued learning opportunities that the evolution of microcredentialing could offer learners of all ages. Since joining Autodesk, I have become increasingly intrigued by how frameworks from powerful emerging practices such as generative design could be transposed to education through the lens of what we might call generative learning.

Generative Design options for a chair

With generative design, the design process starts by collaborating with intelligent computer systems fueled by the nearly infinite computing power of the cloud. You work with the system to frame not so much a blind instrumental action advancing the creation of your project, but how you want it to collaborate with you to achieve a design outcome. By co-creatively working with the system to frame design problems, you give it the fuel to explore a massive solution space no individual could ever conceive of alone. The designer becomes both a problem framer and a curator of the design solution set.

Generative Learning

Generative learning would borrow from this practice by working with intelligent computer systems to co-create learning pathways we could never conceive of on our own. Forget the fixed professions of the industrial era—those days are over. And forget the palate of professional majors at most universities. The potential of generative learning is to help us identify fluctuating “flows” of professional activities that we might not even have words for yet. Generative learning also embraces the reality that learners are no longer bound by time, place and graduation dates. We now need to learn and grow forever as our professional world morphs. Generative learning systems could help align the unending process of learning with constantly shifting flows of professional activities.

The microcredentialing movement can help lead this charge. What if microcredentials became more than simple certifications for learning outcomes? Imagine if they were machine-learning agents that defined learning pathways based on the emergent behaviors of millions of learners, inquiries from grad schools for students, hiring manager requests or the needs of colleagues and teammates. What if these intelligent microcredentials incessantly communicated with each other in a system that identified, even helped define, emergent practices and trends that aligned with but also expanded a student’s view of professional flows?

A generative learning system would incorporate existing educational institutions, but integrate them into a much broader framework of learning experiences that shift as professional flows morph and mutate into new kinds of jobs. I happen to think this would be a very positive development that would challenge the legacy university to its core.

We look forward to hearing more about the future of generative learning in the context of networked matter from Mickey McManus, Autodesk visiting research fellow and principal and chairman of the board at MAYA Design, at this week’s 2016 IDSA International Conference in Detroit.