Skip to page content

Generative Learning and Complexity Laboratory

The Generative Learning and Complexity Laboratory (GLCL) brings together scholars and practitioners of learning and complexity science to reimagine learning and development. Founded initially through a grant from the Jinks Private Foundation, the laboratory brings together funded projects and other related projects from collaborating faculty and students, partner universities, and organizations to imagine new ways to respond to complex challenges. As a research, learning, and development laboratory, GLCL strives to conduct research and practice that addresses problems impacting all levels and sectors of society.

The lab is not so much a place as an idea—a space of possibility where we can imagine ‘what if.’ We are creating an ecology where we innovate the new internal and external structures to become something new, to lean into the unknown to advance our understanding of generative learning and complexity. The lab serves as a hub and a facilitator for groundbreaking multi-disciplinary research in complexity and learning. We provide expertise and support for emerging and early-stage research through projects, maker spaces, a network, and funding support to initiate research on generative learning and complexity.

Our goals are to:

  1. Pursue research and demonstration projects that advance complexity science and its application to our understanding of learning
  2. Create a community of inquirers advancing research on generative learning and complexity science
  3. Generate and disseminate tools, structures, and resources to support ongoing research and development in generative learning and complexity

Core Faculty

Karen E. Watkins

Professor, Department of Lifelong Education, Administration, and Policy

Aliki Nicolaides

Associate professor and graduate coordinator, Department of Lifelong Education, Administration, and Policy

Graduate Students and Research Fellows

  • Neal Herr
  • Dr. Jill K. Jinks
  • Dr. Ahreum Lim

Becoming an Affiliate of the GLCL

Affiliate researchers are regular, research, or adjunct university faculty or non-university researchers, including post-doctoral fellows, who actively participate in institute activities, including research projects or committees. Membership is ongoing with periodic outreach to confirm active status.

Individuals whose work intersects with the mission of the lab may apply to join the lab. Individuals interested in becoming an affiliate should submit a brief 1-2 page proposal outlining their project and explaining how it fits the mission of the lab. Affiliates will meet with lab staff and provide updates on their projects, work with other lab members on joint research, writing, grant development, or presentations, and agree to share their findings in a project report that can be made available to others through the lab.

Practitioner members include people in government, the voluntary sector, and private sector interested in the lab’s research and findings and who actively participate in GLCL workshops and conferences open to a general audience. Practitioner members may join by paying an annual fee. Practitioners may also fund projects administered through the lab to address problems of generative learning in complexity in their organization. For further information, please contact Aliki Nicolaides .

Small Grants Program

Deadline: March 1, 2023

Generative Learning and Complexity Laboratory

Funds for research and development projects aimed at advancing our understanding of the role of generative learning within complexity and uncertainty will be awarded to individuals whose work extends the work of the lab. Projects may include advanced statistical studies working with our Minecraft study database, research exploring generative learning in complexity and uncertainty, projects drawing on maker space and complexity constructs, etc. For more information, please contact Aliki Nicolaides .

Proposal Format

Proposals may be up to 10 pages in length and should include the proposed project (theoretical framework, methods, project description, rationale for funding, how this project extends the work of the lab, proposed dissemination products/events/creative artifacts for the lab [e.g. white paper, database, webinar, etc.], timeline, and budget). Vitae of project personnel should be attached. Budgets may not exceed $2,400.

If from UGA, fringe benefits for UGA personnel and indirect costs of 10% must be included.

Current Projects/Maker Spaces

Aliki Nicolaides: Designing a Maker Studio for Learning About Learning
Dr. Nicolaides and graduate students facilitate a collective learning lab we call a “maker space,” where we apply the tools of worldbuilding to reimagine adult education as an ecology of transformation. Academics and graduate students explore how to imagine a different world through adult learning in the context of higher education where we have the freedom to create something different—a unique space where imagination can create multiple different worlds that are forged through inquiry, with compassion, and consciousness.
Aliki Nicolaides, Ahreum Lim, Neal Herr, Trisha Barefield: Reimagining Adult Education as Worldbuilding (Routledge, forthcoming)
In this book we trouble adult education as a territory ripe for reimagining its purpose and influence in building a better world through learning. The book presents how the tools of worldbuilding were applied to attempt to grow and catalyze an ecology for transformation as a maker space from January 2021 to June 2021. We ask, how do we create conditions for the emergence of ecologies for transformation in the context of higher education through adult learning? To answer this question, the chapters of the book explore how the tools of worldbuilding catalyzed a vitalizing ontology as a plane for generative emergence in an educational setting.
Jill Jinks and Karen Watkins: Modeling Roughness of Learning Through Gaming
Researchers developed a method for directly extracting and scoring play data from the game of Minecraft to measure complexity in the learning context. In addition, latent variable of crafting (as directly extracted and scored) was combined with latent variables of individual incidental learning and uncertainty to predict adaptiveness to create a SEM using CFA methods.
Aliki Nicolaides and Ahreum Lim: Ethics and AI
The Nudge experiment simulates a manufacturing assembly line where artificial intelligence indirectly guides or nudges workers’ behaviors and tests how young adult learners learn through human-machine interaction in collaboration with a mechanical engineering lab. Participants’ responsiveness and attentive recognition of material conditions are explored with post-phenomenological and new materialist perspectives.
Victoria Marsick (Teacher’s College, Columbia University) and Dimitrios Papagnou (Thomas Jefferson Hospital) with Henriette Lundgren and Grace Alcid: Informal and Incidental Learning and Uncertainty in the Clinical Learning Environment
University and hospital-based researchers study the learning of frontline physicians who worked in the clinical learning environment amidst the uncertainty posed by the height of the COVID-19 pandemic. Using critical incident interviews, the study inquires about the informal and incidental learning of physicians and how their learning can inform curriculum changes to prepare medical students for uncertainty in clinical practice.
Dr. Allie Cox: Navigating Polarities of Womanhood
When women lead by example in rejecting forced binary choices, we create worlds where circumstances and actions become more complex. This complexity is liberating if supported by structures and tools for sensemaking; without them, we may suffer double binds and intractable pathways. “Unsimple truths” that define women’s lives may not have either/or answers, but finding a third way opens up new possibilities for themselves, their families, their organizations, their communities, and their worlds.

Resources

Learning Through Complexity Webinar Videos

On January 29, 2021, the lab hosted a webinar on learning through complexity featuring three scholars of complexity: Alicia Juarrero, Ann Pendleton-Jullian, and George Siemens. With these three scholars, we examined the question, “How might informal and incidental learning be reimagined from a complexity science perspective?”

© University of Georgia, Athens, GA 30602
706‑542‑3000